feat: initial changes

samples/APOLLO-2-leaderboard.tsv

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+year_of_birth	days_to_birth	gender	race	ethnicity	bmi	alcohol_history	alcohol_intensity	smokestat_apollo2	cigarettes_per_day2	years_smoked2	family_cancer_history	dzextent_beyondabd	dzextentpriortosurg	primary_diagnosis	site_of_resection_or_biopsy	classification_of_tumor	stage_figo_2014	morphology	celltype	tumor_grade	sticpresent	brcastat	brca1ihc_apollo	disease_distribution	diseasehigh	miliarypresent	residual_disease	anyresidualdisease	days_to_last_known_disease_status	last_known_disease_status	fuflag	days_to_recurrence	pfstimeindays	pfs_status	survivaltimeindays	vital_status	causeofdeath_apollo2	year_of_death	days_to_death	days_to_treatment	treatment_intent_type	treatment_or_therapy	apollo2_adv_hg_serous_complete
+1927	-30246	FEMALE	Caucasian or White	Hispanic or Latina	20.12307203	Yes	14	Previous Smoker		1	2 members Mother with liver cancer Father with prostate cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G2-moderately differentiated	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Measurable > 1 cm	Yes	1023	Residual or persistent disease no progression	Not lost	607	607	Event	1023	Alive				19	Adjuvant Chemotherapy	No	0
+1930	-29118	FEMALE	Caucasian or White	Hispanic or Latina	20.85277293	No		Previous Smoker		1	3 members Maternal Uncle with esophageal cancer at 50 Other Relative nos 1 with breast cancer at 47 Other Relative nos with lung cancer at 60		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DM R0	Ovary	PRIMARY	IIIA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	Yes	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	Macroscopic < 1 cm	Yes	278	Disease progression	Died	217	217	Event	278	Deceased	Disease progression	2010	278	26	Adjuvant Chemotherapy	No	0
+1930	-28671	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	21.32720483	Yes		Current Smoker	10	2	1 member Father with lung cancer at 74		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R1	OVARY	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	695	Disease progression		129				Deceased		2013	903	55	Adjuvant Chemotherapy	No	0
+1930	-29312	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.07856301	No		Previous Smoker	20	4	2 members Father with  colon cancer Mother with lung cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Macroscopic < 1 cm	Yes	200	Residual or persistent disease no progression	Alive less than 1 year follow up then lost		308	Event	308	Alive				7	Adjuvant Chemotherapy	No	0
+1931	-29686	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	23.32450917	Unknown		Previous Smoker	17	4	3 members Sister with breast cancer Maternal Grandmother with breast cancer Other Family Member NOS with ovarian cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DH R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	Macroscopic < 1 cm	Yes	568	Disease progression	Died	383	383	Event	568	Deceased	Disease progression	2010	568	25	Adjuvant Chemotherapy	No	0
+1934	-27475	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	34.38271971	Yes	0.6	Previous Smoker	10	7	2 members Mother with leukemia Daughter with breast cancer at 32	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	1071	Disease progression	Died	623	623	Event	1071	Deceased	Disease progression	2013	1071	34	Adjuvant Chemotherapy	No	0
+1934	-27670	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.47871	No		Previous Smoker	0.5	7	2 members Mother with breast cancer Sister with breast cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	1323	Residual or persistent disease no progression	Not lost	390	390	Event	1323	Alive				20	Adjuvant Chemotherapy	No	0
+1935	-27658	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.49433107	Yes	2.5	Previous Smoker	20	8	3 members Father with lung cancer Maternal Aunt with breast cancer in 40s Paternal Aunt with colon cancer in late 50s		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DM R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	399	Disease progression	Not lost	399	399	Event	399	Alive				58	Adjuvant Chemotherapy	No	0
+1935	-27857	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.02958907	No		Previous Smoker		8	2 members Father with prostate cancer Paternal Grandmother with breast cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Positive expression level NOS	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	1100	Residual or persistent disease no progression	Not lost	432	432	Event	1294	Alive				16	Adjuvant Chemotherapy	No	0
+1935	-28021	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.53531247	Yes	14	Previous Smoker	10	10	1 member Maternal Uncle with lung cancer at 40	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DH R1 post NACT	OVARY LEFT	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	273	Disease progression	Died	64	64	Event	273	Deceased	Disease progression	2010	273	46	Adjuvant Chemotherapy	No	0
+1935	-27521	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.93917914	No		Previous Smoker	20	13	1 member Paternal Grandfather with lung cancer		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	Yes Mild	Macroscopic < 1 cm	Yes	742	Residual or persistent disease no progression	Not lost	517	517	Event	742	Alive				50	Adjuvant Chemotherapy	No	0
+1936	-27256	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.18231105	Unknown		Previous Smoker	60	14		No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	1579	Residual or persistent disease no progression	Not lost	825	825	Event	1579	Alive				56	Adjuvant Chemotherapy	No	0
+1937	-26527	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	29.09640326	Yes	0.5	Previous Smoker	20	15	2 members Brother with brain cancer died at 32 Brother with lung cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	876	Disease progression	Died	307	307	Event	876	Deceased	Disease progression	2013	876	35	Adjuvant Chemotherapy	No	0
+1937	-26675	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.16687996	Yes	3	Previous Smoker	10	15			Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R0 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	876	Disease progression	Died	307	307	Event	876	Deceased	Disease progression	2013	876	23	Adjuvant Chemotherapy	No	0
+1937	-27456	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	21.2584689	Yes	0.1	Previous Smoker	30	16	1 member Father with brain cancer died at 64		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary HD R3	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Mutant	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	1086	Residual or persistent disease no progression	Not lost	516	516	Event	1086	Alive				54	Adjuvant Chemotherapy	No	0
+1937	-27130	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.50811353	Yes	3	Previous Smoker	10	20	2 members Maternal Cousin with breast cancer Maternal Cousin with uterine cancer	Yes	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DM R0 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	815	Disease progression	Died	383	383	Event	815	Deceased	Disease progression	2012	815	3	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1938	-26118	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	23.29590458	Yes	4	Previous Smoker	10	20	2 members Mother with basal cell carcinoma Maternal Grandmother with ovarian cancer and uterine cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	Yes	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	Macroscopic < 1 cm	Yes	534	Disease progression	Died	425	425	Event	534	Deceased	Disease progression	2012	534	15	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1938	-26151	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.02064258	Yes		Previous Smoker	15	20	4 members Father with stomach cancer at 56 and colon cancer Sister 1 with cancer type unknown at 61 Sister 2 with cancer type unknown Maternal Aunt with breast cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R1	OVARY LEFT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Non-measurable > 1 cm	Yes	1159	Disease progression	Died	605	605	Event	1159	Deceased	Disease progression	2013	1159	16	Adjuvant Chemotherapy	No	0
+1938	-27029	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.53592684	Yes	0.2	Current Smoker	20	24			Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	1263	Disease progression	Died	576	576	Event	1263	Deceased	Disease progression	2013	1263	16	Neoadjuvant and Adjuvant Chemotherapy	No	0
+1939	-25166	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.58334743	Yes	0.1		10	25	5 members Mother with skin cancer Maternal Grandmother with skin cancer Maternal Aunt with pancreatic cancer at 86 Cousin with breast cancer at 58 Paternal Uncle with cancer type unknown		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DM R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	1428	Disease progression	Not lost	471	471	Event	1428	Alive				21	Adjuvant Chemotherapy	No	0
+1939	-26064	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.61644288	No		Current Smoker	20	25	Father with prostate cancer and pancreatic cancer Mother with lung cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	Non-measurable > 1 cm	Yes	570	Recurrence new lesion	Not lost	570	570	Event	570	Alive				10	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1939	-25794	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.84186767	Yes	3.5	Previous Smoker	20	30	1 member Father with colorectal cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R2	OVARY RIGHT	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	784	No evidence of disease	Not lost		784	Censored	784	Alive				10	Neoadjuvant and Adjuvant Chemotherapy	No	0
+1940	-25649	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	29.79257498	Unknown		Current Smoker	20	30	4 members Mother with breast cancer Maternal Aunt with breast cancer Paternal Aunt 1 with breast cancer Paternal Aunt 2 with colorectal cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the peritoneum DH R2	OVARY	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Measurable > 1 cm	Yes	831	Disease progression	Died		831	Censored	831	Deceased	Disease progression	2013	831	4	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1940	-25094	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.5545495	Yes		Previous Smoker	10	30		Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	Macroscopic < 1 cm	Yes	1660	Disease progression	Died	520	520	Event	1660	Deceased	Disease progression	2013	1660	16	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1940	-26074	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.6265161	Yes	3.5	Previous Smoker	10	32	1 member Father with cancer type unknown	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R1 post NACT	Ovary	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	244	Disease progression	Died	238	238	Event	244	Deceased	Disease progression	2012	244	24	Adjuvant Chemotherapy	No	0
+1940	-25886	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.13113805	Yes	11	Previous Smoker	20	35	3 members Maternal Aunt with liver cancer and esophageal cancer Cousin with lung cancer Maternal Uncle cancer type unknown	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R0 post NACT	FALLOPIAN TUBE	PRIMARY		Serous adenocarcinoma	SEROUS ADENOCARCINOMA	G3-poorly differentiated	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	474	No evidence of disease	Alive 1 to 2 years follow up then lost		474	Censored	474	Alive				16	Neoadjuvant Chemotherapy	Yes	0
+1941	-24531	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	27.7321388	Yes	2	Previous Smoker	20	40	3 members Father with lung cancer Sister with lung cancer and skin cancer Mother with pancreatic cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R3	OVARY	PRIMARY	IIIA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	142	No evidence of disease	Alive less than 1 year follow up then lost		142	Censored	142	Alive				18	Neoadjuvant Chemotherapy	Yes	0
+1941	-24541	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	32.91859384	No		Previous Smoker		40	5 members Father with lung cancer Mother with bone cancer and ovarian cancer Maternal Grandmother with cancer type unknown Grandchild with cancer type unknown Nephew with cancer type unknown		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	283	Disease progression	Died	272	272	Event	283	Deceased	Disease progression	2011	283	25	Adjuvant Chemotherapy	No	0
+1941	-24938	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	19.86351239	No		Current Smoker	20	40	1 member Father with stomach cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Macroscopic < 1 cm	Yes	319	Disease progression	Died	319	319	Event	319	Deceased	Disease progression	2011	319	56	Adjuvant Chemotherapy	No	0
+1941	-24735	FEMALE	Asian	Non-Hispanic or Non-Latina	24.19655895	No		Current Smoker	20	49	2 members Mother with breast cancer at 65 Father with stomach cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OVARY LEFT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	446	Disease progression	Died	310	310	Event	446	Deceased	Disease progression	2013	446	21	Adjuvant Chemotherapy	No	0
+1941	-24880	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	27.57718644	Yes		Current Smoker	14	50	1 member Father with lung cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R3 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	824	Residual or persistent disease no progression	Not lost	268	268	Event	824	Alive				32	Adjuvant Chemotherapy	No	0
+1941	-25925	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	33.84257813	Unknown		Current Smoker	20	55	3 members Father with prostate cancer Female Cousin with breast cancer at 35 Maternal Uncle with leukemia	Yes	Unknown	Advanced high grade serous cancer of the peritoneum DH R1	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	None or microscopic	No	1046	Recurrence new lesion	Not lost	948	948	Event	1046	Alive				19	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1941	-25212	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	21.81183326	Yes	0	Never Smoked			2 members Mother with breast cancer Sister with leukemia	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen			None or microscopic		1801	No evidence of disease	Not lost	1214	1214	Event	1812	Alive				20	Adjuvant Chemotherapy	No	0
+1942	-25583	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.46394815	Yes	0	Never Smoked			2 members Mother with breast cancer Sister with leukemia		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer  of the Fallopian tube DH R1 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	1138	No evidence of disease	Not lost		1138	Censored	1138	Alive				27	Adjuvant Chemotherapy	No	0
+1942	-24801	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	32.98605086	Yes	0	Never Smoked				No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	666	Disease progression	Died	333	333	Event	666	Deceased	Disease progression	2009	666	39	Adjuvant Chemotherapy	No	0
+1942	-25668	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	16.65625	Yes	0	Never Smoked			3 members Aunt with breast cancer Cousin with ovarian cancer Grandfather with leukemia		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DL R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	Measurable > 1 cm	Yes	1039	Recurrence new lesion	Not lost	1039	1039	Event	1272	Alive				20	Adjuvant Chemotherapy	No	0
+1943	-25380	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	38.86423323	Yes	0	Never Smoked					Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1479	Disease progression	Died	416	416	Event	1479	Deceased	Disease progression	2014	1479	36	Adjuvant Chemotherapy	No	0
+1943	-25357	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.224959	Yes	0	Never Smoked			4 members Mother with lung cancer at 72 Sister with lung cancer Daughter with breast cancer Paternal Aunt with gynecologic cancer nos	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer  of the Fallopian tube DM R0 post NACT	TERMINAL ILEUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Mutant	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	77	Disease progression	Died	30	30	Event	77	Deceased	Disease progression	2010	77	5	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1943	-25135	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	23.77378393	Yes	0.08	Never Smoked			1 member Mother with melanoma	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DL R0	OVARY RIGHT	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Mutant	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	882	Disease progression	Died	372	372	Event	882	Deceased	Disease progression	2012	882	12	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1944	-23961	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.65325444	Yes	0.08	Never Smoked			1 member Maternal Grandfather with prostate cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R2	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	727	Disease progression	Not lost	377	377	Event	727	Alive				70	Adjuvant Chemotherapy	No	0
+1944	-23822	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	17.8076743	Yes	0.1	Never Smoked			1 member Mother with leukemia		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	893	Residual or persistent disease no progression	Not lost	403	403	Event	893	Alive				22	Adjuvant Chemotherapy	No	0
+1945	-23042	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	17.8953125	Yes	0.1	Never Smoked					Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R2	OVARY LEFT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	958	No evidence of disease	Not lost	374	374	Event	958	Alive				35	Adjuvant Chemotherapy	No	0
+1945	-24368	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	18.59905312	Yes	0.1	Never Smoked			1 member Mother with colon cancer at 63	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1069	No evidence of disease	Not lost		1069	Censored	1069	Alive				5	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1945	-24247	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	19.08880674	Yes	0.1	Never Smoked			1 member Paternal grandfather with colon cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	1169	Disease progression	Died	90	90	Event	1169	Deceased	Disease progression	2013	1169	6	Neoadjuvant Chemotherapy	No	0
+1945	-24719	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	19.31984017	Yes	0.2	Previous Smoker			4 members Mother with colon cancer in 70s Brother with colon cancer Aunt 1 with breast cancer at 57 Aunt 2 with bladder cancer		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DL R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	404	Disease progression	Died	287	287	Event	404	Deceased	Disease progression	2010	404	20	Adjuvant Chemotherapy	No	0
+1945	-23799	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.67823854	Yes	0.25	Never Smoked					Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the peritoneum DH R3	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Measurable > 1 cm	Yes	405	Disease progression	Died	356	356	Event	405	Deceased	Disease progression	2013	405	41	Adjuvant Chemotherapy	No	0
+1945	-23515	FEMALE	Asian	Non-Hispanic or Non-Latina	20.79755639	Yes	0.5	Never Smoked			3 members Maternal Grandmother with breast cancer Paternal Grandfather with cancer type unknown Paternal Aunt with cancer type unknown		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DM R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	784	No evidence of disease	Not lost		784	Censored	784	Alive				18	Adjuvant Chemotherapy	No	0
+1945	-24131	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.9469767	Yes	0.6	Never Smoked				No	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DL R1 post NACT	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	904	Residual or persistent disease no progression	Not lost	711	711	Event	904	Alive					Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1946	-23624	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	20.97265235	Yes	0.6	Never Smoked					Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	1045	Residual or persistent disease no progression	Not lost	502	502	Event	1273	Alive				37	Adjuvant Chemotherapy	No	0
+1946	-23540	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	21	Yes	0.6	Never Smoked				No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the peritoneum DM R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	751	Disease progression	Died	386	386	Event	751	Deceased	Disease progression	2012	751	13	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1946	-22853	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	21.20433359	Yes	1	Never Smoked			4 members Mother with breast Cancer at 60 recurred twice Brother with rectal cancer at 68 Paternal Aunt 1 with breast cancer Paternal Aunt 2 with breast cancer	Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DM R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Low expression	Moderate disease distribution greater than low but less than high	No	Yes Mild	None or microscopic	No	241	Disease progression	Died	209	209	Event	241	Deceased	Disease progression	2010	241	6	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1946	-23048	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	21.29729683	Yes	1	Never Smoked				Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	807	Residual or persistent disease no progression	Not lost	311	311	Event	807	Alive				24	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1946	-23247	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.44379628	Yes	1	Never Smoked				No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DM R1	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	None or microscopic	No	987	Disease progression	Died	452	452	Event	987	Deceased	Both disease progression and cancer treatment	2013	987	45	Adjuvant Chemotherapy	No	0
+1946	-23534	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.96030049	Yes	2	Never Smoked			4 members Mother with pancreatic cancer Father with skin cancer Brother with cancer type unknown Maternal Grandmother with throat cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R1	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	Moderate disease distribution greater than low but less than high		No	None or microscopic		1623	Disease progression	Not lost	761	761	Event	1623	Alive				64	Adjuvant Chemotherapy	No	0
+1946	-23168	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	22.9977045	Yes	3	Never Smoked			2 relatives Mother with uterine cancer in 1990 died unknown cause Father with lung cancer in 1989 died unknown cause	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer  of the Fallopian tube DH R3 pre NACT	UTERUS	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No			High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Non-measurable > 1 cm	Yes	412	Disease progression	Died	333	333	Event	412	Deceased	Disease progression	2012	412	13	Adjuvant Chemotherapy	No	0
+1947	-23240	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	23.65	Yes	5	Never Smoked			1 member Mother with pancreatic cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the peritoneum DH R0 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	1082	Disease progression	Died	85	85	Event	1082	Deceased	Disease progression	2011	1082	15	Neoadjuvant and Adjuvant Chemotherapy	No	0
+1947	-23519	FEMALE	Black or African American	Non-Hispanic or Non-Latina	23.92291643	Yes	14	Never Smoked			1 member Grandfather with colon cancer	Yes	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R3 pre NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	117	Disease progression	Died	31	31	Event	117	Deceased	Both disease progression and cancer treatment	2010	117	21	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1947	-23545	FEMALE	Asian	Non-Hispanic or Non-Latina	24.40139559	No		Never Smoked			1 member Maternal Grandmother with breast cancer at 55	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the peritoneum DM R0	PERITONEUM	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	663	Residual or persistent disease no progression	Not lost biopsy taken for suspious progression	663	663	Censored	663	Alive				11	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1948	-22734	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	24.60629921	No		Never Smoked			1 member Mother with breast cancer	No	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1 post NACT	OVARY	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	915	No evidence of disease	Not lost	375	375	Event	915	Alive				8	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1948	-22688	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	25.05798003	Yes		Previous Smoker			2 members Sister with colorectal cancer at 82 Sister with esophageal cancer at 72		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer  of the Fallopian tube DL R0 post NACT	Fallopian Tube	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	1452	Residual or persistent disease no progression	Not lost	550	550	Event	1452	Alive				14	Adjuvant Chemotherapy	No	0
+1948	-22349	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.3383081	No		Previous Smoker	10		3 members Paternal Grandmother with colon cancer Paternal Grandfather with colon cancer Paternal Aunt with colon cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Mutant	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1516	Disease progression	Died	782	782	Event	1516	Deceased	Disease progression	2012	1516	29	Adjuvant Chemotherapy	No	0
+1948	-22111	FEMALE	Black or African American	Non-Hispanic or Non-Latina	25.47007104	No		Never Smoked			2 members Father with cancer type unknown Son with lung cancer		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R3 pre NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Positive expression level NOS	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1571	No evidence of disease	Not lost		1571	Censored	1571	Alive				34	Adjuvant Chemotherapy	No	0
+1948	-22417	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.48954397	Yes		Never Smoked			6 members Father with lung cancer and liver cancer Sister 1 with gynecologic cancer nos at 40 died at 44 Sister 2 with lung cancer at 65 died at 67 Brother with BRCA positive prostate cancer Paternal Uncle with colorectal cancer Paternal Aunt with colon cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R2	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	954	No evidence of disease	Not lost		954	Censored	954	Alive				34	Adjuvant Chemotherapy	No	0
+1949	-21991	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.49664697	No		Never Smoked			3 members Mother with kidney cancer Father with prostate cancer  Brother with bone cancer and lung cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R2	Ovary	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	1429	No evidence of disease	Not lost		1429	Censored	1429	Alive				27	Adjuvant Chemotherapy	No	0
+1949	-22841	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.54573027	Yes		Previous Smoker			5 members Mother with lung cancer Brother with colorectal cancer Maternal Aunt with breast cancer Other Relative nos 1 with Breast Cancer Other Relative nos 2 with uterine cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DL R0	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	None or microscopic	No	1493	Disease progression	Died	527	527	Event	1493	Deceased	Disease progression	2012	1493	47	Adjuvant Chemotherapy	No	0
+1949	-22432	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.62408892	Yes		Previous Smoker			2 members Sister 1 with ovarian cancer at 41 and breast cancer at 48 Sister 2 with ovarian cancer at 48	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R3	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS				High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	828	No evidence of disease	Not lost		926	Censored	926	Alive					Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1949	-21882	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	25.8912764	Yes		Never Smoked			3 members Brother 1 with prostate cancer Sister with melanoma Brother 2 with non melanoma skin cancer		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer  of the Fallopian tube DM R2	FALLOPIAN TUBE	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes			High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	1720	Disease progression	Died	922	922	Event	1720	Deceased	Disease progression	2013	1720	59	Adjuvant Chemotherapy	No	0
+1950	-21322	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	26.3	Yes		Never Smoked			1 member Aunt with uterine cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R2 pre NACT	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1287	Disease progression	Died	664	664	Event	1287	Deceased	Disease progression	2013	1287	14	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1950	-22149	FEMALE	Caucasian or white	Non-Hispanic or Non-Latina	26.49345034	No		Never Smoked			2 members Mother with lung cancer Maternal Aunt with breast cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1662	Residual or persistent disease no progression	Not lost	1141	1141	Event	1662	Alive				13	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1950	-22506	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	26.63	No		Current Smoker	20		1 member Maternal Aunt with kidney cancer at unspecified age		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the peritoneum DH R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	1709	No evidence of disease	Not lost		1709	Censored	1709	Alive				32	Adjuvant Chemotherapy	No	0
+1951	-22435	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	26.92492959	No		Previous Smoker			4 members Brother with bone cancer and prostate cancer at 11 deceased, Brother with cancer site not specified at 64 Sister with lymphoma died of cancer Son with leukemia		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DH R1 post NACT	OVARY LEFT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	1532	Residual or persistent disease no progression		1322				Alive				58	Adjuvant Chemotherapy	No	0
+1951	-21114	FEMALE	Black or African American	Non-Hispanic or Non-Latina	27.19353957	No		Never Smoked			1 member Sister with colorectal cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Measurable > 1 cm	Yes	1320	Residual or persistent disease no progression	Not lost	365	365	Event	1320	Alive				13	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1952	-21500	FEMALE	Caucasian or white	Non-Hispanic or Non-Latina	27.64808636	No		Never Smoked				No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	Measurable > 1 cm	Yes	1824	Residual or persistent disease no progression	Not lost	581	581	Event	1824	Alive				2	Neoadjuvant and Adjuvant Chemotherapy	No	0
+1952	-21116	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	27.87426146	Unknown		Previous Smoker			1 member Sister with kidney cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DM R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	88	Disease progression	Died	88	88	Event	88	Deceased	Unknown	2011	88	49	Adjuvant Chemotherapy	No	0
+1953	-19965	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.1141101	No		Never Smoked			3 members Father with breast cancer Mother with breast cancer Sister with breast cancer and ovarian cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R1 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Low expression	Moderate disease distribution greater than low but less than high	No	Yes Mild	Macroscopic < 1 cm	Yes	991	Disease progression	Died	535	535	Event	991	Deceased	Unknown	2013	991	5	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1953	-20786	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.84845009	No		Never Smoked			1 member Father with colorectal cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R3	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	None or microscopic	No	1399	No evidence of disease	Not lost	1066	1066	Event	1399	Alive				43	Adjuvant Chemotherapy	No	0
+1953	-20941	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.92685467	No		Never Smoked					Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R2	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	Measurable > 1 cm	Yes	1756	Residual or persistent disease no progression	Not lost	544	544	Event	1756	Alive				26	Adjuvant Chemotherapy	No	0
+1953	-21538	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	28.9528752	Unknown		Never Smoked			1 member Father with prostate cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R2	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	352	Disease progression	Died	202	202	Event	352	Deceased	Disease progression	2012	352	31	Adjuvant Chemotherapy	No	0
+1953	-21538	FEMALE	Black or African American	Non-Hispanic or Non-Latina	29.12905234	No		Never Smoked			1 member Mother with breast cancer		Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	Measurable > 1 cm	Yes	717	Residual or persistent disease no progression	Not lost	389	389	Event	717	Alive				78	Adjuvant Chemotherapy	No	0
+1953	-21318	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	29.49942579	Yes		Never Smoked					Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the peritoneum DM R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	990	Disease progression	Died	381	381	Event	990	Deceased	Disease progression	2013	990	21	Adjuvant Chemotherapy	No	0
+1953	-20550	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	29.50592237	No		Never Smoked			1 member Father with prostate cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R2	OVARY RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	1478	Residual or persistent disease no progression	Not lost	770	770	Event	1478	Alive				37	Adjuvant Chemotherapy	No	0
+1953	-21048	FEMALE	Caucasian or White	Hispanic or Latina	30.13932852	No		Never Smoked			1 member Mother with breast cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	Yes Mild	None or microscopic	No	1290	Residual or persistent disease no progression	Not lost	753	753	Event	1290	Alive				24	Adjuvant Chemotherapy	No	0
+1953	-21048	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	30.22796383	No		Never Smoked			1 member Father with lung cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R2 post NACT	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1597	Residual or persistent disease no progression	Not lost	422	422	Event	1597	Alive				63	Adjuvant Chemotherapy	No	0
+1954	-20911	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	30.32366608	No		Never Smoked					Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	769	Disease progression	Died	376	376	Event	769	Deceased	Both disease progression and cancer treatment	2014	769	36	Adjuvant Chemotherapy	No	0
+1954	-20375	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	30.58409897	No		Never Smoked			1 member Mother with breast cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DM R0	OVARY LEFT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	Macroscopic < 1 cm	Yes	785	No evidence of disease	Alive 1 to 2 years follow up then lost		785	Censored	785	Alive				27	Adjuvant Chemotherapy	No	0
+1954	-19927	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	30.89261781	Unknown		Never Smoked			1 member Father with cancer type unknown	Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1258	Disease progression	Died	411	411	Event	1258	Deceased	Disease progression	2013	1258	14	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1954	-20002	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.1809005	No		Never Smoked			3 members Father with basal cell cancer of the skin at 71 Maternal Grandmother with vulvar cancer Paternal Grandmother with liver cancer	No	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	1658	No evidence of disease	Not lost	841	841	Event	1658	Alive				21	Neoadjuvant and Adjuvant Chemotherapy	No	0
+1954	-21262	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.19638668	Unknown		Never Smoked			1 member Paternal Grandmother with throat cancer	Yes	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the peritoneum DH R1	UTERINE MYOMETRIUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1911	No evidence of disease	Not lost		1911	Censored	1911	Alive				40	Adjuvant Chemotherapy	No	0
+1954	-20241	FEMALE	Mixed	Non-Hispanic or Non-Latina	31.22399686	No		Never Smoked			3 members Mother with breast cancer Father with prostate cancer and non melanoma cancer Brother with prostate cancer	No	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DL R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	2325	Residual or persistent disease no progression	Not lost	650	650	Event	2325	Alive				78	Adjuvant Chemotherapy	No	0
+1954	-20079	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.30501386	Unknown		Never Smoked			1 member Father with prostate cancer		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer  of the Fallopian tube DH R2 pre NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	931	No evidence of disease	Not lost	801	801	Event	1014	Alive				45	Adjuvant Chemotherapy	No	0
+1955	-20338	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	31.609375	Yes		Never Smoked			2 members Mother with squamous cell and basal cell cancer of the skin Cousin with colon cancer in 60s		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R2	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	1353	Disease progression	Died	455	455	Event	1353	Deceased	Disease progression	2012	1353	9	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1955	-20328	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.75071682	No		Never Smoked			1 member Mother with breast cancer and colon or colorectal cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	Measurable > 1 cm	Yes	660	Disease progression	Died	171	171	Event	660	Deceased	Both disease progression and cancer treatment	2011	660	14	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1955	-20500	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	31.91484375	Unknown		Never Smoked			1 member Mother with pancreatic cancer at 80		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer  of the Fallopian tube DM R1	FALLOPIAN TUBE RIGHT	PRIMARY	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1165	No evidence of disease	Not lost		1290	Censored	1290	Alive				43	Adjuvant Chemotherapy	No	0
+1955	-20083	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	32.09560038	Yes		Never Smoked					Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the peritoneum DM R1	UTERUS	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	562	Residual or persistent disease no progression	Alive 1 to 2 years follow up then lost		562	Censored	562	Alive				53	Adjuvant Chemotherapy	No	0
+1955	-20262	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	32.25107042	No		Never Smoked			1 member Mother with breast Cancer		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R2 post NACT	OMENTUM	METASTATIC	IIIC	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	1446	Disease progression	Died	613	613	Event	1446	Deceased	Disease progression	2012	1446	56	Adjuvant Chemotherapy	No	0
+1956	-20415	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	32.80259733	Yes		Previous Smoker					Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R3	OVARY RIGHT	PRIMARY	IV	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	298	Disease progression	Died	177	177	Event	298	Deceased	Disease progression	2009	298	30	Adjuvant Chemotherapy	No	0
+1956	-20217	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	32.91106072	No		Never Smoked			2 members Father with skin cancer Sister with breast cancer	Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer  of the Fallopian tube DM R1 post NACT	OMENTUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	Yes Mild	Macroscopic < 1 cm	Yes	1737	Residual or persistent disease no progression	Not lost	955	955	Event	1737	Alive				30	Adjuvant Chemotherapy	No	0
+1956	-19789	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	33.1998818	No		Never Smoked				Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R3	OMENTUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	923	Disease progression	Died	905	905	Event	923	Deceased	Disease progression	2012	923			No	0
+1957	-18914	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	33.2863569	Yes		Never Smoked			2 members Father with prostate cancer Paternal Grandmother with cancer type unknown	Yes	Unknown	Advanced high grade serous cancer  of the Fallopian tube DH R1	OMENTUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis			None or microscopic		1075	No evidence of disease	Not lost		1075	Censored	1075	Alive				16	Adjuvant Chemotherapy	No	0
+1957	-19279	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	34.26555808	No		Never Smoked			1 member Mother with breast cancer		Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DH R1	CUL DE SAC	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	34	No evidence of disease	Alive less than 1 year follow up with progression missing date		216		216	Alive				28	Adjuvant Chemotherapy	No	0
+1957	-19303	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	34.28814169	Unknown		Never Smoked			4 members Mother with colorectal cancer Brother with cancer type unknown Maternal Uncle with cancer type unknown Other Relative nos with colorectal cancer	Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	None or microscopic	No	81	Disease progression	Died	49	49	Event	81	Deceased	Disease progression	2011	81	50	Adjuvant Chemotherapy	No	0
+1958	-19358	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	34.48490921	No		Never Smoked				Yes	Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R0 post NACT	PELVIS	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	None or microscopic	No	686	Recurrence new lesion	Alive 2 to 3 years follow up then lost	686				Alive				18	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1958	-19724	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	34.95722144	No		Never Smoked			2 members Mother with cervical cancer, Brother with brain cancer		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DM R1 post NACT	OMENTUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Mild	Macroscopic < 1 cm	Yes	354	Disease progression	Died		354	Censored	354	Deceased	Unknown	2012	354	34	Adjuvant Chemotherapy	No	0
+1958	-18997	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	35.27690173	No		Never Smoked			4 members Mother with esophageal cancer Sister with esophageal cancer Sister with cervical cancer Son with prostate cancer		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the peritoneum DH R0 post NACT	ENDOMETRIUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS				Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	912	Recurrence new lesion	Alive 2 to 3 years follow up then lost	912	912	Event	912	Alive				20	Adjuvant Chemotherapy	No	0
+1958	-19121	FEMALE	Caucasian or white	Non-Hispanic or Non-Latina	35.80307382	Unknown		Previous Smoker	20		2 members Mother with ovarian cancer at 70 Maternal Aunt with breast cancer in 80s		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DM R1	UTERUS	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Mutant	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Non-measurable > 1 cm	Yes	1659	Residual or persistent disease no progression	Not lost	194	194	Event	1659	Alive				53	Adjuvant Chemotherapy	No	0
+1959	-19253	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	36.14079497	No		Never Smoked					Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer  of the Fallopian tube DH R1 post NACT	OMENTUM	METASTATIC	IVA	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	119	No evidence of disease	Alive less than 1 year follow up then lost		119	Censored	119	Alive				17	Adjuvant Chemotherapy	No	0
+1960	-18068	FEMALE	Caucasian or white	Non-Hispanic or Non-Latina	36.98671084	No		Never Smoked			1 member Father with cancer type unknown		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Macroscopic < 1 cm	Yes	1073	Disease progression	Died	583	583	Event	1073	Deceased	Disease progression	2011	1073	31	Adjuvant Chemotherapy	No	0
+1960	-18392	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	38.625	Unknown		Never Smoked			1 relative Paternal Aunt with breast cancer	No	Low Disease Distribution, limited to the pelvis or retroperitoneal nodal metastasis	Advanced high grade serous cancer of the ovary DH R2	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	None or microscopic	No	1578	No evidence of disease	Not lost	569	569	Event	1578	Alive				16	Neoadjuvant and Adjuvant Chemotherapy	Yes	0
+1960	-18616	FEMALE	Caucasian or White	Non-Spanish / Non-Hispanic / Non-Latina	38.73584423	No		Never Smoked			1 member Sister with ovarian cancer and stomach cancer		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DM R2	UTERUS	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extent NOS	Measurable > 1 cm	Yes	1081	Disease progression	Died	764	764	Event	1081	Deceased	Disease progression	2011	1081	46	Adjuvant Chemotherapy	No	0
+1961	-17212	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	38.94824893	No		Never Smoked			3 members Mother with uterine cancer in 50s died of cancer at 58 Maternal Aunt 1 with uterine cancer in 70s Maternal Aunt 2 with breast cancer in 70s		High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	Yes	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	612	Disease progression	Died	470	470	Event	612	Deceased	Disease progression	2011	612	127	Adjuvant Chemotherapy	No	0
+1961	-18124	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	41.30968293	No		Previous Smoker			3 members Mother with skin cancer Maternal Aunt with breast cancer Paternal Aunt with colon cancer		Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer  of the Fallopian tube DH R0	DIAPHRAGM	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Low disease distribution limited to the pelvis or retroperitoneal nodal metastasis	No	No	None or microscopic	No	864	Disease progression	Died	384	384	Event	864	Deceased	Disease progression	2011	864	28	Adjuvant Chemotherapy	No	0
+1962	-17290	FEMALE	Black or African American	Non-Hispanic or Non-Latina	42.5234375	No		Current Smoker	2				High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer  of the Fallopian tube DH R0	OVARY	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Macroscopic < 1 cm	Yes	725	Disease progression	Died	667	667	Event	725	Deceased	Disease progression	2012	725	27	Adjuvant Chemotherapy	No	0
+1962	-17960	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	42.64071833	No		Never Smoked					Disease Beyond the Abdomen and Pelvis	Advanced high grade serous cancer of the ovary DH R1	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	Moderate disease distribution greater than low but less than high	No	Yes Mild	None or microscopic	No	1880	Disease progression	Not lost	789	789	Event	1989	Alive				31	Adjuvant Chemotherapy	No	0
+1962	-16777	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	43.09869731	No		Never Smoked				Yes	High Disease Distribution in the diaphragm, gallbladder, epigastrium, liver and/or spleen	Advanced high grade serous cancer of the ovary DH R0	OVARY	PRIMARY	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	None or microscopic	No	1423	No evidence of disease	Alive 3 to 4 years follow up then lost		1423	Censored	1423	Alive				43	Adjuvant Chemotherapy	No	0
+1963	-17373	FEMALE	Black or African American	Non-Spanish / Non-Hispanic / Non-Latina	43.48031157	No		Never Smoked			2 members Mother with breast cancer at 65 Father with prostate cancer	No	Moderate Disease Distribution greater than Low, but less than High	Advanced high grade serous cancer of the ovary DH R3 pre NACT	PLEURAL IMPLANT	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Negative expression	Moderate disease distribution greater than low but less than high	No	No	None or microscopic	No	505	Disease progression	Died	421	421	Event	505	Deceased	Disease progression	2010	505	3	Neoadjuvant Chemotherapy	Yes	0
+1969	-15054	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	49.59697498	No		Never Smoked			5 members Paternal grandmother diagnosed with breast cancer, Second cousin diagnosed with ovarian cancer, Second cousin diagnosed with ovarian cancer, Father diagnosed with lung cancer, Brother diagnosed with lung cancer			Advanced high grade serous cancer of the ovary DM R0 post NACT	METASTATIC SITE NOS	METASTATIC	IVB	Serous adenocarcinoma	SEROUS ADENOCARCINOMA	High grade NOS	No	Unknown	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	Yes Extensive	None or microscopic	No	749	Residual or persistent disease no progression	Not lost	568	568	Event	749	Alive				31	Adjuvant Chemotherapy	No	0
+1972	-13684	FEMALE	Caucasian or White	Non-Hispanic or Non-Latina	52.79704179	No		Never Smoked						Advanced low grade serous cancer of the peritoneum DL R0	OMENTUM	METASTATIC		Serous adenocarcinoma	SEROUS ADENOCARCINOMA	Low grade NOS	No	Wild Type	Unknown	High disease distribution in the diaphragm, gall bladder, epigastrium, liver and/ or spleen	Yes	No	Measurable > 1 cm	Yes	930	Disease progression	Died		930	Censored	930	Deceased	Unknown	2013	930	55	Adjuvant Chemotherapy	No	0

samples/APOLLO-2-leaderboard_meta.csv

@@ -0,0 +1,45 @@
+dtype,count,unique,null,freq,min,max,PV_match,Enumerated,NonEnumerated
+year_of_birth,int64,117,35,0,,1927.0,1972.0,0.0,False,True
+days_to_birth,int64,117,115,0,,-30246.0,-13684.0,,False,True
+gender,object,117,1,0,117,,,1.0,True,False
+race,object,117,5,0,103,,,1.0,True,False
+ethnicity,object,117,3,0,106,,,0.0,False,True
+bmi,float64,117,117,0,,16.65625,52.79704179,,False,True
+alcohol_history,object,117,3,0,55,,,1.0,True,False
+alcohol_intensity,float64,40,17,77,,0.0,14.0,,False,True
+smokestat_apollo2,object,116,4,1,73,,,0.6666666666666666,False,True
+cigarettes_per_day2,float64,32,10,85,,0.5,60.0,,False,True
+years_smoked2,float64,32,21,85,,1.0,55.0,,False,True
+family_cancer_history,object,91,81,26,5,,,,False,True
+dzextent_beyondabd,object,54,3,63,40,,,1.0,True,False
+dzextentpriortosurg,object,115,6,2,38,,,0.2,False,True
+primary_diagnosis,object,117,39,0,15,,,0.0,False,True
+site_of_resection_or_biopsy,object,117,18,0,50,,,0.6111111111111112,False,True
+classification_of_tumor,object,117,2,0,68,,,1.0,True,False
+stage_figo_2014,object,115,7,2,85,,,1.0,True,False
+morphology,object,117,1,0,117,,,1.0,True,False
+celltype,object,117,1,0,117,,,1.0,True,False
+tumor_grade,object,117,4,0,90,,,0.5,False,True
+sticpresent,object,115,3,2,95,,,1.0,True,False
+brcastat,object,113,4,4,79,,,1.0,True,False
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+fuflag,object,115,9,2,53,,,0.125,False,True
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+vital_status,object,117,2,0,63,,,1.0,True,False
+causeofdeath_apollo2,object,53,4,64,45,,,0.6666666666666666,False,True
+year_of_death,float64,54,7,63,,2009.0,2014.0,,False,True
+days_to_death,float64,54,54,63,,77.0,1720.0,,False,True
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samples/APOLLO-2.txt

@@ -0,0 +1,493 @@
+Clin Pharmacol Ther. 2019 Jul; 106(1): 52–57.  Published online 2019
+Apr 29. doi: 10.1002/cpt.1425 PMCID: PMC6617989 PMID: 30838639
+
+From
+Discovery to Practice and Survivorship: Building a National Real‐World
+Data Learning Healthcare Framework for Military and Veteran Cancer
+Patients Jerry S. H. Lee,corresponding author 1 , 2 , 3 , 4 , 5 , 6
+Kathleen M. Darcy, 4 , 7 , 8 Hai Hu, 9 Yovanni Casablanca, 7 , 8
+Thomas P. Conrads, 10 Clifton L. Dalgard, 11 , 12 John B. Freymann, 13
+Sean E. Hanlon, 5 Grant D. Huang, 6 Leonid Kvecher, 9 George
+L. Maxwell, 10 Frank Meng, 14 , 15 Joel T. Moncur, 16 Clesson Turner,
+17 Justin M. Wells, 18 Matthew D. Wilkerson, 4 , 11 , 12 Kangmin Zhu,
+8 Rachel B. Ramoni, 6 and Craig D. Shriver corresponding author 8 , 19
+Author information Article notes Copyright and License information
+Disclaimer
+
+The Applied Proteogenomics OrganizationaL Learning and Outcomes
+(APOLLO) network is implementing a prospective curation and
+translation of real‐world data (RWD) into real‐world evidence (RWE)
+within the learning healthcare environment of the Department of
+Defense and Department of Veterans Affairs. To support basic,
+translational, clinical, and epidemiological sciences, APOLLO will
+release data to public repositories for secondary analysis to assist
+others in assessing whether similar molecular‐driven clinical practice
+guidelines will improve health outcomes for their relevant cancer
+populations.
+
+In the United States, > 80% of patients with cancer are initially
+diagnosed and treated in a community hospital setting rather than an
+academic hospital setting. Despite the increased adoption of
+electronic health records (EHRs), the lack of interoperable health
+information systems makes it challenging to aggregate RWD generated
+from a cancer patient’s journey before diagnosis, during treatment,
+and throughout survivorship. RWD might include data collected as part
+of routine health and cancer care delivery or for research
+(translational, implementation science, and/or epidemiological)
+efforts. Longitudinal collection of RWD is essential to generating RWE
+and is often absent when elucidating long‐term consequences of care
+strategies.
+
+Recent studies have demonstrated the success of individualized cancer
+care strategies enabled by molecular profiling and targeted
+therapies. In the past 2 years, the US Food and Drug Administration
+(FDA) has approved tumor site–agnostic, biomarker‐driven cancer
+treatments and next‐generation sequencing in vitro diagnostic
+devices.1 A parallel review process by the Center for Medicare &
+Medicaid Services led to a national coverage determination
+next‐generation sequencing‐based in vitro diagnostics. The rapid
+development and approval of such technologies underscored this
+widening gap in capturing real‐world use of molecular‐driven cancer
+care to generate RWE to help inform regulatory and clinical
+decisions.2
+
+Conducting valid real‐world studies requires data quality assurance
+through auditable data abstraction methods and incentives to drive
+electronic capture of data during delivery of care.2 The Department of
+Veterans Affairs (VA) has the nation's largest integrated healthcare
+system with over 9 million veterans enrolled and is a high‐volume
+provider of cancer care with nearly 50,000 incident cancer cases
+reported in 2010.3 The VA Office of Research and Development has as
+its three major priorities to: (i) enhance veteran access to multisite
+clinical trials, (ii) make VA data a national resource, and (iii)
+increase the real‐world impact of research findings. The VA Office of
+Research and Development's national Cooperative Studies Program4 and
+data resources enable researchers to access and identify initial
+cohorts for further studies to advance RWD analysis have been
+leveraged through partnerships with federal collaborators to further a
+learning health care system within the VA. The Department of Defense
+(DoD) Military Health System (MHS) is responsible for maintaining the
+health and readiness of 1.7 million active‐duty and reserve service
+members (SMs) and caring for 9.4 million beneficiaries in TRICARE
+health benefit plans. The John P. Murtha Cancer Center at Uniformed
+Services University and Walter Reed National Military Medical Center
+offers a comprehensive cancer care operational view in 64 capability
+areas to proactively mitigate and close gaps in cancer care and
+research in the MHS. The John P. Murtha Cancer Center utilizes
+agreements with other federal agencies and extramural collaborators to
+provide return on investment by deploying the most robust and modern
+molecular technologies under various programs. The administrative and
+medical care data from both direct and indirect care are stored in the
+military data repository, which includes detailed information on
+demographics, diagnoses, diagnostic procedures, prescriptions,
+ancillary and radiology services, treatments, cost of care, and vital
+status. The DoD also has a cancer registry that collects detailed data
+on cancer diagnosis and features, including some cancer
+biomarkers. These RWD have been widely used for cancer research among
+DoD beneficiaries.5, 6
+
+Leveraging the two largest nationwide connected healthcare systems,
+the APOLLO network was launched in 2016 with the intent of curating
+longitudinal RWD and health outcome data to create and assess adoption
+of new molecular‐driven clinical practice guidelines. By developing,
+defining, and aligning RWD elements of MHS, patients with cancer from
+prediagnosis through survivorship among the federal and civilian
+partners, the APOLLO network is implementing an integrated
+multifederal network for prospective curation and translation of RWD
+into RWE in a learning healthcare environment that will assist other
+payers in assessing whether similar clinical practice guidelines will
+improve health outcomes for their relevant populations.
+
+MOVING TOWARD RWD: LESSONS LEARNED AND ONGOING PILOTS TO BUILD
+THE APOLLO ECOSYSTEM Previous large‐scale tumor characterization
+projects, such as The Cancer Genome Atlas and the ongoing Clinical
+Proteomics Tumor Analysis Consortium, focused on analyzing the
+genomics and proteomics profile of tumors at a single time point.7 The
+lack of focus on longitudinal RWD collection limits the clinical
+utilization of these programs’ data.8 APOLLO is distinct from The
+Cancer Genome Atlas and other previous tumor characterization projects
+as it was focused on integrated proteogenomic analyses, the collection
+of longitudinal RWD, and development of a sustainable collection
+pipeline from its inception. The foundation of the approach is a
+network of biospecimen collection sites throughout the DoD and VA plus
+select civilian sites. APOLLO tissue collection is infused into
+pathology departments to preserve patient care, optimize collections,
+and control for preanalytic variables while involving the local
+organizations as true partners. This culture of collaboration also
+promotes the capture of longitudinal clinical, radiology imaging, and
+patient data throughout patients’ disease cycles that can otherwise be
+difficult to obtain. This culture expands to Clinical Laboratory
+Improvement Amendment (CLIA) laboratories, biobanking, imaging
+characterization, and proteogenomic analysis centers to form a robust
+APOLLO ecosystem that will be leveraged to enable additional
+longitudinal oncology studies of both established and new patients.
+
+To maximize longitudinal clinical data collection, APOLLO uniquely
+designed a combination of disease‐specific pilot retrospective studies
+of hundreds of cases (APOLLOs 1–4) and prospective studies of ~ 8,000
+cases (APOLLO 5). Successes and lessons learned during the
+implementation of these pilot projects, as well as those from past
+large‐scale molecular and clinical studies, are being leveraged to
+successfully forge the APOLLO ecosystem. Central to generating RWE
+from RWD in combination with molecular data is the challenge of
+balancing effective biospecimen matching and integration of data from
+multiple modalities from the same patient while maintaining accuracy
+and privacy over time. One way the network tackled this issue was
+bringing together early stakeholders to develop and adopt a
+prospectively generated unique APOLLO participant and aliquot
+identifiers (APOLLO ID; Figure 1). APOLLO ID will also be linked to a
+128‐byte global unique participant and aliquot identifiers with an
+“AP‐” prefix when data are uploaded to public repositories for
+secondary analysis. The APOLLO system is electronically supported by
+an enterprise informatics infrastructure, which includes a Data
+Tracking System (DTS‐APOLLO) for transactional activities, a Data
+Warehouse for Translational Research for (DW4TR‐APOLLO),9 and a
+network of connected public data repositories to support capturing,
+management, and delivery of RWD to the study team and the public to
+enable discovery of RWE. Initial pilot datasets have been successfully
+uploaded to the National Cancer Institute's Genomic Data Commons and
+The Cancer Imaging Archive (TCIA) from both VA and DoD studies. The
+length of patient follow‐up time within APOLLO will be pre‐estimated
+for each cancer type using prior literature rather than by duration of
+a funding cycle, so advanced planning will enable continued capturing
+of such data from both the regulatory and technical perspectives.
+
+An external file that holds a picture, illustration, etc.  Object name
+is CPT-106-52-g001.jpg Figure 1 Applied Proteogenomics OrganizationaL
+Learning and Outcomes (APOLLO) data ecosystem and workflow to enable
+longitudinal real‐world data (RWD) collection and analysis. Clinical
+activities are separated from research functions by a firewall so that
+only de identified, limited datasets are available for research and
+further, only safe‐harbor datasets are made publicly
+available. Patient will be followed from the time of diagnosis through
+remission and when disease recurs, for as long as possible. Tracking
+of all such RWD is enabled by APOLLO IDs in a program‐wide Data
+Tracking System for APOLLO (DTS‐APOLLO). Activities in molecular
+center are tracked by local LIMS with metadata and higher‐level
+molecular data tracked in DTS‐APOLLO. Transactional data in DTS‐APOLLO
+will be quality assured and integrated in the Data Warehouse for
+Translational Research for APOLLO (DW4TR‐APOLLO) for integrated
+analysis to generate real‐world evidence (RWE), which will in turn
+directly impact patient clinical services. Lower‐level raw molecular
+and imaging data of very large size, on the other hand, will be
+directly uploaded to public data repositories, including The Cancer
+Imaging Archive (TCIA),11 Genomic Data Commons (GDC),12 and upcoming
+Proteomic Data Commons (PDC) maintained by the National Cancer
+Institute (NCI) following appropriate protocols and regulatory
+procedures coordinated through DW4TR‐APOLLO. Such raw data, after
+integration with the data in the DW4TR‐APOLLO enabled by APOLLO ID,
+will become substrates for integrated research analysis for hypothesis
+generation and testing, which will be the basis for the design of new
+scientific experiments and clinical trials with results will
+eventually impact future patient clinical care. Solid lines are for
+clinical‐grade RWD and dotted lines for research‐grade RWD. DoD,
+Department of Defense; EHR, electronic health record; VA, Veteran's
+Affairs.
+
+LOOKING AHEAD: INITIAL EFFORTS TO ELEVATE RWD TO RWE The APOLLO
+program aspires to accelerate the application of next‐generation
+proteogenomic profiling with deep baseline and longitudinal RWD from
+DoD and VA EHRs and research records into RWE for FDA‐approved tests
+and treatments for development and deployment of tools and strategies
+used in the prevention, diagnosis, and treatment of cancer. These
+activities support readiness and health by empowering patients and
+providers to optimize their care and health through customized and
+enterprise solutions. The program will deploy both retrospective and
+prospective observational designs with provisions for clinical trial
+participation. Select civilian cohorts with aggressive or rare cancers
+will be incorporated with SMs and veterans to contribute diversity,
+events, experiences, and outcomes to the disease‐oriented and
+pan‐cancer cohorts to learn about, treat, and prevent cancers that
+develop in warfighters.
+
+Types of clinical and research RWD that will be collected by the
+APOLLO network are listed in Table 1. This program will require and
+utilize operationalized processes and procedures tracked via a
+user‐friendly APOLLO Dashboard. Integrated analyses will incorporate a
+deep complement of RWD from medical and research records. Sequencing
+and proteomic data generated by CLIA facilities and analytical core
+facilities will not only be analyzed using current clinical databases
+but will be available for iterative reanalysis over time applying new
+clinical databases and trusted sources to advance reinterpretation of
+the patients’ molecular profiling data to determine future access to
+new FDA‐approved drugs and/or clinical trial opportunities. This
+program will provide data in support studies of basic science,
+translational medicine, epidemiology, comparative effectiveness,
+cost‐effectiveness, and health disparities. Various data‐release
+provisions were incorporated into the APOLLO framework, including
+release to repositories for future research, clinical trials,
+indications and guidelines, dissemination to scientists, healthcare
+professionals, and the public, release to study doctors when research
+results meet guidelines for medical consideration for follow‐up and
+clinical assessments, and return to patients when the research results
+qualifies for release without clinical certification, as recommended
+recently by the National Academies of Sciences, Engineering, and
+Medicine.10
+
+Table 1 Types of RWD from medical and research records for APOLLO
+
+Captured into smart electronic clinical reporting and XML forms with
+data dictionaries, valid value requirements, logging features, and
+business rules. Data elements are labeled with a unique coded APOLLO
+ID participant identifier.  Baseline data: Registration, eligibility,
+consent, demographics, height, weight, risk factors, smoking status,
+marital status, type of insurance, medical history, medications,
+supplements, reproductive history, and family cancer history.
+Surgical treatment: Surgical date, surgical procedures performed, AJCC
+stage with edition details, and disease site–specific surgical
+findings, including primary tumor size, disease distribution (location
+and size pre/post surgery), residual disease status, military disease,
+laterality, margins, redacted operative report(s), and comments.
+Pathologic findings: Diagnosis date, definitive surgery date, ICD site
+and behavior codes, detailed College of American Pathology electronic
+cancer checklist13 with harmonized data dictionaries and conversion
+between versions, redacted pathology reports, including cytologic
+findings, clinical biomarker assessments, and other findings.
+Case‐level data: Case organ type, lesion type, malignancy type,
+primary site of diagnosis, ICD‐10 code, histology code, TNM edition
+number, pathological group stage at diagnosis, CAP organ data creation
+status, and biomarker creation status.  Research pathology
+characterization: Baseline and in‐depth research pathology
+characterization will be provided and compared with the clinical
+diagnosis for tumor samples by expert pathologists and tissue imaging
+researchers. The types of annotation may include tissue composition
+details, clinical biomarker staining, and computer‐generated
+annotation in imaged slides with intact tumor tissues or tissues
+before and after laser microdissection.  Molecular data: Including
+redacted report, primary findings, and secondary findings when
+applicable from CLIA testing, clinical recommendations, clinical
+actions taken and outcomes, and XML data from CLIA assays when
+available implementing best practices and guidelines from the College
+of American Pathology, American Society of Clinical Oncology, National
+Comprehensive Cancer Network, and American College of Genetics and
+Genomic for risk assessments, interpretation, certification, and
+genetic counseling health conditions, including cancer.  DoD uses the
+Illumina TruSight Tumor 15 tumor profiling assay with plans to deploy
+the TruSight Oncology 500 tumor profiling DNA + RNA assay. VA uses the
+Personalis AC CancerPlus DNA + RNA assay to evaluate 181 clinically
+actionable genes or the PGDx Cancer Select 125 assay. Research
+analytical facilities generate next generation sequencing and multiple
+proteomic data. Immunoassay, cell‐free DNA, metabolomic, glycoprotein,
+and lipidomic data may be available in subsets.  Clinical imaging: May
+be acquired when accessible from medical records, imaging facilities,
+and research records with regulatory approval and consent at a
+baseline time point and as longitudinal series of collections to
+monitor and document disease distribution patterns and features
+utilizing enterprise solutions by the VA and customized solutions by
+DoD programs in partnership with TCIA.  Baseline details regarding
+imaging, including method, contrast, facility location, and dates for
+acquisition, curation, and submissions to and receipt of annotation.11
+Disease‐oriented features will be annotated by expert radiologists
+using custom workstation configuration and standardized data
+dictionary, including assessments of mass: laterality, calcifications,
+thick septations, internal architecture; disease: presence,
+calcification, locations, shape; ascites or effusion: volume;
+lymphadenopathy: pathologic lymph nodes.  Computer‐generated features,
+including but not limited to segmentation using machine learning and
+artificial intelligence.  Pharmacologic therapies: Pharmacologic
+therapy status by regimen, treatment line, or indication with
+individual agent details with drug name, ICD‐O cancer site for
+treatment, doses, route/delivery method, cycles, date first dose/start
+date, date last dose/end date, dose schedule, active medication, dose
+reduction, treatment selection (approved assay or an integral,
+integrated, or exploratory biomarker), best response, and serious
+adverse events.  FDA indication with companion diagnostic assays:
+Non‐small cell lung cancer: Treat an EGFR exon 19 deletions or EGFR
+exon 21 L858R alterations with afatinib, gefitinib, or erlotinib; an
+EGFR exon 20 T790M alteration with osimertinib; ALK rearrangement with
+alectinib, crizotinib, or ceritinib; BRAF V600E with dabrafenib and
+trametinib. Melanoma: Treat BRAF V600E with dabrafenib or vemurafenib;
+BRAF V600E or V600K with trametinib or cobimetinib with
+vemurafenib. Breast cancer: Treat ERBB2/HER2 amplification with
+trastuzumab, ado‐trastuzumab emtansine, or pertuzumab. Colorectal
+cancer: Treat wild‐type KRAS (absence of mutations in codons 12 and
+13) with cetuximab; wild‐type KRAS (absence of mutations in exons 2,
+3, and 4) or wild‐type NRAS (absence of mutations in exons 2, 3, and
+4) with panitumumab. Ovarian cancer: Treat BRCA1/2 alterations with
+rucaparib. Treatment of adult and pediatric patients with cancer with
+an NTRK fusion, including solid tumors and hematologic malignancies
+with larotrectinib.  Radiotherapies: Radiotherapy status by location,
+indication, radiation treatment line/regimen, laterality, field
+treated, radiation site code (ICD‐O), start date, end date, number of
+fractions, dose/fraction cGy, total dose cGy, best response, and best
+response assessment method, and comments.  Outcome assessments: If
+living: Disease status (alive with disease, no evidence of disease),
+date of last visit or date last activity if different than visit and
+capture individual dates of recurrence or progression with assessment
+method(s) and additional details when available. If deceased: Date of
+death and cause of death (cancer‐related, noncancer related, and
+unknown), if other cause then specify. Clinical trial participation
+will also be documented.  Epidemiologic data: May be provided directly
+by patients or with research staff during interviews with patients
+using a standardized data dictionary. Veterans may also contribute
+data through the Million's Veterans Program.  Patient demographics,
+including race, ethnicity, sex, marital status, education, employment,
+and military service. Medical history regarding health conditions,
+prior cancer diagnoses and treatments, height, and weight. Physical
+activity for 12 months prior to the current diagnosis. Alcohol history
+in entire life and currently. Tobacco products use in entire life and
+currently. Work environment, including occupations, exposures, and
+deployments. Family cancer history for blood relatives, including half
+blood relatives. Reproductive history for women.  Patient‐reported
+outcomes: Using validated instruments from trusted sources.  Patient
+Reported Outcomes Measurements for Personalizing Treatment (PROMPT
+Assessments): Quality of life using the 28‐item FACT‐G for physical,
+social/family, emotional, and functional well‐being. Global health
+using the 10‐item PROMIS Global Health version 1.2 instrument. Pain
+and fatigue using the 3‐item PROMIS Pain 3a and the 4‐item PROMIS
+Fatigue 4a instruments. Stress, anxiety, and depression combination
+using the 10‐item NIH ToolBox Perceived Stress, 4‐item PROMIS Anxiety
+4a, and 4‐item PROMIS Depression 4a instruments. Symptoms using the
+4‐item FACT‐NTX‐4, the 4‐item PROMIS Cognitive Function 4a, and the
+4‐item PROMIS Sleep Disturbance 4a instruments. Support for daily
+living using the 11‐item PROMIS Instrumental Support version 2.0
+instrument.  Focus assessments using validated instruments from
+trusted sources and working to deploy novel surveys to address gaps
+and support prevention, survivorship, palliative and end‐of‐life care
+to strengthen cancer capabilities across the continuum from
+prevention, early detection, treatment selection, mitigation of
+effects, rehabilitation, and survivorship, including palliative and
+end‐of‐life care. This may include assessments of barriers to care,
+patient preferences regarding treatment and care, resilience, cancer
+pain management, young adult survivorship, and serious adverse event
+reporting.  Open in a separate window AJCC, American Joint Commission
+on Cancer; ALK, anaplastic lymphoma kinase; APOLLO, Applied
+Proteogenomics OrganizationaL Learning and Outcomes; BRAF, B‐type Raf;
+BRCA, breast cancer; CAP, College of American Pathologists; cGy,
+centigray; CLIA, Clinical Laboratory Improvement Amendment; DoD,
+Department of Defense; EGFR, epidermal growth factor receptor; ERBB,
+erythroblastic leukemia viral oncogene; FACT‐G, functional assessment
+of cancer therapy general; FDA, US Food and Drug Administration; HER2,
+human epidermal growth factor receptor 2; ICD‐10, International
+Classification of Disease‐10th edition; ICD‐O, International
+Classification of Disease for Oncology; KRAS, Kirsten RAt Sarcoma
+virus; NTRK, Neurotrophic tropomyosin receptor kinase; PGDx, Personal
+Genome Diagnostics; PROMIS, Patient‐Reported Outcomes Measurement
+Information System; RWD, real‐world data; TCIA, The Cancer Imaging
+Archive; TNM, Tumor, Node, Metastasis staging system; VA, Veteran's
+Affairs.
+
+Translation of RWD into RWE is a key component of APOLLO with
+integrated systems for enhancing capabilities across the cancer care
+continuum, driving efficiencies, and enhancing quality, thereby
+improving health outcomes and the readiness of warfighters and the
+operational medical force. The full potential of APOLLO will be
+realized when interoperable EHRs are readily and securely exchangeable
+across the DoD and VA with enterprise solutions and clinical decision
+tools for molecular pathology, clinical imaging, patient‐reported
+outcomes, clinical trials, serious adverse events reporting,
+prevention clinics, rehabilitative and other supportive services, pain
+management, survivorship, palliative care, end‐of‐life care, research,
+and education.
+
+RETURN ON INVESTMENT: LEVERAGING RWD AND RWE FOR DOD, VA, AND
+THE GLOBAL CANCER ECOSYSTEM Improvements in readiness, health care,
+and outcomes for SMs, veterans, health beneficiaries, and civilians
+will be achieved not only from deliverables generated by the APOLLO
+network but also from release of RWD and RWE to the public for
+secondary research. APOLLO patients may also benefit from release of
+research data that qualify either for clinical certification or direct
+release based on criteria, such as level and quality of the
+evidence. Federal agencies may also benefit from the generated
+agreements, established working groups, and taskforces with
+representation from the stakeholders and invited nonfederal experts,
+aligned resources and assets, integrated and expanded infrastructure
+and workforces, and the capabilities developed for APOLLO and
+operationalized across the DoD and VA for implementing precision
+oncology solutions to acquire and translate RWD from APOLLO into RWE
+for SMs, veterans, and the global cancer ecosystem.
+
+Funding Funding for these efforts was provided from Uniformed
+Services University of the Health Sciences (USUHS) awards from the
+Defense Health Program to the Murtha Cancer Center Research Program
+(HU0001‐16‐2‐0014, C.D. Shriver and J.S.H. Lee), the Gynecologic
+Cancer Center of Excellence (HU0001‐16‐2‐0006, Y. Casablanca and
+G. Larry Maxwell), and HU0001‐16‐2‐004 (L. Kvecher and H. Hu)
+administered by the Henry M. Jackson Foundation for the Advancement of
+Military Medicine. This project has also been funded in whole or in
+part with federal funds from the National Cancer Institute, National
+Institutes of Health, under Contract No. HHSN261200800001E
+(J.B. Freymann).
+
+Conflict of Interest The authors declared no competing
+interests for this work.
+
+Disclaimer The contents of this publication are the sole
+responsibility of the authors and do not necessarily reflect the
+views, opinions, or policies of the USUHS, the Henry M. Jackson
+Foundation for the Advancement of Military Medicine, Inc., the
+Department of Defense (DoD), the Departments of the Army, Navy, or Air
+Force, Department of Health and Human Services, or Department of
+Veterans Affairs. Mention of trade names, commercial products, or
+organization does not imply endorsement by the U.S. Government.
+
+Acknowledgments The authors would like to thank Joseph Shaw,
+Sara Sakura, Autumn Beemer Phillips, Gregory Samuel, Olga Castellanos,
+Jillian Infusino, and Mayada Aljehani for their critical review of the
+figure and paper.
+
+Contributor Information Jerry S. H. Lee, Email:
+ude.csu@yrrej.rd.
+
+Craig D. Shriver, Email: lim.liam@vic.revirhs.d.giarc.
+
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+
+10. Returning individual research results to participants: guidance
+for a new research paradigm. National Academies of Sciences,
+Engineering, and Medicine
+<http://nationalacademies.org/hmd/Reports/2018/returning-individual-research-results-to-participants.aspx>
+(2018). Accessed February 12, 2019.
+
+11. APOLLO‐1‐VA pilot lung cancer study data in The Cancer Imaging
+Archive (TCIA)
+<https://wiki.cancerimagingarchive.net/display/Public/APOLLO-1-VA>
+(2018). Accessed February 12, 2019.
+
+12. APOLLO‐1‐VA pilot lung cancer study data in Genomic Data Commons
+(GDC) <https://portal.gdc.cancer.gov/projects/VAREPOP-APOLLO>
+(2018). Accessed February 12, 2019.
+
+13. College of American Pathologists: cancer protocol templates
+<http://www.cap.org/cancerprotocols> (2019). Accessed February 12,
+2019.

samples/APOLLO-2_description.txt

@@ -0,0 +1,21 @@
+The Applied Proteogenomics Organizational Learning and Outcomes
+(APOLLO) network is a collaboration between NCI, the Department of
+Defense (DoD), and the Department of Veterans Affairs (VA) to
+incorporate proteogenomics into patient care as a way of looking
+beyond the genome, to the activity and expression of the proteins that
+the genome encodes. The emerging field of proteogenomics aims to
+better predict how patients will respond to therapy by screening their
+tumors for both genetic abnormalities and protein information, an
+approach that has been made possible in recent years due to advances
+in proteomic technology.
+
+The APOLLO network collects data that include a full set of medical
+images, including CT and MRI scans, obtained before and during
+treatment. Each set of images can be connected to the patient’s
+genomic, proteomic, and clinical data. The real data will be made
+available publicly through the Genomic Data Commons, Proteomics Data
+Commons, and Cancer Imaging Archive. By using all available data,
+researchers will be able to study the relationships among these data,
+validate results, and develop predictive and prognostic models to
+improve patient care. Aligning this data with the NCI Cancer Research
+Data Commons is currently a time intensive manual effort.

samples/APOLLO-5-leaderboard.tsv

@@ -0,0 +1,2 @@
+race	ethnicity	prior_malignancy	alcohol_history	smokestat_apollo2	any_family_cancer_history	dxextent_prenact	dzextent_beyondabd	dzextentpriortosurg	site_code	stage_figo_2014	tumor_stage	celltype	tumor_grade	sticpresent	intraepilocation	disease_distribution	diseasehigh	miliarypresent	residual_disease	anyresidualdisease	last_known_disease_status	progression_or_recurrence	survival_status	vital_status	causeofdeath_apollo2	dtdatalocked	project_id	submitter_id	encounter	date_of_consent	year_of_birth	days_to_birth	age_at_diagnosis	gender	specify_prior_malignancy	height	weight	bmi	alcohol_intensity	cigarettes_per_day2	years_smoked2	family_cancer_history	primary_diagnosis	classification_of_tumor	morphology	brcastat	pfstimeindays	pfs_status	survivaltimeindays	year_of_death	days_to_death	days_to_treatment	therapeutic_agents	treatment_intent_type	treatment_or_therapy	dtform_apollo2	form_by_apollo2	dt_amend_apollo2	form_aby_apollo2	brca1ihc_apollo	days_to_last_follow_up	days_to_last_known_disease_status	fuflag	days_to_recurrence
+1	1		1			1		1			1				1			1			1			1		1		1		1		1		1		1			1			1		1		1			1			1				1				1		1		1			1		1		1		1		1		1		1		1			1	1				1	1	1	1			1			1		1			1			1			1		1		1		1		1			1		1		1			1			1			1			1		1		1			1			1		1			1					1	1	1	1	1	1	1	1	1	1	1	1	

samples/Apollo-5-headings.txt

@@ -0,0 +1 @@
+race, ethnicity, prior_malignancy, alcohol_history, smokestat_apollo2, any_family_cancer_history, dxextent_prenact, dzextent_beyondabd, dzextentpriortosurg, site_code, stage_figo_2014, tumor_stage, celltype, tumor_grade, sticpresent, intraepilocation, disease_distribution, diseasehigh, miliarypresent, residual_disease, anyresidualdisease, last_known_disease_status, progression_or_recurrence, survival_status, vital_status, causeofdeath_apollo2, dtdatalocked, project_id, submitter_id, encounter, date_of_consent, year_of_birth, days_to_birth, age_at_diagnosis, gender, specify_prior_malignancy, height, weight, bmi, alcohol_intensity, cigarettes_per_day2, years_smoked2, family_cancer_history, primary_diagnosis, classification_of_tumor, morphology, brcastat, pfstimeindays, pfs_status, survivaltimeindays, year_of_death, days_to_death, days_to_treatment, therapeutic_agents, treatment_intent_type, treatment_or_therapy, dtform_apollo2, form_by_apollo2, dt_amend_apollo2, form_aby_apollo2, brca1ihc_apollo, days_to_last_follow_up, days_to_last_known_disease_status, fuflag, days_to_recurrence

samples/Outcome-Predictors-leaderboard.csv

@@ -0,0 +1,46 @@
+,Round,TCGAID,MajorAxisLength,MinorAxisLength,PropnCET,T1FLAIR,nCETCrossMidline,rCBVmean,rCBVmax,rCBVfl,Machine,Subtype_by_phils,Subtype_by_Verhaak,age_at_initial_pathologic_diagno,date_of_initial_pathologic_diagn,days_to_birth,days_to_death,days_to_last_followup,ethnicity,gender,histological_type,karnofsky_performance_score,performance_status_scale_timing,person_neoplasm_cancer_status,prior_glioma,race,tumor_histologic_subtype,tumor_tissue_site,vital_status,days_to_tumor_recurrence,time_to_progression,progEvent,progSurvTime,OStime,rCBVmeanSD,rCBVmaxSD,rCBVflSD,rCBVmean2,rCBVmax2,rCBVfl2,age5,cohort,gcimp,egfrAmp,pdgfraAmp,ptenAmp,egfrMut,ptenMut,sequenced,Extent_of_Resection
+0,1,TCGA-06-0122,71.47023114,40.43448767,None (0%),Mixed T1<FLAIR Ratio,Crosses Midline No,6.86,9.483,1.467,3T,Mes,Mesenchymal,84,2006-00-00,-30967,181,8,NOT HISPANIC OR LATINO,FEMALE,,,,,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,181,181,7.0280743631,4.8061079943,2.9471538976,high,high,high,16.8,6,NEG,2.0,0.0,-1.0,,,1,STR
+1,1,TCGA-06-0127,86.97233129,55.44624428,6-33%,Mixed T1<FLAIR Ratio,Crosses Midline Yes,4.243,5.973,1.177,1.5T,PN,Neural,67,2002-00-00,-24502,121,108,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,90.0,1,90,121,4.3469561986,3.0271942476,2.3645536043,high,high,high,13.4,2,NEG,2.0,0.0,-1.0,"V292L,V292L,V292L",,1,STR
+2,2,TCGA-06-0128,68.54275415,55.25454465,34-67%,Expansive T1~FLAIR Ratio,Crosses Midline No,1.388,2.83,0.713,1.5T,PN,Proneural,66,2000-00-00,-24217,691,691,NOT HISPANIC OR LATINO,MALE,,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,189.0,1,189,691,1.4220068828,1.4342808841,1.432393135,low,low,low,13.2,0,POS,0.0,0.0,-1.0,,,1,GTR
+3,1,TCGA-06-0132,90.38251662,62.26697312,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.173,6.127,0.837,1.5T,PN,Neural,49,2007-00-00,-18125,761,570,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,482.0,1,482,761,2.2262398821,3.1052434547,1.6815049845,low,high,high,9.8,7,NEG,2.0,0.0,-1.0,,,1,STR
+4,1,TCGA-06-0133,102.8050346,62.89969015,34-67%,Mixed T1<FLAIR Ratio,Crosses Midline Yes,2.435,4.663,0.553,3T,PN,Neural,64,2007-00-00,-23402,435,428,NOT HISPANIC OR LATINO,MALE,,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,78.0,1,78,435,2.4946590487,2.363269174,1.1109584904,high,high,low,12.8,7,NEG,2.0,0.0,-1.0,,,1,STR
+5,1,TCGA-06-0137,101.8218393,56.31768036,None (0%),Mixed T1<FLAIR Ratio,Crosses Midline No,2.53,4.317,0.717,1.5T,Mes,Classical,63,2003-00-00,-23273,812,701,NOT HISPANIC OR LATINO,FEMALE,,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,487.0,1,487,812,2.5919866091,2.1879118645,1.4404290011,high,low,low,12.6,3,NEG,2.0,0.0,-1.0,P596L,,1,STR
+6,1,TCGA-06-0139,80.6709788,39.04821797,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.112,4.497,1.24,3T,Mes,Mesenchymal,40,2006-00-00,-14728,383,327,NOT HISPANIC OR LATINO,MALE,,60.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,152.0,1,152,383,2.1637453433,2.2791382105,2.4911184956,low,high,high,8.0,6,NEG,1.0,0.0,-1.0,,,1,STR
+7,1,TCGA-06-0143,114.8301745,65.62670418,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline Yes,2.393,5.657,0.353,3T,Mes,Mesenchymal,58,2006-00-00,-21386,357,357,NOT HISPANIC OR LATINO,MALE,,60.0,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,264.0,264.0,1,264,357,2.451630022,2.8670413291,0.7091651846,low,high,low,11.6,6,NEG,2.0,2.0,-1.0,,,1,STR
+8,1,TCGA-06-0147,74.49334479,51.14346067,None (0%),Expansive T1~FLAIR Ratio,Crosses Midline No,2.24,4.76,0.865,1.5T,Mes,Mesenchymal,51,1999-00-00,-18742,541,508,NOT HISPANIC OR LATINO,FEMALE,,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,92.0,1,92,541,2.2948814247,2.4124300383,1.7377560473,low,high,high,10.2,-1,NEG,1.0,0.0,-1.0,,,1,STR
+9,1,TCGA-06-0149,90.87360905,48.56049078,68-95%,Infiltrative T1<<FLAIR Ratio,Crosses Midline Yes,2.51,3.99,2.057,3T,Mes,Mesenchymal,74,2005-00-00,-27315,262,238,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,203.0,1,203,262,2.5714965964,2.0221840027,4.1324441495,high,low,high,14.8,5,NEG,1.0,0.0,-1.0,,,0,STR
+10,1,TCGA-06-0164,66.76339735,46.13628674,None (0%),Expansive T1~FLAIR Ratio,Crosses Midline No,1.768,4.363,0.607,1.5T,Mes,Mesenchymal,47,2000-00-00,-17510,1730,1729,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,ASIAN,Glioblastoma multiforme,BRAIN,DECEASED,,1428.0,1,1428,1730,1.8113171245,2.2112252641,1.2194426829,low,low,low,9.4,0,NEG,1.0,0.0,-1.0,,,0,GTR
+11,1,TCGA-06-0166,79.76086734,74.46603485,< 5%,Mixed T1<FLAIR Ratio,Crosses Midline No,3.038,4.47,0.763,1.5T,PN,Proneural,51,2001-00-00,-18902,178,161,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,66.0,1,66,178,3.1124329322,2.2654542586,1.5328414614,high,low,high,10.2,1,NEG,1.0,2.0,-1.0,,"T167S,T167S",1,STR
+12,1,TCGA-06-0168,44.13221598,24.29751635,6-33%,Infiltrative T1<<FLAIR Ratio,Crosses Midline No,1.37,3.303,0.62,1.5T,Mes,Neural,59,2002-00-00,-21776,598,579,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,461.0,1,461,598,1.4035658713,1.6740034488,1.2455592478,low,low,low,11.8,2,NEG,1.0,0.0,-1.0,,A328fs,1,STR
+13,1,TCGA-06-0173,107.1367651,52.88218154,6-33%,Infiltrative T1<<FLAIR Ratio,Crosses Midline Yes,2.027,3.73,0.96,3T,Prolif,Neural,72,2003-00-00,-26548,171,7,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,171,171,2.0766627892,1.890412614,1.9286078676,low,low,high,14.4,3,NEG,2.0,2.0,-1.0,,,1,STR
+14,1,TCGA-06-0175,58.76606943,37.35171235,None (0%),Infiltrative T1<<FLAIR Ratio,Crosses Midline No,2.12,3.63,0.577,1.5T,Mes,Mesenchymal,69,2003-00-00,-25558,123,83,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,39.0,1,39,123,2.1719413484,1.8397313107,1.1591736871,low,low,low,13.8,3,NEG,1.0,0.0,-1.0,,,0,GTR
+15,1,TCGA-06-0177,70.2938662,47.73769856,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,1.368,3.067,0.253,1.5T,Prolif,Proneural,64,2004-00-00,-23498,127,60,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,127,127,1.4015168701,1.554395573,0.5082685318,low,low,low,12.8,4,NEG,2.0,2.0,-1.0,,,0,STR
+16,1,TCGA-06-0179,64.06461812,44.22389414,< 5%,Mixed T1<FLAIR Ratio,Crosses Midline No,2.51,5.493,0.623,3T,PN,Neural,64,2004-00-00,-23449,616,578,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,250.0,1,250,616,2.5714965964,2.7839239916,1.2515861474,high,high,low,12.8,4,NEG,2.0,0.0,-1.0,,,0,GTR
+17,1,TCGA-06-0184,82.84546219,64.92510487,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,1.672,3.067,0.71,1.5T,Mes,Mesenchymal,63,2005-00-00,-23317,2126,1228,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,1276.0,1,1276,2126,1.7129650634,1.554395573,1.4263662354,low,low,low,12.6,5,NEG,1.0,0.0,-1.0,,"G36E,G36E,G36E",1,GTR
+18,1,TCGA-06-0185,72.07177397,44.71617175,6-33%,Mixed T1<FLAIR Ratio,Crosses Midline No,1.99,4.267,0.413,1.5T,PN,Neural,54,2005-00-00,-19922,2366,2246,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,711.0,1,711,2366,2.0387562657,2.1625712129,0.8297031764,low,low,low,10.8,5,NEG,2.0,0.0,-2.0,"V651M,V651M,V651M",,1,GTR
+19,1,TCGA-06-0187,65.87112795,44.41677325,None (0%),Expansive T1~FLAIR Ratio,Crosses Midline No,1.835,3.233,0.517,1.5T,Mes,Classical,69,2006-00-00,-25317,828,801,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,531.0,531.0,1,531,828,1.8799586671,1.6385265365,1.0386356953,low,low,low,13.8,6,NEG,2.0,0.0,-1.0,,"G132D,G132D,G132D",1,STR
+20,2,TCGA-06-0189,85.25564146,56.4416166,< 5%,Mixed T1<FLAIR Ratio,Crosses Midline No,2.708,4.99,0.573,3T,Mes,Mesenchymal,55,2006-00-00,-20296,468,454,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,468,468,2.7743477223,2.5289970359,1.1511378209,high,high,low,11.0,6,NEG,2.0,0.0,-1.0,,,1,STR
+21,2,TCGA-06-0190,74.76880933,60.24171094,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,4.376,6.68,1.333,1.5T,Mes,Mesenchymal,62,2006-00-00,-22835,317,313,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,88.0,1,88,317,4.4832147832,3.3855110621,2.6779523828,high,high,high,12.4,6,NEG,1.0,1.0,-1.0,,"D92E,D92E,D92E",1,STR
+22,1,TCGA-06-0192,79.16025289,42.82469307,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.425,4.16,1.22,3T,Mes,Mesenchymal,58,2007-00-00,-21243,1185,556,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,648.0,1,648,1185,2.4844140423,2.1083422183,2.450939165,high,low,high,11.6,7,NEG,2.0,2.0,-1.0,,Y315*,1,GTR
+23,1,TCGA-06-0213,72.9466112,43.71555926,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.167,3.763,0.767,1.5T,Mes,Mesenchymal,55,1998-00-00,-20134,16,6,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,16,16,2.2200928782,1.9071374441,1.5408773275,low,low,high,11.0,-2,NEG,1.0,0.0,-2.0,,"R335*,R335*",1,STR
+24,1,TCGA-06-0237,70.35187771,28.66265438,68-95%,Infiltrative T1<<FLAIR Ratio,Crosses Midline No,3.365,5.537,0.613,1.5T,PN,Neural,75,2006-00-00,-27735,415,314,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,415,415,3.4474446402,2.8062237651,1.2314964821,high,high,low,15.0,6,NEG,2.0,1.0,-1.0,"L62R,L62R",,1,STR
+25,2,TCGA-06-0238,76.80296366,48.00510283,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.346,4.023,0.62,3T,PN,Proneural,46,2007-00-00,-17037,405,359,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,311.0,1,311,405,2.4034784921,2.0389088328,1.2455592478,low,low,low,9.2,7,NEG,1.0,0.0,-1.0,,,1,STR
+26,1,TCGA-06-0241,53.7870232,33.79282207,None (0%),Mixed T1<FLAIR Ratio,Crosses Midline No,2.912,4.43,0.66,3T,Prolif,Proneural,65,2007-00-00,-24101,1481,455,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,100.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,196.0,196.0,1,196,1481,2.9833458521,2.2451817373,1.3259179089,high,low,low,13.0,7,NEG,1.0,2.0,-1.0,,,1,STR
+27,1,TCGA-06-0644,51.55889274,40.19048554,None (0%),Expansive T1~FLAIR Ratio,Crosses Midline No,2.555,4.19,0.617,3T,Mes,Mesenchymal,71,2007-00-00,-26246,384,375,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,BLACK OR AFRICAN AMERICAN,Glioblastoma multiforme,BRAIN,DECEASED,85.0,85.0,1,85,384,2.617599125,2.1235466093,1.2395323482,high,low,low,14.2,7,NEG,1.0,0.0,-1.0,,"T202fs,I203fs",1,STR
+28,1,TCGA-06-0646,47.0471611,36.60848593,34-67%,Expansive T1~FLAIR Ratio,Crosses Midline No,3.393,4.86,1.033,3T,Mes,Proneural,60,2007-00-00,-22272,175,136,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,90.0,1,90,175,3.476130658,2.4631113416,2.0752624241,high,high,high,12.0,7,NEG,2.0,1.0,-2.0,,,1,STR
+29,1,TCGA-06-0648,89.38226471,60.540485,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,1.925,4.0,0.76,3T,PN,Proneural,77,2007-00-00,-28477,298,293,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Operative,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,201.0,1,201,298,1.9721637243,2.027252133,1.5268145618,low,low,high,15.4,7,NEG,1.0,0.0,-1.0,,,1,STR
+30,1,TCGA-08-0352,115.0557228,66.04929696,< 5%,Mixed T1<FLAIR Ratio,Crosses Midline No,2.752,5.727,0.56,1.5T,Mes,Mesenchymal,79,2003-00-00,-29106,39,39,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,39,39,2.8194257503,2.9025182414,1.1250212561,high,high,low,15.8,3,NEG,2.0,0.0,-1.0,,K263*,1,
+31,1,TCGA-08-0353,79.35522434,44.92923295,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.748,4.98,0.94,1.5T,Prolif,Proneural,58,2003-00-00,-21332,256,195,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Post-Adjuvant Therapy,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,164.0,1,164,256,2.8153277478,2.5239289056,1.888428537,high,high,high,11.6,3,NEG,,,,,,1,
+32,1,TCGA-08-0354,53.97760228,38.37069558,34-67%,Expansive T1~FLAIR Ratio,Crosses Midline Yes,3.038,5.393,0.827,1.5T,Mes,Classical,52,2003-00-00,-19198,546,458,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,60.0,Post-Adjuvant Therapy,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,253.0,1,253,546,3.1124329322,2.7332426883,1.6614153192,high,high,high,10.4,3,NEG,2.0,0.0,-1.0,,,1,
+33,1,TCGA-08-0355,77.67814706,56.93133533,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,3.073,5.27,0.463,1.5T,Mes,Classical,30,2003-00-00,-11098,747,685,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,100.0,Other,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,519.0,519.0,1,519,747,3.1482904545,2.6709046852,0.9301515028,high,high,low,6.0,3,,2.0,0.0,-1.0,A289D,,1,
+34,1,TCGA-08-0356,67.52694124,38.67870135,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.058,4.89,0.273,1.5T,Mes,Classical,59,2004-00-00,-21900,946,447,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,80.0,Pre-Adjuvant Therapy,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,447.0,447.0,1,447,946,2.1084223089,2.4783157326,0.5484478623,low,high,low,11.8,4,NEG,2.0,0.0,-1.0,,,1,
+35,1,TCGA-08-0357,65.42796422,41.479033,6-33%,Mixed T1<FLAIR Ratio,Crosses Midline No,2.972,4.567,1.01,1.5T,PN,Classical,49,2004-00-00,-18143,1143,1084,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Other,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,155.0,155.0,1,155,1143,3.0448158902,2.3146151229,2.029056194,high,high,high,9.8,4,NEG,2.0,0.0,-1.0,,,1,
+36,1,TCGA-08-0358,62.85813516,42.12099332,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.968,4.8,0.473,1.5T,PN,Classical,50,2005-00-00,-18383,678,593,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Adjuvant Therapy,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,263.0,263.0,1,263,678,3.0407178877,2.4327025596,0.9502411681,high,high,low,10.0,5,NEG,2.0,0.0,-1.0,,,1,
+37,1,TCGA-08-0359,57.70535869,53.43134242,6-33%,Mixed T1<FLAIR Ratio,Crosses Midline Yes,1.518,3.413,0.933,1.5T,PN,Proneural,59,2005-00-00,-21748,102,29,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,102,102,1.5551919655,1.7297528825,1.8743657713,low,low,high,11.8,5,NEG,,,,,"R47G,R47G",1,
+38,1,TCGA-08-0360,33.67883942,25.59985695,6-33%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.252,3.993,0.587,1.5T,Mes,Mesenchymal,76,2005-00-00,-27894,468,352,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Pre-Adjuvant Therapy,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,112.0,112.0,1,112,468,2.3071754323,2.0237044418,1.1792633523,low,low,low,15.2,5,NEG,,,,,,1,
+39,1,TCGA-08-0385,77.56004839,55.03851551,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,2.546,16.267,1.125,1.5T,PN,Proneural,71,2003-00-00,-26233,82,31,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Pre-Adjuvant Therapy,WITH TUMOR,NO,,Glioblastoma multiforme,BRAIN,DECEASED,,,1,82,82,2.6083786193,8.2443276119,2.2600873448,high,high,high,14.2,3,,,,,,,1,
+40,1,TCGA-08-0389,62.87975086,36.42895664,68-95%,Mixed T1<FLAIR Ratio,Crosses Midline No,1.862,3.317,1.123,1.5T,PN,Proneural,59,2005-00-00,-21638,467,97,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,80.0,Other,WITH TUMOR,NO,,Glioblastoma multiforme,BRAIN,DECEASED,,,1,467,467,1.9076201843,1.6810988313,2.2560694117,low,low,high,11.8,5,NEG,1.0,0.0,-1.0,,F271S,1,
+41,1,TCGA-08-0392,96.34986554,56.55214654,< 5%,Expansive T1~FLAIR Ratio,Crosses Midline No,1.728,3.923,0.457,1.5T,Prolif,Mesenchymal,60,2005-00-00,-22056,22,9,NOT HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,,,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,,1,22,22,1.770337099,1.9882275294,0.9180977036,low,low,low,12.0,5,NEG,1.0,0.0,-1.0,,,0,
+42,1,TCGA-08-0521,71.92146975,45.32140912,None (0%),Mixed T1<FLAIR Ratio,Crosses Midline No,1.74,4.72,1.017,1.5T,Mes,Mesenchymal,17,2002-00-00,-6376,146,146,HISPANIC OR LATINO,MALE,Untreated primary (de novo) GBM,60.0,Post-Adjuvant Therapy,WITH TUMOR,NO,BLACK OR AFRICAN AMERICAN,Glioblastoma multiforme,BRAIN,DECEASED,,125.0,1,125,146,1.7826311067,2.3921575169,2.0431189597,low,high,high,3.4,2,NEG,2.0,0.0,-1.0,,,0,
+43,1,TCGA-08-0524,114.4584859,58.49940496,6-33%,Mixed T1<FLAIR Ratio,Crosses Midline Yes,2.216,5.003,1.103,1.5T,PN,Proneural,17,2002-00-00,-6464,220,198,NOT HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,80.0,Other,WITH TUMOR,NO,WHITE,Glioblastoma multiforme,BRAIN,DECEASED,,61.0,1,61,220,2.2702934094,2.5355856054,2.2158900812,low,high,high,3.4,2,NEG,0.0,2.0,0.0,,,0,
+44,1,TCGA-08-0529,70.00860426,43.9033772,None (0%),Expansive T1~FLAIR Ratio,Crosses Midline No,4.313,5.373,0.8,1.5T,Mes,Classical,56,2004-00-00,-20556,559,526,HISPANIC OR LATINO,FEMALE,Untreated primary (de novo) GBM,80.0,Pre-Adjuvant Therapy,WITH TUMOR,NO,,Glioblastoma multiforme,BRAIN,DECEASED,328.0,328.0,1,328,559,4.4186712431,2.7231064277,1.607173223,high,high,high,11.2,4,NEG,2.0,0.0,-1.0,,,0,

samples/Outcome-Predictors-leaderboard.tsv

@@ -0,0 +1,46 @@
+Round	TCGAID	MajorAxisLength	MinorAxisLength	PropnCET	T1FLAIR	nCETCrossMidline	rCBVmean	rCBVmax	rCBVfl	Machine	Subtype_by_phils	Subtype_by_Verhaak	age_at_initial_pathologic_diagno	date_of_initial_pathologic_diagn	days_to_birth	days_to_death	days_to_last_followup	ethnicity	gender	histological_type	karnofsky_performance_score	performance_status_scale_timing	person_neoplasm_cancer_status	prior_glioma	race	tumor_histologic_subtype	tumor_tissue_site	vital_status	days_to_tumor_recurrence	time_to_progression	progEvent	progSurvTime	OStime	rCBVmeanSD	rCBVmaxSD	rCBVflSD	rCBVmean2	rCBVmax2	rCBVfl2	age5	cohort	gcimp	egfrAmp	pdgfraAmp	ptenAmp	egfrMut	ptenMut	sequenced	Extent_of_Resection
+1	TCGA-06-0122	71.47023114	40.43448767	None (0%)	Mixed T1<FLAIR Ratio	Crosses Midline No	6.86	9.483	1.467	3T	Mes	Mesenchymal	84	2006-00-00	-30967	181	8	NOT HISPANIC OR LATINO	FEMALE	null				NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	181	181	7.0280743631	4.8061079943	2.9471538976	high	high	high	16.8	6	NEG	2	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0127	86.97233129	55.44624428	6-33%	Mixed T1<FLAIR Ratio	Crosses Midline Yes	4.243	5.973	1.177	1.5T	PN	Neural	67	2002-00-00	-24502	121	108	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		90	1	90	121	4.3469561986	3.0271942476	2.3645536043	high	high	high	13.4	2	NEG	2	0	-1	V292L,V292L,V292L	NaN	1	STR
+2	TCGA-06-0128	68.54275415	55.25454465	34-67%	Expansive T1~FLAIR Ratio	Crosses Midline No	1.388	2.83	0.713	1.5T	PN	Proneural	66	2000-00-00	-24217	691	691	NOT HISPANIC OR LATINO	MALE	null	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		189	1	189	691	1.4220068828	1.4342808841	1.432393135	low	low	low	13.2	0	POS	0	0	-1	NaN	NaN	1	GTR
+1	TCGA-06-0132	90.38251662	62.26697312	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.173	6.127	0.837	1.5T	PN	Neural	49	2007-00-00	-18125	761	570	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		482	1	482	761	2.2262398821	3.1052434547	1.6815049845	low	high	high	9.8	7	NEG	2	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0133	102.8050346	62.89969015	34-67%	Mixed T1<FLAIR Ratio	Crosses Midline Yes	2.435	4.663	0.553	3T	PN	Neural	64	2007-00-00	-23402	435	428	NOT HISPANIC OR LATINO	MALE	null			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		78	1	78	435	2.4946590487	2.363269174	1.1109584904	high	high	low	12.8	7	NEG	2	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0137	101.8218393	56.31768036	None (0%)	Mixed T1<FLAIR Ratio	Crosses Midline No	2.53	4.317	0.717	1.5T	Mes	Classical	63	2003-00-00	-23273	812	701	NOT HISPANIC OR LATINO	FEMALE	null			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		487	1	487	812	2.5919866091	2.1879118645	1.4404290011	high	low	low	12.6	3	NEG	2	0	-1	P596L	NaN	1	STR
+1	TCGA-06-0139	80.6709788	39.04821797	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.112	4.497	1.24	3T	Mes	Mesenchymal	40	2006-00-00	-14728	383	327	NOT HISPANIC OR LATINO	MALE	null	60	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		152	1	152	383	2.1637453433	2.2791382105	2.4911184956	low	high	high	8	6	NEG	1	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0143	114.8301745	65.62670418	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline Yes	2.393	5.657	0.353	3T	Mes	Mesenchymal	58	2006-00-00	-21386	357	357	NOT HISPANIC OR LATINO	MALE	null	60		WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	264	264	1	264	357	2.451630022	2.8670413291	0.7091651846	low	high	low	11.6	6	NEG	2	2	-1	NaN	NaN	1	STR
+1	TCGA-06-0147	74.49334479	51.14346067	None (0%)	Expansive T1~FLAIR Ratio	Crosses Midline No	2.24	4.76	0.865	1.5T	Mes	Mesenchymal	51	1999-00-00	-18742	541	508	NOT HISPANIC OR LATINO	FEMALE	null			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		92	1	92	541	2.2948814247	2.4124300383	1.7377560473	low	high	high	10.2	-1	NEG	1	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0149	90.87360905	48.56049078	68-95%	Infiltrative T1<<FLAIR Ratio	Crosses Midline Yes	2.51	3.99	2.057	3T	Mes	Mesenchymal	74	2005-00-00	-27315	262	238	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		203	1	203	262	2.5714965964	2.0221840027	4.1324441495	high	low	high	14.8	5	NEG	1	0	-1	NaN	NaN	0	STR
+1	TCGA-06-0164	66.76339735	46.13628674	None (0%)	Expansive T1~FLAIR Ratio	Crosses Midline No	1.768	4.363	0.607	1.5T	Mes	Mesenchymal	47	2000-00-00	-17510	1730	1729	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	ASIAN	Glioblastoma multiforme	BRAIN	DECEASED		1428	1	1428	1730	1.8113171245	2.2112252641	1.2194426829	low	low	low	9.4	0	NEG	1	0	-1	NaN	NaN	0	GTR
+1	TCGA-06-0166	79.76086734	74.46603485	< 5%	Mixed T1<FLAIR Ratio	Crosses Midline No	3.038	4.47	0.763	1.5T	PN	Proneural	51	2001-00-00	-18902	178	161	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		66	1	66	178	3.1124329322	2.2654542586	1.5328414614	high	low	high	10.2	1	NEG	1	2	-1	NaN	T167S,T167S	1	STR
+1	TCGA-06-0168	44.13221598	24.29751635	6-33%	Infiltrative T1<<FLAIR Ratio	Crosses Midline No	1.37	3.303	0.62	1.5T	Mes	Neural	59	2002-00-00	-21776	598	579	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		461	1	461	598	1.4035658713	1.6740034488	1.2455592478	low	low	low	11.8	2	NEG	1	0	-1	NaN	A328fs	1	STR
+1	TCGA-06-0173	107.1367651	52.88218154	6-33%	Infiltrative T1<<FLAIR Ratio	Crosses Midline Yes	2.027	3.73	0.96	3T	Prolif	Neural	72	2003-00-00	-26548	171	7	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	171	171	2.0766627892	1.890412614	1.9286078676	low	low	high	14.4	3	NEG	2	2	-1	NaN	NaN	1	STR
+1	TCGA-06-0175	58.76606943	37.35171235	None (0%)	Infiltrative T1<<FLAIR Ratio	Crosses Midline No	2.12	3.63	0.577	1.5T	Mes	Mesenchymal	69	2003-00-00	-25558	123	83	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		39	1	39	123	2.1719413484	1.8397313107	1.1591736871	low	low	low	13.8	3	NEG	1	0	-1	NaN	NaN	0	GTR
+1	TCGA-06-0177	70.2938662	47.73769856	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	1.368	3.067	0.253	1.5T	Prolif	Proneural	64	2004-00-00	-23498	127	60	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	127	127	1.4015168701	1.554395573	0.5082685318	low	low	low	12.8	4	NEG	2	2	-1	NaN	NaN	0	STR
+1	TCGA-06-0179	64.06461812	44.22389414	< 5%	Mixed T1<FLAIR Ratio	Crosses Midline No	2.51	5.493	0.623	3T	PN	Neural	64	2004-00-00	-23449	616	578	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		250	1	250	616	2.5714965964	2.7839239916	1.2515861474	high	high	low	12.8	4	NEG	2	0	-1	NaN	NaN	0	GTR
+1	TCGA-06-0184	82.84546219	64.92510487	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	1.672	3.067	0.71	1.5T	Mes	Mesenchymal	63	2005-00-00	-23317	2126	1228	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		1276	1	1276	2126	1.7129650634	1.554395573	1.4263662354	low	low	low	12.6	5	NEG	1	0	-1	NaN	G36E,G36E,G36E	1	GTR
+1	TCGA-06-0185	72.07177397	44.71617175	6-33%	Mixed T1<FLAIR Ratio	Crosses Midline No	1.99	4.267	0.413	1.5T	PN	Neural	54	2005-00-00	-19922	2366	2246	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		711	1	711	2366	2.0387562657	2.1625712129	0.8297031764	low	low	low	10.8	5	NEG	2	0	-2	V651M,V651M,V651M	NaN	1	GTR
+1	TCGA-06-0187	65.87112795	44.41677325	None (0%)	Expansive T1~FLAIR Ratio	Crosses Midline No	1.835	3.233	0.517	1.5T	Mes	Classical	69	2006-00-00	-25317	828	801	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	531	531	1	531	828	1.8799586671	1.6385265365	1.0386356953	low	low	low	13.8	6	NEG	2	0	-1	NaN	G132D,G132D,G132D	1	STR
+2	TCGA-06-0189	85.25564146	56.4416166	< 5%	Mixed T1<FLAIR Ratio	Crosses Midline No	2.708	4.99	0.573	3T	Mes	Mesenchymal	55	2006-00-00	-20296	468	454	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	468	468	2.7743477223	2.5289970359	1.1511378209	high	high	low	11	6	NEG	2	0	-1	NaN	NaN	1	STR
+2	TCGA-06-0190	74.76880933	60.24171094	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	4.376	6.68	1.333	1.5T	Mes	Mesenchymal	62	2006-00-00	-22835	317	313	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80		WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		88	1	88	317	4.4832147832	3.3855110621	2.6779523828	high	high	high	12.4	6	NEG	1	1	-1	NaN	D92E,D92E,D92E	1	STR
+1	TCGA-06-0192	79.16025289	42.82469307	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.425	4.16	1.22	3T	Mes	Mesenchymal	58	2007-00-00	-21243	1185	556	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		648	1	648	1185	2.4844140423	2.1083422183	2.450939165	high	low	high	11.6	7	NEG	2	2	-1	NaN	Y315*	1	GTR
+1	TCGA-06-0213	72.9466112	43.71555926	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.167	3.763	0.767	1.5T	Mes	Mesenchymal	55	1998-00-00	-20134	16	6	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	16	16	2.2200928782	1.9071374441	1.5408773275	low	low	high	11	-2	NEG	1	0	-2	NaN	R335*,R335*	1	STR
+1	TCGA-06-0237	70.35187771	28.66265438	68-95%	Infiltrative T1<<FLAIR Ratio	Crosses Midline No	3.365	5.537	0.613	1.5T	PN	Neural	75	2006-00-00	-27735	415	314	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	415	415	3.4474446402	2.8062237651	1.2314964821	high	high	low	15	6	NEG	2	1	-1	L62R,L62R	NaN	1	STR
+2	TCGA-06-0238	76.80296366	48.00510283	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.346	4.023	0.62	3T	PN	Proneural	46	2007-00-00	-17037	405	359	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		311	1	311	405	2.4034784921	2.0389088328	1.2455592478	low	low	low	9.2	7	NEG	1	0	-1	NaN	NaN	1	STR
+1	TCGA-06-0241	53.7870232	33.79282207	None (0%)	Mixed T1<FLAIR Ratio	Crosses Midline No	2.912	4.43	0.66	3T	Prolif	Proneural	65	2007-00-00	-24101	1481	455	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	100	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	196	196	1	196	1481	2.9833458521	2.2451817373	1.3259179089	high	low	low	13	7	NEG	1	2	-1	NaN	NaN	1	STR
+1	TCGA-06-0644	51.55889274	40.19048554	None (0%)	Expansive T1~FLAIR Ratio	Crosses Midline No	2.555	4.19	0.617	3T	Mes	Mesenchymal	71	2007-00-00	-26246	384	375	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	BLACK OR AFRICAN AMERICAN	Glioblastoma multiforme	BRAIN	DECEASED	85	85	1	85	384	2.617599125	2.1235466093	1.2395323482	high	low	low	14.2	7	NEG	1	0	-1	NaN	T202fs,I203fs	1	STR
+1	TCGA-06-0646	47.0471611	36.60848593	34-67%	Expansive T1~FLAIR Ratio	Crosses Midline No	3.393	4.86	1.033	3T	Mes	Proneural	60	2007-00-00	-22272	175	136	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		90	1	90	175	3.476130658	2.4631113416	2.0752624241	high	high	high	12	7	NEG	2	1	-2	NaN	NaN	1	STR
+1	TCGA-06-0648	89.38226471	60.540485	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	1.925	4	0.76	3T	PN	Proneural	77	2007-00-00	-28477	298	293	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Operative	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		201	1	201	298	1.9721637243	2.027252133	1.5268145618	low	low	high	15.4	7	NEG	1	0	-1	NaN	NaN	1	STR
+1	TCGA-08-0352	115.0557228	66.04929696	< 5%	Mixed T1<FLAIR Ratio	Crosses Midline No	2.752	5.727	0.56	1.5T	Mes	Mesenchymal	79	2003-00-00	-29106	39	39	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	39	39	2.8194257503	2.9025182414	1.1250212561	high	high	low	15.8	3	NEG	2	0	-1	NaN	K263*	1	
+1	TCGA-08-0353	79.35522434	44.92923295	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.748	4.98	0.94	1.5T	Prolif	Proneural	58	2003-00-00	-21332	256	195	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Post-Adjuvant Therapy	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		164	1	164	256	2.8153277478	2.5239289056	1.888428537	high	high	high	11.6	3	NEG	NaN	NaN	NaN	NaN	NaN	1	
+1	TCGA-08-0354	53.97760228	38.37069558	34-67%	Expansive T1~FLAIR Ratio	Crosses Midline Yes	3.038	5.393	0.827	1.5T	Mes	Classical	52	2003-00-00	-19198	546	458	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	60	Post-Adjuvant Therapy	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		253	1	253	546	3.1124329322	2.7332426883	1.6614153192	high	high	high	10.4	3	NEG	2	0	-1	NaN	NaN	1	
+1	TCGA-08-0355	77.67814706	56.93133533	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	3.073	5.27	0.463	1.5T	Mes	Classical	30	2003-00-00	-11098	747	685	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	100	Other	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	519	519	1	519	747	3.1482904545	2.6709046852	0.9301515028	high	high	low	6	3		2	0	-1	A289D	NaN	1	
+1	TCGA-08-0356	67.52694124	38.67870135	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.058	4.89	0.273	1.5T	Mes	Classical	59	2004-00-00	-21900	946	447	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	80	Pre-Adjuvant Therapy	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	447	447	1	447	946	2.1084223089	2.4783157326	0.5484478623	low	high	low	11.8	4	NEG	2	0	-1	NaN	NaN	1	
+1	TCGA-08-0357	65.42796422	41.479033	6-33%	Mixed T1<FLAIR Ratio	Crosses Midline No	2.972	4.567	1.01	1.5T	PN	Classical	49	2004-00-00	-18143	1143	1084	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Other	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	155	155	1	155	1143	3.0448158902	2.3146151229	2.029056194	high	high	high	9.8	4	NEG	2	0	-1	NaN	NaN	1	
+1	TCGA-08-0358	62.85813516	42.12099332	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.968	4.8	0.473	1.5T	PN	Classical	50	2005-00-00	-18383	678	593	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Adjuvant Therapy	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	263	263	1	263	678	3.0407178877	2.4327025596	0.9502411681	high	high	low	10	5	NEG	2	0	-1	NaN	NaN	1	
+1	TCGA-08-0359	57.70535869	53.43134242	6-33%	Mixed T1<FLAIR Ratio	Crosses Midline Yes	1.518	3.413	0.933	1.5T	PN	Proneural	59	2005-00-00	-21748	102	29	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	102	102	1.5551919655	1.7297528825	1.8743657713	low	low	high	11.8	5	NEG	NaN	NaN	NaN	NaN	R47G,R47G	1	
+1	TCGA-08-0360	33.67883942	25.59985695	6-33%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.252	3.993	0.587	1.5T	Mes	Mesenchymal	76	2005-00-00	-27894	468	352	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Pre-Adjuvant Therapy	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED	112	112	1	112	468	2.3071754323	2.0237044418	1.1792633523	low	low	low	15.2	5	NEG	NaN	NaN	NaN	NaN	NaN	1	
+1	TCGA-08-0385	77.56004839	55.03851551	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	2.546	16.267	1.125	1.5T	PN	Proneural	71	2003-00-00	-26233	82	31	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Pre-Adjuvant Therapy	WITH TUMOR	NO		Glioblastoma multiforme	BRAIN	DECEASED			1	82	82	2.6083786193	8.2443276119	2.2600873448	high	high	high	14.2	3		NaN	NaN	NaN	NaN	NaN	1	
+1	TCGA-08-0389	62.87975086	36.42895664	68-95%	Mixed T1<FLAIR Ratio	Crosses Midline No	1.862	3.317	1.123	1.5T	PN	Proneural	59	2005-00-00	-21638	467	97	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	80	Other	WITH TUMOR	NO		Glioblastoma multiforme	BRAIN	DECEASED			1	467	467	1.9076201843	1.6810988313	2.2560694117	low	low	high	11.8	5	NEG	1	0	-1	NaN	F271S	1	
+1	TCGA-08-0392	96.34986554	56.55214654	< 5%	Expansive T1~FLAIR Ratio	Crosses Midline No	1.728	3.923	0.457	1.5T	Prolif	Mesenchymal	60	2005-00-00	-22056	22	9	NOT HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM			WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED			1	22	22	1.770337099	1.9882275294	0.9180977036	low	low	low	12	5	NEG	1	0	-1	NaN	NaN	0	
+1	TCGA-08-0521	71.92146975	45.32140912	None (0%)	Mixed T1<FLAIR Ratio	Crosses Midline No	1.74	4.72	1.017	1.5T	Mes	Mesenchymal	17	2002-00-00	-6376	146	146	HISPANIC OR LATINO	MALE	Untreated primary (de novo) GBM	60	Post-Adjuvant Therapy	WITH TUMOR	NO	BLACK OR AFRICAN AMERICAN	Glioblastoma multiforme	BRAIN	DECEASED		125	1	125	146	1.7826311067	2.3921575169	2.0431189597	low	high	high	3.4	2	NEG	2	0	-1	NaN	NaN	0	
+1	TCGA-08-0524	114.4584859	58.49940496	6-33%	Mixed T1<FLAIR Ratio	Crosses Midline Yes	2.216	5.003	1.103	1.5T	PN	Proneural	17	2002-00-00	-6464	220	198	NOT HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	80	Other	WITH TUMOR	NO	WHITE	Glioblastoma multiforme	BRAIN	DECEASED		61	1	61	220	2.2702934094	2.5355856054	2.2158900812	low	high	high	3.4	2	NEG	0	2	0	NaN	NaN	0	
+1	TCGA-08-0529	70.00860426	43.9033772	None (0%)	Expansive T1~FLAIR Ratio	Crosses Midline No	4.313	5.373	0.8	1.5T	Mes	Classical	56	2004-00-00	-20556	559	526	HISPANIC OR LATINO	FEMALE	Untreated primary (de novo) GBM	80	Pre-Adjuvant Therapy	WITH TUMOR	NO		Glioblastoma multiforme	BRAIN	DECEASED	328	328	1	328	559	4.4186712431	2.7231064277	1.607173223	high	high	high	11.2	4	NEG	2	0	-1	NaN	NaN	0	

samples/Outcome-Predictors-leaderboard_meta.csv

@@ -0,0 +1,51 @@
+dtype,count,unique,null,freq,min,max,PV_match,Enumerated,NonEnumerated
+Round,int64,45,2,0,,1.0,2.0,1.0,True,True
+TCGAID,object,45,45,0,1,,,,False,True
+MajorAxisLength,float64,45,45,0,,33.67883942,115.0557228,,False,True
+MinorAxisLength,float64,45,45,0,,24.29751635,74.46603485,,False,True
+PropnCET,object,45,5,0,15,,,0.0,False,True
+T1FLAIR,object,45,3,0,25,,,0.0,False,True
+nCETCrossMidline,object,45,2,0,37,,,0.0,False,True
+rCBVmean,float64,45,43,0,,1.368,6.86,,False,True
+rCBVmax,float64,45,44,0,,2.83,16.267,,False,True
+rCBVfl,float64,45,44,0,,0.253,2.057,,False,True
+Machine,object,45,2,0,31,,,0.5,False,True
+Subtype_by_phils,object,45,3,0,24,,,0.3333333333333333,False,True
+Subtype_by_Verhaak,object,45,4,0,17,,,0.5,False,True
+age_at_initial_pathologic_diagno,int64,45,30,0,,17.0,84.0,,False,True
+date_of_initial_pathologic_diagn,object,45,10,0,8,,,0.0,False,True
+days_to_birth,int64,45,45,0,,-30967.0,-6376.0,,False,True
+days_to_death,int64,45,44,0,,16.0,2366.0,,False,True
+days_to_last_followup,int64,45,45,0,,6.0,2246.0,,False,True
+ethnicity,object,45,2,0,43,,,1.0,True,False
+gender,object,45,2,0,30,,,1.0,True,False
+histological_type,object,38,2,7,38,,,0.0,False,True
+karnofsky_performance_score,float64,32,4,13,,60.0,100.0,,False,True
+performance_status_scale_timing,object,30,5,15,18,,,1.0,True,False
+person_neoplasm_cancer_status,object,44,2,1,44,,,1.0,True,False
+prior_glioma,object,45,1,0,45,,,1.0,True,False
+race,object,42,4,3,39,,,1.0,True,False
+tumor_histologic_subtype,object,45,1,0,45,,,1.0,True,False
+tumor_tissue_site,object,45,1,0,45,,,1.0,True,False
+vital_status,object,45,1,0,45,,,1.0,True,False
+days_to_tumor_recurrence,float64,10,11,35,,85.0,531.0,,False,True
+time_to_progression,float64,34,34,11,,39.0,1428.0,,False,True
+progEvent,int64,45,1,0,,1.0,1.0,1.0,True,True
+progSurvTime,int64,45,43,0,,16.0,1428.0,,False,True
+OStime,int64,45,44,0,,16.0,2366.0,,False,True
+rCBVmeanSD,float64,45,43,0,,1.4015168701,7.0280743631,,False,True
+rCBVmaxSD,float64,45,44,0,,1.4342808841,8.2443276119,,False,True
+rCBVflSD,float64,45,44,0,,0.5082685318,4.1324441495,,False,True
+rCBVmean2,object,45,2,0,23,,,1.0,True,False
+rCBVmax2,object,45,2,0,23,,,1.0,True,False
+rCBVfl2,object,45,2,0,23,,,1.0,True,False
+age5,float64,45,30,0,,3.4,16.8,,False,True
+cohort,int64,45,10,0,,-2.0,7.0,1.0,True,True
+gcimp,object,43,3,2,42,,,0.5,False,True
+egfrAmp,float64,41,4,4,,0.0,2.0,,False,True
+pdgfraAmp,float64,41,4,4,,0.0,2.0,,False,True
+ptenAmp,float64,41,4,4,,-2.0,0.0,,False,True
+egfrMut,object,5,6,40,1,,,,False,True
+ptenMut,object,11,12,34,1,,,,False,True
+sequenced,int64,45,2,0,,0.0,1.0,1.0,True,True
+Extent_of_Resection,object,30,3,15,23,,,0.0,False,True

samples/Outcome-Predictors.txt

@@ -0,0 +1,30 @@
+From: https://pubs.rsna.org/doi/10.1148/radiol.14131691
+
+Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor
+Rajan Jain1 , Laila M. Poisson, David Gutman, Lisa Scarpace, Scott N. Hwang, Chad A. Holder, Max Wintermark, Arvind Rao, Rivka R. Colen2, Justin Kirby, John Freymann, C. Carl Jaffe, Tom Mikkelsen, Adam Flanders
+Author Affiliations
+Published Online:Mar 17 2014https://doi.org/10.1148/radiol.14131691
+
+Abstract
+In the current study, we focused on the role of the nonenhancing region (NER) of glioblastomas and showed that there are imaging phenotypic features related specifically to the NER—most notably the NER crossing the midline and relative cerebral blood volume of NER, which provide important prognostic information; these are complementary to clinical and genomic features and can improve models of patient prognosis.
+
+Purpose
+To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers.
+
+Materials and Methods
+An institutional review board waiver was obtained for this HIPAA-compliant retrospective study. Forty-five patients with GBM underwent baseline imaging with contrast material–enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging. Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests.
+
+Results
+Worsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBVNER), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBVNER and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBVNER marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBVNER as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBVNER, age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49–1.79 years).
+
+Conclusion
+Patients with high rCBVNER and NER crossing the midline and those with high rCBVNER and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBVNER provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.
+
+© RSNA, 2014
+
+Online supplemental material is available for this article.
+
+Article History
+Received August 16, 2013; revision requested September 18; revision received December 20; accepted January 10, 2014; final version accepted January 20.
+Published online: Mar 17 2014
+Published in print: Aug 2014

samples/Outcome-Predictors_description.txt

@@ -0,0 +1,16 @@
+The manuscript in which this dataset is used correlates patient
+survival with morphologic imaging features and hemodynamic parameters
+obtained from the non-enhancing region (NER) of glioblastoma (GBM),
+along with clinical and genomic markers. Forty-five patients with GBM
+underwent baseline imaging with contrast material-enhanced magnetic
+resonance (MR) imaging and dynamic susceptibility contrast-enhanced
+T2*-weighted perfusion MR imaging. Molecular and clinical predictors
+of survival were obtained. Single and multivariable models of overall
+survival (OS) and progression-free survival (PFS) were explored with
+Kaplan-Meier estimates, Cox regression, and random survival
+forests. This dataset correlates with images on the TCIA web portal
+and includes supplemental data including clinical, genomic, and
+radiologist derived information from
+JainPoisson_2014_Radiology_Dataset.xlsx. The xlsx file contains 2
+sheets: the dataset, and a second worksheet of descriptions of the
+variables.

samples/README.md

@@ -0,0 +1,27 @@
+# Metadata Challenge Input Files
+
+[Metadata Automation DREAM Challenge Data Sources](https://www.synapse.org/#!Synapse:syn18065891/wiki/600450)
+
+## Tables and Files
+
+There are 4 input tables:
+- APOLLO-2
+- REMBRANDT
+- Outcome-Predictors
+- ROI-Masks
+
+APOLLO-5 was an attempt of getting more data to train on.
+
+Each has:
+- A -leaderboard.tsv spreadsheet of the RCT data
+- a PDF paper of the results of the RCT trail
+- a txt version of the PDF paper
+- a _description.txt short paragraph description of the data provided at the competition
+
+While ALL files for the train data were available at the start of the
+competition, the compute environment for the test data did not provide
+access to the txt and PDF files.
+
+Still, it seems obvious that those files should be available at the
+time of annotation, and we should find a way to use them.
+

samples/REMBRANDT-leaderboard.tsv

@@ -0,0 +1,128 @@
+Sample	Age at Dx (years)	Survival (months)	Race	Karnofsky	MRI Desc	Followup Month	Steroid Dose Status	Anti-Convulsant Status	Prior Therapy Radiation Fraction Dose	Prior Therapy Radiation Fraction Number	Prior Therapy Radiation Type	Prior Therapy Chemo Course Count	Prior Therapy Surgery Procedure Title	Prior Therapy Surgery Outcome	OnStudy Therapy Radiation Site	OnStudy Therapy Radiation Neurosis Status	OnStudy Therapy Radiation Fraction Number	OnStudy Therapy Radiation Type	OnStudy Therapy Chemo Agent Name	OnStudy Therapy Chemo Course Count	OnStudy Therapy Surgery Procedure Title	OnStudy Therapy Surgery Indication	OnStudy Therapy Surgery Histo Diagnosis	OnStudy Therapy Surgery Outcome
+900_00_1961		15																						
+900_00_5332		15																						
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+900_00_5477		5																						
+900_00_5299		6																						
+900_00_5303		5																						
+HF0608	50-54	10.6	WHITE		rim enhancement and nodular foci		NASS	NASS									NONE	EBRT	9-AC(2)		subtotal x2	recurrence	GBM with necrosis	subtotal
+HF0652.4	50-54	19.6																						
+HF0763																								
+HF0828	35-39																							
+HF0835	35-39	45.3	WHITE	90	non contrast enhancing		NASS	Yes NASS										EBRT (3D-CRT)	PCV+CCNU; EMD; Temodar; PCV+CCNU(2; 1; 2; 1)		subtotal x 2	recurrence	anaplastic oligodenroglioma; glioblastoma multiforme	subtotal
+HF0855	55-59	13.7	WHITE	90	ring enhancement; thick, irregular and nodular wall			NASS										NONE	EBRT	BCNU(4)		subtotal	recurrence	radiation necrosis
+HF0868																								
+HF0883																								
+HF0899	55-59	66.7	WHITE		noncontrast enhancing		NASS	NASS										EBRT	NONE(NONE)		subtotal	recurrence	malignant glioma	subtotal
+HF0920	85-89	1	WHITE	90	noncontrast enhancing; minimal mass effect		12 mg/day	Dilantin									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF0931	35-39	119	WHITE	90	noncontrast enhancing		8 mg/day	Dilantin										EBRT	PCV(4)		subtotal	recurrence	foreign body granuloma	subtotal
+HF0953	35-39	44.6	WHITE	100	complex multicompartment tumor		NONE	NONE									NONE	EBRT	BCNU (2)		subtotal	recurrence	Gemistocytic Astrocytoma	subtotal
+HF0960	30-34	88.7	WHITE		subtle contrast enhancement; cystic; midline shift		Yes dose unknown	Dilantin										EBRT (3D-CRT)	Temozolomide; Bay 43; PCV/CCNU(13	1	1)		subtotal x 2	recurrence
+HF0962	30-34	116.5	WHITE	100	subtle contrast enhancement		NONE	Dilantin									NONE	NONE	Temozolomide(6)		NONE	NONE	NONE	NONE
+HF0966	50-54	137.7	WHITE		noncontrast enhancing		NONE	Dilantin										EBRT	PCV  (6)		NONE	NONE	NONE	NONE
+HF0986	35-39	62.4	WHITE	90	thick ring enhancing nodular mass		NASS	NASS										EBRT	PCV(4)		subtotal	recurrence	mixed oligoastrocytoma	subtotal
+HF0990	40-44	88.3	WHITE		mixed signal intesnsity lesion; bi-frontal; inhomogeneous areas of intense enhancement		NASS	NASS										EBRT	5-FU/Carboplatin/Gamma IFN/Thalidomide/plasmapheresis(4)		subtotal	recurrence	GBM	subtotal
+HF0996	50-54	120.5	WHITE	90	3cm x 2cm slightly heterogeneously enahncment		NASS	NASS										EBRT	BCNU(6)		NONE	NONE	NONE	NONE
+HF1000	30-34	40.3	WHITE	90	minimal enhancement		Yes dose unkown	Yes type unknown										EBRT	SU-101(6)		subtotal	recurrence	anaplastic astrocytoma	subtotal
+HF1032	40-44	28.1	WHITE	100	non enhancing; small amount of edema		NASS	Dilantin										EBRT	PCV(5)		subtotal	recurrence	abcess/infection arteritis	subtotal
+HF1057	60-64	24.5	WHITE	90	irregularly enhancing mass; multiple; nodular enhancing		NASS	NASS										EBRT	CI-980(4)		subtotal	recurrence	GBM	subtotal
+HF1058	50-54	18	WHITE		large mass; significant vasogenic edema; mass effect		NASS	NASS										EBRT	BCNU(1)		NONE	NONE	NONE	NONE
+HF1059	60-64	11.5	WHITE		diffuse abnormality; mild compression of R lateral ventrile with mild midline shift		4mg t.i.d.	NASS										EBRT	BCNU(2)		NONE	NONE	NONE	NONE
+HF1071	55-59	8.8	WHITE		shaggy, irregular		peripheral enahcnement; central necrosis and surrounding edema		NASS											EBRT	TMZ+Thalidomide(3)		NONE	NONE
+HF1077	40-44	73.4	BLACK		enhancing lesion; very little mass effect		NASS	NASS										EBRT	PCV(4)		subtotal	recurrence	GBM	subtotal
+HF1078	45-49	22.8	WHITE	80	ring enhancing; multicystic; vasogenic edema; significant mass effect and midline shift		NASS	NASS										EBRT	penicillamine/low copper diet(9)		subtotal	recurrence	malignant astrocytoma	subtotal
+HF1097	50-54	9	WHITE	90	enhancing		NASS	Dilantin										EBRT	TMZ(2)		NONE	NONE	NONE	NONE
+HF1113																								
+HF1122	35-39	7.3	WHITE	90	multiple enhancing lesions; in leptomeninges		NONE	Dilantin										EBRT (L Frontal) + WBRT	ARA-C(5)		NONE	NONE	NONE	NONE
+HF1136	35-39	45.3	WHITE	100	contrast enhancing		NONE	Dilantin										EBRT (3D-CRT)	PCV + Temozolomide(2 PCV; 5 TMZ)		subtotal	recurrence	anaplastic oligodenroglioma with necrosis	subtotal
+HF1137	70-74	18.3	WHITE	80	irregular enhancign mass with vasogenic edema and mass effect		NASS	NASS										EBRT	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1139	40-44	15.8	WHITE	80	large 6cm x 5cm x 7.2 cm hetrogeneous enhancing mass; edema; mass effect		4mg/day	Dilantin										EBRT	TMZ(2)		subtotal	recurrence	malignant glioma	subtotal
+HF1150	70-74	21.2	WHITE	90	contrast enhancing; ring enhancing; edema		NONE	Dilantin										EBRT	Temozolomide(11)		NONE	NONE	NONE	NONE
+HF1156	30-34	105.3	WHITE	90	large T2 abnormality; tiny focal areas of enhancement		NONE	NASS										EBRT	NONE(NONE)		gross total	recurrence	oligodendroglioma	Gross Total
+HF1167	45-49	17.9	BLACK		noncontrast enhancing; mild mass effect		NONE	Dilantin										EBRT	Gliadel Wafer(1)		subtotal	recurrence	oligodenroglioma and radiation necrosis	subtotal
+HF1185	25-29	95.2	WHITE	90	contrast enhancing minimally		NONE	Dilantin + Tegratol XR										EBRT	Temozolomide(12)		subtotal x 3	recurrence	Atypical oligodenroglioma; anaplastic oligodenroglioma x 2	subtotal
+HF1191	70-74	0.3	WHITE		nodular enhancement		NONE	Dilantin										NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1199																								
+HF1219	50-54	27.1	WHITE	90	contrast enhancing; mass effect		16 mg/day	Dilantin										EBRT	Temozolomide(12)		subtotal x 2	recurrence	necrosis; GBM	subtotal
+HF1226																								
+HF1227	25-29	251.7	WHITE	100	large T2 abnormality with nodular patchy enhancement		NASS	Yes Unknown										EBRT	TMZ(11)		subtotal	recurrence	atypical oligodenroglioma	subtotal
+HF1232	50-54	20.2	WHITE	100	calcified; enhancing		NASS	NASS										EBRT	TMZ(11)		NONE	NONE	NONE	NONE
+HF1235	35-39	98.4	WHITE	90	solitary mass without significant edema or enhancemnt		NONE	NONE										NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1242	35-39	149	WHITE	80	enhancing mass with significant edema		16mg/day	Dilantin										EBRT	TMZ(8)		subtotal	recurrence	GBM	subtotal
+HF1246	65-69	0.2	WHITE	80	enhancing and non enhancing; leptomeningeal		4 mg t.i.d.	NASS										NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1264	45-49	89.1	WHITE		non contrast enhancing		NONE	Tegretol and Dilantin									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1269	45-49	13	WHITE	80	intense ray-like and nodular enhancements		12 mg q 6 hours	Dilantin										EBRT	BCNU(4)		subtotal	recurrence	Anaplastic Astrocytoma	subtotal
+HF1280	40-44	15.8	WHITE		mulitple large 4cm enhancing lesions; vasogenic edema		Yes Unknown	NONE										EBRT	TMZ(12)		NONE	NONE	NONE	NONE
+HF1292	45-49	57.7	ASIAN NOS	100	2cm x 3cm well circumscribed lesion; vasogenic edema		NASS	NASS										EBRT	TMZ(15)		subtotal	recurrence	GBM	subtotal
+HF1293																								
+HF1297	60-64	17.2	WHITE	80	linear hyperintense lesion		NASS	NASS										EBRT	TMZ(7)		NONE	NONE	NONE	NONE
+HF1300																								
+HF1307																								
+HF1316	70-74	6.9	BLACK		small foci of enhancment; small, old hemorrhages			NASS											EBRT	NONE(NONE)		NONE	NONE	NONE
+HF1325	35-39	84.5	WHITE	90	non contrast enhancing		NONE	Carbamazepine										EBRT	NONE(NONE)		subtotal	recurrence	oligoastrocytoma	subtotal
+HF1331																								
+HF1334	20-24	115.7	WHITE		enhancing; mass effect		NASS	Tegretol-XR										EBRT	Temozolomide(2)		sub total x 2	recurrence	anaplastic gemistocytic glioma; gemistocytic glioma	subtotal
+HF1344	60-64	9																						
+HF1345	15-19	83.5	BLACK		enhancing		NASS	Tegretol									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1357	20-24	30.8	WHITE		cystic, abnormal nodular enhancement; large T2 signal			Yes Dose Unknown											EBRT	TMZ(5)		subtotal	recurrence	subtotal
+HF1381	25-29	136.2	BLACK		non enhancing		NASS	Depakote									No	No	NO(NO)		NO	NO	NO	NO
+HF1397	60-64	30	WHITE		large enhancing mass with vasogenic edema		4 mg b.i.d.	Trileptal and Neurontin										EBRT	TMZ(8)		NONE	NONE	NONE	NONE
+HF1398	55-59	66.8	WHITE	80	thick irregular shaggy enhancement with vasogenic edema and mass effect		8mg q. daily	Dilantin										EBRT	TMZ+cRA(4)		NONE	NONE	NONE	NONE
+HF1407	55-59	5.2	WHITE	80	vasogenic edema; subfalcine herniation		NASS	NASS										EBRT	TMZ(0)		NONE	NONE	NONE	NONE
+HF1409	50-54	12.7	WHITE	90	multicentric lesion with numerous enhancing lesions		NONE	Depakote										EBRT	TMZ(1)		subtotal	recurrence	GBM	subtotal
+HF1420																								
+HF1429																								
+HF1433	45-49	78.2	WHITE		mass effect; necrosis; heterogeneous enhancement		NASS	Phenytoin										EBRT	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1437																								
+HF1442	35-39	47.2	WHITE	100	non enhancing; mass effect		NASS	NASS										EBRT	TMZ(2)		subtotal	recurrence	Anaplastic Astrocytoma	subtotal
+HF1458	45-49	8.8	WHITE	80	hetergeneous, hyperintense lobular and multicentric lesion; ring enhancing			NASS											EBRT	PZA(2)		NONE	NONE	NONE
+HF1463	40-44	72	WHITE		non enhancing		NASS	NASS										EBRT	TMZ(12)		subtotal	recurrence	GBM	subtotal
+HF1475	15-19	31.7	WHITE	100	unusual enhancment		6mg/day	NONE										EBRT	TMZ(22)		subtotal	recurrence	undifferentiated malignant glioma	subtotal
+HF1489	50-54	68.3	WHITE	100	non enhancing		None	Dilantin										EBRT	Temozolomide(2)		NO	NO	No	No
+HF1490	65-69	4	WHITE	100	ring enhancing		NASS	NASS										EBRT	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1502	35-39	6.4	WHITE	100	cystic; non-enhancing; edema		None	Keppra									NO	No	No(No)		NO	NO	No	No
+HF1510																								
+HF1511	25-29	56.6	OTHER	100	non enhancing		NASS	NASS										EBRT	TMZ(5)		subtotal	recurrence	GBM	subtotal
+HF1517	55-59	8.3	WHITE	100	enhancing; edema		8mg/day	Dilantin										EBRT	TMZ(3)		subtotal	recurrence	radiation necrosis	subtotal
+HF1538	70-74	3.2	WHITE		large enhancing mass		NASS	NASS										EBRT	TMZ(0)		NONE	NONE	NONE	NONE
+HF1540	75-79	10.2	BLACK	90	4.5cm large enhancing mass with subependymal spread; mild mass effect		NONE	NONE									NONE	EBRT	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1551	30-34	70.9	WHITE	80	cystic; enhancing		None	Topiramate									NO	No	Temozolomide(12)		NO	NO	No	No
+HF1553	10-14	71.2	WHITE	100	cystic; ring enhancement		None	Dilantin									NONE	No	No(No)		NO	NO	No	No
+HF1560	75-79	1.2	WHITE	80	extensive vasogenic edema; bilateral frontal enhancing mass		NONE	NONE									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1568	30-34	42.6	WHITE	100	minimal areas of enhancement; large T2 abnormality		NONE	NONE									NONE	EBRT	Temodar(2)		subtotal	recurrence	GBM	subtotal
+HF1587	30-34	75.3	WHITE	90	compression of the left lateral horn of the lateral ventricle; high intensity on diffusion; scattered areas of enhancement		NASS	NASS									NONE	EBRT	Temodar(6)		NONE	NONE	NONE	NONE
+HF1588	40-44	75.2	WHITE	90	mildly hypointense on T1; no enhancement		NASS	NASS									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1606	60-64	73.6	WHITE	90	Ill defined hypointense on T1 images; minimal mass effect; no enhancement		NONE	Tegretol									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE
+HF1613	35-39	66.8	WHITE	100	no enhancement		NASS	NASS									NO	NO	NO(NO)		NO	NO	NO	NO
+HF1628	45-49	14.6	WHITE	100	enhancing mass		NONE	NONE										EBRT	TMZ(4)		subtotal	recurrence	GBM and radiation necrosis	subtotal
+HF1652																								
+HF1671	65-69	13.3	WHITE		pre op CT only		NASS	NASS										EBRT	TMZ(1)		subtotal	recurrence	CRN + minimal residual GBM	subtotal
+HF1677	50-54	63.5	WHITE	100	no enhancement; mild mass effect		none	Dilantin									NO	NO	NO(NO)		NO	No	NO	NO
+HF1702	75-79	5.4	WHITE	80	enhancing mass with vasogenic edema		NASS	NASS										Brachytherapy	NASS(NASS)		NASS	NASS	NASS	NASS
+HF1708	20-24	67.8	WHITE		nonenhancing abnormal signal intensity		NASS	NASS									NONE	NONE	NONE(NONE)		NONE	NONE	NONE	NONE

samples/REMBRANDT.txt

@@ -0,0 +1,196 @@
+Rembrandt: Helping Personalized Medicine Become a Reality through Integrative Translational Research 
+Subha Madhavan; Jean-Claude Zenklusen; Yuri Kotliarov; Himanso Sahni; Howard A. Fine; Kenneth Buetow
+Crossmark: Check for Updates
+Author & Article Information
+Mol Cancer Res (2009) 7 (2): 157–167.
+https://doi.org/10.1158/1541-7786.MCR-08-0435
+Article history
+Split-Screen
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+Abstract
+Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set and the ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed, and analyzed both within and across functional domains. Novel biomedical informatics infrastructure and tools are essential for developing individualized patient treatment based on the specific genomic signatures in each patient's tumor. Here, we present Repository of Molecular Brain Neoplasia Data (Rembrandt), a cancer clinical genomics database and a Web-based data mining and analysis platform aimed at facilitating discovery by connecting the dots between clinical information and genomic characterization data. To date, Rembrandt contains data generated through the Glioma Molecular Diagnostic Initiative from 874 glioma specimens comprising ∼566 gene expression arrays, 834 copy number arrays, and 13,472 clinical phenotype data points. Data can be queried and visualized for a selected gene across all data platforms or for multiple genes in a selected platform. Additionally, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-anomaly pairs to facilitate the discovery of novel biomarkers and therapeutic targets. We believe that Rembrandt represents a prototype of how high-throughput genomic and clinical data can be integrated in a way that will allow expeditious and efficient translation of laboratory discoveries to the clinic. (Mol Cancer Res 2009;7(2):157–67)
+
+Introduction
+Primary brain tumors are a leading cause of cancer mortality in adults and children in the United States (1). The molecular and genetic heterogeneity of gliomas undoubtedly contributes to the varied and often suboptimal response to treatment that is usually predicated on standard pathologic diagnoses. Improvement in the prognosis of patients with gliomas will likely come about through the use of new targeted therapies based on the biological knowledge of the tumors at a molecular level.
+
+To identify glioma-specific targets, consistent molecular characterization of a large number of tumors is required. To date, all the studies published have limitations due to incomplete coverage of whole-genome expression due to the usage of small or outdated, legacy, microarray platforms (2, 3), limited number of samples studied and/or incomplete inclusion of various different glioma subtypes and grades (4, 5), or the narrow scope of targets being investigated. Thus, we have put together a national, publicly funded effort that we call the Glioma Molecular Diagnostic Initiative (GMDI), which, coupled with its bioinformatics counterpart, Repository of Molecular Brain Neoplasia Data (Rembrandt), is designed to breach the gap of biological information related to primary brain tumors to help patients receive a better, biologically oriented therapy tailored to their specific needs.
+
+Rembrandt is a powerful and intuitive informatics system designed to integrate genetic and clinical information for improved research, disease diagnosis, and treatment (as shown in Fig. 1). The platform supports clinical genomic research and (as data are collected and analyzed) will create a knowledge base that allows physicians to predict clinical outcomes and therapeutic efficacy based on an individual's clinical and genetic profiles, thereby enabling personalized medicine.
+
+FIGURE 1.
+FIGURE 1. Data integration via the Rembrandt discovery platform.
+VIEW LARGEDOWNLOAD SLIDE
+Data integration via the Rembrandt discovery platform.
+
+To support discovery, the Rembrandt platform also allows researchers to search, import, and aggregate additional data from internal and external databases (such as GenBank, University of California at Santa Cruz golden path data sets, and Biocarta pathways), analyze the combined data sets to identify meaningful patterns (including specific chromosomal abnormalities), and share their research with other physicians and researchers within their own institution or in other physical locations. Each user is assigned a specific role that governs how much of the study data are accessible. A series of intuitive tools enable users to easily analyze and interact with the integrated data to achieve greater insight into molecular signatures that characterize each tumor and correlate with clinical outcome.
+
+Unlike many biomedical database systems, Rembrandt is a fully integrated platform that supports multiple facets of clinical and molecular research, discovery, and hypothesis generation. This shared environment crosses many disciplines including genetic research and clinical care. As such, the platform should serve to foster cooperation and integration between research and clinical disciplines and expedite the time and increase the depth to which molecular data become relevant to the clinical environment.
+
+Materials and Methods
+Glioma Molecular Diagnostic Initiative
+Sample Acquisition and Diagnosis. To better understand the genetic pathogenesis of gliomas and begin to identify potential glioma-specific molecular therapeutic targets, consistent molecular characterization of a large number of tumors is required.
+
+This process was undertaken under a national prospective clinical trial that would eventually be institutional review board approved both within the National Cancer Institute intramural program and through both Cancer Therapy Evaluation Program-sponsored adult brain tumor consortia (NABTT and NABTC protocol 01-07). With the activation of this study, we collected matched tumor, blood, and plasma from the 14 contributing institutions (NIH, Henry Ford Hospital, Thomas Jefferson University, University of California at San Francisco, H. Lee Moffitt Hospital, University of Wisconsin, University of Pittsburgh Medical Center, University of California at Los Angeles, The University of Texas M. D. Anderson Cancer Center, Dana-Farber Cancer Center, Duke University, Johns Hopkins University, Massachusetts General Hospital, and Memorial Sloan Kettering Cancer Center). All tissues collected are sent to the Neuro-Oncology Branch laboratory for processing. The samples were provided as snap-frozen sections of areas immediately adjacent to the region used for the histopathologic diagnosis. Initial histopathologic diagnosis is done at the tissue collecting institution following the WHO standards (6). The initial diagnosis is reviewed by in-house neuropathologists to assure a measure of consistency across samples. To date, 874 complete frozen sample sets have been accrued, of those 389 are glioblastoma multiformes, 122 are astrocytomas, 113 are oligodendrogliomas, and 33 are mixed, with the reminder still unclassified.
+
+Clinical data on the patients are collected prospectively until the patient's death through the NABTC Operations Office at The University of Texas M. D. Anderson Cancer Center and the NABTT Operations office at the Johns Hopkins University. The clinical data collected are updated into the Rembrandt database on a quarterly basis.
+
+To assure consistency in the collection, shipment, processing, assaying, storage, data retrieval, and dissemination, we have put together a series of standard operating procedures that have resulted in a streamlined, high-throughput operation capable of handling large numbers of samples in a consistent, operator-independent fashion. Consistency of data over time is continuously monitored by looking for any signs of batch effect in the analyses.
+
+mRNA Extraction and Gene Expression Data Processing. Tissue (∼50-80 mg) from each tumor was used to extract total RNA using the Trizol reagent (Invitrogen) following the manufacturer's instructions. The quality of RNA obtained was verified with the Bioanalyzer System (ref. 7; Agilent Technologies) using the RNA Pico Chips. RNA (5 μg) extracted from the accrued samples has been processed using U133 2 Plus mRNA expression chips (Affymetrix), which contains >54,000 probe sets analyzing the expression level of >47,000 transcripts and variants, including 38,500 well-characterized human genes.
+
+All arrays were confirmed to be within an acceptable minimal quality-control according to internal standard operating procedure variables following these criteria: (a) A scaling factor of <5 when the expression values are scaled to a target mean signal intensity of 500. (b) Signal intensity ratios of the 3′ to 5′ end of the internal control genes of β-actin and GAPDH < 3. (c) Affymetrix spike control (BioC, BioDN, and CreX) are always present, and percentage present calls is >35% for brain tissue.
+
+The .cel and .txt files of all the arrays that passed the minimal quality-control were input into dChip for normalization. The model-based expression index algorithm implemented in dChip selects an invariant set with a small within-subset rank difference to serve as basis for adjusting the brightness of the arrays to a comparable level. The normalization was done at the PM and MM probe levels, and model-based expression levels were calculated using normalized probe level data. We choose the average difference model (PM > MM) to compute expression values; negative average differences were truncated to 1 or log-transformed values of zeros to flag negative signal intensities with no biological meaning.
+
+For data preprocessing, probe-level data were consolidated into probe-set data using the Affymetrix MAS5 algorithm, with the target scaling value at 500. Probe-level data were also processed with custom Chip Definition Files (1) that rearranged Affymetrix probes into gene-based probe sets. Probes mapped to alternatively spliced exons were grouped into distinct probe sets. Most 3′ probes were selected for processing. Nonspecific probes were masked before processing.
+
+Single tumor samples were compared with the nontumor pool and the sample average to the nontumor pool. Samples were averaged based on tumor subtypes in six categories: glioblastoma multiforme, oligodendroglioma, astrocytoma, mixed, unclassified, and unknown tumors. Group comparisons were done in R with two sample t tests. Signal values were first transformed to logarithm (base 2). The averages of the log2 signals of tumor and nontumor groups were computed. The magnitude of the differences between the geometric means of expression levels for each reporter from the two groups was computed. The significance of the differences between tumors (or each tumor subtype) and nontumor samples for each reporter was also evaluated.
+
+For each individual tumor sample, signals for each tumor and the ratio between each tumor and the average of normal (geometric means, computed the same way as described above) were computed. All processes were done separately for various data groups (public data and institution-based data).
+
+DNA Extraction and Genomic Alteration Analysis. Tissue (∼10 μg; as recommended by the manufacturer) from each tumor was used to extract high molecular weight, genomic DNA using QIAamp DNA Micro DNA extraction kit (Qiagen) following the manufacturer's instructions. The quality of DNA was checked by electrophoresis run in a 2% agarose gel.
+
+Genomic DNA (250 ng) from samples received has been hybridized to 100K single nucleotide polymorphism chips (ref. 8; Affymetrix), which covers 116,204 single nucleotide polymorphism loci in the human genome with a mean intermarker distance of 23.6 kb. These arrays give two simultaneous data types: allelic calls and signal intensity, allowing for the determination of both copy number alterations and regions of allelic imbalances (loss of heterozygosity). Calls were determined by the GTYPE software version 3.0 with 25% level of confidence. Only samples with call rates of >90% were accepted for any analysis.
+
+Clinical Data Processing. The University of Texas M. D. Anderson Cancer Center serves as the operating center for clinical data collection for the GMDI trial. Clinical data reports from the case report forms were accessed through the Data Management Initiative Web portal at The University of Texas M. D. Anderson Cancer Center, parsed, and uploaded to the Rembrandt data warehouse after various preprocessing and data validations steps. The clinical data collected are updated into the Rembrandt database on a quarterly basis.
+
+Results
+A Rembrandt Storyboard
+To exemplify the powerful integration that Rembrandt provides to analyze a large data set of both molecular and clinical data, we would like to show how one could come about to explore the validity of a scientific hypothesis using the system.
+
+Suppose that one would have come across two publications on Glioma Tumor Stem Cells that mentioned the irregular expression of BMPR1B in such cells (9, 10).
+
+A typical Rembrandt usage scenario might be to ask if BMPR1B is a potential therapeutic target as it has been recently been postulated to be involved in cell differentiation. To answer this question, a researcher can take a stepwise workflow approach in Rembrandt as shown in Figs. 2 and 3.
+
+FIGURE 2.
+FIGURE 2. A. Gene expression box plot for BMPR1B. Samples are categorized by histologic type. Different Affymetrix probe sets are shown as different color bars. B. BMPR1B probe set in Affymetrix probe-set viewer. Information for selected probe set can be displayed, allowing the user to decide on the quality of information retrieved. C. BMPR1B probe set of interest showing outliers in glioblastoma multiforme samples. The ability to display expression graphs in different formats allows the use to gain a wealth of information without having to redo the queries.
+VIEW LARGEDOWNLOAD SLIDE
+A. Gene expression box plot for BMPR1B. Samples are categorized by histologic type. Different Affymetrix probe sets are shown as different color bars. B. BMPR1B probe set in Affymetrix probe-set viewer. Information for selected probe set can be displayed, allowing the user to decide on the quality of information retrieved. C. BMPR1B probe set of interest showing outliers in glioblastoma multiforme samples. The ability to display expression graphs in different formats allows the use to gain a wealth of information without having to redo the queries.
+
+FIGURE 3.
+FIGURE 3. A. Kaplan-Meier survival plot showing survival comparing BMRP1 up-regulating samples and the rest of the gliomas in the database. This plot allows the identification of putative clinically relevant genes to explore as new targets for therapy. Users can query gene expression and graph changes in survival rate at each time point on the study. Kaplan-Meier estimates are calculated based on the last follow-up time and the censor status (0, alive; 1, dead) from the samples of interest. Kaplan-Meier estimates are then plotted against the survival time. Users can dynamically modify the fold change (up-regulation and down-regulation) thresholds and redraw the plot. A log-rank P value is provided as an indication of significance of the difference in survival between any two groups of samples segregated based on gene expression of the gene of interest. B. Performing PCA and correlating with clinical data. An example of PCA report from the Rembrandt application. These two-dimensional (top) and three-dimensional (bottom) graphs plot the various principal components from the gene expression PCA. Various analysis options are provided to the user to select from an array of gene/reporter filtering and sample selection settings. Users can select samples in the two-dimensional plot to retrieve related clinical information on the selected patients.
+VIEW LARGEDOWNLOAD SLIDE
+A. Kaplan-Meier survival plot showing survival comparing BMRP1 up-regulating samples and the rest of the gliomas in the database. This plot allows the identification of putative clinically relevant genes to explore as new targets for therapy. Users can query gene expression and graph changes in survival rate at each time point on the study. Kaplan-Meier estimates are calculated based on the last follow-up time and the censor status (0, alive; 1, dead) from the samples of interest. Kaplan-Meier estimates are then plotted against the survival time. Users can dynamically modify the fold change (up-regulation and down-regulation) thresholds and redraw the plot. A log-rank P value is provided as an indication of significance of the difference in survival between any two groups of samples segregated based on gene expression of the gene of interest. B. Performing PCA and correlating with clinical data. An example of PCA report from the Rembrandt application. These two-dimensional (top) and three-dimensional (bottom) graphs plot the various principal components from the gene expression PCA. Various analysis options are provided to the user to select from an array of gene/reporter filtering and sample selection settings. Users can select samples in the two-dimensional plot to retrieve related clinical information on the selected patients.
+
+Explore the expression levels of BMPR1B in different subtypes of glioma. Analysis of the box plots in Rembrandt (Fig. 2A) indicates that probe-set 210523_at is differentially expressed in glioblastoma multiformes when compared with nontumors (borderline significance: P < 0.04).
+
+Where does this probe map onto the transcripts of BMPR1B? Review of probe mapping in Affymetrix probe viewer integrated into Rembrandt (Fig. 2B) shows that this probe maps to coding region.
+
+Are there two subpopulations of BMPR1B regulating samples? Review of the “box and whisker” plot in Fig. 2C indicates that glioblastoma multiformes have low-end outliers for BMPR1B expression.
+
+Now, can we identify samples that show high (up >2) and low (down <1.5) expression of BMPR1B? Advanced queries can be set up in the Rembrandt application to create sample sets with separate up-regulation and down-regulation criteria for BMPR1 expression.
+
+Does BMPR1 up-regulation affect survival? Can this sample group be compared with the rest of the gliomas? Figure 3A shows the difference in probability of survival between BMRP1 up-regulating group and the rest of the gliomas. Results indicate that BMPR1B up-regulation is bad as a prognostic factor and could be a good target for therapy.
+
+How different are these sample groups beyond BMPR1B expression? By analyzing the whole gene expression patterns in both groups using the high-order analysis tool of principal component analysis (PCA; Fig. 3B), it is possible to see that BMPR1B overexpressors and underexpressors are indeed quite different at a global expression level, suggesting that this gene may hold a key to glioma diversity.
+
+The storyboard here presented indicates that Rembrandt can effectively be used to test in silico a scientific hypothesis and allow for additional experimentation to occur. In fact, this has been the case with the scenario here presented and we have shown that BMPR1B is able in fact to modulate the tumorigenic potential of glioma cells (11). Additionally, a Rembrandt search of newly identified (NF1) and well-known (IGFBP2) targets of deregulation in gliomas shows that the result produced by our data set are concordant with the current knowledge of clinical features (Supplementary Fig. S1).
+
+Key Features in Rembrandt
+Integrating Genome Characterization Data with Clinical Outcomes
+Users can query gene expression or copy number data and graph changes in survival rate at each time point in the study. Kaplan-Meier estimates are calculated based on the last follow-up time and the censor status (0 = alive, 1 = dead) from the samples of interest. Kaplan-Meier estimates are then plotted against survival time (Fig. 3A). The points that correspond to the events with a censor status of 0 are indicated on the graph. Users can dynamically modify the fold change (up-regulation and down-regulation) thresholds and redraw the plot. A log-rank P value is provided as an indication of significance of the difference in survival between any two groups of samples segregated based on gene expression of the gene of interest. The log-rank P value is calculated using the Mantel-Haenszel procedure (12). P values are recalculated every time a new threshold is selected. Users can toggle to a unified gene expression view with lesser reporters to get a gene-based view of the expression data. To obtain the unified gene expression values, the probe-level data are processed with custom Chip Definition Files that rearrange Affymetrix probes into gene-based probe sets. Probes mapped to alternatively spliced exons are grouped into distinct probe sets. Most 3′ probes are selected for processing. Nonspecific probes are masked before processing. Similar to Kaplan-Meier plots for differential fold change analysis, Kaplan-Meier plots can be drawn for copy number data where genes are mapped to single nucleotide polymorphism probe sets by aligning the probe's physical position to aligned mRNA sequences plus 50 kb upstream and downstream for maximum coverage. Also, Kaplan-Meier plots can be drawn by selecting two patient groups of interest. These groups can be user-defined or predefined lists of patients.
+
+Performing Higher-Order Statistical Analysis on Genomic and Clinical Data Set
+Rembrandt supports computer-intensive, high-memory utilizing tasks such as higher-order gene expression analyses (such as class comparison, clustering, and PCA), where the data sets could be as large as 4 GB with an analytic cluster to allow for several simultaneous analytic jobs.
+
+Figure 3B shows an example of a PCA report from the Rembrandt application. This two-dimensional graph plots the various principal components from the gene expression PCA. Various analysis options are provided from which users can select gene/reporter filtering and sample selection settings. Users can click on the three tabs at the top of the graph to display PC1 versus PC2, PC1 versus PC3, or PC2 versus PC3. Each point on the graph represents a sample. The samples are colored by disease type. Users can click on the link on the top left-hand corner of the graph to color by gender. Patients with different survival ranges are indicated by different shapes on the graph. Users can select samples of interest by clicking on the graph and drawing a rectangle around samples to save them for future use.
+
+GenePattern Link
+Broad's GenePattern (13) combines a powerful scientific workflow platform with >90 computational and visualization tools for the analysis of genomic data. To expand a researcher's ability to analyze the glioma data sets, Rembrandt has been seamlessly integrated with GenePattern. Shown in Fig. 4A is an expression heat map of 50 additional genes that have expression patterns related to stem cell factor (14) in glioblastoma multiforme.
+
+FIGURE 4.
+FIGURE 4. A. Heat-map view in GenePattern. Subsets of data from Rembrandt can be transferred to GenePattern using standard interfaces to invoke several run-time data analysis capabilities. A heat map for 50 neighbors of stem cell factor is shown for astrocytoma and mixed glioma samples in Rembrandt. B. Scatter plot for copy number data across physical genomic locations. Scatter plots display measured copy number against physical genome location in an application called webGenome, which has been integrated with Rembrandt via standard data interfaces. These plots are context sensitive to the copy number reports generated from the copy number queries in the caIntegrator application. Users can view data at arbitrary resolutions from the entire genome on down.
+VIEW LARGEDOWNLOAD SLIDE
+A. Heat-map view in GenePattern. Subsets of data from Rembrandt can be transferred to GenePattern using standard interfaces to invoke several run-time data analysis capabilities. A heat map for 50 neighbors of stem cell factor is shown for astrocytoma and mixed glioma samples in Rembrandt. B. Scatter plot for copy number data across physical genomic locations. Scatter plots display measured copy number against physical genome location in an application called webGenome, which has been integrated with Rembrandt via standard data interfaces. These plots are context sensitive to the copy number reports generated from the copy number queries in the caIntegrator application. Users can view data at arbitrary resolutions from the entire genome on down.
+
+Plotting Copy Number Data from Patient DNA Samples against Genomic Location
+Scatter plots (shown in Fig. 4B) display measured copy number against the physical genome location in an application called webGenome, which has been integrated with Rembrandt. These plots are context sensitive to the copy number reports generated from the copy number queries in the Rembrandt application. Users can view data at arbitrary resolutions from the entire genome on down. When users move the mouse over specific probes, the system provides mouse-over probe names. Clicking on the name of an experiment or bioassay in the plot legend will highlight the corresponding data.
+
+Advanced Query and Report Interfaces
+Biomedical researchers struggle to meaningfully integrate their findings across multiple data types. Cancer is a complex disease requiring genomic, proteomic, pathology, imaging, and clinical data for a true understanding of the scope of the problem. Advanced query interfaces (as shown in Fig. 5) in Rembrandt enable this meaningful integration across data types. It allows users to mine the Rembrandt database using various genomic and clinical criteria. These queries can be combined to arrive at reports (shown in Fig. 6) that integrate data from various data domains, such as gene expression, copy number analysis, and clinical trials. Several filtering and data download options are presented in Rembrandt reports.
+
+FIGURE 5.
+FIGURE 5. User-friendly data query interface. Query pages enable users to restrict their searches in the database to specific genomic and/or clinical criteria.
+VIEW LARGEDOWNLOAD SLIDE
+User-friendly data query interface. Query pages enable users to restrict their searches in the database to specific genomic and/or clinical criteria.
+
+FIGURE 6.
+FIGURE 6. Gene expression fold report. All reports in Rembrandt are fully customizable at the report window, making unnecessary to re-run queries to refine the results.
+VIEW LARGEDOWNLOAD SLIDE
+Gene expression fold report. All reports in Rembrandt are fully customizable at the report window, making unnecessary to re-run queries to refine the results.
+
+Rembrandt System Architecture
+Rembrandt was developed using a n-tier architecture. The system was developed using Java 2 Enterprise Edition, a hybrid star data warehouse schema and various open source technologies. The back end consists of an Oracle 10g database for storing precomputed microarray differential expression, computed copy number, clinical data, and user security information. For performance reasons, normalized gene expression data used by the real-time analysis module are stored as R-binary files. The middle tier, which handles application logic and core functionality, was developed using Java and cancer Biomedical Informatics Grid software development and compatibility guidelines (15). Rembrandt application consists of standard interfaces that enable integration with third-party tools such as caArray, webGenome, and GenePattern. Rembrandt has an Analytical Server that provides on-the-fly computational analysis capability. The Analytical Server communicates asynchronously with Rembrandt's middle tier via the Java Messaging Service. Java Messaging Service allows Rembrandt to abstract the statistical packages being used for heavy computational tasks.
+
+Rembrandt Cancer Biomedical Informatics Grid Service
+Basic and clinical research has increasingly become dependent on advanced information technologies for management, exchange, and analysis of diverse biomedical data. Although a wealth of information is collected by the cancer research community, any one given researcher is faced with challenges in discovering, extracting, and analyzing the information relevant to his/her research. To address this need, the National Cancer Institute has initiated a national-scale effort, called the cancer Biomedical Informatics Grid, to develop a federation of interoperable research information systems. At the heart of the cancer Biomedical Informatics Grid approach to federated interoperability effort is a Grid middleware infrastructure, called caGrid (16). caGrid Data Services provide the means to share data via the caGrid federated infrastructure. One of the major goals of the current release of Rembrandt was to create a clinical genomic object model and expose the domain model through a caGrid data service. The purpose of the object model is to help capture the relationships between the clinical study and its associated experimental observations. The Rembrandt caGrid service can be used to obtain programmatic access to public data in Rembrandt in a federated fashion and can be found at http://caintegrator.nci.nih.gov/wsrf-rbt/services/cagrid/RembrandtGridService.
+
+Conclusion
+Large-scale data sets from genomics, proteomics, population genetics, and imaging are driving research at a previously unprecedented pace. Bioinformatics data management providers must serve these data sets in a usable way that helps find the needle in a haystack effectively and accurately. The goal of the “omic” sciences is not to generate numbers but rather “insight.” The Web interfaces are burdened with displaying terabytes of data in ways that physician scientists can comprehend and use the results to develop hypothesis for their next study or trial. Ultimately, we feel that information must be standardized, integrated, and made available at the point of care to help patients and physicians make optimal decisions.
+
+Tools such as Rembrandt have primarily focused on the usability aspect of high-throughput heterogeneous data and yet enabling power users and bioinformaticians to tap into runtime analysis tools such as gene pattern or use the programmatic interfaces that are provided via the caGrid service. From a technical standpoint, the Rembrandt platform provides developer tools for a highly scalable system to include new data types (as shown in Fig. 1) and connect with existing ones to present integrated data views to users. This flexible discovery informatics platform has aided in implementing data portals to host several other cancer clinical data sets including those from the I-SPY stage III breast cancer study and The Cancer Genome Atlas (TCGA; ref. 17) project data included in the Cancer Molecular Analysis Portal. In this respect, it is worth to point out that the new Cancer Molecular Data portal has reutilized many of the features available in Rembrandt to suit a more general set of tumor sample analysis. At the sample level, GMDI and TCGA are complementary in many levels. GMDI is a prospective study wherein 14 institutions recruited patients with any type of glioma giving a wide spectrum of demographic sampling due to the geographic dispersion of the sites. The TCGA sample collection pipeline included two centers that had retrospective sample collections of glioblastoma multiforme. Thus, TCGA focused its analysis on high-grade glioblastoma multiformes, whereas the samples in GMDI represent all glioma grades and subtypes described in the WHO classification, allowing for studies on the differences of gliomas as they progress. The clinical data obtained by the GMDI project are comprehensive, because the study was conceived as a prospective, natural history clinical trial, thus allowing for the collection of a wide range of clinical data points. On the other hand, the TCGA project, in virtue of its more focused nature, has produced more molecular data types (methylation, sequencing, and miRNA expression) than GMDI. However, the GMDI samples are being used to acquire those data types, and they will be incorporated to Rembrandt as sufficient numbers of samples are processed.
+
+The ultimate beneficiaries of Rembrandt are the brain tumor patients themselves. Rembrandt is designed to bridge the gap between biological and clinical information to help patients receive a better, biologically oriented therapy tailored to their specific needs. As such, we plan to incorporate new and useful capabilities in future releases that are not available at present time, such as the ability for researchers to incorporate their own data to the system to compare with the large data set already in the database. It is hoped that the GMDI and Rembrandt will provide a much needed resource for scientists and physicians combating brain cancer, and ultimately other forms of cancer, for providing the data and bioinformatics tool set that may allow the development of a biologically and clinically significant pathologic classification of brain tumors and help elucidate novel molecular targets for therapy.
+
+Availability
+Rembrandt is freely available to all users at https://caintergator.nci.nih.gov/rembrandt. The source code for Rembrandt is also available under a nonviral cancer Biomedical Informatics Grid license at https://gforge.nci.nih.gov/frs/download.php/1489/rembrandt_1_0.zip. The Rembrandt caGrid service is accessible at http://caintegrator.nci.nih.gov/wsrf-rbt/services/cagrid/RembrandtGridService.
+
+Web Resources
+Rembrandt clinical genomics object model: http://Rembrandt.nci.nih.gov/content/Rembrandtlfs/RembrandtEA1.0docs/index.htm.
+
+Rembrandt clinical genomics data model: http://Rembrandt.nci.nih.gov/developers/images/db_model2.jpg.
+
+Rembrandt application: http://rembrandt-db.nci.nih.gov.
+
+Rembrandt information site: http://rembrandt.nci.nih.gov.
+
+webGenome: http://webgenome.nci.nih.gov/webgenome/home.do.
+
+GenePattern: http://www.broad.mit.edu/cancer/software/genepattern/.
+
+caArray: https://array.nci.nih.gov/caarray/home.action.
+
+I-SPY trial: http://ncicb.nci.nih.gov/tools/translation_research/ispy.
+
+TCGA: http://cancergenome.nih.gov/.
+
+Cancer molecular analysis portal (access to TCGA data sets): http://cma.nci.nih.gov.
+
+Disclosure of Potential Conflicts of Interest
+No potential conflicts of interest were disclosed.
+
+Grant support: Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research and National Institute of Neurological Disorders and Stroke.
+The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
+Note: Supplementary data for this article are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/).
+S. Madhavan and J-C. Zenklusen contributed equally to this work.
+Acknowledgments
+We thank Anand Basu, Shine Jacobs, Alex Jiang, Huaitian Liu, Ram Bhattaru, Michael Harris, Kevin Rosso, Ryan Landy, Hangjiong Chen, and Ying Long for contributions to Rembrandt software development and data loading; George Komatsoulis for reviewing data sharing policies and contributing to the Rembrandt domain information model; Carl Schaefer and Tracy Lively for reviewing usecases and interim releases of the software; Juli Klemm for helping with the integration of Rembrandt with caArray data repository; Jill Hadfield for technical documentation; David Hall, Dean Jackman, and Vessalina Bakalov for efforts on webGenome; and The University of Texas M. D. Anderson Cancer Center Data Management Initiative team for making the clinical reports available from the NABTC GMDI study for populating the Rembrandt database.
+
+References
+1Cancer Statistics Branch, NIH. Cancer survival rates. In: Harras A, editor. Cancer: rates & risks. Washington (DC): U.S. Department of Health & Human Services, NIH; 1996. p. 28–34.
+2Nutt CL, Mani DR, Betensky RA, et al. Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res 2003;63:1602–7.
+3Mischel PS, Shai R, Shi T, et al. Identification of molecular subtypes of glioblastoma by gene expression profiling. Oncogene 2003;22:2361–73.
+4Phillips HS, Kharbanda S, Chen R, et al. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell 2006;9:157–73.
+5Nigro JM, Misra A, Zhang L, et al. Integrated array-comparative genomic hybridization and expression array profiles identify clinically relevant molecular subtypes of glioblastoma. Cancer Res 2005;65:1678–86.
+6Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol (Berl) 2007;114:97–109.
+7Miller CL, Diglisic S, Leister F, Webster M, Yolken RH. Evaluating RNA status for RT-PCR in extracts of postmortem human brain tissue. Biotechniques 2004;36:628–33.
+8Matsuzaki H, Dong S, Loi H, et al. Genotyping over 100,000 SNPs on a pair of oligonucleotide arrays. Nat Methods 2004;1:109–11.
+9Lee J, Kotliarova S, Kotliarov Y, et al. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell 2006;9:391–403.
+10Galli R, Binda E, Orfanelli U, et al. Isolation and characterization of tumorigenic, stem-like neural precursors from human glioblastoma. Cancer Res 2004;64:7011–21.
+11Lee J, Son MJ, Woolard K, et al. Epigenetic-mediated dysfunction of the bone morphogenetic protein pathway inhibits differentiation of glioblastoma-initiating cells. Cancer Cell 2008;13:69–80.
+12Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958;53:457–81.
+13Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP. GenePattern 2.0. Nat Genet 2006;38:500–1.
+14Sun L, Hui AM, Su Q, et al. Neuronal and glioma-derived stem cell factor induces angiogenesis within the brain. Cancer Cell 2006;9:287–300.
+15Phillips J, Chilukuri R, Fragoso G, Warzel D, Covitz PA. The caCORE Software Development Kit: streamlining construction of interoperable biomedical information services. BMC Med Inform Decis Mak 2006;6:2.
+16Oster S, Langella S, Hastings S, et al. caGrid 1.0: an enterprise Grid infrastructure for biomedical research. J Am Med Inform Assoc 2008;15:138–49.
+17McLendon R, Friedman A, Bigner D, et al. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008;455:1061–8.

samples/REMBRANDT_description.txt

@@ -0,0 +1,23 @@
+Finding better therapies for the treatment of brain tumors, is
+hampered for several reasons: 1) lack of consistently obtained
+molecular data in a large sample sets; and 2) the ability to integrate
+biomedical data from disparate sources, which would enable translation
+of therapies from bench to bedside. Hence, a critical factor in the
+advancement of biomedical research and clinical translation is the
+ease with which data can be obtained, integrated, and analyzed both
+within and across functional domains. Novel biomedical informatics
+infrastructure and tools are essential for developing individualized
+patient treatment based on the specific genomic signatures in each
+patient's tumor. The Repository of Molecular Brain Neoplasia Data
+(REMBRANDT) aims to facilitate discovery by connecting the dots
+between clinical information and genomic characterization data.
+
+REMBRANDT contains data generated through the Glioma Molecular
+Diagnostic Initiative from 874 glioma specimens, comprised of
+approx. 566 gene expression arrays, 834 copy number arrays, and 13,472
+clinical phenotype data points. These data are currently housed in
+Georgetown University's G-DOC System and are described in a related
+manuscript. The TCIA image collection was created as a companion data
+set to augment the larger REMBRANDT project. It contains the
+pre-surgical magnetic resonance (MR) multi-sequence images from 130
+REMBRANDT patients.

samples/ROI-Masks-leaderboard.tsv

@@ -0,0 +1,189 @@
+Tumor	1p_19q_co_del_status	neoplasm_histologic_grade	ProgFreeSurvEvent01	ProgFreeSurvTime_days	IDH/1p19q Subtype	death01	TERT-Promoter	ATRX	CIC	EGFR	TP53	histological_type	gender	age_at_initial_pathologic	cqcf_method_of_sample_procuremen	karnofsky_performance_sco	primary_radiation_therapy	primary_pharma_therapy	RNASeqCluster	miRNACluster	CNCluster	OncosignCluster
+TCGA-CS-4938	0	G2	0	143	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	31	Gross Total Resection	90	NA	NA	R1	mi1	C1	O2
+TCGA-CS-4941	0	G3	1	9	0	1	NA	wt	wt	wt	wt	Astrocytoma	MALE	67	Gross Total Resection	90	NO	NA	R2	mi2	C2	O3
+TCGA-CS-4942	0	G3	1	1184	2	1	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	44	Gross Total Resection	90	NO	NO	R1	mi2	C1	O2
+TCGA-CS-4943	0	G3	0	552	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	37	Gross Total Resection	50	NA	NO	R1	mi2	C1	O2
+TCGA-CS-4944	0	G2	NA	NA	2	0	NA	wt	wt	wt	wt	Astrocytoma	MALE	50	Gross Total Resection	90	NA	NA	NA	mi2	C1	O1
+TCGA-CS-5390	1	G2	0	1966	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	47	Gross Total Resection	100	YES	NO	R3	mi2	C3	O1
+TCGA-CS-5393	0	G3	0	1222	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	39	Gross Total Resection	100	NA	NA	R4	mi2	C1	O3
+TCGA-CS-5394	1	G3	NA	NA	1	0	NA	wt	Mutant	wt	wt	Astrocytoma	MALE	40	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-CS-5395	0	G2	1	287	0	1	Mutant	wt	wt	wt	wt	Oligodendroglioma	MALE	43	Gross Total Resection	90	YES	NO	R2	mi2	C2	O3
+TCGA-CS-5396	1	G3	0	303	1	0	NA	wt	wt	wt	Mutant	Oligodendroglioma	FEMALE	53	Gross Total Resection	90	YES	YES	R3	mi2	C3	O2
+TCGA-CS-5397	0	G3	1	194	0	1	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	54	Gross Total Resection	80	YES	YES	NA	mi1	C2	O3
+TCGA-CS-6186	0	G3	1	188	0	1	NA	wt	wt	wt	wt	Oligoastrocytoma	MALE	58	Gross Total Resection	90	YES	NO	R2	mi1	C2	O3
+TCGA-CS-6188	0	G3	1	647	0	0	NA	wt	wt	wt	wt	Astrocytoma	MALE	48	Gross Total Resection	90	YES	NA	R2	mi3	C2	O3
+TCGA-CS-6290	0	G3	0	546	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	31	Gross Total Resection	90	NA	NA	R1	mi2	C1	O2
+TCGA-CS-6665	0	G3	0	378	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	51	Gross Total Resection	90	YES	NA	R2	mi1	C1	O2
+TCGA-CS-6666	0	G3	0	258	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	22	Gross Total Resection	90	NA	NA	NA	mi2	C1	O2
+TCGA-CS-6667	0	G2	0	230	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	39	Gross Total Resection	90	YES	NA	R1	mi1	C1	O2
+TCGA-CS-6668	1	G2	0	244	1	0	Mutant	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	57	Gross Total Resection	90	NA	NA	R3	mi2	C3	O1
+TCGA-CS-6669	0	G2	0	225	0	0	wt	wt	wt	wt	wt	Oligodendroglioma	FEMALE	26	Gross Total Resection	90	NA	YES	R4	mi1	C1	O1
+TCGA-DU-5849	1	G2	0	443	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	48	Biopsy Only	NA	NA	YES	R4	mi2	C3	O1
+TCGA-DU-5851	0	G3	0	531	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	40	Biopsy Only	90	YES	YES	R4	mi1	C1	O2
+TCGA-DU-5852	0	G3	1	24	0	1	NA	wt	wt	Mutant	wt	Oligoastrocytoma	FEMALE	61	Subtotal Resection	80	NO	NA	R2	mi4	C2	O3
+TCGA-DU-5853	0	G2	0	407	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	29	Gross Total Resection	100	YES	YES	R1	mi2	C1	O2
+TCGA-DU-5854	0	G3	1	202	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	57	Biopsy Only	90	NA	NA	R2	mi1	C2	O3
+TCGA-DU-5855	0	G3	0	207	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	49	Subtotal Resection	100	YES	YES	R1	mi4	C1	O2
+TCGA-DU-5871	0	G2	0	576	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	37	Biopsy Only	100	NA	NA	R1	mi2	C1	O2
+TCGA-DU-5872	0	G2	1	265	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	43	Biopsy Only	NA	YES	YES	NA	mi4	C1	O2
+TCGA-DU-5874	1	G2	0	461	1	0	Mutant	wt	wt	wt	wt	Oligodendroglioma	FEMALE	62	Subtotal Resection	100	NA	YES	R3	mi2	C3	O1
+TCGA-DU-6395	0	G2	1	1197	2	1	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	31	Subtotal Resection	NA	NA	NO	R1	mi2	C1	O2
+TCGA-DU-6397	1	G3	1	837	1	1	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	45	Subtotal Resection	NA	YES	NO	R3	mi2	C3	O1
+TCGA-DU-6399	0	G2	1	1629	0	1	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	54	Subtotal Resection	NA	YES	NA	R1	mi2	C1	O2
+TCGA-DU-6400	1	G2	1	37	1	1	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	66	Subtotal Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-DU-6401	0	G2	1	1886	2	1	wt	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	31	Subtotal Resection	NA	NO	NO	R1	mi2	C1	O2
+TCGA-DU-6402	0	G3	1	103	0	1	NA	wt	wt	wt	wt	Astrocytoma	MALE	52	Subtotal Resection	NA	YES	NO	R2	mi3	C2	O3
+TCGA-DU-6404	0	G3	1	1154	0	1	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	24	Gross Total Resection	100	NA	NA	R2	mi1	C1	O2
+TCGA-DU-6405	0	G3	1	486	0	1	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	51	Subtotal Resection	90	YES	YES	R2	mi1	C2	O3
+TCGA-DU-6407	0	G2	1	2397	2	1	wt	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	35	Subtotal Resection	90	NA	NA	R1	mi1	C1	O2
+TCGA-DU-6408	0	G3	1	2097	2	1	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	23	Subtotal Resection	90	NA	NO	NA	mi2	C1	O2
+TCGA-DU-6410	1	G3	0	242	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	56	Subtotal Resection	50	NA	YES	R3	mi4	C3	O1
+TCGA-DU-6542	0	G3	NA	NA	2	0	NA	wt	wt	wt	Mutant	Oligoastrocytoma	MALE	25	Subtotal Resection	NA	NA	NA	NA	mi2	C1	O2
+TCGA-DU-7008	0	G2	1	330	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	41	Subtotal Resection	NA	NA	NA	R4	mi2	C1	O2
+TCGA-DU-7010	0	G3	1	193	2	1	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	58	Subtotal Resection	NA	NA	NA	R2	mi2	C2	O2
+TCGA-DU-7013	0	G3	1	187	0	1	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	59	Subtotal Resection	80	NA	NA	R2	mi3	C2	O2
+TCGA-DU-7014	0	G2	1	3437	NA	1	NA	NA	NA	NA	NA	Oligodendroglioma	MALE	59	Subtotal Resection	100	NA	NA	R1	mi1	C1	NA
+TCGA-DU-7015	0	G2	1	591	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	41	Subtotal Resection	90	NA	NA	R1	mi2	C1	O2
+TCGA-DU-7018	1	G3	1	338	1	1	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	57	Subtotal Resection	90	NA	NA	R3	mi2	C3	O1
+TCGA-DU-7019	0	G3	0	800	2	0	NA	wt	wt	wt	Mutant	Oligoastrocytoma	MALE	39	Subtotal Resection	100	YES	YES	NA	mi2	C1	O2
+TCGA-DU-7294	1	G2	0	2869	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	53	Subtotal Resection	100	NA	NA	R3	mi2	C3	O1
+TCGA-DU-7298	0	G3	1	200	2	1	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	38	Subtotal Resection	80	NA	NA	R4	mi2	C1	O2
+TCGA-DU-7299	0	G3	1	675	2	1	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	33	Subtotal Resection	90	YES	NA	NA	mi4	C1	O2
+TCGA-DU-7300	1	G3	1	317	1	1	NA	wt	wt	wt	Mutant	Oligodendroglioma	FEMALE	53	Subtotal Resection	90	NA	NA	R4	mi1	C3	O1
+TCGA-DU-7301	0	G2	1	366	2	1	wt	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	53	Subtotal Resection	100	NA	NA	R1	mi2	C1	O2
+TCGA-DU-7302	1	G3	1	1374	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	48	Subtotal Resection	90	NA	NA	R4	mi2	C3	O1
+TCGA-DU-7304	0	G3	1	309	2	1	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	43	Gross Total Resection	80	NA	NA	R4	mi1	C1	O2
+TCGA-DU-7306	0	G2	1	1250	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	67	Subtotal Resection	100	YES	YES	NA	mi2	C1	O2
+TCGA-DU-7309	0	G3	0	84	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	41	Gross Total Resection	90	NA	NA	R4	mi1	C1	O2
+TCGA-HT-7684	0	G3	0	184	2	0	NA	wt	Mutant	wt	wt	Oligoastrocytoma	FEMALE	29	Gross Total Resection	NA	NO	NO	R4	mi2	C3	O1
+TCGA-HT-7681	1	G2	0	1359	1	0	NA	wt	wt	wt	wt	Oligoastrocytoma	MALE	58	Gross Total Resection	NA	NA	NA	NA	mi1	C3	O1
+TCGA-HT-7686	0	G3	0	1300	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	29	Gross Total Resection	NA	YES	YES	R2	mi3	C1	O2
+TCGA-HT-7687	1	G3	NA	NA	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	74	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-HT-7688	0	G3	0	964	2	0	NA	wt	wt	wt	Mutant	Oligodendroglioma	MALE	59	Gross Total Resection	NA	YES	YES	R4	mi1	C1	O2
+TCGA-HT-7689	0	G2	0	455	2	0	wt	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	58	Gross Total Resection	60	YES	YES	R1	mi2	C1	O2
+TCGA-HT-7690	0	G3	0	3	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	29	Gross Total Resection	NA	NA	NA	R2	mi2	C1	O2
+TCGA-HT-7691	0	G2	0	3	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	31	Gross Total Resection	NA	NA	NA	R2	mi1	C1	O1
+TCGA-HT-7692	1	G2	0	90	1	0	NA	wt	wt	wt	wt	Oligoastrocytoma	MALE	43	Gross Total Resection	100	YES	NA	R3	mi2	C3	O1
+TCGA-HT-7693	0	G2	0	533	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	51	Gross Total Resection	90	NA	NA	R1	mi2	C3	O2
+TCGA-HT-7694	1	G3	0	210	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	60	Gross Total Resection	90	YES	NA	R4	mi1	C3	O1
+TCGA-HT-7695	1	G2	0	442	1	0	Mutant	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	29	Gross Total Resection	NA	YES	YES	R4	mi1	C3	O1
+TCGA-HT-7854	0	G2	1	1147	0	0	NA	wt	wt	wt	wt	Astrocytoma	MALE	62	Gross Total Resection	100	NO	NA	R2	mi1	C1	O3
+TCGA-HT-7855	0	G3	0	585	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	39	Gross Total Resection	NA	YES	YES	R1	mi2	C1	O2
+TCGA-HT-7856	1	G3	0	1189	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	35	Gross Total Resection	NA	YES	YES	R4	mi1	C3	O1
+TCGA-HT-7857	0	G3	0	7	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	24	Gross Total Resection	NA	NA	NA	R2	mi3	C1	O2
+TCGA-HT-7858	0	G2	0	1540	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	28	Gross Total Resection	NA	YES	NA	R1	mi1	C1	O2
+TCGA-HT-7860	0	G3	NA	NA	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	60	Gross Total Resection	NA	NA	NA	R2	mi1	C2	O3
+TCGA-HT-7873	0	G2	0	718	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	29	Gross Total Resection	NA	YES	NA	R1	mi2	C1	O2
+TCGA-HT-7874	1	G3	0	1130	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	41	Gross Total Resection	NA	YES	YES	R4	mi1	C3	O1
+TCGA-HT-7875	1	G2	0	10	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	56	Gross Total Resection	80	NA	NA	R4	mi2	C3	O1
+TCGA-HT-7877	1	G2	0	4	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	20	Gross Total Resection	NA	NA	NA	R4	mi2	C3	O1
+TCGA-HT-7879	0	G3	0	112	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	31	Gross Total Resection	NA	YES	YES	R1	mi2	C1	O2
+TCGA-HT-7880	0	G2	0	162	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	30	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O2
+TCGA-HT-7881	1	G2	0	89	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	38	Gross Total Resection	NA	YES	NA	R4	mi1	C3	O1
+TCGA-HT-7882	0	G3	1	113	0	1	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	66	Gross Total Resection	NA	NA	NA	R2	mi3	C1	O1
+TCGA-HT-7884	0	G2	0	343	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	44	Gross Total Resection	80	YES	YES	NA	mi2	C1	O2
+TCGA-HT-7902	0	G2	0	956	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	30	Gross Total Resection	NA	NA	NA	NA	mi1	C1	O2
+TCGA-HT-8010	1	G2	0	50	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	64	Gross Total Resection	NA	NA	NA	R4	mi1	C3	O1
+TCGA-HT-8011	0	G3	1	278	0	0	NA	wt	wt	wt	wt	Astrocytoma	MALE	55	Gross Total Resection	NA	YES	YES	R2	mi4	C2	O3
+TCGA-HT-8012	1	G2	1	133	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	30	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-HT-8013	0	G2	1	1306	2	1	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	37	Gross Total Resection	NA	NO	NO	R1	mi1	C1	O2
+TCGA-HT-8015	0	G2	NA	NA	0	0	NA	wt	wt	wt	wt	Astrocytoma	MALE	21	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O3
+TCGA-HT-8018	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	40	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O2
+TCGA-HT-8019	0	G3	NA	NA	0	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	34	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O1
+TCGA-HT-8104	0	G3	NA	NA	0	0	NA	wt	wt	Mutant	wt	Astrocytoma	FEMALE	51	Gross Total Resection	NA	YES	NA	R2	mi1	C2	O3
+TCGA-HT-8105	1	G3	0	190	1	0	NA	wt	Mutant	wt	Mutant	Oligodendroglioma	MALE	54	Gross Total Resection	NA	YES	NA	R3	mi2	C3	O1
+TCGA-HT-8106	0	G3	0	3	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	53	Gross Total Resection	NA	NA	NA	R2	mi3	C1	O2
+TCGA-HT-8107	0	G2	0	14	0	0	NA	wt	wt	Mutant	wt	Oligodendroglioma	MALE	62	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O3
+TCGA-HT-8108	0	G2	0	76	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	26	Gross Total Resection	NA	NA	NA	R1	mi2	C1	O2
+TCGA-HT-8109	1	G3	NA	NA	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	64	Gross Total Resection	NA	NA	NA	R4	mi1	C3	O1
+TCGA-HT-8110	0	G3	NA	NA	0	0	NA	wt	wt	Mutant	wt	Astrocytoma	MALE	57	Gross Total Resection	NA	YES	NA	R2	mi1	C2	O3
+TCGA-HT-8111	0	G3	NA	NA	2	0	NA	wt	wt	wt	Mutant	Oligoastrocytoma	MALE	32	Gross Total Resection	NA	NA	NA	R1	mi1	C1	O2
+TCGA-HT-8113	0	G2	0	900	2	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	49	Gross Total Resection	NA	YES	YES	R4	mi1	C1	O1
+TCGA-HT-8114	0	G3	0	118	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	36	Gross Total Resection	NA	YES	YES	R1	mi2	C1	O2
+TCGA-HT-8558	NA	G2	0	52	0	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	29	Gross Total Resection	NA	NO	NO	R4	mi1	NA	NA
+TCGA-HT-8563	0	G3	0	488	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	30	Gross Total Resection	NA	YES	NO	R2	mi3	C1	O2
+TCGA-HT-8564	0	G3	1	120	0	0	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	47	Gross Total Resection	80	YES	YES	R4	mi4	C1	O2
+TCGA-HT-A4DS	0	G3	NA	NA	0	0	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	55	Gross Total Resection	NA	NA	NA	R2	mi2	C1	O2
+TCGA-HT-A4DV	1	G3	0	319	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	51	Gross Total Resection	90	YES	YES	R4	mi2	C3	O1
+TCGA-HT-A5R5	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	33	Gross Total Resection	NA	NA	NA	R4	mi2	C1	O2
+TCGA-HT-A5R7	0	NA	NA	NA	2	NA	NA	Mutant	wt	wt	wt	NA	NA	NA	Gross Total Resection	NA	NA	NA	R4	mi2	C1	O2
+TCGA-HT-A5RA	0	G3	0	447	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	65	Gross Total Resection	70	YES	YES	R2	mi2	C2	O3
+TCGA-HT-A5RB	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	24	Gross Total Resection	NA	NA	NA	R4	mi2	C1	O2
+TCGA-HT-A5RC	0	G3	1	162	0	1	NA	wt	wt	Mutant	wt	Astrocytoma	FEMALE	70	Gross Total Resection	40	YES	YES	R2	mi2	C2	O3
+TCGA-HT-A61A	0	G2	NA	NA	NA	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	20	Subtotal Resection	80	YES	YES	NA	mi2	C1	O2
+TCGA-HT-A61B	1	G2	0	396	2	NA	NA	wt	wt	wt	Mutant	NA	NA	NA	Gross Total Resection	NA	NA	NA	NA	mi2	C3	O1
+TCGA-HT-A61C	0	G2	NA	NA	0	NA	NA	wt	wt	Mutant	wt	NA	NA	NA	Gross Total Resection	NA	NA	NA	NA	mi2	C1	O2
+TCGA-HT-A614	0	G2	1	395	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	47	Gross Total Resection	NA	NA	NA	NA	mi2	C2	O3
+TCGA-HT-A615	0	G3	0	162	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	38	Gross Total Resection	90	YES	NO	NA	mi2	C1	O2
+TCGA-HT-A616	1	NA	NA	NA	2	0	NA	Mutant	wt	wt	wt	Astrocytoma	FEMALE	36	Gross Total Resection	NA	NO	NO	NA	mi2	C3	O1
+TCGA-HT-A617	NA	G2	NA	NA	0	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	47	Gross Total Resection	60	NA	NA	NA	mi2	NA	NA
+TCGA-HT-A618	0	NA	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	37	Gross Total Resection	80	YES	YES	NA	mi2	C1	O2
+TCGA-HT-A619	0	NA	NA	NA	1	NA	NA	wt	Mutant	wt	wt	NA	NA	NA	Gross Total Resection	NA	NA	NA	NA	mi4	C2	O3
+TCGA-DU-8158	0	G3	NA	NA	0	1	NA	wt	wt	Mutant	wt	Astrocytoma	FEMALE	57	Subtotal Resection	80	YES	YES	R2	mi4	C2	O3
+TCGA-DU-8162	0	G3	1	402	0	1	NA	wt	wt	Mutant	wt	Oligoastrocytoma	FEMALE	61	Subtotal Resection	80	YES	YES	R4	mi1	C1	O3
+TCGA-DU-8163	0	G3	1	509	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	29	Subtotal Resection	90	YES	YES	R1	mi1	C1	O2
+TCGA-DU-8164	1	G2	0	651	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	51	Subtotal Resection	NA	NA	YES	R4	mi2	C3	O3
+TCGA-DU-8165	0	G3	0	582	0	0	NA	wt	wt	wt	Mutant	Oligodendroglioma	FEMALE	60	Subtotal Resection	90	YES	YES	R2	mi3	C2	O2
+TCGA-DU-8166	0	G2	1	193	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	29	Subtotal Resection	NA	YES	YES	R4	mi2	C1	O2
+TCGA-DU-8167	0	G2	0	471	2	0	NA	wt	wt	wt	Mutant	Oligoastrocytoma	FEMALE	69	Subtotal Resection	100	YES	NA	R1	mi1	C1	O2
+TCGA-DU-8168	1	G3	0	431	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	55	Gross Total Resection	70	YES	YES	R3	mi2	C3	O1
+TCGA-DU-A5TP	0	G3	1	203	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	33	Subtotal Resection	70	YES	YES	R2	mi2	C3	O2
+TCGA-DU-A5TR	0	G2	0	383	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	51	Biopsy Only	90	YES	YES	R2	mi2	C1	O2
+TCGA-DU-A5TS	0	G2	0	460	2	0	NA	Mutant	wt	wt	wt	Oligodendroglioma	MALE	42	Subtotal Resection	100	YES	YES	NA	mi2	C1	O2
+TCGA-DU-A5TT	0	G3	0	151	0	0	NA	wt	wt	Mutant	wt	Oligodendroglioma	MALE	70	Subtotal Resection	NA	YES	YES	R2	mi2	C2	O2
+TCGA-DU-A5TU	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	62	Subtotal Resection	50	NO	NO	R2	mi4	C1	O2
+TCGA-DU-A5TW	0	G3	0	172	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	33	Subtotal Resection	100	NO	NO	R1	mi2	C1	O2
+TCGA-DU-A5TY	0	G3	0	371	0	0	NA	wt	wt	Mutant	wt	Astrocytoma	FEMALE	46	Subtotal Resection	NA	YES	YES	R2	mi4	C2	O3
+TCGA-EZ-7264	1	G2	0	436	1	0	Mutant	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	47	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-FG-5962	1	G3	0	1453	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	54	Subtotal Resection	NA	YES	YES	R4	mi1	C3	NA
+TCGA-FG-5963	0	G3	1	497	0	1	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	23	Subtotal Resection	90	YES	NO	R2	mi1	C1	NA
+TCGA-FG-5964	1	G2	0	1045	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	62	Subtotal Resection	NA	NO	NA	NA	mi2	C3	NA
+TCGA-FG-5965	0	G2	1	1035	2	1	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	39	Subtotal Resection	90	YES	NO	NA	mi1	C3	NA
+TCGA-FG-6688	0	G3	1	405	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	59	Subtotal Resection	80	YES	NO	R2	mi1	C2	O3
+TCGA-FG-6689	0	G2	1	218	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	30	Subtotal Resection	70	NO	NO	R4	mi2	C1	O2
+TCGA-FG-6690	0	G2	0	760	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	70	Subtotal Resection	90	YES	NA	R1	mi2	C3	O2
+TCGA-FG-6691	0	G2	0	729	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	FEMALE	23	Gross Total Resection	100	NA	NA	R1	mi2	C1	O2
+TCGA-FG-6692	0	G3	1	561	0	1	NA	wt	wt	Mutant	wt	Oligodendroglioma	MALE	63	Subtotal Resection	NA	YES	NO	R2	mi4	C2	O3
+TCGA-FG-7634	1	G2	0	467	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	28	Subtotal Resection	NA	NA	NA	NA	mi2	C2	O1
+TCGA-FG-7637	NA	G2	0	1219	NA	0	NA	wt	wt	wt	wt	Oligoastrocytoma	MALE	49	Subtotal Resection	NA	NA	NA	R3	mi2	NA	NA
+TCGA-FG-7641	1	G2	0	627	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	31	Gross Total Resection	NA	NA	NA	R4	mi2	C3	O1
+TCGA-FG-7643	0	G2	1	254	0	0	NA	wt	wt	wt	wt	Oligoastrocytoma	FEMALE	49	Subtotal Resection	NA	NA	NA	R4	mi1	C2	O1
+TCGA-FG-8186	1	G3	0	487	1	0	NA	wt	wt	wt	wt	Oligoastrocytoma	FEMALE	42	Subtotal Resection	70	YES	NA	NA	mi2	C3	O1
+TCGA-FG-8189	0	G2	0	361	2	0	NA	wt	wt	wt	wt	Oligodendroglioma	FEMALE	33	Subtotal Resection	70	YES	YES	R4	mi2	C1	O1
+TCGA-FG-A4MT	0	G2	1	499	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	FEMALE	27	Gross Total Resection	100	NO	NO	R1	mi2	C1	O2
+TCGA-FG-A4MU	0	G3	NA	NA	0	0	NA	wt	wt	Mutant	wt	Oligoastrocytoma	MALE	58	Subtotal Resection	NA	NA	NA	R2	mi3	C2	O3
+TCGA-FG-A60K	1	G2	0	202	1	0	NA	wt	Mutant	wt	wt	Oligoastrocytoma	FEMALE	34	Gross Total Resection	NA	NO	NO	NA	mi2	C3	O1
+TCGA-HT-7467	1	G2	NA	NA	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	54	Gross Total Resection	NA	NA	NA	R4	mi1	C3	O1
+TCGA-HT-7468	1	G3	0	203	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	30	Gross Total Resection	80	NA	YES	R3	mi2	C3	O1
+TCGA-HT-7469	0	G3	1	92	0	1	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	30	Gross Total Resection	NA	YES	YES	R2	mi2	C1	O2
+TCGA-HT-7470	0	G3	0	268	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	37	Gross Total Resection	90	YES	YES	R4	mi1	C1	O2
+TCGA-HT-7471	1	G3	NA	NA	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	FEMALE	37	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-HT-7472	0	G2	0	1	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	38	Gross Total Resection	NA	NA	NA	R1	mi2	C3	O2
+TCGA-HT-7473	0	G2	0	503	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	28	Gross Total Resection	NA	NO	NA	R1	mi2	C1	O2
+TCGA-HT-7474	0	G2	0	114	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	52	Gross Total Resection	NA	NA	NA	R4	mi1	C1	O2
+TCGA-HT-7475	0	G3	0	530	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	67	Gross Total Resection	70	YES	NO	R4	mi2	C1	O2
+TCGA-HT-7476	0	G2	0	199	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	26	Gross Total Resection	NA	YES	YES	R4	mi1	C1	O2
+TCGA-HT-7477	0	G3	0	738	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	62	Gross Total Resection	80	YES	YES	R2	mi2	C2	O2
+TCGA-HT-7478	0	G2	0	194	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	36	Gross Total Resection	NA	YES	NA	R2	mi4	C1	O2
+TCGA-HT-7479	0	G3	0	216	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	MALE	44	Gross Total Resection	NA	NA	YES	R1	mi1	C1	O2
+TCGA-HT-7480	1	G2	1	1943	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	33	Gross Total Resection	NA	YES	YES	R4	mi2	C3	O1
+TCGA-HT-7481	1	G2	1	880	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	39	Gross Total Resection	NA	NO	NA	R4	mi2	C3	O1
+TCGA-HT-7482	0	G2	1	374	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	18	Gross Total Resection	NA	NO	NO	R1	mi1	C1	O2
+TCGA-HT-7483	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	14	Gross Total Resection	NA	NA	NA	R4	mi2	C1	O2
+TCGA-HT-7485	0	G2	0	122	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	42	Gross Total Resection	100	NA	NA	R1	mi1	C1	O2
+TCGA-HT-7601	0	G3	0	153	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	30	Gross Total Resection	NA	YES	YES	R2	mi3	C3	O2
+TCGA-HT-7602	0	G2	NA	NA	2	0	wt	wt	wt	wt	Mutant	Oligodendroglioma	MALE	21	Gross Total Resection	NA	NA	NA	R1	mi1	C1	O2
+TCGA-HT-7603	0	G2	0	705	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	29	Gross Total Resection	NA	YES	NA	R4	mi1	C1	O2
+TCGA-HT-7604	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Astrocytoma	MALE	50	Gross Total Resection	NA	NA	NA	R1	mi2	C1	O2
+TCGA-HT-7605	1	G2	0	139	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	38	Gross Total Resection	NA	NA	NA	R4	mi1	C3	O1
+TCGA-HT-7606	0	G2	0	526	2	0	NA	wt	wt	wt	Mutant	Astrocytoma	FEMALE	30	Gross Total Resection	NA	YES	YES	R1	mi2	C1	O2
+TCGA-HT-7607	1	G2	1	96	1	1	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	61	Gross Total Resection	70	NA	NA	R4	mi1	C3	O1
+TCGA-HT-7608	1	G2	0	671	1	0	NA	wt	wt	wt	wt	Oligoastrocytoma	MALE	61	Gross Total Resection	NA	NA	NA	NA	mi2	C3	O1
+TCGA-HT-7609	0	G3	0	1399	2	0	NA	wt	wt	wt	Mutant	Oligoastrocytoma	MALE	34	Gross Total Resection	90	YES	YES	R1	mi2	C1	O2
+TCGA-HT-7610	0	G2	1	1205	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	FEMALE	25	Gross Total Resection	NA	NA	NA	R4	mi2	C3	O2
+TCGA-HT-7611	0	G2	0	1752	2	0	NA	Mutant	wt	wt	Mutant	Oligoastrocytoma	MALE	36	Gross Total Resection	90	NO	NO	R1	mi2	C1	O2
+TCGA-HT-7616	1	G3	1	7	1	1	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	75	Gross Total Resection	NA	NA	NA	R3	mi2	C3	O1
+TCGA-HT-7620	1	G3	1	280	1	0	NA	wt	wt	wt	wt	Oligodendroglioma	MALE	40	Gross Total Resection	NA	YES	NO	NA	mi1	C3	O1
+TCGA-HT-7676	0	G2	NA	NA	2	0	NA	Mutant	wt	wt	Mutant	Oligodendroglioma	MALE	26	Gross Total Resection	NA	NA	NA	R1	mi2	C1	O2
+TCGA-HT-7677	1	G3	0	494	1	0	NA	wt	Mutant	wt	wt	Oligodendroglioma	MALE	53	Gross Total Resection	NA	YES	YES	R3	mi2	C3	O1
+TCGA-HT-7680	0	G2	0	23	0	0	NA	wt	wt	wt	wt	Astrocytoma	FEMALE	32	Gross Total Resection	NA	NA	NA	R2	mi1	C1	O2

samples/ROI-Masks.txt

@@ -0,0 +1,211 @@
+From : https://academic.oup.com/neuro-oncology/article/19/6/862/2948265
+
+MRI features predict survival and molecular markers in diffuse lower-grade gliomas 
+Hao Zhou, Martin Vallières, Harrison X. Bai, Chang Su, Haiyun Tang, Derek Oldridge, Zishu Zhang, Bo Xiao, Weihua Liao, Yongguang Tao ... Show moreAuthor Notes
+Neuro-Oncology, Volume 19, Issue 6, 1 June 2017, Pages 862–870, https://doi.org/10.1093/neuonc/now256
+Published: 24 January 2017
+A correction has been published: Neuro-Oncology, Volume 19, Issue 12, December 2017, Page 1701, https://doi.org/10.1093/neuonc/nox110
+pdfPDF
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+Abstract
+Background.
+Previous studies have shown that MR imaging features can be used to predict survival and molecular profile of glioblastoma. However, no study of a similar type has been performed on lower-grade gliomas (LGGs).
+
+Methods.
+Presurgical MRIs of 165 patients with diffuse low- and intermediate-grade gliomas (histological grades II and III) were scored according to the Visually Accessible Rembrandt Images (VASARI) annotations. Radiomic models using automated texture analysis and VASARI features were built to predict isocitrate dehydrogenase 1 (IDH1) mutation, 1p/19q codeletion status, histological grade, and tumor progression.
+
+Results.
+Interrater analysis showed significant agreement in all imaging features scored (k = 0.703–1.000). On multivariate Cox regression analysis, no enhancement and a smooth non-enhancing margin were associated with longer progression-free survival (PFS), while a smooth non-enhancing margin was associated with longer overall survival (OS) after taking into account age, grade, tumor location, histology, extent of resection, and IDH1 1p/19q subtype. Using logistic regression and bootstrap testing evaluations, texture models were found to possess higher prediction potential for IDH1 mutation, 1p/19q codeletion status, histological grade, and progression of LGGs than VASARI features, with areas under the receiver-operating characteristic curves of 0.86 ± 0.01, 0.96 ± 0.01, 0.86 ± 0.01, and 0.80 ± 0.01, respectively.
+
+Conclusion.
+No enhancement and a smooth non-enhancing margin on MRI were predictive of longer PFS, while a smooth non-enhancing margin was a significant predictor of longer OS in LGGs. Textural analyses of MR imaging data predicted IDH1 mutation, 1p/19q codeletion, histological grade, and tumor progression with high accuracy.
+
+1p/19q codeletion, IDH1 mutation, lower-grade gliomas, MR imaging, texture analysis
+Topic: magnetic resonance imagingmutationglioblastomagliomadiagnostic imagingneoplasmscox proportional hazards modelstumor progressionidh1 geneprogression-free survivalradiomics
+Issue Section: CLINICAL INVESTIGATIONS
+Importance of the study
+Previous studies have shown that MRI features scored according to VASARI annotations can be used to predict survival and molecular profile of glioblastoma. However, no study of similar type has been performed on LGGs. On multivariate analysis, we showed that no enhancement on MRI was associated with longer PFS, while a smooth non-enhancing margin was associated with longer PFS and OS compared with an irregular non-enhancing margin. Our results demonstrated that imaging features scored using a standardized vocabulary had prognostic value in addition to traditionally recognized clinical and molecular markers in LGGs. In addition, multivariable texture models extracted from baseline MRI scans have the potential to accurately classify LGGs in terms of IDH1 mutation, 1p/19q codeletion, histological grade, and tumor progression. With proven accuracy, textural analysis will complement invasive tissue sampling, guiding patient management at an earlier stage of disease and in follow-up. Textural analysis may even serve as the standard in cases where invasive procedure is not available or appropriate.
+
+Diffuse lower-grade gliomas (LGGs) are infiltrative neoplasms that generally include diffuse low- and intermediate-grade gliomas (World Health Organization [WHO] grade II or III).1 The outcomes of these tumors are variable—some recur after treatment within months and even progress to glioblastoma (WHO grade IV gliomas), while others remain indolent for years.2 Traditionally, the natural progression of LGGs is thought to be dependent on their histological class (astrocytomas vs oligoastrocytomas vs oligodendrogliomas). However, a recent study from The Cancer Genome Atlas (TCGA) Research Network classified LGGs into 3 categories based on isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status: gliomas with an IDH mutation and 1p/19q codeletion, gliomas with an IDH mutation but no 1p/19q codeletion, and gliomas with wild-type IDH.1 This new classification scheme has been shown to capture the biologic characteristics of LGGs with greater fidelity than does histological class.1
+
+MRI has served as an important noninvasive method for diagnosing gliomas and monitoring their treatment response. Previous radiogenomic analyses of glioblastoma have shown that the proportion of contrast enhancement (CE) and longest axis length of tumor on MR were significantly associated with poor survival.3 In a recent study of 120 patients with primary grades III (n = 35) and IV (n = 85) gliomas, Zhang et al. built a model using nonredundant preoperative MRIs and clinical data with a random forest algorithm that achieved accuracies of 86% in the training cohort and 89% in the validation cohort in predicting IDH genotype.4 However, no similar study has been performed to determine the association of MR imaging features with survival and molecular markers in LGGs.
+
+To make the assessment of MR imaging features in gliomas more accurate and reproducible, a comprehensive feature set known as the Visually Accessible Rembrandt Images (VASARI) was developed in 2008. The VASARI annotations include 30 distinct imaging features with corresponding criteria clustered by categories related to lesion location, morphology of the lesion substance, morphology of the lesion margin, alterations in the vicinity of the lesion, and remote alterations (https://wiki.nci.nih.gov/display/CIP/VASARI).5 Previous studies have shown that measurements of these features by VASARI were highly reproducible, clinically meaningful, and biologically relevant in glioblastoma.3,6
+
+Radiomics extracts and mines a large number of medical imaging features.7 These approaches based on machine learning have been increasingly used to quantify tumor phenotypic characteristics and to predict clinical outcomes.7 In 2014, Aerts et al.8 demonstrated that imaging features quantifying tumor image intensity, shape, and texture extracted from computed tomography data of 1019 patients with lung or head-and-neck cancer not only had prognostic power in the independent datasets of lung and head-and-neck cancer patients, but also had associations with gene-expression patterns. In 2015, Vallières et al.9 built a radiomics model from joint 2-fluoro-2-deoxy-D-glucose PET and MRI texture features using bootstrapping evaluations that predicted lung metastases in soft tissue sarcomas of the extremities with high sensitivity and specificity.
+
+The purpose of our study was to perform a comprehensive analysis of MR imaging features of LGGs by using the VASARI feature set, as they relate to patient survival and molecular markers. In addition, we explored the possibility of using textural features extracted from MR imaging to make binary predictions of wild-type IDH versus IDH1 mutation; IDH1 mutation with 1p/19q codeletion versus IDH1 mutation without 1p/19q codeletion; grade II versus grade III LGGs; and progression versus nonprogression of LGGs.
+
+Materials and Methods
+Study Data
+We identified 165 patients with diffuse low- and intermediate-grade gliomas (histological grades II and III) from TCGA who have overlapping presurgical MRI data from The Cancer Imaging Archive (TCIA),10,11 an imaging sharing resource that houses images corresponding to TCGA patients. A flowchart of the number of patients included for each analysis, along with the number of and reason why patients were excluded from each analysis, is shown in Fig. 1. As the patients had been previously de-identified by TCGA/TCIA, and their relevant information was available for public download, no institutional review board or Health Insurance Portability and Accountability Act approval was required for our study.
+
+Fig. 1
+Flowchart of patients included and excluded for each analysis.
+Open in new tabDownload slide
+Flowchart of patients included and excluded for each analysis.
+
+Imaging Review: VASARI Scores and Computation of Textures
+For each patient, 2 neuroradiologists (H.T. and W.L.) with 7 and 20 years of experience, respectively, independently reviewed axial T1-weighted MR images before (T1W) and after gadolinium-based CE material administration (T1CE) as well as axial T2-weighted (T2W) and axial T2-weighted fluid attenuated inversion recovery (FLAIR) (T2F) images of the 165 LGG patients. The readers were blinded to the clinical data. Clear Canvas workstation, which allows visualization as well as annotation and markup of Digital Imaging and Communications in Medicine (DICOM) images, was used for imaging review. Each tumor was independently scored by the readers using the 30 imaging features defined according to the VASARI scoring system as previously described. The reader is referred to the Supplementary material for a complete description of the VASARI feature set. The interreader agreement for the imaging features was assessed using the kappa consistency test. Kappa values >0.81, in the range of 0.61–0.80, and <0.60 were considered to reflect excellent, good, and poor agreement, respectively. Final disagreement was resolved in a panel format including 2 additional coauthors (H.X.B. and L.Y.). For texture analysis, 3D regions of interest (ROIs) for each MR imaging set of each patient were manually drawn slice-by-slice in the axial plane for each of the available sequences (T1W, T2W, T1CE, T2F) by an expert radiologist. A total of 42 texture features were then extracted using 3D analysis from the T1W, T2W, T1CE, and T2F scans: 3 histogram-based textures, 8 texture features from the Gray-Level Co-occurrence Matrix (GLCM), 13 texture features from the Gray-Level Run-Length Matrix (GLRLM), 13 texture features from the Gray-Level Size Zone Matrix (GLSZM), and 5 texture features from the Neighborhood Gray-Tone Difference Matrix (NGTDM). The reader is referred to the Supplementary material for a complete description of all texture features, acronyms, and references.
+
+Association of VASARI Imaging Features with Survival
+Progression-free survival (PFS) was defined as the time that passes from the day on which a patient is enrolled and the date on which tumor progresses. Overall survival (OS) was defined as the time between initial diagnosis and death or last follow-up. We examined the association between each VASARI imaging feature with PFS and OS using the Kaplan–Meier survival curves and log-rank analyses. Features that were significant on the univariate analysis (P < .05) were entered into multivariate survival analysis based on the Cox proportional hazards ratio model, after incorporating clinical and pathological variables, including age, gender, extent of resection, histological type, histological grade, pretreatment Karnofsky performance scale (KPS), and IDH1 1p/19q codeletion status.
+
+Prediction of IDH1 Mutation, 1p/19q Codeletion Status, Histological Grade, and LGG Progression with Textural Imaging Features
+For this part of the work, the patient imaging data and outcome availability for each modeled outcome were as follows: (i) IDH1 mutation: 63 mutations, 21 wild type; (ii) 1p/19q codeletion status: 17 codeletion, 50 non-codeletion; (iii) histological grade: 35 grade II gliomas, 49 grade III gliomas; and (iv) LGG progression: 28 progressions, 47 nonprogressions. Binary clinical outcomes were modeled by predicting the class with the lowest number of instances.
+
+Forty-two texture features were computed as described by Vallières et al.9 using the 40 possible combinations of the following extraction parameters: (i) 3D isotropic scales of 0.5 mm, 1 mm, 2 mm, 3 mm, and 4 mm; (ii) “uniform” and “equal-probability” quantization; (iii) number of gray-levels of 8, 16, 32, and 64. The 4 initial feature sets that were tested comprised one T1-based and one T2-based MR imaging sequence (each containing 2 × 42 × 40 = 3360 scan-texture-parameters): (i) T1W-T2W, (ii) T1W-T2F, (iii) T1CE-T2W, and (iv) T1CE-T2F.
+
+Multivariate models were constructed for each initial feature set and modeled outcome using imbalanced-adjusted logistic regression, an adaptation of the method based on Schiller et al9 following the general methodology developed by Vallières et al.12 All initial feature sets first underwent feature set reduction using 100 bootstrap training samples to yield reduced feature sets of 25 different scan-texture features. Then, feature selection was performed by maximizing the area under the receiver-operating characteristic curve (AUC)632+ metric in 100 bootstrap training and testing samples to obtain texture models combining 1 to 10 variables (model order).13 For each outcome, the feature set and model order providing the combination of texture variables with the best parsimonious properties (ie, the simplest model with the best predictive properties) were chosen. The model was built using the feature set that provided the highest prediction curve while using the lowest model order before the AUC632+ metric started reaching a plateau or decreasing. Finally, the prediction performance of the 4 chosen texture models was estimated using average AUCs, sensitivities, and specificities obtained in 100 bootstrap testing samples.
+
+Prediction of IDH1 Mutation, 1p/19q Codeletion Status, Histological Grade, and LGG Progression with VASARI Features
+In order to directly compare the prognostic potential of VASARI features and texture features, we built VASARI multivariable models to predict IDH1 mutation, 1p/19q codeletion status, histological grade, and LGG progression. From the full set of VASARI features, the feature selection, model choice, and prediction estimation methods were the same as described in the section above for texture analysis.
+
+Comparison of the Predictive Potential of Models Using Clinical Variables, VASARI Features, and Texture Features with Random Forest Analysis
+Logistic or Cox regression analysis is best suited for modeling continuous variables only (eg, texture and VASARI features). These types of analyses provide a fast way to mine the best features for that category of inputs. On the other hand, random forests are more complex classifiers and are designed to implement any type of inputs, either categorical, as is often the case for clinical information, or continuous for radiomics data. In order to directly compare their predictive potential, clinical variables (categorical data), VASARI features, and texture features (continuous data) were thus included in a random forest analysis to predict IDH1 mutation, 1p/19q codeletion status, histological grade, and LGG progression. The clinical variables included age, KPS, histological type, grade (removed for histological grade outcome), laterality, location, gender, radiotherapy (yes vs no; removed for all outcomes except LGG progression), chemotherapy (yes vs no; removed for all outcomes except LGG progression), and IDH1 1p/19q subtype (removed for IDH1, 1p/19q outcomes). The VASARI and texture features included in the random forest analysis were the variables forming the best multivariable models as determined using the methods described in the 2 previous sections above. Random forest classifiers were trained (inherently using bootstrapping) on the whole cohort using 500 trees. Prediction performance was estimated using out-of-bag observations. Prediction balance between sensitivity and specificity was achieved by finding the optimal cost (ie, emphasis) on the classification of positive instances, and by maximizing 0.5*AUC + 0.5*(1 − |Sensitivity − Specificity|) on out-of-bag estimates. Random forest analysis was performed using clinical variables only; VASARI features only; texture features only; a combination of VASARI and texture features; and a combination of clinical variables, VASARI, and texture features.
+
+Results
+Interreader Agreement
+Interrater analysis showed significant agreement in all VASARI imaging features scored. Interreader agreements for all the imaging features were good to excellent (kappa value = 0.703–1.000) (Supplementary Table 1).
+
+Correlation between VASARI Imaging Features and Progression-Free Survival
+Kaplan–Meier analysis showed that 7 VASARI features were significantly associated with PFS (P < .1): enhancement quality, proportion of enhancing tumor, proportion of non-enhancing tumor, definition of the non-enhancing margin, diffusion, satellites, and lesion size. On multivariate Cox regression analysis, enhancement quality, definition of the non-enhancing margin, the presurgical KPS score, and IDH1 1p/19q subtype were significantly associated with PFS after taking into account gender, tumor location, and histology (Table 1). Specifically, tumors with no enhancement had longer PFS than tumors with either mild or marked enhancement (P = .048 by log-rank test; Supplementary Fig. 1A). Tumors with a smooth margin were associated with improved PFS compared with those with an irregular margin (P = .02 by log-rank test; Supplementary Fig. 1B).
+
+
+Table 1Correlation between VASARI imaging features and PFS on multivariate Cox analysis
+Variable	Hazard Ratio	P-value
+Enhancement quality 	1.485 (1.051, 2.099) 	.025 
+Definition of the non- enhancing margin 	2.056 (1.168, 3.518) 	.012 
+KPS 	0.969 (0.942, 0.996) 	.023 
+IDH1 1p/19q subtype 	3.035 (1.937, 4.756) 	<.001 
+Note: Data are hazard ratio estimates, with 95% CIs in parentheses, for variables included in the Cox regression model involving imaging features plus clinical variables, for the analysis of the association between the imaging features and PFS after adjusted for standard clinical variables.
+
+Open in new tab
+Correlation between VASARI Imaging Features and Overall Survival
+Kaplan–Meier analysis showed that 10 VASARI features were significantly associated with OS: eloquent brain involved, proportion of enhancing tumor, proportion of non-enhancing tumor, cysts, multifocal or multicentric, definition of the non-enhancing margin, proportion of edema, diffusion, enhancing tumor crosses midline, and satellites. On multivariate Cox regression analysis, definition of the non-enhancing margin, age, tumor grade, and IDH1 1p/19q subtype were significantly associated with OS after taking into account gender, tumor location, and histology (Table 2). Specifically, tumors with a smooth margin had longer OS than those with an irregular margin (P = .002 by log-rank test; Supplementary Fig. 1C).
+
+
+Table 2Correlation between VASARI imaging features and OS on multivariate Cox analysis
+Variable	Hazard Ratio	P-value
+Definition of the non-enhancing margin 	1.088 (1.047, 1.131) 	.017 
+Age 	1.088 (1.047, 1.131) 	<.001 
+WHO grade 	5.298 (2.027, 13.849) 	.001 
+IDH1 1p/19q subtype 	2.655 (1.489, 4.732) 	.001 
+Note: Data are hazard ratio estimates, with 95% CIs in parentheses, for variables included in the Cox regression model involving imaging features plus clinical variables, for the analysis of the association between the imaging features and OS after adjusted for standard clinical variables.
+
+Open in new tab
+Prediction of IDH1 Mutation, 1p/19q Codeletion Status, Histological Grade, and LGG Progression with Textural Imaging Features
+Following feature set reduction and feature selection using imbalanced-adjusted logistic regression and bootstrap resampling, texture models with orders 1 to 10 that maximized the AUC632+ metric were computed for each of the 4 feature sets to model the 4 outcomes (Fig. 2A–D). By inspecting the curves in Fig. 1, we determined that the combinations of 3 textures from the T1CE-T2W set, 3 textures from the T1CE-T2W set, 4 textures from the T1CE-T2W set, and 4 textures from the T1W-T2W set provided the best predictive properties for IDH1 mutation, 1p/19q codeletion status, histological grade, and LGG progression outcomes, respectively. For the IDH1 mutation outcome, the optimal set of features included global-skewness (T2W), GLRLM run-length variance (T2W), and GLRLM short run low Gray-level emphasis (T2W), which reached an AUC of 0.86 ± 0.01, a sensitivity of 0.75 ± 0.03, and a specificity of 0.78 ± 0.02. For 1p/19q codeletion status, the optimal set of features included GLRLM low Gray-level run emphasis (LGRE) (T1CE), GLSZM short zone low Gray-level emphasis (SZHGE) (T2W), and GLRLM long run high Gray-level emphasis (T2W), which reached an AUC of 0.96 ± 0.01, a sensitivity of 0.90 ± 0.02, and a specificity of 0.89 ± 0.02. For the histological grade outcome, the optimal set of features included GLCM-homogeneity (T1CE), GLSZM short-zone emphasis (SZE) (T2W), GLSZM-SZE (T1CE), and global-kurtosis (T1CE), which reached an AUC of 0.86 ± 0.01, a sensitivity of 0.74 ± 0.02, and a specificity of 0.79 ± 0.02. For the LGG progression outcome, the optimal set of features included GLRLM long run low Gray-level emphasis (T1W), GLRLM-LGRE (T2W), GLSZM-SZHGE (T1W),and GLSZM zone size variance (T2W), which reached an AUC of 0.80 ± 0.01, a sensitivity of 0.76 ± 0.03, and a specificity of 0.72 ± 0.03. The direction of correlation between each significant texture feature included in the final model and outcome is shown in Supplementary Table 2.
+
+Fig. 2
+Inspection of predictive properties of multivariable texture models constructed from 4 feature sets: (i) T1W-T2W, (ii) T1W-T2F, (iii) T2CE-T2W, and (iv) T1CE-T2F. Estimation of prediction performance is shown for combinations of 1 to 10 texture features (model orders) in terms of the AUC632+ metric for: (A) IDH1 mutation, (B) 1p/19q codeletion status, (C) histological grade, and (D) LGG progression.
+Open in new tabDownload slide
+Inspection of predictive properties of multivariable texture models constructed from 4 feature sets: (i) T1W-T2W, (ii) T1W-T2F, (iii) T2CE-T2W, and (iv) T1CE-T2F. Estimation of prediction performance is shown for combinations of 1 to 10 texture features (model orders) in terms of the AUC632+ metric for: (A) IDH1 mutation, (B) 1p/19q codeletion status, (C) histological grade, and (D) LGG progression.
+
+To demonstrate the classification capability of the optimal models shown in Supplementary Table 2, final logistic regression coefficients were computed for all models using 100 bootstrap training samples. The posterior probability of observing a given outcome as a function of the logistic regression response of the models was calculated along with the associated 95% CIs of the model responses in the bootstrap samples (Fig. 3).
+
+Fig. 3
+Probability of observing a given outcome as a function of the response of optimal multivariable texture models developed in this work, for all patients of the cohort: (A) IDH1 mutation (nonIDH1), (B) 1p/19q codeletion status (IDHcodel), (C) histological grade (lowGrade), and (D) LGG progression (progression). It can be seen that the optimal texture models can significantly separate the patients of the 2 classes for each outcome, especially in the case of the 1p/19q codeletion status.
+Open in new tabDownload slide
+Probability of observing a given outcome as a function of the response of optimal multivariable texture models developed in this work, for all patients of the cohort: (A) IDH1 mutation (nonIDH1), (B) 1p/19q codeletion status (IDHcodel), (C) histological grade (lowGrade), and (D) LGG progression (progression). It can be seen that the optimal texture models can significantly separate the patients of the 2 classes for each outcome, especially in the case of the 1p/19q codeletion status.
+
+Prediction of IDH1 Mutation, 1p/19q Codeletion Status, Histological Grade, and LGG Progression with VASARI Features
+For the IDH1 mutation outcome, the optimal set of features included proportion necrosis and lesion size, which reached an AUC of 0.73 ± 0.02, a sensitivity of 0.69 + 0.03, and a specificity of 0.69 ± 0.02. For the 1p/19q codeletion outcome, the optimal set of features included multifocal or multicentric, edema proportion, tumor location, and enhancing proportion, which reached an AUC of 0.78 ± 0.01, a sensitivity of 0.72 ± 0.03, and a specificity of 0.67 ± 0.03. For the histological grade outcome, the optimal set of features included enhancing proportion, definition of the non-enhancing margin, and diffusion, which reached an AUC of 0.78 ± 0.01, a sensitivity of 0.72 ± 0.03, and a specificity of 0.67 ± 0.03. For the LGG progression outcome, the optimal set of features included tumor location, enhancement quality, necrosis proportion, T1/FLAIR ratio, and thickness of enhancing margin, which reached an AUC of 0.58 ± 0.02, a sensitivity of 0.54 ± 0.04, and a specificity of 0.58 ± 0.03. The results are shown in Fig. 4. The direction of correlation between each significant VASARI feature included in the final model and outcome is shown in Supplementary Table 3.
+
+Fig. 4
+Inspection of predictive properties of VASARI models constructed for 4 different outcomes: (i) IDH1 mutation, (ii) 1p/19q codeletion status, (iii) histological grade, and (iv) LGG progression. Estimation of prediction performance is shown for combinations of 1 to 10 texture features (model orders) in terms of the AUC632+ metric.
+Open in new tabDownload slide
+Inspection of predictive properties of VASARI models constructed for 4 different outcomes: (i) IDH1 mutation, (ii) 1p/19q codeletion status, (iii) histological grade, and (iv) LGG progression. Estimation of prediction performance is shown for combinations of 1 to 10 texture features (model orders) in terms of the AUC632+ metric.
+
+Comparison of the Predictive Potential of Models Using Clinical Variables, VASARI Features, and Texture Features with Random Forest Analysis
+Random forest analysis was used to directly compare the predictive potential of clinical, VASARI, and texture features (Supplementary Table 4). For IDH1 mutation, 1p/19q codeletion, and LGG progression, we found that the best category of predictor was texture features, with AUCs of 0.79, 0.88, and 0.70, respectively. For histological grade, the best category of predictor was VASARI features, with an AUC of 0.73. However, the combination of clinical, VASARI, and texture variables showed that clinical variables can successfully complement imaging features for the prediction of IDH1 mutation and histological grade, with respective AUCs of 0.86 and 0.78. On the other hand, 1p/19q codeletion was best modeled with a combination of texture and VASARI features only (AUC = 0.89), and LGG progression was best modeled with texture features only (AUC = 0.70). The detailed results are shown in Supplementary Tables 5, 6, 7, 8, and 9.
+
+Discussion
+We found a significant association between enhancement quality (none vs mild vs marked) and PFS. Specifically, no enhancement was associated with longer PFS than either mild or marked enhancement. In addition, a smooth definition of the non-enhancing margin was associated with longer PFS and OS than an irregular non-enhancing margin. Of note, these imaging features were still strongly associated with patients’ survival after incorporating age, KPS, extent of resection, tumor grade, and IDH 1p/19q subtype.
+
+In glioblastoma, previous studies have shown that the proportion of CE on MRI was associated with survival.3,14 However, in LGG, the prognostic significance of CE on survival remains less well understood, and differing results have been reported depending on LGG and mutation status.15–17 In our study, the proportion of CE was not a significant predictor of either PFS or OS, but the lack of CE was a positive predictor of PFS. There was no significant difference in survival between patients who had tumors with mild enhancement and those who had tumors with marked enhancement. Grade III tumors were more likely to enhance than grade II tumors (84% vs 44%, respectively), but a significant proportion of the grade II tumors demonstrated CE as well.
+
+We found that a smooth non-enhancing margin was associated with longer PFS and OS compared with an irregular non-enhancing margin. This is in contrast to a prior study in glioblastoma which found that a smooth edge of CE predicted poor prognosis, while a sharp edge was a positive factor.6 However, a previous study of 43 grade III gliomas found no significant association of non-enhancing margin with survival.18 To our knowledge, our study was the first to demonstrate that the definition of the non-enhancing margin on MRI can predict survival in a combined cohort of grade II and grade III gliomas.
+
+In this study, we constructed a multivariable texture model extracted from baseline MRI scans that achieved an AUC of 0.86, a sensitivity of 0.75, and a specificity of 0.78 in predicting IDH1 mutation in LGGs. This logistic regression model performed better than a model using VASARI features via the same methods and comparable to the models built with random forest analysis incorporating clinical variables, VASARI, and texture features. In comparison to previous studies that relied on complete clinical data19 or advanced imaging techniques,20 our results demonstrated the ability of machine-learning algorithms to achieve accurate prediction of IDH mutation in LGGs with very few preoperative MRI texture features alone. These results, if validated with other datasets, may affect clinical management in the future, since these imaging studies were obtained routinely before surgery. They can also be useful in a research setting where a large amount of samples have to be genotyped for IDH mutation.
+
+The codeletion of chromosomal arms 1p and 19q is a characteristic and early genetic event in oligodendroglial tumors.15 Tumors with 1p/19q codeletion are associated with a better prognosis and enhanced response to therapy.16 Moreover, grades II and III gliomas with 1p/19q codeletion are also mutated in IDH1/2.21 In a smaller study of 55 patients with oligodendrogliomas, Brown et al.17 used S-transform-based texture analysis of preoperative MR images to predict 1p/19q codeletion with an AUC of 0.94, a sensitivity of 0.93, and a specificity of 0.96, versus a sensitivity of 0.70 and a specificity of 0.63 for genotype prediction by blinded experts. We corroborated these results in a larger cohort of patients that included both astrocytomas and oligodendrogliomas, and our optimal texture model achieved an average bootstrap testing AUC of 0.96, a sensitivity of 0.90, and a specificity of 0.89 in predicting 1p/19q codeletion status in LGGs. This logistic regression multivariable model was superior to that built using either VASARI features or random forest analysis. Our results afforded a method for predicting 1p/19q codeletion that is both noninvasive and uses data from routinely acquired MR images.
+
+The current standard for glioma grading is based on histopathological assessment, which has 2 major limitations. First, it is an invasive procedure. Second, it has an inherent sampling error, especially with stereotactic biopsy. Our multivariable texture model achieved an AUC of 0.86, a sensitivity of 0.74, and a specificity of 0.79 in distinguishing grade II from grade III gliomas, a performance which compared favorably with previous studies.20–22 However, these prior studies relied on carefully selected ROIs drawn by neuroradiologists and multiple advanced MR imaging modalities, including diffusion-weighted imaging, diffusion-tensor imaging, MR spectroscopy, and perfusion-weighted imaging. These resources may not be available in non-academic institutions. Our algorithm demonstrated the potential of achieving high predictive accuracy using only conventional MRI sequences.
+
+One texture feature in our final model that predicted histological grade was GLCM-homogeneity on contrast-enhanced T1-weighted images. We found that high tumor “homogeneity” was associated with higher grade. This result may be counterintuitive, since previous studies in breast cancer23 and soft tissue sarcomas24 have demonstrated that tumor heterogeneity is associated with higher tumor grade and more aggressive pathological features. We have 2 possible explanations for our results. First, MR CE in grade II tumors is more heterogeneous than CE in grade III tumors. This characteristic of CE in grade II gliomas was not captured by the corresponding VASARI feature key, but was demonstrated by Pallud et al.,25 where among the 143 cases of grade II tumor with CE, CE was characterized as “patchy and faint” in 93 and “nodular-like” in 50. Second, for those tumors without CE, our previous observation in soft tissue sarcoma was that high texture homogeneity was mostly due to large homogeneous necrotic centers.9 This suggests that the tumor has a fast growing rate, thus compatible with higher grade.
+
+The ultimate goal of using machine-learning algorithm to study glioma is to predict patient outcome. Our multivariable texture model constructed using logistic regression achieved an AUC of 0.80, a sensitivity of 0.76, and a specificity of 0.72 in predicting LGG progression. These results were superior to those obtained using either VASARI features (AUC of 0.58) or random forest analysis (AUC of 0.69). Few studies have investigated the use of radiomics, specifically texture analysis based on baseline MR imaging, to predict outcomes in patients with gliomas, and existing studies focused exclusively on glioblastoma.21,26 Our study was the first in the literature to demonstrate the potential of using textural analysis from baseline MR imaging to predict glioma progression.
+
+We acknowledge several limitations to our study. First, some patients could not be included due to incompleteness of MR sequence data from TCIA. In addition, the heterogeneity of different imaging parameters used by different investigators contributing to TCGA/TCIA data could not be controlled. Second, clinical variables, such as PFS and extent of resection, are not available for all patients from TCGA. Third, this study was partly based on the radiologist-scored imaging features. Although a good to excellent interreader agreement based on kappa consistency test has been achieved, the scores can be subject to interreader variability and random errors during manual contour tracing. Lastly, collection and assessment of new LGGs is still ongoing by our group, and we need more cases to validate our initial conclusions made in this paper.
+
+In conclusion, tumor enhancement and an irregular non-enhancing margin on MR imaging were associated with shorter PFS, while a smooth non-enhancing margin was a positive predictor of OS. Multivariable texture models extracted from baseline MRI scans were able to classify LGGs in terms of IDH1 mutation, 1p/19q codeletion, histological grade, and tumor progression with high sensitivity and specificity.
+
+Online Resources
+The ROI masks used for texture analysis are made available in DICOM format on the TCIA website: http://www.cancerimagingarchive.net/. All MATLAB software code used to compute the texture features and multivariable model results is freely shared under the GNU General Public License at: https://github.com/mvallieres/radiomics.
+
+Supplementary Material
+Supplementary material is available at Neuro-Oncology online.
+
+Funding
+This work was supported by the Natural Science Foundation of China (81301988 to L.Y., 2014-1 to 2016-12), and China Ministry of Education Doctoral Program Spot Foundation (20130162120061 to L.Y.), Shenghua Yuying Project of Central South University to L.Y., and Natural Science Foundation of Hunan Province of China (14JJ2042, 2014-1 to 2016-12) to J.Z.
+
+Conflict of interest statement. None declared.
+
+References
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+Author notes
+Corresponding Authors: Li Yang, MD, PhD, Department of Neurology, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, Hunan, 410011, P.R. China (yangli762@gmail.com). Bo Xiao, MD,PhD, Department of Neurology, First Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China (xiaobo1962xy@163.com).
+*Hao Zhou and Martin Vallières contributed equally to this work.
+© The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

samples/ROI-Masks_description.txt

@@ -0,0 +1,15 @@
+This collection contains 406 Region Of Interest (ROI) masks in MATLAB
+format defining the low grade glioma (LGG) tumor region on T1-weighted
+(T1W), T2-weighted (T2W), T1-weighted post-contrast (T1CE) and
+T2-flair (T2F) MR images of 108 different patients from the TCGA-LGG
+collection. 81 of the patients have ROI masks drawn for the four MRI
+sequences (T1W, T2W, T1CE and T2F), and 27 patients have ROI masks
+drawn for three or less of the four MRI sequences. The ROI masks were
+used to extract texture features in order to develop radiomic-based
+multivariable models for the prediction of isocitrate dehydrogenase 1
+(IDH1) mutation, 1p/19q codeletion status, histological grade and
+tumor progression. Clinical data (188 patients in total from the
+TCGA-LGG collection, some incomplete depending on the clinical
+attribute), VASARI scores (188 patients in total from the TCGA-LGG
+collection, 178 complete) with feature keys, and source code used in
+this study are also available with this collection.