bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplementary Table 3 from Changes in Geographic Variation and Socioeconomic Inequalities in Esophageal Cancer Mortality in China, 1973–2017
Authors: Ran Xianhui , Zheng Rongshou , Zeng Hongmei , Zhang Siwei , Sun Kexin , Han Bingfeng , Wang Shaoming , Chen Ru , Li Li , Wei Wenqiang , He Jie
Published: October 2023

Supplementary Table 3 shows the difference in age-standardized esophageal cancer mortality rates between 90th and 10th percentile counties by province and time period.
Supplementary Figure 1 from Changes in Geographic Variation and Socioeconomic Inequalities in Esophageal Cancer Mortality in China, 1973–2017
Authors: Ran Xianhui , Zheng Rongshou , Zeng Hongmei , Zhang Siwei , Sun Kexin , Han Bingfeng , Wang Shaoming , Chen Ru , Li Li , Wei Wenqiang , He Jie
Published: October 2023

Supplementary Figure 1 shows the geographic distribution and population coverage of 782 counties included in final analyses, along with the population density of China.
Supplementary Table 4 from The Association of Kidney Function and Inflammatory Biomarkers with Epithelial Ovarian Cancer Risk
Authors: Hathaway Cassandra A. , Townsend Mary K. , Sklar Elliot M. , Thomas-Purcell Kamilah B. , Terry Kathryn L. , Trabert Britton , Tworoger Shelley S.
Published: October 2023

Hazard ratios (HR) and 95% confidence intervals (95%CI) of kidney related markers measured in blood and ovarian cancer risk by C Reactive Protein (CRP) in the UK Biobank.
Supplementary Table 2 from The Association of Kidney Function and Inflammatory Biomarkers with Epithelial Ovarian Cancer Risk
Authors: Hathaway Cassandra A. , Townsend Mary K. , Sklar Elliot M. , Thomas-Purcell Kamilah B. , Terry Kathryn L. , Trabert Britton , Tworoger Shelley S.
Published: October 2023

Hazard ratios (HR) and 95% confidence intervals (95%CI) of kidney related markers measured in blood and ovarian cancer risk by histological subtype in the UK Biobank.
Supplementary Table 1 from The Association of Kidney Function and Inflammatory Biomarkers with Epithelial Ovarian Cancer Risk
Authors: Hathaway Cassandra A. , Townsend Mary K. , Sklar Elliot M. , Thomas-Purcell Kamilah B. , Terry Kathryn L. , Trabert Britton , Tworoger Shelley S.
Published: October 2023

Hazard ratios (HR) and 95% confidence intervals (95%CI) of C Reactive Protein and ovarian cancer risk in the UK Biobank using cutpoints considered in prior literature.
Supplemental Table 6 from New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Krick Benjamin , Thomson Cynthia A. , Shadyab Aladdin , Luo Juhua , Saquib Nazmus , Strickler Howard D. , Chlebowski Rowan , Arthur Rhonda S. , Summers Scott A. , Holland William L. , Jalili Thunder , Playdon Mary C.
Published: October 2023

Supplemental Table 6 provides effect estimates for the association of incident diabetes and cancer-specific mortality among obesity-related cancer survivors, stratified my covariates that did not meet PH assumptions.
Supplemental Table 4 from New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Krick Benjamin , Thomson Cynthia A. , Shadyab Aladdin , Luo Juhua , Saquib Nazmus , Strickler Howard D. , Chlebowski Rowan , Arthur Rhonda S. , Summers Scott A. , Holland William L. , Jalili Thunder , Playdon Mary C.
Published: October 2023

Supplemental Table 4 provides demographic characteristics of cancer-free individuals.
Supplemental Table 3 from New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Krick Benjamin , Thomson Cynthia A. , Shadyab Aladdin , Luo Juhua , Saquib Nazmus , Strickler Howard D. , Chlebowski Rowan , Arthur Rhonda S. , Summers Scott A. , Holland William L. , Jalili Thunder , Playdon Mary C.
Published: October 2023

Supplemental Table 3 provides effect estimates for the association of incident diabetes and all-cause mortality among obesity-related cancer survivors and cancer-free individuals, stratified by covariates that did not meet PH assumptions.
Supplemental Table 2 from New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Krick Benjamin , Thomson Cynthia A. , Shadyab Aladdin , Luo Juhua , Saquib Nazmus , Strickler Howard D. , Chlebowski Rowan , Arthur Rhonda S. , Summers Scott A. , Holland William L. , Jalili Thunder , Playdon Mary C.
Published: October 2023

Supplemental Table 2 provides effect estimates for the association of incident diabetes and all-cause mortality among obesity-related cancer survivors and cancer-free individuals.
Supplementary Table S6 from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

Supplementary Table S6: Crosstabulation of antibiotics use and tumour stage I-IV at diagnosis
Supplementary Figure S7 from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

Supplementary Figure S7: Antibiotics use in relation to overall and cancer-specific survival in stage IV colorectal cancer by
antibiotics classes, typical indications and specific antibiotics drugs.
The hazards ratios (HR) are derived from the Cox proportional hazards models, stratified by tumour sites (proximal
colon, distal colon, rectum, unspecified), sex (male/female), age at diagnosis (</≥ 50 years), prediagnostic Charlson
comorbidity index (no/any comorbidity), income status (1st/2nd/3rd/4th quartile), and adjusted for age and calendar
year of diagnosis and prediagnostic Charlson comorbidity index as continuous variables, place of birth, county, marital
status, level of education, family history of colorectal cancer, palliative chemotherapy and surgical therapy as categorical
variables, defined as presented in Supplementary Table S4. Any use of specific antibiotics class was compared to no
reported use of specific antibiotics class (reference). Antibiotics use during one year before colorectal cancer diagnosis
was excluded to account for potential use due to undiagnosed but clinically manifest colorectal cancer. Antibiotics that
primarily or only affect aerobic bacteria were categorized as anti-aerobic antibiotics. Antibiotics with effect on both
2
anaerobic and aerobic bacteria, and metrodinazoles and/or tinidazoles (which only affect anaerobic bacteria) were categorized as anti-anaerobic antibiotics. Phenoxymethylpenicillin is presented as a specific antibiotic drug but was also the sole typical drug for the indication uncomplicated respiratory infections and some skin and soft tissue infections. Clindamycin is presented as a specific antibiotic drug but was also the sole typical drug for the indication complicated skin and soft tissue and deep-seated infections. Amoxicillin includes amoxicillin with beta-lactamase inhibitor. UTI = urinary tract infection, CI = confidence interval. Detailed antibiotics classification and typical indications are presented in Supplementary Table S1.
Table S6 from Dietary Fish and n-3 Polyunsaturated Fatty Acid Consumption, and Renal Cell Carcinoma Risk in Japan: The Japan Public Health Center-Based Prospective Study
Authors: Takahashi Michiko , Sobue Tomotaka , Zha Ling , Kitamura Tetsuhisa , Iwasaki Motoki , Inoue Manami , Yamaji Taiki , Tsugane Shoichiro , Sawada Norie
Published: October 2023

Supplementary Table S5. Risk of RCC based on the energy-adjusted dietary intakes of fish and n-3 PUFA for each detection method.
Table S4 from Dietary Fish and n-3 Polyunsaturated Fatty Acid Consumption, and Renal Cell Carcinoma Risk in Japan: The Japan Public Health Center-Based Prospective Study
Authors: Takahashi Michiko , Sobue Tomotaka , Zha Ling , Kitamura Tetsuhisa , Iwasaki Motoki , Inoue Manami , Yamaji Taiki , Tsugane Shoichiro , Sawada Norie
Published: October 2023

Supplementary Table S4. Risk of RCC based on n-3 PUFA consumption by various subgroups.
Supplementary Figure S4 from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

Supplementary Figure S4: Antibiotics use in relation to survival outcomes in stage I-III colorectal cancer (crude and completecase
multivariable analyses).
(A) Antibiotics use in relation to overall survival. (B) Antibiotics use in relation to cancer-specific survival.
Prediagnostic antibiotics use was categorized as no use, any use, low use (1-10 days), moderate use (11-60
days), high use (61-180 days) and very high use (>180 days), based on defined daily doses. Antibiotics use
during one year before colorectal cancer diagnosis was excluded to account for potential use due to
undiagnosed but clinically manifest colorectal cancer. CI = confidence interval; HR = Hazard Ratio. Model 0 is
crude or univariable Cox analysis. Model 1 is a Cox proportional hazard model including main demographic and
socioeconomic factors (age and calendar year of diagnosis and prediagnostic Charlson comorbidity index as
continuous variables, and sex, place of birth, county of residence, marital status, level of education, income
status and family history of colorectal cancer as categorical variables). Model 2 includes tumour sites and
tumour stage in addition to the covariates in model 1. Model 3 includes therapy-related variables such as
operation type, preoperative chemotherapy (yes/no) and preoperative radiotherapy (yes/no) in addition to
covariates in model 2. Variable definitions and categorization for the covariates in models 1-3 are as presented
in Table 1. For each multivariable model, variables violating the proportional hazard assumption were
controlled for by stratification in the respective models. They were age at diagnosis (</≥ 50 years), sex
(men/women), prediagnostic Charlson comorbidity index (CCI) (no/any comorbidity), income status (quartile
categories) and family history of colorectal cancer (0/1/≥2 first degree relatives) for model 1; age at diagnosis,
prediagnostic CCI, family history of colorectal cancer, tumour sites (proximal colon, distal colon, rectum,
unspecified) and tumour stage (stage I-III) for model 2, age at diagnosis, prediagnostic CCI, type of surgery
2
(elective/emergency), tumour sites and tumour stage for model 3. For age at diagnosis and prediagnostic CCI (continuous variables), binary variable types (age at diagnosis: </≥ 50 years, prediagnostic CCI: no/any CCI) were used and continuous variable types were also adjusted to account for residual confounding in each stratum.
Table S3 from Dietary Fish and n-3 Polyunsaturated Fatty Acid Consumption, and Renal Cell Carcinoma Risk in Japan: The Japan Public Health Center-Based Prospective Study
Authors: Takahashi Michiko , Sobue Tomotaka , Zha Ling , Kitamura Tetsuhisa , Iwasaki Motoki , Inoue Manami , Yamaji Taiki , Tsugane Shoichiro , Sawada Norie
Published: October 2023

Supplementary Table S3. Risk of RCC based on the energy-adjusted dietary intakes of various fish categories.
Table S2 from Dietary Fish and n-3 Polyunsaturated Fatty Acid Consumption, and Renal Cell Carcinoma Risk in Japan: The Japan Public Health Center-Based Prospective Study
Authors: Takahashi Michiko , Sobue Tomotaka , Zha Ling , Kitamura Tetsuhisa , Iwasaki Motoki , Inoue Manami , Yamaji Taiki , Tsugane Shoichiro , Sawada Norie
Published: October 2023

Supplementary Table S2. Risk of RCC based on the energy-adjusted dietary intakes of fish analyzed based the cutoff of fish intake based on a previous study.
Supplementary Figure S2 from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

Supplementary Figure S2: Model fitness test using Cox-snell residuals for the multivariable model for stage IV colorectal
cancer.
The Cox proportional hazards model was stratified by tumour site (proximal colon, distal colon, rectum,
unspecified), sex (male/female), age at diagnosis (</≥ 50 years), prediagnostic Charlson comorbidity
index (no/any comorbidity), income status (quartiles), and adjusted for age at diagnosis and
prediagnostic Charlson comorbidity index as continuous variables, place of birth, county of residence,
marital status, level of education, family history of colorectal cancer, calendar year at diagnosis, palliative
chemotherapy and surgical therapy as categorical variables, defined as presented in Supplementary
Table S4.
Supplementary Figure S1 from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

Supplementary Figure S1: Model fitness test using Cox-snell residuals for different multivariable models for stage I-III
colorectal cancer.
The variables included in the multivariate models (Model 1, Model 2 and Model 3) are presented in the
statistical methods text and in Supplementary Figure S4. To perform model fitness tests, we used the Stata
commands available from: Introduction to survival analysis with Stata. UCLA: Statistical Consulting Group.
https://stats.oarc.ucla.edu/stata/seminars/stata-survival/ (accessed July 12, 2022).
Data from Prediagnostic Prescription Antibiotics Use and Survival in Patients with Colorectal Cancer: A Swedish National Register-Based Study
Authors: Lu Sai San Moon , Rutegård Martin , Ahmed Maghfoor , Häggström Christel , Gylfe Åsa , Harlid Sophia , Van Guelpen Bethany
Published: October 2023

AbstractBackground:
Antibiotics use is associated with higher colorectal cancer risk, but little is known regarding any potential effects on survival.
Methods:
We conducted a nationwide cohort study, using complete-population data from Swedish national registers between 2005 and 2020, to investigate prediagnostic prescription antibiotics use in relation to survival in colorectal cancer patients.
Results:
We identified 36,061 stage I–III and 11,242 stage IV colorectal cancer cases diagnosed between 2010 and 2019. For stage I–III, any antibiotics use (binary yes/no variable) was not associated with overall or cancer-specific survival. Compared with no use, moderate antibiotics use (total 11–60 days) was associated with slightly better cancer-specific survival [adjusted HR (aHR) = 0.93; 95% confidence interval (CI), 0.86–0.99)], whereas very high use (>180 days) was associated with worse survival [overall survival (OS) aHR = 1.42; 95% CI, 1.26–1.60, cancer-specific survival aHR = 1.31; 95% CI, 1.10–1.55]. In analyses by different antibiotic types, although not statistically significant, worse survival outcomes were generally observed across several antibiotics, particularly macrolides and/or lincosamides. In stage IV colorectal cancer, inverse relationships between antibiotics use and survival were noted.
Conclusions:
Overall, our findings do not support any substantial detrimental effects of prediagnostic prescription antibiotics use on cancer-specific survival after colorectal cancer diagnosis, with the possible exception of very high use in stage I–III colorectal cancer. Further investigation is warranted to confirm and understand these results.
Impact:
Although the study findings require confirmation, physicians probably do not need to factor in prediagnostic prescription antibiotics use in prognosticating patients with colorectal cancer.
Data from Genome-Scale Methylation Analysis Identifies Immune Profiles and Age Acceleration Associations with Bladder Cancer Outcomes
Authors: Chen Ji-Qing , Salas Lucas A. , Wiencke John K. , Koestler Devin C. , Molinaro Annette M. , Andrew Angeline S. , Seigne John D. , Karagas Margaret R. , Kelsey Karl T. , Christensen Brock C.
Published: October 2023

AbstractBackground:
Immune profiles have been associated with bladder cancer outcomes and may have clinical applications for prognosis. However, associations of detailed immune cell subtypes with patient outcomes remain underexplored and may contribute crucial prognostic information for better managing bladder cancer recurrence and survival.
Methods:
Bladder cancer case peripheral blood DNA methylation was measured using the Illumina HumanMethylationEPIC array. Extended cell-type deconvolution quantified 12 immune cell-type proportions, including memory, naïve T and B cells, and granulocyte subtypes. DNA methylation clocks determined biological age. Cox proportional hazards models tested associations of immune cell profiles and age acceleration with bladder cancer outcomes. The partDSA algorithm discriminated 10-year overall survival groups from clinical variables and immune cell profiles, and a semi-supervised recursively partitioned mixture model (SS-RPMM) with DNA methylation data was applied to identify a classifier for 10-year overall survival.
Results:
Higher CD8T memory cell proportions were associated with better overall survival [HR = 0.95, 95% confidence interval (CI) = 0.93–0.98], while higher neutrophil-to-lymphocyte ratio (HR = 1.36, 95% CI = 1.23–1.50), CD8T naïve (HR = 1.21, 95% CI = 1.04–1.41), neutrophil (HR = 1.04, 95% CI = 1.03–1.06) proportions, and age acceleration (HR = 1.06, 95% CI = 1.03–1.08) were associated with worse overall survival in patient with bladder cancer. partDSA and SS-RPMM classified five groups of subjects with significant differences in overall survival.
Conclusions:
We identified associations between immune cell subtypes and age acceleration with bladder cancer outcomes.
Impact:
The findings of this study suggest that bladder cancer outcomes are associated with specific methylation-derived immune cell-type proportions and age acceleration, and these factors could be potential prognostic biomarkers.
Data from Sex-specific associations between adiponectin and leptin signaling and pancreatic cancer survival
Authors: Babic Ana , Wang Qiao-Li , Lee Alice A. , Yuan Chen , Rifai Nader , Luo Juhua , Tabung Fred K. , Shadyab Aladdin , Wactawski-Wende Jean , Saquib Nazmus , Kim Jihye , Kraft Peter , Sesso Howard D. , Buring Julie E. , Giovannucci Edward L. , Manson JoAnn E. , Stampfer Meir J. , Ng Kimmie , Fuchs Charles S. , Wolpin Brian M.
Published: October 2023

Abstract
Background: Circulating adiponectin and leptin have been associated with risk of pancreatic cancer. However, the relationship between long-term exposure to these adipokines in the prediagnostic period with patient survival has not been investigated.

Methods: Adipokine levels were measured in prospectively collected samples from 472 pancreatic cancer patients. Due to sex-specific differences in adipokine levels, associations were evaluated separately for men and women. In a subset of 415 patients, we genotyped 23 nucleotide polymorphisms (SNPs) in adiponectin receptor genes (ADIPOR1, ADIPOR2) and 30 SNPs in the leptin receptor gene (LEPR).

Results: Adiponectin levels were inversely associated with survival in women (HR=1.47, 95% CI: 1.03-2.11, comparing top to bottom quartile) but not in men (HR=0.93, 95% CI: 0.54-1.59). The SNPs rs10753929 and rs1418445 in ADIPOR1 were associated with survival in the combined population (per minor allele HR=0.66, 95% CI: 0.51-0.84, and HR=1.33, 95% CI: 1.12-1.58, respectively). Among SNPs in LEPR, rs12025906, rs3790431, and rs17127601 were associated with survival in the combined population [HRs (95% CI) of 1.54 (1.25-1.90), 0.72 (0.59-0.88), and 0.70 (0.56-0.89), respectively], while rs11585329 was associated with survival in men only (HR=0.39, 95% CI: 0.23-0.66) (P-interaction=0.0002).

Conclusions: High levels of adiponectin in the prediagnostic period were associated with shorter survival among women, but not among men with pancreatic cancer. Several polymorphisms in ADIPOR1 and LEPR are associated with patient survival.

Impact: Our findings reveal the association between adipokine signaling and pancreatic cancer survival and demonstrate the importance of examining obesity-associated pathways in relation to pancreatic cancer in a sex-specific manner.
Data from Germline genetic variants associated with somatic TMPRSS2:ERG fusion status in prostate cancer: a genome-wide association study
Authors: Ma Chaoran , Wang Xiaoyu , Dai James Y. , Turman Constance , Kraft Peter , Stopsack Konrad H. , Loda Massimo , Pettersson Andreas , Mucci Lorelei A. , Stanford Janet L. , Penney Kathryn L.
Published: October 2023

Abstract
Background: The prostate cancer subtype defined by the presence of TMPRSS2:ERG has been shown to be molecularly and epidemiologically distinct. However, few studies have investigated germline genetic variants associating with TMPRSS2:ERG fusion status.

Methods: We performed a genome-wide association study with 396 TMPRSS2:ERG(+) cases, 390 TMPRSS2:ERG(-) cases and 2,386 cancer-free controls from the Physicians' Health Study (PHS), the Health Professionals Follow-up Study (HPFS), and a Seattle-based Fred Hutchinson (FH) Cancer Center Prostate Cancer Study. We applied logistic regression models to test the associations between ~5 million SNPs with TMPRSS2:ERG fusion status accounting for population stratification.

Results: We did not identify genome-wide significant variants comparing the TMPRSS2:ERG(+) to the TMPRSS2:ERG(-) prostate cancer cases in the meta-analysis. When comparing TMPRSS2:ERG(+) prostate cancer cases with controls without prostate cancer, 10 genome-wide significant SNPs on chromosome 17q24.3 were observed in the meta-analysis. When comparing TMPRSS2:ERG(-) prostate cancer cases with controls without prostate cancer, two SNPs on chromosome 8q24.21 in the meta-analysis reached genome-wide significance.

Conclusions: We observed SNPs at several known prostate cancer risk loci (17q24.3, 1q32.1, and 8q24.21) that were differentially and exclusively associated with the risk of developing prostate tumors either with or without the gene fusion.

Impact: Our findings suggest that tumors with the TMPRSS2:ERG fusion exhibit a different germline genetic etiology compared to fusion negative cases.
Data from Germline Genetic Variants Associated with Somatic TMPRSS2:ERG Fusion Status in Prostate Cancer: A Genome-Wide Association Study
Authors: Ma Chaoran , Wang Xiaoyu , Dai James Y. , Turman Constance , Kraft Peter , Stopsack Konrad H. , Loda Massimo , Pettersson Andreas , Mucci Lorelei A. , Stanford Janet L. , Penney Kathryn L.
Published: October 2023

AbstractBackground:
The prostate cancer subtype defined by the presence of TMPRSS2:ERG has been shown to be molecularly and epidemiologically distinct. However, few studies have investigated germline genetic variants associating with TMPRSS2:ERG fusion status.
Methods:
We performed a genome-wide association study with 396 TMPRSS2:ERG(+) cases, 390 TMPRSS2:ERG(−) cases, and 2,386 cancer-free controls from the Physicians’ Health Study (PHS), the Health Professionals Follow-up Study (HPFS), and a Seattle-based Fred Hutchinson (FH) Cancer Center Prostate Cancer Study. We applied logistic regression models to test the associations between ∼5 million SNPs with TMPRSS2:ERG fusion status accounting for population stratification.
Results:
We did not identify genome-wide significant variants comparing the TMPRSS2:ERG(+) to the TMPRSS2:ERG(−) prostate cancer cases in the meta-analysis. When comparing TMPRSS2:ERG(+) prostate cancer cases with controls without prostate cancer, 10 genome-wide significant SNPs on chromosome 17q24.3 were observed in the meta-analysis. When comparing TMPRSS2:ERG(−) prostate cancer cases with controls without prostate cancer, two SNPs on chromosome 8q24.21 in the meta-analysis reached genome-wide significance.
Conclusions:
We observed SNPs at several known prostate cancer risk loci (17q24.3, 1q32.1, and 8q24.21) that were differentially and exclusively associated with the risk of developing prostate tumors either with or without the gene fusion.
Impact:
Our findings suggest that tumors with the TMPRSS2:ERG fusion exhibit a different germline genetic etiology compared with fusion negative cases.
Data from Heritable Traits and Lung Cancer Risk: A Two-Sample Mendelian Randomization Study
Authors: Pettit Rowland W. , Byun Jinyoung , Han Younghun , Ostrom Quinn T. , Coarfa Cristian , Bondy Melissa L. , Amos Christopher I.
Published: October 2023

Abstract
Introduction: Lung cancer is a complex polygenic disorder. Analysis with Mendelian randomization (MR) allows for genetically predicted risks to be estimated between exposures and outcomes.

Methods: We analyzed 345 heritable traits from the United Kingdom biobank and estimated their associated effects on lung cancer outcomes using two sample MR. In addition to estimating effects with overall lung cancer, adenocarcinoma, small cell and squamous cell lung cancers, we performed conditional effect modeling with MVMR and the traits of alcohol use, smoking initiation, average pre-tax income, and educational attainment.

Results: Univariate MR provided evidence for increased age at first sexual intercourse (OR = 0.55, p = 6.15x10-13), educational attainment (OR = 0.24, p = 1.07x10-19), average household income (OR = 0.58, p = 7.85x10-05), and alcohol usually taken with meals (OR = 0.19, p = 1.06x10-06) associating with decreased odds of overall lung cancer development. In contrast a lack of additional educational attainment (OR = 8.00, p = 3.48x10-12), body mass index (OR = 1.28, p = 9.00x10-08), pack years smoking as a proportion of life span (OR = 9.93, p = 7.96x10-12), and weekly beer intake (OR = 3.48, p = 4.08x10-07) were associated with an increased risk of overall lung cancer development.

Conclusions: Many heritable traits associated with an increased or inverse risk of lung cancer development. Effects vary based on histological subtype and conditional third trait exposures.

Impact: We identified several heritable traits and presented their genetically predictable impact on lung cancer development, providing valuable insights for consideration.
Data from New-Onset Diabetes after an Obesity-Related Cancer Diagnosis and Survival Outcomes in the Women's Health Initiative
Authors: Karra Prasoona , Hardikar Sheetal , Winn Maci , Anderson Garnet L. , Haaland Benjamin , Krick Benjamin , Thomson Cynthia A. , Shadyab Aladdin , Luo Juhua , Saquib Nazmus , Strickler Howard D. , Chlebowski Rowan , Arthur Rhonda S. , Summers Scott A. , Holland William L. , Jalili Thunder , Playdon Mary C.
Published: October 2023

AbstractBackground:
Individuals diagnosed with an obesity-related cancer (ORC survivors) are at an elevated risk of incident diabetes compared with cancer-free individuals, but whether this confers survival disadvantage is unknown.
Methods:
We assessed the rate of incident diabetes in ORC survivors and evaluated the association of incident diabetes with all-cause and cancer-specific mortality among females with ORC in the Women's Health Initiative cohort (N = 14,651). Cox proportional hazards regression models stratified by exposure-risk periods (0–1, >1–3, >3–5, >5–7, and >7–10 years) from ORC diagnosis and time-varying exposure (diabetes) analyses were performed.
Results:
Among the ORC survivors, a total of 1.3% developed diabetes within ≤1 year of follow-up and 2.5%, 2.3%, 2.3%, and 3.6% at 1–3, 3–5, 5–7, and 7–10 years of follow-up, respectively, after an ORC diagnosis. The median survival for those diagnosed with diabetes within 1-year of cancer diagnosis and those with no diabetes diagnosis in that time frame was 8.8 [95% confidence interval (CI), 7.0–14.5) years and 16.6 (95% CI, 16.1–17.0) years, respectively. New-onset compared with no diabetes as a time-varying exposure was associated with higher risk of all-cause (HR, 1.27; 95% CI, 1.16–1.40) and cancer-specific (HR, 1.17; 95% CI, 0.99–1.38) mortality. When stratified by exposure-risk periods, incident diabetes in ≤1 year of follow-up was associated with higher all-cause (HR, 1.76; 95% CI, 1.40–2.20) and cancer-specific (HR0–1, 1.82; 95% CI, 1.28–2.57) mortality, compared with no diabetes diagnosis.
Conclusions:
Incident diabetes was associated with worse cancer-specific and all-cause survival, particularly in the year after cancer diagnosis.
Impact:
These findings draw attention to the importance of diabetes prevention efforts among cancer survivors to improve survival outcomes.
Supplementary Data 1 from ILUSTRO: Phase II Multicohort Trial of Zolbetuximab in Patients with Advanced or Metastatic Claudin 18.2–Positive Gastric or Gastroesophageal Junction Adenocarcinoma
Authors: Klempner Samuel J. , Lee Keun-Wook , Shitara Kohei , Metges Jean-Phillippe , Lonardi Sara , Ilson David H. , Fazio Nicola , Kim Tae Yong , Bai Li-Yuan , Moran Diarmuid , Yang Jianning , Arozullah Ahsan , Park Jung Wook , Raizer Jeffrey J. , Bang Yung-Jue , Shah Manish A.
Published: October 2023

Supplementary Data
Supplementary Data 1 from Learning Individual Survival Models from PanCancer Whole Transcriptome Data
Authors: Kumar Neeraj , Skubleny Daniel , Parkes Michael , Verma Ruchika , Davis Sacha , Kumar Luke , Aissiou Amira , Greiner Russell
Published: October 2023

Supplementary
Supplementary Figure S6 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: October 2023

Supplementary figure 6. Wound dehiscence.
Supplementary Figure S5 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: October 2023

A. An MR image revealed a hyperintense signal in the DWI sequence, indicating an acute ischemic stroke in the right ACA region (white arrows). B. CT angiography showed poor visualization of the distal ACA.
Supplementary Figure S4 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: October 2023

A-B. Kaplan-Meier plots of progression-free survival and overall survival (Full analysis set). The x-axes indicated times since enrollment.
Supplementary Figure S3 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: October 2023

A-B. Kaplan-Meier plots of progression-free survival and overall survival (Full analysis set). The x-axes indicated times since enrollment.
Supplementary Figure S1 from Safety and Efficacy of Anlotinib Hydrochloride Plus Temozolomide in Patients with Recurrent Glioblastoma
Authors: Xu Qingsheng , Huang Kaiyuan , Meng Xiangqi , Weng Yuxiang , Zhang Luyuan , Bu Linghao , Zheng Xiujue , Cai Jinquan , Zhan Renya , Chen Qun
Published: October 2023

Axial, sagittal and coronal gadolinium-enhanced MRI at pre-baseline (A-C; yellow arrows), 6 months later demonstrating complete response after anlotinib plus temozolomide (E-G). Axial Fluid-Attenuated Inversion Recovery (FLAIR, D) image at pre-baseline, and no progression was observed during anlotinib plus temozolomide treatment after 6 months (H).
Supplementary Table S5 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

List of known tumour suppressor genes significantly under expressed in patients identified as having del(1p) in RNA-seq data from the CoMMpass dataset.
A. Del(1p12): Using copy number loss of TENT5C to identify cases. B. Del(1p22.1): Using copy number loss of RPL5 to identify cases.
Supplementary Table S4 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

List of dysregulated oncogenes, tumor suppressor genes, and fusion proteins in the presence or absence of gain(1q) based on the Cancer Gene Census
Supplementary Table S1 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

List of GEP70 genes located on chromosome 1 and their cytoband location.
Cytoband
Supplementary Spreadsheet S9 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

CRISPR dependency clustering
Supplementary Spreadsheet S7 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Differential expression between normal chr1 and focal gains group MM patients
Supplementary Spreadsheet S6 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Differential expression between normal chr1 and gain(1q) MM patients with t(11;14) translocation
Supplementary Spreadsheet S4 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Differential expression between normal chr1 and gain(1q) MM patients
Supplementary Spreadsheet S3 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Term dictionary
Supplementary Spreadsheet S2 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Correlation coefficient outbut between genetic variables Corrrelation analysis between deletion region, gain regions, and other genetic events
Supplementary Spreadsheet S10 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Common dependency pathway analysis
Supplementary Spreadsheet S1 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Bayes Factor output between genetic variables Correlation analysis between deletion region, gain regions, and other genetic events
Supplementary Figure S5 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Hi-C interaction and TAD map of CT1, TI1, D7 regions. The chromatin confirmation of the region encompassing CT1, TI1, and D7 across the 3 HMCLs (U266, RPMI8226, and KMS11) and PC for comparison. The region shows significant variability in the TAD strucure at the TENT5C locus across all samples in comparision to PC which could explain its dysregulation
Supplementary Figure S4 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Chromatin state of varying deleted regions. There is a greater variability in terms of chromatin composition of the lost regions in comparision to the region of gain. The D1 region had identical an A-compartment percentage (56%) across all samples and reflected loss of significant subtelomeric region, including TNFRSF4. The D2 region was consistent across all samples (range 96-100% A-compartment) with the exception of KMS11 (47%), however this switch to a B-compartment occurred in a gene-sparse region. The D3 region encompasses the tumour suppressor genes CDKN2C and FAF1 and had similar active chromatin profiles (range 44-77%) except in RPMI8226 (0%). The D4 and D5 regions lie completely (100%) and near completely (>87%) in inactive compartments. Interestingly, the small A-compartments in D5 across U266 and RPMI8226 correspond to the tumour suppressor FUBP1. The D6 region showed conserved A-compartment across the samples specifically at the RPL5 and MTF2 loci while EVI5 and GFI1 showed switching from B-A across the differentiation stages. The D7 region, focused on TENT5C lies within an A-compartment across all samples except for KMS11, NBC=Naïve B-cell, MBC=Memory B-cell, GCBC=Germinal Center B-cell, PC=plasma cell.
Supplementary Figure S17 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Differential methylation of MM relevent genes. Volcano plots of the CpG probes (probes=2498) across chromosome 1 between MM (n=161) and normal PC (n=3), as a result there are 378 probes (genes=360) that are significantly hypomethylated in MM on in comparison to the normal phenotype and 5 probes (genes=7) are significantly hypermethylated. The plot is further annotated to show the probe associated with A. the GEP70 genes located on chromosome 1 (n=20, p-arm=12, q-arm=8), and B. genes that have been previously implicated as driver genes of the gain/1amp(1q) phenotype in MM (n=20, p-arm=7, q-arm=13).
Supplementary Figure S10 from Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma
Authors: Boyle Eileen M. , Blaney Patrick , Stoeckle James H. , Wang Yubao , Ghamlouch Hussein , Gagler Dylan , Braunstein Marc , Williams Louis , Tenenbaum Avital , Siegel Ariel , Chen Xiaoyi , Varma Gaurav , Avigan Jason , Li Alexander , Jinsi Monica , Kaminetzsky David , Arbini Arnaldo , Montes Lydia , Corre Jill , Rustad Even H. , Landgren Ola , Maura Francesco , Walker Brian A. , Bauer Michael , Bruno Benedetto , Tsirigos Aristotelis , Davies Faith E. , Morgan Gareth J.
Published: October 2023

Correlation between age, telomere length and 1q gain subtype. A. Correlation between telomere length and chromosome 1 rearrangement subtype B. Correlation between age and chromosome 1 rearrangement subtype
Supplementary appendix S1 from Liquid Biopsies with Circulating Plasma HPV–DNA Measurements—A Clinically Applicable Surveillance Tool for Patients with HPV-Positive Oropharyngeal Cancer
Authors: Jakobsen Kathrine K. , Bendtsen Simone K. , Pallisgaard Niels , Friborg Jeppe , Lelkaitis Giedrius , Grønhøj Christian , von Buchwald Christian
Published: October 2023

Supplementary method section
Figure S3 from Liquid Biopsies with Circulating Plasma HPV–DNA Measurements—A Clinically Applicable Surveillance Tool for Patients with HPV-Positive Oropharyngeal Cancer
Authors: Jakobsen Kathrine K. , Bendtsen Simone K. , Pallisgaard Niels , Friborg Jeppe , Lelkaitis Giedrius , Grønhøj Christian , von Buchwald Christian
Published: October 2023

Figure S3: Copies of HPV DNA per ml plasma in follow-up samples for patients with residual disease. A black dot denotes a cell-free HPV-DNA negative plasma sample, while a red dot denotes a cell-free HPV-DNA positive plasma sample measured by ddPCR. Missing samples are marked in grey. Size and placement of yellow rectangles and yellow lines indicates time and type of treatment. A red line indicates the date of the recurrence. RT: radiotherapy; OP: Operation; Re-OP: Re-resection and re-operation.
Figure S2 from Liquid Biopsies with Circulating Plasma HPV–DNA Measurements—A Clinically Applicable Surveillance Tool for Patients with HPV-Positive Oropharyngeal Cancer
Authors: Jakobsen Kathrine K. , Bendtsen Simone K. , Pallisgaard Niels , Friborg Jeppe , Lelkaitis Giedrius , Grønhøj Christian , von Buchwald Christian
Published: October 2023

Figure S2: Copies of HPV DNA per ml plasma in the pretreatment sample in follow-up serial samples in patients with an HPV+ follow-up sample but with no clinical or radiological evidence of recurrence or residual disease. Red dots denote an HPV+ sample, black dots denote an HPV- sample measured by ddPCR. Size of yellow RT rectangle indicates time (days) of radiotherapy with curative intent.
Supplementary Figure S6 from Prognostic Markers of DNA Methylation and Next-Generation Sequencing in Progressive Glioblastoma from the EORTC-26101 Trial
Authors: Kessler Tobias , Schrimpf Daniel , Doerner Laura , Hai Ling , Kaulen Leon D. , Ito Jakob , van den Bent Martin , Taphoorn Martin , Brandes Alba A. , Idbaih Ahmed , Dômont Julien , Clement Paul M. , Campone Mario , Bendszus Martin , von Deimling Andreas , Sahm Felix , Platten Michael , Wick Wolfgang , Wick Antje
Published: October 2023

Supplementary Figure 6: Overall Survival according to PTEN mutation status in the group of IDH-wildtype glioblastomas (n = 362).