bluuebunny/crossref_metadata_2025 huggingface dataset:
Data from Targeting KDM2A Enhances T Cell Infiltration in NSD1-Deficient Head and Neck Squamous Cell Carcinoma
Authors: Chen Chen , Shin June Ho. , Fang Zhuoqing , Brennan Kevin , Horowitz Nina B. , Pfaff Kathleen L. , Welsh Emma L. , Rodig Scott J. , Gevaert Olivier , Gozani Or , Uppaluri Ravindra , Sunwoo John B.
Published: September 2024

Abstract
In head and neck squamous cell carcinoma (HNSCC), a significant proportion of tumors have inactivating mutations in the histone methyltransferase NSD1. In these tumors, NSD1 inactivation is a driver of T cell exclusion from the tumor microenvironment (TME). A better understanding of the NSD1-mediated mechanism regulating infiltration of T cells into the TME could help identify approaches to overcome immununosuppression. Here, we demonstrated that NSD1 inactivation results in lower levels of H3K36 di-methylation and higher levels of H3K27 tri-methylation, the latter being a known repressive histone mark enriched on the promoters of key T cell chemokines CXCL9 and CXCL10. HNSCC with NSD1 mutations had lower levels of these chemokines and lacked responses to PD-1 immune checkpoint blockade. Inhibition of KDM2A, the primary lysine demethylase that is selective for H3K36, reversed the altered histone marks induced by NSD1 loss and restored T cell infiltration into the TME. Importantly, KDM2A suppression decreased growth of NSD1-deficient tumors in immunocompetent, but not in immunodeficient, mice. Together, these data indicate that KDM2A is an immunotherapeutic target for overcoming immune exclusion in HNSCC.
Data from The genomic and epigenomic landscape of double-negative metastatic prostate cancer
Authors: Lundberg Arian , Zhang Meng , Aggarwal Rahul , Li Haolong , Zhang Li , Foye Adam , Sjöström Martin , Chou Jonathan , Chang Kevin , Moreno-Rodriguez Thaidy , Shrestha Raunak , Baskin Avi , Zhu Xiaolin , Weinstein Alana S. , Younger Noah , Alumkal Joshi J. , Beer Tomasz M. , Chi Kim N. , Evans Christopher P. , Gleave Martin , Lara Primo N. , Reiter Rob E. , Rettig Matthew B. , Witte Owen N. , Wyatt Alexander W. , Feng Felix Y. , Small Eric J. , Quigley David A.
Published: September 2024

Abstract
Systemic targeted therapy in prostate cancer is primarily focused on ablating androgen signaling. Androgen deprivation therapy and second-generation androgen receptor (AR)-targeted therapy selectively favor the development of treatment-resistant subtypes of metastatic castration-resistant prostate cancer (mCRPC), defined by AR and neuroendocrine (NE) markers. Molecular drivers of double-negative (AR-/NE-) mCRPC are poorly defined. In this study, we comprehensively characterized treatment-emergent mCRPC by integrating matched RNA sequencing, whole-genome sequencing, and whole-genome bisulfite sequencing from 210 tumors. AR-/NE- tumors were clinically and molecularly distinct from other mCRPC subtypes, with the shortest survival, amplification of the chromatin remodeler CHD7, and PTEN loss. Methylation changes in CHD7 candidate enhancers were linked to elevated CHD7 expression in AR-/NE+ tumors. Genome-wide methylation analysis nominated KLF5 as a driver of the AR-/NE- phenotype, and KLF5 activity was linked to RB1 loss. These observations reveal the aggressiveness of AR-/NE- mCRPC and could facilitate the identification of therapeutic targets in this highly aggressive disease.
Data from Elevated Mast Cell Abundance is Associated with Enrichment of CCR2+ Cytotoxic T cells and Favorable Prognosis in Lung Adenocarcinoma
Authors: Fan Fanfan , Gao Jian , Zhao Yue , Wang Jun , Meng Lu , Ma Jiaqiang , Li Teng , Han Han , Lai Jinglei , Gao Zhendong , Li Xiongfei , Guo Ran , Cao Zhiwei , Zhang Yang , Zhang Xiaoming , Chen Haiquan
Published: September 2024

Abstract
Mast cells constitute indispensable immunoregulatory sentinel cells in the tumor microenvironment. A better understanding of the regulation and functions of mast cells in lung adenocarcinoma (LUAD) could uncover therapeutic approaches to reprogram the immunosuppressive tumor microenvironment. Here, we performed flow cytometry and single-cell RNA sequencing of patient LUAD samples to comprehensively characterize LUAD infiltrating mast cells. Mast cells exhibited functional heterogeneity and were enriched in LUAD with ground-glass opacity features (gLUAD). The mast cells in gLUAD exhibited proinflammatory and chemotactic properties while those in radiologically solid LUAD (sLUAD) were associated with tumor angiogenesis. Mast cells were an important source of CCL2 and correlated with the recruitment of CCR2+ cytotoxic T lymphocytes (CTLs), a specific subcluster of pre-exhausted T cells with tissue-resident memory phenotype and enhanced cytotoxicity. Increased infiltration of mast cells and CCR2+ CTLs and their colocalization showed a strong association with favorable prognosis after surgery but were not associated with improved survival after chemotherapy. Collectively, these findings reveal a key role of mast cells in LUAD and their potential crosstalk with CTLs, suggesting that targeting mast cells may be an immunotherapeutic strategy for LUAD.
Keep It Moving: Physical Activity in the Prevention of Obesity-Driven Pancreatic Cancer
Authors: Sogunro Akin , Muzumdar Mandar D.
Published: September 2024

Despite the already dire impact of pancreatic cancer, a growing subset of patients with obesity exhibits an amplified risk of disease and worse outcomes. Mouse models have revealed that obesity is distinctly pathogenic, accelerating pancreatic ductal adenocarcinoma (PDAC) progression and inducing increased desmoplasia and myeloid cell infiltration in the tumor microenvironment. However, whether and how obesity-countering interventions, such as exercise, reverse the protumorigenic effects of obesity is incompletely understood. In this issue of Cancer Research, Pita-Grisanti and colleagues investigate the impact of physical activity (PA) in disrupting obesity-driven PDAC. Employing a variety of sophisticated models, including autochthonous genetically engineered mice, orthotopic syngeneic allografts, high-fat diet–induced obesity, and PA interventions in mice and humans, the authors found that PA impedes PDAC development in obese mice but does not impact the growth of advanced tumors. These antitumor effects correlated with reduced inflammation and fibrosis in the tumor microenvironment, a decline in high-fat diet–induced circulating inflammatory cytokines, and an increase in the IL15 signaling axis in white adipose tissue. Although adipose-targeted IL15 therapy was effective in suppressing advanced tumor growth in lean mice, obese mice were resistant to its therapeutic benefits. Together, the findings argue that PA delays obesity-driven early PDAC progression, implicating the preferential benefit of exercise as a preventative strategy. They further identify changes in obesity-associated local and systemic cytokine production as a possible mechanism for the antitumor effects of PA and help define context-specific determinants of response for emerging IL15-based immunotherapies.

See related article by Pita-Grisanti et al., p. 3058
Hope on the Horizon: A Revolution in KRAS Inhibition Is Creating a New Treatment Paradigm for Patients with Pancreatic Cancer
Authors: Aguirre Andrew J. , Stanger Ben Z. , Maitra Anirban
Published: September 2024

KRAS is the most frequently altered oncogene in pancreatic ductal adenocarcinoma, in which the aberrantly activated RAS signaling pathway plays pleiotropic roles in tumor initiation and maintenance. Nearly four decades after the discovery of the RAS oncoprotein, a multitude of pharmacologic inhibitors are now available that directly target mutant KRAS. This In Focus commentary, published simultaneously with the 2024 AACR Special Conference on Pancreatic Cancer, summarizes the current state of this rapidly changing field, including preclinical data and emerging clinical trends with respect to therapeutic efficacy, mechanisms of resistance, and potential combinations to maximize clinical benefit from this promising class of therapies.
From Inception to Malignancy: the Co-evolution of Pancreatic Cancer and Its Immunosuppressive Microenvironment
Authors: Bednar Filip , Olsen Lee Y. , Pasca di Magliano Marina
Published: September 2024

Published in Cancer Research in 2007, Clark and colleagues first introduced the concept that the immune microenvironment evolves in lockstep with the progression of pancreatic cancer. Leveraging genetically engineered mouse models of the disease that were described a few years earlier, Clark and colleagues used a combination of approaches to describe the dynamics of immune evolution in precursor lesions all the way to overt malignancy. They discovered that immunosuppression is established at the earliest stages of carcinogenesis. Here, we discuss their findings, how they led to a wealth of functional work, and how they have been expanded upon since the advent of -omics technologies.

See related article by Clark and colleagues, Cancer Res 2007;67:9518–27
Pancreatic Cancer–Associated Fibroblasts: Where Do We Go from Here?
Authors: Carpenter Eileen S. , Vendramini-Costa Debora Barbosa , Hasselluhn Marie C. , Maitra Anirban , Olive Kenneth P. , Cukierman Edna , Pasca di Magliano Marina , Sherman Mara H.
Published: September 2024

Pancreatic ductal adenocarcinoma is a deadly disease and is projected to become the second leading cause of cancer-related death by 2030. A major hallmark is the exuberant host response comprising the tumor microenvironment, of which, cancer-associated fibroblasts (CAF) are a prevalent component. Despite the gains in understanding of their heterogeneity and functionality from CAF studies in recent years, there are many unanswered questions surrounding this diverse population of cells. Here, we summarize the views of several experts in the field, focusing on the current understanding of CAFs and challenges to address.
Supplementary Table 9 from Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)
Authors: Wang Shuo , Onyeaghala Guillaume C. , Pankratz Nathan , Nelson Heather H. , Thyagarajan Bharat , Tang Weihong , Norby Faye L. , Ugoji Chinenye , Joshu Corinne E. , Gomez Christian R. , Couper David J. , Coresh Josef , Platz Elizabeth A. , Prizment Anna E.
Published: September 2024

Supplemental Table 9 shows the associations between pre-selected SNPs and mean of Visit 2 and Visit 3 sMICA and sMICB levels (continuous variables).
Supplementary Table 8 from Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)
Authors: Wang Shuo , Onyeaghala Guillaume C. , Pankratz Nathan , Nelson Heather H. , Thyagarajan Bharat , Tang Weihong , Norby Faye L. , Ugoji Chinenye , Joshu Corinne E. , Gomez Christian R. , Couper David J. , Coresh Josef , Platz Elizabeth A. , Prizment Anna E.
Published: September 2024

Supplemental Table 8 shows the associations of pre-selected SNPs with Visit 2 sMICA and sMICB levels and CRC risk without adjustment for ancestry markers.
Supplementary Table 4 from Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)
Authors: Wang Shuo , Onyeaghala Guillaume C. , Pankratz Nathan , Nelson Heather H. , Thyagarajan Bharat , Tang Weihong , Norby Faye L. , Ugoji Chinenye , Joshu Corinne E. , Gomez Christian R. , Couper David J. , Coresh Josef , Platz Elizabeth A. , Prizment Anna E.
Published: September 2024

Supplemental Table 4 shows the associations of Visit 2 sMICA and sMICB levels (in quartiles) with CRC risk.
Supplementary Table 10 from Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)
Authors: Wang Shuo , Onyeaghala Guillaume C. , Pankratz Nathan , Nelson Heather H. , Thyagarajan Bharat , Tang Weihong , Norby Faye L. , Ugoji Chinenye , Joshu Corinne E. , Gomez Christian R. , Couper David J. , Coresh Josef , Platz Elizabeth A. , Prizment Anna E.
Published: September 2024

Supplemental Table 10 shows that associations between mean of Visit 2 and Visit 3 sMICA and sMICB levels (continuous variables) with CRC risk.
Supplementary Table 1 from Associations between MICA and MICB genetic variants, protein levels, and colorectal cancer: Atherosclerosis Risk in Communities (ARIC)
Authors: Wang Shuo , Onyeaghala Guillaume C. , Pankratz Nathan , Nelson Heather H. , Thyagarajan Bharat , Tang Weihong , Norby Faye L. , Ugoji Chinenye , Joshu Corinne E. , Gomez Christian R. , Couper David J. , Coresh Josef , Platz Elizabeth A. , Prizment Anna E.
Published: September 2024

Supplemental Table 1 shows the results from previous studies that found significant associations between the pre-selected SNPs and risk of cancers or autoimmune diseases.
Supplementary Table 9 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 9: The effect of mosaic loss of Y chromosome on death of cardiovascular disease causes, coronary artery disease causes, from cancer and any cause of death
Supplementary Table 6 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 6: Cox regression analyses evaluating the effect of mosaic chromosomal alterations on the risk of death of cardiovascular disease causes, coronary artery disease causes, from cancer, and any cause of death by chemotherapy status
Supplementary Table 4 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 4: Multivariable competing-risks regression model for the prediction of death of CVD causes and CAD causes
Supplementary Table 2 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 2: ICD-9 and ICD-10 diagnostic and procedure codes for inpatient cardiovascular-related endpoints and for the primary endpoints
Supplementary Table 11 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 11: The effect of mosaic chromosomal alterations (mCA) on death of cardiovascular disease causes, coronary artery disease causes, from cancer, and any-cause death with a mCA-by-cancer status interaction term in all patients
Supplementary Table 1 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Table 1: Primary diagnostic codes for selected cancers
Supplementary Figure 1 from Somatic mosaic chromosomal alterations and death of cardiovascular disease causes among cancer survivors
Authors: Sun Maxine , Cyr Marie-Christyne , Sandoval Johanna , Lemieux Perreault Louis-Philippe , Busque Lambert , Tardif Jean-Claude , Dubé Marie-Pierre
Published: September 2024

Supplementary Figure 1: Visual depiction of the proportion of patients with at least 1 mosaic chromosomal alteration
Supplemental Table 5 from Nitrated polycyclic aromatic hydrocarbon (nitro-PAH) signatures and somatic mutations in diesel exhaust-exposed bladder tumors
Authors: Gonzalez Nicole , Rao Nina , Dean Michael , Lee Donghyuk , Hurson Amber N. , Baris Dalsu , Schwenn Molly , Johnson Alison , Prokunina-Olsson Ludmila , Friesen Melissa C. , Zhu Bin , Rothman Nathaniel , Silverman Debra T. , Koutros Stella
Published: September 2024

REC and nitro-PAH signatures in New England
Supplemental Table 2 from Nitrated polycyclic aromatic hydrocarbon (nitro-PAH) signatures and somatic mutations in diesel exhaust-exposed bladder tumors
Authors: Gonzalez Nicole , Rao Nina , Dean Michael , Lee Donghyuk , Hurson Amber N. , Baris Dalsu , Schwenn Molly , Johnson Alison , Prokunina-Olsson Ludmila , Friesen Melissa C. , Zhu Bin , Rothman Nathaniel , Silverman Debra T. , Koutros Stella
Published: September 2024

study characteristics
Table S9 from Exploring the complex relationship between gut microbiota and risk of colorectal neoplasia using bidirectional Mendelian Randomization analysis
Authors: Li Wanxin , Zhou Xuan , Yuan Shuai , Wang Lijuan , Yu Lili , Sun Jing , Chen Jie , Xiao Qian , Wan Zhongxiao , Zheng Ju-Sheng , Zhang Cai-Xia , Larsson Susanna C. , Farrington Susan M. , Law Philip , Houlston Richard S. , Tomlinson Ian , Ding Ke-Feng , Dunlop Malcolm G. , Theodoratou Evropi , Li Xue
Published: September 2024

Table S9 shows the reverse MR analyses of colorectal cancer, adenoma and polyps with the abundance of nine gut microbiota.
Table S7 from Exploring the complex relationship between gut microbiota and risk of colorectal neoplasia using bidirectional Mendelian Randomization analysis
Authors: Li Wanxin , Zhou Xuan , Yuan Shuai , Wang Lijuan , Yu Lili , Sun Jing , Chen Jie , Xiao Qian , Wan Zhongxiao , Zheng Ju-Sheng , Zhang Cai-Xia , Larsson Susanna C. , Farrington Susan M. , Law Philip , Houlston Richard S. , Tomlinson Ian , Ding Ke-Feng , Dunlop Malcolm G. , Theodoratou Evropi , Li Xue
Published: September 2024

Table S7 shows the forward MR analyses of nine gut microbiota with the risk of colorectal cancer.
Table S4 from Exploring the complex relationship between gut microbiota and risk of colorectal neoplasia using bidirectional Mendelian Randomization analysis
Authors: Li Wanxin , Zhou Xuan , Yuan Shuai , Wang Lijuan , Yu Lili , Sun Jing , Chen Jie , Xiao Qian , Wan Zhongxiao , Zheng Ju-Sheng , Zhang Cai-Xia , Larsson Susanna C. , Farrington Susan M. , Law Philip , Houlston Richard S. , Tomlinson Ian , Ding Ke-Feng , Dunlop Malcolm G. , Theodoratou Evropi , Li Xue
Published: September 2024

Table S4 shows the SNPs for colorectal cancer.
Table S3 from Exploring the complex relationship between gut microbiota and risk of colorectal neoplasia using bidirectional Mendelian Randomization analysis
Authors: Li Wanxin , Zhou Xuan , Yuan Shuai , Wang Lijuan , Yu Lili , Sun Jing , Chen Jie , Xiao Qian , Wan Zhongxiao , Zheng Ju-Sheng , Zhang Cai-Xia , Larsson Susanna C. , Farrington Susan M. , Law Philip , Houlston Richard S. , Tomlinson Ian , Ding Ke-Feng , Dunlop Malcolm G. , Theodoratou Evropi , Li Xue
Published: September 2024

Table S3 shows the SNPs that associated with six gut microbial metabolites.
Supplementary Methods from Exploring the complex relationship between gut microbiota and risk of colorectal neoplasia using bidirectional Mendelian Randomization analysis
Authors: Li Wanxin , Zhou Xuan , Yuan Shuai , Wang Lijuan , Yu Lili , Sun Jing , Chen Jie , Xiao Qian , Wan Zhongxiao , Zheng Ju-Sheng , Zhang Cai-Xia , Larsson Susanna C. , Farrington Susan M. , Law Philip , Houlston Richard S. , Tomlinson Ian , Ding Ke-Feng , Dunlop Malcolm G. , Theodoratou Evropi , Li Xue
Published: September 2024

Supplementary Methods shows the formulas for calculating F-statistics.
Supplementary Table 1 from Survival of Middle Eastern and North African Individuals Diagnosed with Colorectal Cancer: A Population-Based Study in California
Authors: Zaki Timothy A. , Ziogas Argyrios , Chang Jenny , Murphy Caitlin C. , Anton-Culver Hoda
Published: September 2024

Supplementary Table 1 provides treatment quality metrics for colon and rectal cancers using adherence to National Comprehensive Cancer Network guidelines.
Supplementary Table S4 from The Association of Neighborhood Characteristics and Frailty in Childhood Cancer Survivors: A Report from the St. Jude Lifetime Cohort Study
Authors: Schwartz Lindsay F. , Dhaduk Rikeenkumar , Howell Carrie R. , Brinkman Tara M. , Ehrhardt Matthew J. , Delaney Angela , Srivastava Deo Kumar , Lanctot Jennifer Q. , Armstrong Gregory T. , Robison Leslie L. , Hudson Melissa M. , Ness Kirsten K. , Henderson Tara O.
Published: September 2024

Supplementary Table S4 shows the data output from nested logistic regression models A (neighborhood score as only predictor of pre-frailty/frailty), B (added chronic health conditions), C (added individual health behaviors), D (added demographics and treatment exposures), and E (added individual socioeconomic factors)
Supplementary Table S8 from Associations of post-diagnosis lifestyle with prognosis in women with invasive breast cancer
Authors: Troeschel Alyssa N. , Hartman Terryl J. , McCullough Lauren E. , Ergas Isaac J. , Collin Lindsay J. , Kwan Marilyn L. , Ambrosone Christine B. , Flanders W Dana , Bradshaw Patrick T. , Cespedes Feliciano Elizabeth M. , Roh Janise M. , Wang Ying , Valice Emily , Kushi Lawrence H.
Published: September 2024

Hazard ratios (HR) and 95% confidence intervals (95% CI) for the association of 2-year post-diagnosis lifestyle with all-cause mortality, breast cancer-mortality, and breast cancer recurrence among women diagnosed with stage I–III breast cancer.
Supplementary Table S6 from Associations of post-diagnosis lifestyle with prognosis in women with invasive breast cancer
Authors: Troeschel Alyssa N. , Hartman Terryl J. , McCullough Lauren E. , Ergas Isaac J. , Collin Lindsay J. , Kwan Marilyn L. , Ambrosone Christine B. , Flanders W Dana , Bradshaw Patrick T. , Cespedes Feliciano Elizabeth M. , Roh Janise M. , Wang Ying , Valice Emily , Kushi Lawrence H.
Published: September 2024

Hazard Ratios and 95% Confidence Intervals for Associations of each of the 9 Components of the 2-Year Post-Diagnosis Lifestyle Score with All-Cause Mortality, Breast Cancer-Specific Mortality, and Breast Cancer Recurrence, Excluding Deaths and Recurrences Occurring within 4 Years of Diagnosis.
Supplementary Table S3 from Associations of post-diagnosis lifestyle with prognosis in women with invasive breast cancer
Authors: Troeschel Alyssa N. , Hartman Terryl J. , McCullough Lauren E. , Ergas Isaac J. , Collin Lindsay J. , Kwan Marilyn L. , Ambrosone Christine B. , Flanders W Dana , Bradshaw Patrick T. , Cespedes Feliciano Elizabeth M. , Roh Janise M. , Wang Ying , Valice Emily , Kushi Lawrence H.
Published: September 2024

Multivariable Cox Proportional Hazards Models for the Associations of Changes in Components of the Lifestyle Score on All-Cause Mortality and Breast Cancer Recurrence in the Pathways Study.
Supplementary Table S1 from Tobacco Smoke is a Major Source of Aromatic Amine Exposure in U.S. Adults: 2013-2014 National Health and Nutrition Examination Survey (NHANES)
Authors: Seyler Tiffany , Mazumder Shrila , Ahamed Rayaj , Zhu Wanzhe , Blount Benjamin C. , Apelberg Benjamin J. , Wang Lanqing
Published: September 2024

Supplementary Table S1: Details of USDA food codes and logic for apportioning dietary intake used in our analysis
Supplementary Figure S3 from Circulating Sex Hormone Levels and Risk of Gastrointestinal Cancer: Systematic Review and Meta-Analysis of Prospective Studies
Authors: Liu Zhiqiang , Zhang Yingfan , Lagergren Jesper , Li Shanshan , Li Jingru , Zhou Zhixian , Hu Zhijian , Xie Shao-Hua
Published: September 2024

Supplementary Figure S3 shows forest plots (1), sensitivity analysis (2) and funnel plots (3) of the associations between prediagnostic circulating sex hormone levels and liver cancer risk.
Table S6 from Incidence trends and survival in early-onset esophagogastric adenocarcinoma: A Swedish population-based cohort study
Authors: Radkiewicz Cecilia , Asplund Johannes , Lagergren Jesper
Published: September 2024

Early-to-later-onset esophagogastric adenocarcinoma excess mortality rate ratios (EMRR) in patients diagnosed in years 2007-2019, exploring effect modification by sex (upper panel) and cancer stage (lower panel), with 95% confidence intervals (CI), model fit compared using the likelihood-ratio test (p-value).
Table S2 from Incidence trends and survival in early-onset esophagogastric adenocarcinoma: A Swedish population-based cohort study
Authors: Radkiewicz Cecilia , Asplund Johannes , Lagergren Jesper
Published: September 2024

Distribution, numbers (n) and percentages (%), of clinicopathological characteristics in early- (age 20-49 years) and later-onset (age 50-99 years) esophagogastric adenocarcinoma.
Table S1 from Incidence trends and survival in early-onset esophagogastric adenocarcinoma: A Swedish population-based cohort study
Authors: Radkiewicz Cecilia , Asplund Johannes , Lagergren Jesper
Published: September 2024

Esophagogastric adenocarcinoma subtypes according to the International Classification of Diseases for Oncology 2nd revision (ICD-O-2).
Supplementary Table 7 from Hepatocellular Carcinoma Surveillance Among Individuals with Cirrhosis: Trends by Payer, Etiology and Calendar Year, from a Statewide, Multi-Payer Dataset, 2010-2018
Authors: Hsu Christine D. , Henderson Louise M. , Jackson Bradford E. , Baggett Christopher D. , Jonsson Funk Michele , Olshan Andrew F. , Gupta Parul , Barritt A Sidney. , Sanoff Hanna K. , Wheeler Stephanie B. , Moon Andrew M. , Lund Jennifer L.
Published: September 2024

Supplementary Table 7 includes baseline characteristics of individuals with cirrhosis eligible for HCC surveillance – Medicare only (N, %) (N=32,723).
Supplementary Table 6 from Hepatocellular Carcinoma Surveillance Among Individuals with Cirrhosis: Trends by Payer, Etiology and Calendar Year, from a Statewide, Multi-Payer Dataset, 2010-2018
Authors: Hsu Christine D. , Henderson Louise M. , Jackson Bradford E. , Baggett Christopher D. , Jonsson Funk Michele , Olshan Andrew F. , Gupta Parul , Barritt A Sidney. , Sanoff Hanna K. , Wheeler Stephanie B. , Moon Andrew M. , Lund Jennifer L.
Published: September 2024

Supplementary Table 6 includes baseline characteristics of individuals with cirrhosis eligible for HCC surveillance – Medicaid insurance only (N, %) (N=6,790).
Supplementary Table 4 from Hepatocellular Carcinoma Surveillance Among Individuals with Cirrhosis: Trends by Payer, Etiology and Calendar Year, from a Statewide, Multi-Payer Dataset, 2010-2018
Authors: Hsu Christine D. , Henderson Louise M. , Jackson Bradford E. , Baggett Christopher D. , Jonsson Funk Michele , Olshan Andrew F. , Gupta Parul , Barritt A Sidney. , Sanoff Hanna K. , Wheeler Stephanie B. , Moon Andrew M. , Lund Jennifer L.
Published: September 2024

Supplementary Table 4 includes descriptive statistics of the cohort, by cirrhosis etiology and by insurance type.
Supplementary Table 13 from Hepatocellular Carcinoma Surveillance Among Individuals with Cirrhosis: Trends by Payer, Etiology and Calendar Year, from a Statewide, Multi-Payer Dataset, 2010-2018
Authors: Hsu Christine D. , Henderson Louise M. , Jackson Bradford E. , Baggett Christopher D. , Jonsson Funk Michele , Olshan Andrew F. , Gupta Parul , Barritt A Sidney. , Sanoff Hanna K. , Wheeler Stephanie B. , Moon Andrew M. , Lund Jennifer L.
Published: September 2024

Supplementary Table 13 includes the two-year cumulative incidences for HCC surveillance overall and by insurance type, by calendar year of cirrhosis diagnosis, excluding individuals with decompensated cirrhosis (% and 95% confidence intervals).
Supplementary Table 10 from Hepatocellular Carcinoma Surveillance Among Individuals with Cirrhosis: Trends by Payer, Etiology and Calendar Year, from a Statewide, Multi-Payer Dataset, 2010-2018
Authors: Hsu Christine D. , Henderson Louise M. , Jackson Bradford E. , Baggett Christopher D. , Jonsson Funk Michele , Olshan Andrew F. , Gupta Parul , Barritt A Sidney. , Sanoff Hanna K. , Wheeler Stephanie B. , Moon Andrew M. , Lund Jennifer L.
Published: September 2024

Supplementary Table 10 includes two-year cumulative incidences by cirrhosis etiology and by insurance (% and 95% confidence intervals).
Supplementary Table S2 from Associations of race and ethnicity with hepatocellular carcinoma, decompensation, and mortality in US Veterans with cirrhosis
Authors: VoPham Trang , Cravero Anne , Feld Lauren D. , Green Pamela , Feng Ziding , Berry Kristin , Kim Nicole J. , Vutien Philip , Mendoza Jason A. , Ioannou George N.
Published: September 2024

Supplementary Table S2. ICD-9 codes for type 2 diabetes mellitus, alcohol use disorders, hemochromatosis, primary biliary cirrhosis, primary sclerosing cholangitis, autoimmune hepatitis, human immunodeficiency virus, and low socioeconomic status
Supplementary Table 9 from Sleep Behaviors, Genetic Predispositions, and Risk of Esophageal Cancer
Authors: Wang Xiaoyan , Tian Ruiyi , Zong Xiaoyu , Jeon Myung Sik , Luo Jingqin , Colditz Graham A. , Wang Jean S. , Tsilidis Konstantinos K. , Ju Yo-El S. , Govindan Ramaswamy , Puri Varun , Cao Yin
Published: September 2024

Supplementary Table 9 shows the additive interaction between composite sleep score and genetic risk with EAC risk
Supplementary Table 3 from Sleep Behaviors, Genetic Predispositions, and Risk of Esophageal Cancer
Authors: Wang Xiaoyan , Tian Ruiyi , Zong Xiaoyu , Jeon Myung Sik , Luo Jingqin , Colditz Graham A. , Wang Jean S. , Tsilidis Konstantinos K. , Ju Yo-El S. , Govindan Ramaswamy , Puri Varun , Cao Yin
Published: September 2024

Supplementary Table 3 shows the sensitivity analyses for the association between sleep and EAC and ESCC by excluding cancer cases diagnosed within 2 years of enrollment
Supplementary Table 2 from Sleep Behaviors, Genetic Predispositions, and Risk of Esophageal Cancer
Authors: Wang Xiaoyan , Tian Ruiyi , Zong Xiaoyu , Jeon Myung Sik , Luo Jingqin , Colditz Graham A. , Wang Jean S. , Tsilidis Konstantinos K. , Ju Yo-El S. , Govindan Ramaswamy , Puri Varun , Cao Yin
Published: September 2024

Supplementary Table 2 shows the weights used to construct the weighted sleep score
Supplementary Figure 1 from Sleep Behaviors, Genetic Predispositions, and Risk of Esophageal Cancer
Authors: Wang Xiaoyan , Tian Ruiyi , Zong Xiaoyu , Jeon Myung Sik , Luo Jingqin , Colditz Graham A. , Wang Jean S. , Tsilidis Konstantinos K. , Ju Yo-El S. , Govindan Ramaswamy , Puri Varun , Cao Yin
Published: September 2024

Supplementary Figure 1 shows the sample selection process
Supplemental Table 1 from Cost-effectiveness of human papillomavirus (HPV) self-collection intervention on cervical cancer screening uptake among underscreened US persons with a cervix
Authors: Spees Lisa P. , Biddell Caitlin B. , Smith Jennifer S. , Des Marais Andrea C. , Hudgens Michael G. , Sanusi Busola , Jackson Sarah , Brewer Noel T. , Wheeler Stephanie B.
Published: September 2024

Randomized Controlled Trials Included to Populate In-Clinic Screening Uptake Estimates for Usual Care Alternative
Supplement Table 2 from Cost-effectiveness of human papillomavirus (HPV) self-collection intervention on cervical cancer screening uptake among underscreened US persons with a cervix
Authors: Spees Lisa P. , Biddell Caitlin B. , Smith Jennifer S. , Des Marais Andrea C. , Hudgens Michael G. , Sanusi Busola , Jackson Sarah , Brewer Noel T. , Wheeler Stephanie B.
Published: September 2024

Deterministic Sensitivity Analyses Results
Table S4 from Field synopsis of environmental and genetic risk factors of sporadic early-onset colorectal cancer and advanced adenoma
Authors: Zhang Rongqi , Boakye Daniel , Yang Nan , Zhou Xuan , Zhou Yajing , Jiang Fangyuan , Yu Lili , Wang Lijuan , Sun Jing , Yuan Shuai , Chen Jie , Hamilton Ashleigh C. , Coleman Helen G. , Larsson Susanna C. , Little Julian , Dunlop Malcolm G. , Giovannucci Edward L. , Theodoratou Evropi , Li Xue
Published: September 2024

Supplementary Table 4 shows the list of environmental risk factors and their associations with early-onset colorectal advanced adenomas (EOCRA).
Table S4 from Associations between etiologic or prognostic tumor tissue markers and neighborhood contextual factors in male health professionals diagnosed with prostate cancer
Authors: Iyer Hari S. , Kensler Kevin H. , Vaselkiv Jane B. , Stopsack Konrad H. , Roscoe Charlotte , Bandera Elisa V. , Qin Bo , Jang Thomas L. , Lotan Tamara L. , James Peter , Hart Jaime E. , Mucci Lorelei A. , Laden Francine , Rebbeck Timothy R.
Published: September 2024

Odds Ratios and 95% Confidence Intervals for Association Between Neighborhood Contextual Factors at Diagnosis and Somatic Alterations in Tumor Tissue Among US Male Health Professionals with Prostate Cancer Without Adjustment for Body Mass Index
Supplementary Methods from Associations between etiologic or prognostic tumor tissue markers and neighborhood contextual factors in male health professionals diagnosed with prostate cancer
Authors: Iyer Hari S. , Kensler Kevin H. , Vaselkiv Jane B. , Stopsack Konrad H. , Roscoe Charlotte , Bandera Elisa V. , Qin Bo , Jang Thomas L. , Lotan Tamara L. , James Peter , Hart Jaime E. , Mucci Lorelei A. , Laden Francine , Rebbeck Timothy R.
Published: September 2024

inverse probability of censoring weights
Figure S1 from Associations between etiologic or prognostic tumor tissue markers and neighborhood contextual factors in male health professionals diagnosed with prostate cancer
Authors: Iyer Hari S. , Kensler Kevin H. , Vaselkiv Jane B. , Stopsack Konrad H. , Roscoe Charlotte , Bandera Elisa V. , Qin Bo , Jang Thomas L. , Lotan Tamara L. , James Peter , Hart Jaime E. , Mucci Lorelei A. , Laden Francine , Rebbeck Timothy R.
Published: September 2024

Correlation Between Demographic, Lifestyle, and Neighborhood Factors Assessed at Diagnosis Among US Male Health Professionals with Prostate Cancer (n=1,157)
Supplemental Table 6 from Elevated EVL methylation level in the normal colon mucosa is a potential risk biomarker for developing recurrent adenomas
Authors: Yu Ming , Carter Kelly T. , Baker Kelsey K. , Redman Mary W. , Wang Ting , Vickers Kathy , Li Christopher I. , Cohen Stacey A. , Krane Mukta , Ose Jennifer , Gigic Biljana , Figueiredo Jane C. , Toriola Adetunji T. , Siegel Erin M. , Shibata David , Schneider Martin , Ulrich Cornelia M. , Dzubinski Lynda Ann. , Schoen Robert E. , Grady William M.
Published: September 2024

Supplemental Table 6: Summary statistics for methylated EVL measurements in Comparison Set 2
Supplemental Table 5 from Elevated EVL methylation level in the normal colon mucosa is a potential risk biomarker for developing recurrent adenomas
Authors: Yu Ming , Carter Kelly T. , Baker Kelsey K. , Redman Mary W. , Wang Ting , Vickers Kathy , Li Christopher I. , Cohen Stacey A. , Krane Mukta , Ose Jennifer , Gigic Biljana , Figueiredo Jane C. , Toriola Adetunji T. , Siegel Erin M. , Shibata David , Schneider Martin , Ulrich Cornelia M. , Dzubinski Lynda Ann. , Schoen Robert E. , Grady William M.
Published: September 2024

Supplemental Table 5: Summary statistics for methylated EVL measurements in Comparison Set 1
Supplemental Table 3 from Elevated EVL methylation level in the normal colon mucosa is a potential risk biomarker for developing recurrent adenomas
Authors: Yu Ming , Carter Kelly T. , Baker Kelsey K. , Redman Mary W. , Wang Ting , Vickers Kathy , Li Christopher I. , Cohen Stacey A. , Krane Mukta , Ose Jennifer , Gigic Biljana , Figueiredo Jane C. , Toriola Adetunji T. , Siegel Erin M. , Shibata David , Schneider Martin , Ulrich Cornelia M. , Dzubinski Lynda Ann. , Schoen Robert E. , Grady William M.
Published: September 2024

Supplemental Table 3: Summary patient characteristics for Comparison Set 2
Supplemental Table 2 from Elevated EVL methylation level in the normal colon mucosa is a potential risk biomarker for developing recurrent adenomas
Authors: Yu Ming , Carter Kelly T. , Baker Kelsey K. , Redman Mary W. , Wang Ting , Vickers Kathy , Li Christopher I. , Cohen Stacey A. , Krane Mukta , Ose Jennifer , Gigic Biljana , Figueiredo Jane C. , Toriola Adetunji T. , Siegel Erin M. , Shibata David , Schneider Martin , Ulrich Cornelia M. , Dzubinski Lynda Ann. , Schoen Robert E. , Grady William M.
Published: September 2024

Supplemental Table 2: Summary patient characteristics for Comparison Set 1
Supplemental Table 1 from Elevated EVL methylation level in the normal colon mucosa is a potential risk biomarker for developing recurrent adenomas
Authors: Yu Ming , Carter Kelly T. , Baker Kelsey K. , Redman Mary W. , Wang Ting , Vickers Kathy , Li Christopher I. , Cohen Stacey A. , Krane Mukta , Ose Jennifer , Gigic Biljana , Figueiredo Jane C. , Toriola Adetunji T. , Siegel Erin M. , Shibata David , Schneider Martin , Ulrich Cornelia M. , Dzubinski Lynda Ann. , Schoen Robert E. , Grady William M.
Published: September 2024

Supplemental Table 1: Primer/probe sequences used in the duplex mEVL assay
Supplementary Table S5 from Development of a breast cancer risk prediction model incorporating polygenic risk scores and non-genetic risk factors for Korean women
Authors: Choi Jihye , Ha Tae-woong , Choi Hye-Mi , Lee Han-Byoel , Shin Hee-Chul , Chung Woosung , Han Wonshik
Published: September 2024

Comparison of AUC and E/O ratio between NGRF, PRS and PRS+NGRF models
Supplementary Table 5 from Sex-specific associations between body mass index and thyroid cancer incidence among Korean adults
Authors: Kim Kyoung-Nam , Kim Kyungsik , Lee Sangjun , Park Sue K.
Published: September 2024

Supplementary Table 5 shows the impact of calendar year enrolled in the Korean Multi-center Cancer Cohort (KMCC) study on the association between body mass index and thyroid cancer incidence
Supplementary Table 4 from Sex-specific associations between body mass index and thyroid cancer incidence among Korean adults
Authors: Kim Kyoung-Nam , Kim Kyungsik , Lee Sangjun , Park Sue K.
Published: September 2024

Supplementary Table 4 shows the associations between body mass (BMI) and thyroid cancer incidence in the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) at 5-year latency
Supplementary Table 1 from Association Between Sleep Duration and Colorectal Adenomas: Findings from a Case-Control Study in Vietnam
Authors: Tran Chi Thi-Du. , Paragomi Pedram , Tran Mo Thi. , Nguyen Mai Vu-Tuyet. , Tuong Thuy Thi-Van. , Tran Quang Hong. , Le Linh Cu. , Pham Huong Thi-Thu. , Ha Hien Thi-Thu. , Bui Nam Chi. , Vu Hien Huy. , Ta Phuong Que. , Shrubsole Martha J. , Cai Qiuyin , Ye Fei , Le Song Huu. , Vu Khien Van. , Tran Huong TT. , Tran Thuan V. , Boffetta Paolo , Shu Xiao-Ou , Luu Hung N.
Published: September 2024

This supplementary table describes the distributions of baseline characteristics among study participants by cases versus controls
Supplemental Table 5 from Validating Wave 1 (2014) urinary cotinine and TNE-2 cut-points for differentiating Wave 4 (2017) cigarette use from non-use in the US using data from the PATH Study.
Authors: Edwards Kathryn C. , Khan Asia , Sharma Eva , Wang Lanqing , Feng June , Blount Benjamin C. , Sosnoff Connie S. , Smith Danielle M. , Goniewicz Maciej L. , Pearson Jennifer , Villanti Andrea C. , Delnevo Cristine D. , Bover Manderski Michelle T. , Hatsukami Dorothy K. , Niaura Raymond , Everard Colm , Kimmel Heather L. , Duffy Kara , Rostron Brian L. , Del Valle-Pinero Arseima Y. , van Bemmel Dana M. , Stanton Cassandra A. , Hyland Andrew
Published: September 2024

Supplemental Table 5 provides Wave 1 and Wave 4 cotinine cut-points for any tobacco use.
Supplemental Table 3 from Validating Wave 1 (2014) urinary cotinine and TNE-2 cut-points for differentiating Wave 4 (2017) cigarette use from non-use in the US using data from the PATH Study.
Authors: Edwards Kathryn C. , Khan Asia , Sharma Eva , Wang Lanqing , Feng June , Blount Benjamin C. , Sosnoff Connie S. , Smith Danielle M. , Goniewicz Maciej L. , Pearson Jennifer , Villanti Andrea C. , Delnevo Cristine D. , Bover Manderski Michelle T. , Hatsukami Dorothy K. , Niaura Raymond , Everard Colm , Kimmel Heather L. , Duffy Kara , Rostron Brian L. , Del Valle-Pinero Arseima Y. , van Bemmel Dana M. , Stanton Cassandra A. , Hyland Andrew
Published: September 2024

Supplemental Table 3 provides prevalence rates of any tobacco use using cotinine cut-points.
Supplementary Table 4 from Relationship between ABO blood group alleles and pancreatic cancer is modulated by secretor (FUT2) genotype, but not Lewis antigen (FUT3) genotype
Authors: Kim Jihye , Yuan Chen , Amundadottir Laufey T. , Wolpin Brian M. , Klein Alison P. , Risch Harvey A. , Kraft Peter
Published: September 2024

Table S4 presents adjusted associations of ABO blood group alleles and pancreatic cancer risk by Lewis antigen and interactions between ABO blood group alleles and Lewis antigen.
Supplementary Table S7 from Genetic susceptibility to nonalcoholic fatty liver disease and risk for pancreatic cancer: Mendelian randomization
Authors: King Sontoria D. , Veliginti Swathi , Brouwers Martijn C G J. , Ren Zhewen , Zheng Wei , Setiawan Veronica Wendy. , Wilkens Lynne R. , Shu Xiao-Ou , Arslan Alan A. , Beane Freeman Laura E. , Bracci Paige M. , Canzian Federico , Du Mengmeng , Gallinger Steven J. , Giles Graham G. , Goodman Phyllis J. , Haiman Christopher A. , Kogevinas Manolis , Kooperberg Charles , Le Marchand Loic , Neale Rachel E. , Visvanathan Kala , White Emily , Albanes Demetrius , Andreotti Gabriella , Babic Ana , Berndt Sonja I. , Brais Lauren K. , Brennan Paul , Buring Julie E. , Rabe Kari G. , Bamlet William R. , Chanock Stephen J. , Fuchs Charles S. , Gaziano J. Michael , Giovannucci Edward L. , Hackert Thilo , Hassan Manal M. , Katzke Verena , Kurtz Robert C. , Lee I-Min , Malats Nuria , Murphy Neil , Oberg Ann L. , Orlow Irene , Porta Miquel , Real Francisco X. , Rothman Nathaniel , Sesso Howard D. , Silverman Debra T. , Thompson Ian M. , Wactawski-Wende Jean , Wang Xiaoliang , Wentzensen Nicolas , Yu Herbert , Zeleniuch-Jacquotte Anne , Yu Kai , Wolpin Brian M. , Duell Eric J. , Li Donghui , Hung Rayjean J. , Perdomo Sandra , McCullough Marjorie L. , Freedman Neal D. , Patel Alpa V. , Peters Ulrike , Riboli Elio , Sund Malin , Tjønneland Anne , Zhong Jun , Van Den Eeden Stephen K. , Kraft Peter , Risch Harvey A. , Amundadottir Laufey T. , Klein Alison P. , Stolzenberg-Solomon Rachael Z. , Antwi Samuel O.
Published: September 2024

Supplementary Table S7 shows results of univariate analysis for 36 biopsy-confirmed nonalcoholic fatty liver disease SNPs in the PanC4 sample
Supplementary Table S5 from Genetic susceptibility to nonalcoholic fatty liver disease and risk for pancreatic cancer: Mendelian randomization
Authors: King Sontoria D. , Veliginti Swathi , Brouwers Martijn C G J. , Ren Zhewen , Zheng Wei , Setiawan Veronica Wendy. , Wilkens Lynne R. , Shu Xiao-Ou , Arslan Alan A. , Beane Freeman Laura E. , Bracci Paige M. , Canzian Federico , Du Mengmeng , Gallinger Steven J. , Giles Graham G. , Goodman Phyllis J. , Haiman Christopher A. , Kogevinas Manolis , Kooperberg Charles , Le Marchand Loic , Neale Rachel E. , Visvanathan Kala , White Emily , Albanes Demetrius , Andreotti Gabriella , Babic Ana , Berndt Sonja I. , Brais Lauren K. , Brennan Paul , Buring Julie E. , Rabe Kari G. , Bamlet William R. , Chanock Stephen J. , Fuchs Charles S. , Gaziano J. Michael , Giovannucci Edward L. , Hackert Thilo , Hassan Manal M. , Katzke Verena , Kurtz Robert C. , Lee I-Min , Malats Nuria , Murphy Neil , Oberg Ann L. , Orlow Irene , Porta Miquel , Real Francisco X. , Rothman Nathaniel , Sesso Howard D. , Silverman Debra T. , Thompson Ian M. , Wactawski-Wende Jean , Wang Xiaoliang , Wentzensen Nicolas , Yu Herbert , Zeleniuch-Jacquotte Anne , Yu Kai , Wolpin Brian M. , Duell Eric J. , Li Donghui , Hung Rayjean J. , Perdomo Sandra , McCullough Marjorie L. , Freedman Neal D. , Patel Alpa V. , Peters Ulrike , Riboli Elio , Sund Malin , Tjønneland Anne , Zhong Jun , Van Den Eeden Stephen K. , Kraft Peter , Risch Harvey A. , Amundadottir Laufey T. , Klein Alison P. , Stolzenberg-Solomon Rachael Z. , Antwi Samuel O.
Published: September 2024

Supplementary Table S5 shows results of univariate analysis for 77 chronically elevated serum alanine aminotransferase (cALT)-defined nonalcoholic fatty liver disease in the Pancreatic Cancer Case-Control Consortium (PanC4) data
Supplementary Figure S2 from Genetic susceptibility to nonalcoholic fatty liver disease and risk for pancreatic cancer: Mendelian randomization
Authors: King Sontoria D. , Veliginti Swathi , Brouwers Martijn C G J. , Ren Zhewen , Zheng Wei , Setiawan Veronica Wendy. , Wilkens Lynne R. , Shu Xiao-Ou , Arslan Alan A. , Beane Freeman Laura E. , Bracci Paige M. , Canzian Federico , Du Mengmeng , Gallinger Steven J. , Giles Graham G. , Goodman Phyllis J. , Haiman Christopher A. , Kogevinas Manolis , Kooperberg Charles , Le Marchand Loic , Neale Rachel E. , Visvanathan Kala , White Emily , Albanes Demetrius , Andreotti Gabriella , Babic Ana , Berndt Sonja I. , Brais Lauren K. , Brennan Paul , Buring Julie E. , Rabe Kari G. , Bamlet William R. , Chanock Stephen J. , Fuchs Charles S. , Gaziano J. Michael , Giovannucci Edward L. , Hackert Thilo , Hassan Manal M. , Katzke Verena , Kurtz Robert C. , Lee I-Min , Malats Nuria , Murphy Neil , Oberg Ann L. , Orlow Irene , Porta Miquel , Real Francisco X. , Rothman Nathaniel , Sesso Howard D. , Silverman Debra T. , Thompson Ian M. , Wactawski-Wende Jean , Wang Xiaoliang , Wentzensen Nicolas , Yu Herbert , Zeleniuch-Jacquotte Anne , Yu Kai , Wolpin Brian M. , Duell Eric J. , Li Donghui , Hung Rayjean J. , Perdomo Sandra , McCullough Marjorie L. , Freedman Neal D. , Patel Alpa V. , Peters Ulrike , Riboli Elio , Sund Malin , Tjønneland Anne , Zhong Jun , Van Den Eeden Stephen K. , Kraft Peter , Risch Harvey A. , Amundadottir Laufey T. , Klein Alison P. , Stolzenberg-Solomon Rachael Z. , Antwi Samuel O.
Published: September 2024

Supplementary Figure S2 shows forest plot for minimally adjusted model for PanC4 sample
Supplementary Figure 1 from Intake of Proton-Pump Inhibitors and Gastric Cancer Within the Stomach cancer Pooling (StoP) Project
Authors: Sassano Michele , Mariani Marco , Pelucchi Claudio , Lunet Nuno , Morais Samantha , Martín Vicente , Moreno Victor , Curado Maria Paula. , Dias-Neto Emmanuel , Leja Marcis , Gašenko Evita , La Vecchia Carlo , Boccia Stefania , Pastorino Roberta
Published: September 2024

Supplementary Figure 1: Pooled adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for the association between intake of proton-pump inhibitors and gastric cancer, stratified by H. pylori infection and socioeconomic status (SES).
Table S7 from Using DEPendency of association on the number of Top Hits (DEPTH) as a complementary tool to identify novel colorectal cancer susceptibility loci.
Authors: Lai John , Wong Chi Kuen , Schmidt Daniel F. , Kapuscinski Miroslaw K. , Alpen Karen , Maclnnis Robert J. , Buchanan Daniel D. , Win Aung K. , Figueiredo Jane C. , Chan Andrew T. , Harrison Tabitha A. , Hoffmeister Michael , White Emily , Le Marchand Loic , Pai Rish K. , Peters Ulrike , Hopper John L. , Jenkins Mark A. , Makalic Enes
Published: September 2024

Supplementary Table S7 shows the number of risk regions that are common to both CCFR and GECCO datasets in stage 1 DEPTH analysis, as well as whether they are detected by logistic regression analysis or were in previous CRC GWAS studies.
Table S4 from Using DEPendency of association on the number of Top Hits (DEPTH) as a complementary tool to identify novel colorectal cancer susceptibility loci.
Authors: Lai John , Wong Chi Kuen , Schmidt Daniel F. , Kapuscinski Miroslaw K. , Alpen Karen , Maclnnis Robert J. , Buchanan Daniel D. , Win Aung K. , Figueiredo Jane C. , Chan Andrew T. , Harrison Tabitha A. , Hoffmeister Michael , White Emily , Le Marchand Loic , Pai Rish K. , Peters Ulrike , Hopper John L. , Jenkins Mark A. , Makalic Enes
Published: September 2024

Supplementary Table S4 shows the number of participants filtered out at each QC stage (according to Supplementary Table S2).