Clinical trial NCT05556603: AssesSment of Early-deteCtion basEd oN liquiD Biopsy in PANCEATIC Cancer (ASCEND-PANCREATIC)
Official title: Pancreatic Cancer Detection by Liquid Biopsy in Peripheral Blood: A Prospective Study
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Cancer
Keywords: Cancer
liquid biopsy
cell-free DNA (cfDNA) methylation
circulating tumor DNA (ctDNA) mutation
whole blood miRNA
Lead sponsor: Ruijin Hospital
Sponsor class: OTHER
Collaborators: name: Guangzhou Burning Rock Dx Co., Ltd.
First posted: 2022-09-27
Enrollment: 7062
Sex: ALL
Minimum age (years): 40
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Eligible participants will be recruited from medical centers and assigned into three arms to develop a predictive diagnostic model in pancreatic cancer, including participants with new diagnosis of malignancy or corresponding benign disease and participants without the presence of malignancy or benign diseases. Participants with high risk for pancreatic cancer will be recruited from medical centers to evaluate the performance of pancreatic cancer early detection test.

Brief summary: ASCEND-PANCREATIC is a prospective, multi-omics, observational study aimed at early detecting pancreatic cancer by combined assays for biomarkers of cfDNA methylation, circulating tumor DNA (ctDNA) mutation, serum protein markers and blood miRNA markers, in which of 7,062 participants will be enrolled. The development and validation of the model will be conducted in participants with early stage cancers or benign diseases, along with healthy individuals. The performance of the pancreatic cancer detection test will be evaluated in participants with high risk of pancreatic cancer.


Eligibility criteria: Inclusion Criteria for Cancer Arm Participants:

* Age 40-75 years old.
* Able to provide a written informed consent.
* No prior cancer treatment (local or systematic) with either of the following:

A. Pathologically confirmed cancer diagnosis within 42 days prior to blood draw.

B. High suspicious for cancer diagnosis by imaging tests or other routine clinical examinations, with confirmed pathological cancer diagnosis within 42 days after the blood draw.

Exclusion Criteria for Cancer Arm Participants:

* Insufficient qualified blood samples.
* During pregnancy or lactation.
* Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant.
* Recipient of blood transfusion within 7 days prior to blood draw.
* Recipient of anti-tumor drugs to treat non-cancer diseases within 30 days prior to blood draw.
* With other known malignant tumors or multiple primary tumors.

Inclusion Criteria for Benign Disease Arm Participants:

* Age 40-75 years old.
* Able to provide a written informed consent.
* Able to provide sufficient and qualified blood samples for study tests.
* Have either of the following:

A. Pathological confirmed diagnosis of benign diseases within 90 days prior to the study blood draw, with no prior treatment such as surgical resection.

B. High suspicious for benign diseases diagnosis by radiological or other routine clinical assessments, with confirmed benign diseases diagnosis within 42 days after study blood draw.

Exclusion Criteria for Benign Disease Arm Participants:

* Insufficient qualified blood sample for study test.
* During pregnancy or lactation.
* Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant.
* Recipient of blood transfusion within 7 days prior to study blood draw.
* Recipient of anti-tumor drugs to treat non-cancer diseases within 30 days prior to blood draw.

Inclusion Criteria for Healthy Arm Participants:

* Age 40-75 years at the day of consenting to the study.
* Able to provide a written informed consent.
* Able to provide sufficient and qualified blood samples for study tests.
* No cancer related symptoms within 30 days prior to study screening.
* No abnormal medical examination within 30 days prior to screening.
* Cancer history with curative treatment completed over 3 years without recurrence prior to study enrollment.

Exclusion Criteria for Healthy Arm Participants:

* Insufficient qualified blood sample for study test.
* During pregnancy or lactation.
* Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant.
* Recipient of blood transfusion within 7 days prior to study blood draw.
* Recipient of anti-tumor drugs to treat non-cancer diseases within 30 days prior to blood draw.
* Have received or are undergoing curative cancer treatment within three years prior to study screening.
* With autoimmune or other diseases with severe comorbidities.

Inclusion Criteria for High Risk for Pancreatic Cancer Arm Participants:

* Age 40-75 years old.
* Able to provide a written informed consent.
* Able to provide sufficient and qualified blood samples for study tests.
* Accompanied by known risk factors of pancreatic cancer, including carrier of any pathogenic variant, chronic pancreatitis and other risk factors.

Exclusion Criteria for High Risk for Pancreatic Cancer Arm Participants:

* Insufficient qualified blood sample for study test.
* During pregnancy or lactation.
* Recipient of organ transplant or prior non-autologous (allogeneic) bone marrow or stem cell transplant.
* Recipient of blood transfusion within 7 days prior to study blood draw.
* Recipient of anti-tumor drugs to treat non-cancer diseases within 30 days prior to blood draw.
* Received radical therapy within 3 years and without recurrence, with malignant tumors with pathogenic or suspected pathogenic variants of germ-line genetic susceptibility genes.

Primary outcomes:
measure: Sensitivity and specificity of the cfDNA methylation-based model in detecting pancreatic cancer.
timeFrame: 30 months
measure: The performance of the cfDNA methylation-based model in pancreatic cancer early detection in participants at high risk for pancreatic cancer.
timeFrame: 90 months
Secondary outcomes:
measure: The difference of sensitivity and specificity in pancreatic cancer participants at different clinical stages.
timeFrame: 30 months
measure: Sensitivity and specificity for detecting pancreatic cancer of a cfDNA methylation-based model, in combination with other biomarkers.
timeFrame: 30 months
measure: Sensitivity and specificity of a ctDNA mutation-based model and a serum protein-based model in detecting pancreatic cancer, respectively.
timeFrame: 30 months
Other outcomes:
measure: Sensitivity and specificity of a blood miRNA-based model in detecting pancreatic cancer.
timeFrame: 30 months
Locations:
city: Shanghai
country: China
facility: Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
state: Shanghai
city: Shanghai
country: China
facility: Huashan Hospital, Fudan University
state: Shanghai
city: Shanghai
country: China
facility: Zhongshan Hospital, Fudan University
state: Shanghai
Study officials:
affiliation: Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
name: Baiyong Shen, M.D.&Ph.D
role: STUDY_DIRECTOR
References:
citation: Steel N, Ford JA, Newton JN, Davis ACJ, Vos T, Naghavi M, Glenn S, Hughes A, Dalton AM, Stockton D, Humphreys C, Dallat M, Schmidt J, Flowers J, Fox S, Abubakar I, Aldridge RW, Baker A, Brayne C, Brugha T, Capewell S, Car J, Cooper C, Ezzati M, Fitzpatrick J, Greaves F, Hay R, Hay S, Kee F, Larson HJ, Lyons RA, Majeed A, McKee M, Rawaf S, Rutter H, Saxena S, Sheikh A, Smeeth L, Viner RM, Vollset SE, Williams HC, Wolfe C, Woolf A, Murray CJL. Changes in health in the countries of the UK and 150 English Local Authority areas 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2018 Nov 3;392(10158):1647-1661. doi: 10.1016/S0140-6736(18)32207-4. Epub 2018 Oct 24.
citation: Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016 Mar-Apr;66(2):115-32. doi: 10.3322/caac.21338. Epub 2016 Jan 25.
citation: Smith RA, Andrews KS, Brooks D, Fedewa SA, Manassaram-Baptiste D, Saslow D, Brawley OW, Wender RC. Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2018 Jul;68(4):297-316. doi: 10.3322/caac.21446. Epub 2018 May 30.
citation: Chen M, Zhao H. Next-generation sequencing in liquid biopsy: cancer screening and early detection. Hum Genomics. 2019 Aug 1;13(1):34. doi: 10.1186/s40246-019-0220-8.
citation: Moore LD, Le T, Fan G. DNA methylation and its basic function. Neuropsychopharmacology. 2013 Jan;38(1):23-38. doi: 10.1038/npp.2012.112. Epub 2012 Jul 11.
citation: Curradi M, Izzo A, Badaracco G, Landsberger N. Molecular mechanisms of gene silencing mediated by DNA methylation. Mol Cell Biol. 2002 May;22(9):3157-73. doi: 10.1128/MCB.22.9.3157-3173.2002.
citation: Guibert S, Weber M. Functions of DNA methylation and hydroxymethylation in mammalian development. Curr Top Dev Biol. 2013;104:47-83. doi: 10.1016/B978-0-12-416027-9.00002-4.
citation: Widschwendter M, Jones A, Evans I, Reisel D, Dillner J, Sundstrom K, Steyerberg EW, Vergouwe Y, Wegwarth O, Rebitschek FG, Siebert U, Sroczynski G, de Beaufort ID, Bolt I, Cibula D, Zikan M, Bjorge L, Colombo N, Harbeck N, Dudbridge F, Tasse AM, Knoppers BM, Joly Y, Teschendorff AE, Pashayan N; FORECEE (4C) Consortium. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat Rev Clin Oncol. 2018 May;15(5):292-309. doi: 10.1038/nrclinonc.2018.30. Epub 2018 Feb 27.
citation: Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr, Kinzler KW. Cancer genome landscapes. Science. 2013 Mar 29;339(6127):1546-58. doi: 10.1126/science.1235122.
citation: Guo S, Diep D, Plongthongkum N, Fung HL, Zhang K, Zhang K. Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA. Nat Genet. 2017 Apr;49(4):635-642. doi: 10.1038/ng.3805. Epub 2017 Mar 6.
citation: Johnson DA, Barclay RL, Mergener K, Weiss G, Konig T, Beck J, Potter NT. Plasma Septin9 versus fecal immunochemical testing for colorectal cancer screening: a prospective multicenter study. PLoS One. 2014 Jun 5;9(6):e98238. doi: 10.1371/journal.pone.0098238. eCollection 2014.
citation: Church TR, Wandell M, Lofton-Day C, Mongin SJ, Burger M, Payne SR, Castanos-Velez E, Blumenstein BA, Rosch T, Osborn N, Snover D, Day RW, Ransohoff DF; PRESEPT Clinical Study Steering Committee, Investigators and Study Team. Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer. Gut. 2014 Feb;63(2):317-25. doi: 10.1136/gutjnl-2012-304149. Epub 2013 Feb 13.
citation: Ilse P, Biesterfeld S, Pomjanski N, Wrobel C, Schramm M. Analysis of SHOX2 methylation as an aid to cytology in lung cancer diagnosis. Cancer Genomics Proteomics. 2014 Sep-Oct;11(5):251-8.
citation: 中国肺癌防治联盟 中, 肺癌工作委员会. 肺癌筛查与管理中国专家共识. . 国际呼吸杂志 2019;39(21):1604-1615.
citation: Cristiano S, Leal A, Phallen J, Fiksel J, Adleff V, Bruhm DC, Jensen SO, Medina JE, Hruban C, White JR, Palsgrove DN, Niknafs N, Anagnostou V, Forde P, Naidoo J, Marrone K, Brahmer J, Woodward BD, Husain H, van Rooijen KL, Orntoft MW, Madsen AH, van de Velde CJH, Verheij M, Cats A, Punt CJA, Vink GR, van Grieken NCT, Koopman M, Fijneman RJA, Johansen JS, Nielsen HJ, Meijer GA, Andersen CL, Scharpf RB, Velculescu VE. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature. 2019 Jun;570(7761):385-389. doi: 10.1038/s41586-019-1272-6. Epub 2019 May 29.
citation: Minetta C. Liu EAK, Earl Hubbell, et al. Plasma cell-free DNA (cfDNA) assays for early multi-cancer detection: the Circulating Cell-Free Genome Atlas (CCGA) study. Annals of Oncology. 2018;29(suppl_8):viii14-viii57.
citation: Liu MC, Oxnard GR, Klein EA, Swanton C, Seiden MV; CCGA Consortium. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020 Jun;31(6):745-759. doi: 10.1016/j.annonc.2020.02.011. Epub 2020 Mar 30.
citation: Haber DA, Velculescu VE. Blood-based analyses of cancer: circulating tumor cells and circulating tumor DNA. Cancer Discov. 2014 Jun;4(6):650-61. doi: 10.1158/2159-8290.CD-13-1014. Epub 2014 May 6.
citation: Dawson SJ, Tsui DW, Murtaza M, Biggs H, Rueda OM, Chin SF, Dunning MJ, Gale D, Forshew T, Mahler-Araujo B, Rajan S, Humphray S, Becq J, Halsall D, Wallis M, Bentley D, Caldas C, Rosenfeld N. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013 Mar 28;368(13):1199-209. doi: 10.1056/NEJMoa1213261. Epub 2013 Mar 13.
citation: Abbosh C, Birkbak NJ, Wilson GA, Jamal-Hanjani M, Constantin T, Salari R, Le Quesne J, Moore DA, Veeriah S, Rosenthal R, Marafioti T, Kirkizlar E, Watkins TBK, McGranahan N, Ward S, Martinson L, Riley J, Fraioli F, Al Bakir M, Gronroos E, Zambrana F, Endozo R, Bi WL, Fennessy FM, Sponer N, Johnson D, Laycock J, Shafi S, Czyzewska-Khan J, Rowan A, Chambers T, Matthews N, Turajlic S, Hiley C, Lee SM, Forster MD, Ahmad T, Falzon M, Borg E, Lawrence D, Hayward M, Kolvekar S, Panagiotopoulos N, Janes SM, Thakrar R, Ahmed A, Blackhall F, Summers Y, Hafez D, Naik A, Ganguly A, Kareht S, Shah R, Joseph L, Marie Quinn A, Crosbie PA, Naidu B, Middleton G, Langman G, Trotter S, Nicolson M, Remmen H, Kerr K, Chetty M, Gomersall L, Fennell DA, Nakas A, Rathinam S, Anand G, Khan S, Russell P, Ezhil V, Ismail B, Irvin-Sellers M, Prakash V, Lester JF, Kornaszewska M, Attanoos R, Adams H, Davies H, Oukrif D, Akarca AU, Hartley JA, Lowe HL, Lock S, Iles N, Bell H, Ngai Y, Elgar G, Szallasi Z, Schwarz RF, Herrero J, Stewart A, Quezada SA, Peggs KS, Van Loo P, Dive C, Lin CJ, Rabinowitz M, Aerts HJWL, Hackshaw A, Shaw JA, Zimmermann BG; TRACERx consortium; PEACE consortium; Swanton C. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017 Apr 26;545(7655):446-451. doi: 10.1038/nature22364.
citation: Cree IA, Uttley L, Buckley Woods H, Kikuchi H, Reiman A, Harnan S, Whiteman BL, Philips ST, Messenger M, Cox A, Teare D, Sheils O, Shaw J; UK Early Cancer Detection Consortium. The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review. BMC Cancer. 2017 Oct 23;17(1):697. doi: 10.1186/s12885-017-3693-7.
citation: Cohen JD, Javed AA, Thoburn C, Wong F, Tie J, Gibbs P, Schmidt CM, Yip-Schneider MT, Allen PJ, Schattner M, Brand RE, Singhi AD, Petersen GM, Hong SM, Kim SC, Falconi M, Doglioni C, Weiss MJ, Ahuja N, He J, Makary MA, Maitra A, Hanash SM, Dal Molin M, Wang Y, Li L, Ptak J, Dobbyn L, Schaefer J, Silliman N, Popoli M, Goggins MG, Hruban RH, Wolfgang CL, Klein AP, Tomasetti C, Papadopoulos N, Kinzler KW, Vogelstein B, Lennon AM. Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers. Proc Natl Acad Sci U S A. 2017 Sep 19;114(38):10202-10207. doi: 10.1073/pnas.1704961114. Epub 2017 Sep 5.
citation: Cohen JD, Li L, Wang Y, Thoburn C, Afsari B, Danilova L, Douville C, Javed AA, Wong F, Mattox A, Hruban RH, Wolfgang CL, Goggins MG, Dal Molin M, Wang TL, Roden R, Klein AP, Ptak J, Dobbyn L, Schaefer J, Silliman N, Popoli M, Vogelstein JT, Browne JD, Schoen RE, Brand RE, Tie J, Gibbs P, Wong HL, Mansfield AS, Jen J, Hanash SM, Falconi M, Allen PJ, Zhou S, Bettegowda C, Diaz LA Jr, Tomasetti C, Kinzler KW, Vogelstein B, Lennon AM, Papadopoulos N. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018 Feb 23;359(6378):926-930. doi: 10.1126/science.aar3247. Epub 2018 Jan 18.
citation: Fehlmann T, Kahraman M, Ludwig N, Backes C, Galata V, Keller V, Geffers L, Mercaldo N, Hornung D, Weis T, Kayvanpour E, Abu-Halima M, Deuschle C, Schulte C, Suenkel U, von Thaler AK, Maetzler W, Herr C, Fahndrich S, Vogelmeier C, Guimaraes P, Hecksteden A, Meyer T, Metzger F, Diener C, Deutscher S, Abdul-Khaliq H, Stehle I, Haeusler S, Meiser A, Groesdonk HV, Volk T, Lenhof HP, Katus H, Balling R, Meder B, Kruger R, Huwer H, Bals R, Meese E, Keller A. Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients. JAMA Oncol. 2020 May 1;6(5):714-723. doi: 10.1001/jamaoncol.2020.0001.
citation: So JBY, Kapoor R, Zhu F, Koh C, Zhou L, Zou R, Tang YC, Goo PCK, Rha SY, Chung HC, Yoong J, Yap CT, Rao J, Chia CK, Tsao S, Shabbir A, Lee J, Lam KP, Hartman M, Yong WP, Too HP, Yeoh KG. Development and validation of a serum microRNA biomarker panel for detecting gastric cancer in a high-risk population. Gut. 2021 May;70(5):829-837. doi: 10.1136/gutjnl-2020-322065. Epub 2020 Oct 7.
citation: Puleo F, Nicolle R, Blum Y, Cros J, Marisa L, Demetter P, Quertinmont E, Svrcek M, Elarouci N, Iovanna J, Franchimont D, Verset L, Galdon MG, Deviere J, de Reynies A, Laurent-Puig P, Van Laethem JL, Bachet JB, Marechal R. Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features. Gastroenterology. 2018 Dec;155(6):1999-2013.e3. doi: 10.1053/j.gastro.2018.08.033. Epub 2018 Aug 27.
citation: Cancer Genome Atlas Research Network. Electronic address: andrew_aguirre@dfci.harvard.edu; Cancer Genome Atlas Research Network. Integrated Genomic Characterization of Pancreatic Ductal Adenocarcinoma. Cancer Cell. 2017 Aug 14;32(2):185-203.e13. doi: 10.1016/j.ccell.2017.07.007.
citation: Notta F, Chan-Seng-Yue M, Lemire M, Li Y, Wilson GW, Connor AA, Denroche RE, Liang SB, Brown AM, Kim JC, Wang T, Simpson JT, Beck T, Borgida A, Buchner N, Chadwick D, Hafezi-Bakhtiari S, Dick JE, Heisler L, Hollingsworth MA, Ibrahimov E, Jang GH, Johns J, Jorgensen LG, Law C, Ludkovski O, Lungu I, Ng K, Pasternack D, Petersen GM, Shlush LI, Timms L, Tsao MS, Wilson JM, Yung CK, Zogopoulos G, Bartlett JM, Alexandrov LB, Real FX, Cleary SP, Roehrl MH, McPherson JD, Stein LD, Hudson TJ, Campbell PJ, Gallinger S. A renewed model of pancreatic cancer evolution based on genomic rearrangement patterns. Nature. 2016 Oct 20;538(7625):378-382. doi: 10.1038/nature19823. Epub 2016 Oct 12.
citation: Bailey P, Chang DK, Nones K, Johns AL, Patch AM, Gingras MC, Miller DK, Christ AN, Bruxner TJ, Quinn MC, Nourse C, Murtaugh LC, Harliwong I, Idrisoglu S, Manning S, Nourbakhsh E, Wani S, Fink L, Holmes O, Chin V, Anderson MJ, Kazakoff S, Leonard C, Newell F, Waddell N, Wood S, Xu Q, Wilson PJ, Cloonan N, Kassahn KS, Taylor D, Quek K, Robertson A, Pantano L, Mincarelli L, Sanchez LN, Evers L, Wu J, Pinese M, Cowley MJ, Jones MD, Colvin EK, Nagrial AM, Humphrey ES, Chantrill LA, Mawson A, Humphris J, Chou A, Pajic M, Scarlett CJ, Pinho AV, Giry-Laterriere M, Rooman I, Samra JS, Kench JG, Lovell JA, Merrett ND, Toon CW, Epari K, Nguyen NQ, Barbour A, Zeps N, Moran-Jones K, Jamieson NB, Graham JS, Duthie F, Oien K, Hair J, Grutzmann R, Maitra A, Iacobuzio-Donahue CA, Wolfgang CL, Morgan RA, Lawlor RT, Corbo V, Bassi C, Rusev B, Capelli P, Salvia R, Tortora G, Mukhopadhyay D, Petersen GM; Australian Pancreatic Cancer Genome Initiative; Munzy DM, Fisher WE, Karim SA, Eshleman JR, Hruban RH, Pilarsky C, Morton JP, Sansom OJ, Scarpa A, Musgrove EA, Bailey UM, Hofmann O, Sutherland RL, Wheeler DA, Gill AJ, Gibbs RA, Pearson JV, Waddell N, Biankin AV, Grimmond SM. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature. 2016 Mar 3;531(7592):47-52. doi: 10.1038/nature16965. Epub 2016 Feb 24.
citation: Waddell N, Pajic M, Patch AM, Chang DK, Kassahn KS, Bailey P, Johns AL, Miller D, Nones K, Quek K, Quinn MC, Robertson AJ, Fadlullah MZ, Bruxner TJ, Christ AN, Harliwong I, Idrisoglu S, Manning S, Nourse C, Nourbakhsh E, Wani S, Wilson PJ, Markham E, Cloonan N, Anderson MJ, Fink JL, Holmes O, Kazakoff SH, Leonard C, Newell F, Poudel B, Song S, Taylor D, Waddell N, Wood S, Xu Q, Wu J, Pinese M, Cowley MJ, Lee HC, Jones MD, Nagrial AM, Humphris J, Chantrill LA, Chin V, Steinmann AM, Mawson A, Humphrey ES, Colvin EK, Chou A, Scarlett CJ, Pinho AV, Giry-Laterriere M, Rooman I, Samra JS, Kench JG, Pettitt JA, Merrett ND, Toon C, Epari K, Nguyen NQ, Barbour A, Zeps N, Jamieson NB, Graham JS, Niclou SP, Bjerkvig R, Grutzmann R, Aust D, Hruban RH, Maitra A, Iacobuzio-Donahue CA, Wolfgang CL, Morgan RA, Lawlor RT, Corbo V, Bassi C, Falconi M, Zamboni G, Tortora G, Tempero MA; Australian Pancreatic Cancer Genome Initiative; Gill AJ, Eshleman JR, Pilarsky C, Scarpa A, Musgrove EA, Pearson JV, Biankin AV, Grimmond SM. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature. 2015 Feb 26;518(7540):495-501. doi: 10.1038/nature14169.
citation: Moffitt RA, Marayati R, Flate EL, Volmar KE, Loeza SG, Hoadley KA, Rashid NU, Williams LA, Eaton SC, Chung AH, Smyla JK, Anderson JM, Kim HJ, Bentrem DJ, Talamonti MS, Iacobuzio-Donahue CA, Hollingsworth MA, Yeh JJ. Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma. Nat Genet. 2015 Oct;47(10):1168-78. doi: 10.1038/ng.3398. Epub 2015 Sep 7.
citation: Collisson EA, Sadanandam A, Olson P, Gibb WJ, Truitt M, Gu S, Cooc J, Weinkle J, Kim GE, Jakkula L, Feiler HS, Ko AH, Olshen AB, Danenberg KL, Tempero MA, Spellman PT, Hanahan D, Gray JW. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat Med. 2011 Apr;17(4):500-3. doi: 10.1038/nm.2344. Epub 2011 Apr 3.
citation: Aung KL, Fischer SE, Denroche RE, Jang GH, Dodd A, Creighton S, Southwood B, Liang SB, Chadwick D, Zhang A, O'Kane GM, Albaba H, Moura S, Grant RC, Miller JK, Mbabaali F, Pasternack D, Lungu IM, Bartlett JMS, Ghai S, Lemire M, Holter S, Connor AA, Moffitt RA, Yeh JJ, Timms L, Krzyzanowski PM, Dhani N, Hedley D, Notta F, Wilson JM, Moore MJ, Gallinger S, Knox JJ. Genomics-Driven Precision Medicine for Advanced Pancreatic Cancer: Early Results from the COMPASS Trial. Clin Cancer Res. 2018 Mar 15;24(6):1344-1354. doi: 10.1158/1078-0432.CCR-17-2994. Epub 2017 Dec 29.