bluuebunny/crossref_metadata_2025 huggingface dataset:
Table S2 from CD36 Drives Metastasis and Relapse in Acute Myeloid Leukemia
Authors: Farge Thomas , Nakhle Jean , Lagarde Damien , Cognet Guillaume , Polley Nathaniel , Castellano Rémy , Nicolau Marie-Laure , Bosc Claudie , Sabatier Marie , Sahal Ambrine , Saland Estelle , Jeanson Yannick , Guiraud Nathan , Boet Emeline , Bergoglio Camille , Gotanègre Mathilde , Mouchel Pierre-Luc , Stuani Lucille , Larrue Clément , Sallese Marie , De Mas Véronique , Moro Cedric , Dray Cédric , Collette Yves , Raymond-Letron Isabelle , Ader Isabelle , Récher Christian , Sarry Jean-Emmanuel , Cabon Florence , Vergez François , Carrière Audrey
Published: September 2023

CD36 gene signature
Table S1 from Breast Cancer Mutations HER2V777L and PIK3CAH1047R Activate the p21–CDK4/6–Cyclin D1 Axis to Drive Tumorigenesis and Drug Resistance
Authors: Cheng Xiaoqing , Sun Yirui , Highkin Maureen , Vemalapally Nagalaxmi , Jin Xiaohua , Zhou Brandon , Prior Julie L. , Tipton Ashley R. , Li Shunqiang , Iliuk Anton , Achilefu Samuel , Hagemann Ian S. , Edwards John R. , Bose Ron
Published: September 2023

Phosphoproteins
Figures S1-S8 from Breast Cancer Mutations HER2V777L and PIK3CAH1047R Activate the p21–CDK4/6–Cyclin D1 Axis to Drive Tumorigenesis and Drug Resistance
Authors: Cheng Xiaoqing , Sun Yirui , Highkin Maureen , Vemalapally Nagalaxmi , Jin Xiaohua , Zhou Brandon , Prior Julie L. , Tipton Ashley R. , Li Shunqiang , Iliuk Anton , Achilefu Samuel , Hagemann Ian S. , Edwards John R. , Bose Ron
Published: September 2023

Figures S1-S8
Supplementary Data from CD36 Drives Metastasis and Relapse in Acute Myeloid Leukemia
Authors: Farge Thomas , Nakhle Jean , Lagarde Damien , Cognet Guillaume , Polley Nathaniel , Castellano Rémy , Nicolau Marie-Laure , Bosc Claudie , Sabatier Marie , Sahal Ambrine , Saland Estelle , Jeanson Yannick , Guiraud Nathan , Boet Emeline , Bergoglio Camille , Gotanègre Mathilde , Mouchel Pierre-Luc , Stuani Lucille , Larrue Clément , Sallese Marie , De Mas Véronique , Moro Cedric , Dray Cédric , Collette Yves , Raymond-Letron Isabelle , Ader Isabelle , Récher Christian , Sarry Jean-Emmanuel , Cabon Florence , Vergez François , Carrière Audrey
Published: September 2023

Supplemental Text
Supplementary Data from SENP1 Decreases RNF168 Phase Separation to Promote DNA Damage Repair and Drug Resistance in Colon Cancer
Authors: Wei Min , Huang Xinping , Liao Liming , Tian Yonglu , Zheng Xiaofeng
Published: September 2023

Figures S1-S6
Supplementary Data from SENP1 Decreases RNF168 Phase Separation to Promote DNA Damage Repair and Drug Resistance in Colon Cancer
Authors: Wei Min , Huang Xinping , Liao Liming , Tian Yonglu , Zheng Xiaofeng
Published: September 2023

Supplementary video 1
Supplementary Data from SENP1 Decreases RNF168 Phase Separation to Promote DNA Damage Repair and Drug Resistance in Colon Cancer
Authors: Wei Min , Huang Xinping , Liao Liming , Tian Yonglu , Zheng Xiaofeng
Published: September 2023

Supplementary video 2
Data from A Nonconserved Histidine Residue on KRAS Drives Paralog Selectivity of the KRASG12D Inhibitor MRTX1133
Authors: Keats Miles A. , Han John J.W. , Lee Yeon-Hwa , Lee Chih-Shia , Luo Ji
Published: September 2023

Abstract
MRTX1133 is the first noncovalent inhibitor against the KRASG12D mutant that demonstrated specificity and potency in preclinical tumor models. Here, we used isogenic cell lines expressing a single RAS allele to evaluate the selectivity of this compound. In addition to KRASG12D, MRTX1133 showed significant activity against several other KRAS mutants as well as wild-type KRAS protein. In contrast, MRTX1133 exhibited no activity against both G12D and wild-type forms of HRAS and NRAS proteins. Functional analysis revealed that the selectivity of MRTX1133 toward KRAS is associated with its binding to H95 on KRAS, a residue that is not conserved in HRAS and NRAS. Reciprocal mutation of amino acid 95 among the three RAS paralogs resulted in reciprocal change in their sensitivity toward MRTX1133. Thus, H95 is an essential selectivity handle for MRTX1133 toward KRAS. Amino acid diversity at residue 95 could facilitate the discovery of pan‐KRAS inhibitors as well as HRAS and NRAS paralog‐selective inhibitors.
Significance:
The nonconserved H95 residue on KRAS is required for the selectivity of the KRASG12D inhibitor MRTX1133 and can be exploited for the development of pan-KRAS inhibitors.
Supplementary Table 1 from Diabetes and Prostate Cancer Outcomes in Men with Nonmetastatic Castration-Resistant Prostate Cancer: Results from the SEARCH Cohort
Authors: Sergeyev Andrei , Gu Lin , De Hoedt Amanda M. , Amling Christopher L. , Aronson William J. , Cooperberg Matthew R. , Kane Christopher J. , Klaassen Zachary , Terris Martha K. , Guerrios-Rivera Lourdes , Freedland Stephen J. , Csizmadi Ilona
Published: September 2023

Supplementary Table 1. Demographic and disease characteristics of patients with and without biopsy grade groups
Table S8 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 , MacInnis 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 2023

Supplementary Table S8 shows the number of risk regions that are common to both CCFR and GECCO in stage 2 DEPTH analysis, as well as whether they are detected by logistic regression analysis or were in previous CRC GWAS studies.
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 , MacInnis 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 2023

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 S11 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 , MacInnis 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 2023

Supplementary Table S11 shows the ranking of SNPs at the HLA locus.
Table S1 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 , MacInnis 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 2023

Supplementary Table S1 shows the original number of cases and controls in both the CCFR and GECCO datasets.
Figure S5 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 , MacInnis 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 2023

Supplementary Figure S5 showing the QQ and Manhattan plots of conventional GWAS on the GECCO and CCFR datasets
Figure 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 , MacInnis 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 2023

Supplementary Figure S4 shows how DEPTH common risk regions are defined.
Supplementary Table S4 from Development of a Breast Cancer Risk Prediction Model Incorporating Polygenic Risk Scores and Nongenetic 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 2023

Association between PRS38_ASN+PRS190_EB and breast cancer risks in different age groups
Table S2 from Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility
Authors: Gregga Isabelle , Pharoah Paul D. P. , Gayther Simon A. , Manichaikul Ani , Im Hae Kyung , Kar Siddhartha P. , Schildkraut Joellen M. , Wheeler Heather E.
Published: September 2023

Table S2. Replication of cancer PWAS results in independent cohort with meta-analysis FDR<0.05.
Supplementary Table S2 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

Supplementary Table S2 shows additional study design and analysis characteristics of population-based cancer metabolomics studies.
Supplementary Table 1 from Associations of Dietary Patterns with Colorectal Adenomas in the Prostate, Lung, Colorectal, and Ovarian Cancer Cohort
Authors: Nepal Sushma , Aslani Zahra , Shi Ni , Tabung Fred K.
Published: September 2023

Supplementary table 1 contains results for subgroup analysis by BMI and age group
Supplementary Figure S5 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

Supplementary Figure S5 shows scatterplot illustrating 80 cancer-metabolomics primary analyses from 77 studies. Studies that had multiple cancer outcomes were considered separately in the analysis.
Supplementary Figure S4 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

Supplementary Figure S4 shows bar graph displaying distribution of metabolomic epidemiology studies of cancer by number of cancer cases recruited.
Supplementary Figure S2 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

Supplementary Figure S2 shows geographic distribution of participant recruitment for metabolomic epidemiology studies of cancer.
Figure 3 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

Bar graph depicts cancer types studied in the metabolomic epidemiology literature. *Other includes extrahepatic cholangiocarcinoma, leucoma, and other not specified.
Figure 1 from Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review
Authors: Yu Catherine T. , Farhat Zeinab , Livinski Alicia A. , Loftfield Erikka , Zanetti Krista A.
Published: September 2023

PRISMA flow diagram for selecting sources of evidence. The flow diagram shows the process used to select sources of evidence to be included in the scoping review examining population-based cancer metabolomics research.
Supplementary Table 3 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 2023

Supplementary Table 3: History of exposure to proton-pump inhibitors (PPIs) among cases and controls, according to different exposure definitions.
Supplementary Table 2 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 2023

Supplementary Table 2: Questionnaire items used to assess exposure for each study included in the analysis.
Supplementary Table 5 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 2023

Table S5 presents adjusted associations of ABO blood group alleles and pancreatic cancer risk, stratified by Lewis antigen and cohorts, and interactions between ABO blood group alleles and Lewis antigen.
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 2023

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 Figure 2 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 2023

Supplementary Figure 2: Pooled adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs) for the association between intake of proton-pump inhibitors and gastric cancer, by smoking status and alcohol drinking status.
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 2023

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).
Supplementary Table S5 from HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation
Authors: Grigoryan Hasmik , Imani Partow , Sacerdote Carlotta , Masala Giovanna , Grioni Sara , Tumino Rosario , Chiodini Paolo , Dudoit Sandrine , Vineis Paolo , Rappaport Stephen M.
Published: September 2023

Supplementary Table S5: Features selected for association with NHL
Supplementary Table S4 from HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation
Authors: Grigoryan Hasmik , Imani Partow , Sacerdote Carlotta , Masala Giovanna , Grioni Sara , Tumino Rosario , Chiodini Paolo , Dudoit Sandrine , Vineis Paolo , Rappaport Stephen M.
Published: September 2023

Supplementary Table S4: Variance components, ICCs and CVs for logged peak areas
Supplementary Table S9 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S9 shows descriptive Statistics for PanScan sample
Supplementary Table S3 from HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation
Authors: Grigoryan Hasmik , Imani Partow , Sacerdote Carlotta , Masala Giovanna , Grioni Sara , Tumino Rosario , Chiodini Paolo , Dudoit Sandrine , Vineis Paolo , Rappaport Stephen M.
Published: September 2023

Supplementary Table S3: Fold changes and p-values for adducts
Supplementary Table S8 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S8 shows results of univariate analysis for 17 imaging and biopsy validated SNPs in the PanC4 sample
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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S7 shows results of univariate analysis for 36 biopsy-confirmed nonalcoholic fatty liver disease SNPs in the PanC4 sample
Supplementary Methods S1 from HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation
Authors: Grigoryan Hasmik , Imani Partow , Sacerdote Carlotta , Masala Giovanna , Grioni Sara , Tumino Rosario , Chiodini Paolo , Dudoit Sandrine , Vineis Paolo , Rappaport Stephen M.
Published: September 2023

Supplementary Methods S1: Detailed nLC-HRMSMS methods
Supplementary Figure S2 from HSA Adductomics Reveals Sex Differences in NHL Incidence and Possible Involvement of Microbial Translocation
Authors: Grigoryan Hasmik , Imani Partow , Sacerdote Carlotta , Masala Giovanna , Grioni Sara , Tumino Rosario , Chiodini Paolo , Dudoit Sandrine , Vineis Paolo , Rappaport Stephen M.
Published: September 2023

Supplementary Figure S2: Plots of ln(case/matched-control fold change) versus time to diagnosis (ttd) in days from recruitment for adduct features selected for MALES and FEMALES
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 W. , 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 , LeMarchand 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 Núria , 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 2023

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 Table S4 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S4 shows results of univariate analysis for 17 imaging and biopsy validated SNPs in the PanScan sample
Supplementary Table 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S2 shows results of univariate analysis for 22 imaging-defined nonalcoholic fatty liver disease SNPs in the PanScan sample
Supplementary Table S10 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S10 shows descriptive Statistics for PanC4 sample
Supplementary Table S1 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Table S1 shows results of univariate analysis for 77 chronically elevated serum alanine aminotransferase (cALT)-defined nonalcoholic fatty liver disease SNPs in the Pancreatic Cancer Cohort Consortium (PanScan) 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Figure S2 shows forest plot for minimally adjusted model for PanC4 sample
Supplementary Figure S1 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 W. , 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 , LeMarchand 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 Núria , 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 2023

Supplementary Figure S1 shows forest plot for minimally adjusted model for the PanScan sample.
Supplemental Table 7 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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Table 7: Summary statistics for methylated EVL measurements in Comparison Set 3
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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Table 5: Summary statistics for methylated EVL measurements in Comparison Set 1
Supplemental Table 4 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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Table 4: Summary patient characteristics for Comparison Set 3
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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Table 3: Summary patient characteristics for Comparison Set 2
Supplemental Figure 4 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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Figure 4: Methylation levels of normal colon for patients with no history of adenoma or cancer after initial amongst those at least 4 years of follow-up (left group) and levels for patients with an adenoma or colorectal cancer detected after initial colonoscopy (middle group). Patients without an adenoma or colorectal cancer and less than 4 years of follow-up (right group) were not included in the analyses for Comparison Set 3. %mEVL=percentage of DNA that is methylated at the EVL locus assayed.
Supplemental Figure 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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Figure 2: Methylation levels of normal colon mucosa in patients with no history of adenoma or cancer ever (group on left) and levels for patients with a history of adenoma(s) or colorectal cancer at initial or a follow-up colonoscopy (group on right) in Comparison Set 1. %mEVL=percentage of DNA that is methylated at the EVL locus assayed.
Supplemental Figure 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 A. , Schoen Robert E. , Grady William M.
Published: September 2023

Supplemental Figure 1. Flowchart of patient selection. * Subjects with hereditary conditions or inflammatory bowel disease (IBD) were excluded. A flowchart showing the selection process for the subjects included in the studies is shown. The primary exclusion criteria that affected subject selection were lack of serial colonoscopy data and lack of tissue from the normal colon
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 2023

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 2 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 2023

Supplementary Table 2 shows the associations between body mass index (BMI) and thyroid cancer incidence in the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) using the Western BMI cutoff
Supplementary Figure 2 from Hospitalizations and Cost of Inpatient Care for Physical Diseases in Survivors of Childhood Cancer in Western Australia: A Longitudinal Matched Cohort Study
Authors: Abdalla Tasnim , Walwyn Thomas , White Daniel , Choong Catherine S. , Bulsara Max , Preen David B. , Ohan Jeneva L.
Published: September 2023

The mean cumulative count of hospitalisations for any physical-health disease by attained age, in childhood cancer survivors and their matched comparisons.
Supplemental Table 2 from Validating Wave 1 (2014) Urinary Cotinine and TNE-2 Cut-points for Differentiating Wave 4 (2017) Cigarette Use from Non-use in the United States 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 2023

Supplemental Table 2 provides demographic and tobacco use characteristics of any tobacco users.
Data from Associations of Dietary Patterns with Colorectal Adenomas in the Prostate, Lung, Colorectal, and Ovarian Cancer Cohort
Authors: Nepal Sushma , Aslani Zahra , Shi Ni , Tabung Fred K.
Published: September 2023

AbstractBackground:
Most colorectal cancers arise from adenomas, and although insulinemic and inflammatory dietary patterns have been associated with colorectal cancer risk, these dietary patterns have not been studied in relation to adenoma risk.
Methods:
Using data from 21,192 participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer screening cohort, we calculated the Empirical Dietary Index for Hyperinsulinemia (EDIH), Empirical Dietary Inflammatory Pattern (EDIP), and overall dietary quality measured via the Healthy Eating Index (HEI-2015), from food frequency questionnaires (FFQ). In multivariable-adjusted logistic regression, we investigated associations of these dietary indices with adenoma (any adenoma, advanced adenoma, n = 19,493) and recurrent adenoma (n = 1,699).
Results:
EDIH was not associated with adenoma or advanced adenoma but was marginally associated with recurrent adenoma. The OR (95% CI) comparing highest (lowest insulinemic) versus lowest (most hyperinsulinemic) quintiles was 0.76 (0.55–1.05) after multivariable adjustment including BMI. EDIP and HEI-2015 were not associated with any of the three outcomes.
Conclusions:
In the PLCO cohort, we did not observe substantial associations between dietary patterns and risk of colorectal adenomas.
Impact:
Pending confirmation in larger prospective studies, our findings suggest that these dietary patterns may not substantially affect colorectal cancer risk via the adenoma–carcinoma sequence.
Data from Development of a Breast Cancer Risk Prediction Model Incorporating Polygenic Risk Scores and Nongenetic 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 2023

AbstractBackground:
To develop a breast cancer prediction model for Korean women using published polygenic risk scores (PRS) combined with nongenetic risk factors (NGRF).
Methods:
Thirteen PRS models generated from single or multiple combinations of the Asian and European PRSs were evaluated among 20,434 Korean women. The AUC and increase in OR per SD were compared for each PRS. The PRSs with the highest predictive power were combined with NGRFs; then, an integrated prediction model was established using the Individualized Coherent Absolute Risk Estimation (iCARE) tool. The absolute breast cancer risk was stratified for 18,142 women with available follow-up data.
Results:
PRS38_ASN+PRS190_EB, a combination of Asian and European PRSs, had the highest AUC (0.621) among PRSs, with an OR per SD increase of 1.45 (95% confidence interval: 1.31–1.61). Compared with the average risk group (35%–65%), women in the top 5% had a 2.5-fold higher risk of breast cancer. Incorporating NGRFs yielded a modest increase in the AUC of women ages >50 years. For PRS38_ASN+PRS190_EB+NGRF, the average absolute risk was 5.06%. The lifetime absolute risk at age 80 years for women in the top 5% was 9.93%, whereas that of women in the lowest 5% was 2.22%. Women at higher risks were more sensitive to NGRF incorporation.
Conclusions:
Combined Asian and European PRSs were predictive of breast cancer in Korean women. Our findings support the use of these models for personalized screening and prevention of breast cancer.
Impact:
Our study provides insights into genetic susceptibility and NGRFs for predicting breast cancer in Korean women.
Data 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 2023

AbstractBackground:
A potential association between proton-pump inhibitors (PPI) and gastric cancer remains undefined. Thus, we aimed to evaluate such association within the Stomach cancer Pooling (StoP) Project.
Methods:
Data from five case–control studies of the StoP Project were included (1,889 cases and 6,517 controls). We assessed the impact of different exposure definitions, specifically any reported use of PPIs and exposure definitions based on the duration of PPI intake. Additionally, we modeled the dose–response relationship between the cumulative duration of PPI intake and gastric cancer.
Results:
Significant associations between PPI intake and gastric cancer, both overall and in the stratified analyses, were limited to exposure definitions based on short durations of intake. The overall odds ratio (OR) for any reported PPI intake was 1.78 [95% confidence interval (CI): 0.76–4.14]. In the dose–response analysis, the ORs of gastric cancer were found to be higher for short durations of PPI intake (6 months: OR 3.26; 95% CI: 2.40–4.42; one year: OR 2.14; 95% CI: 1.69–2.70; 2 years: OR 1.50; 95% CI: 1.22–1.85; 3 years: OR 1.27; 95% CI: 1.03–1.56), with the association becoming not significant for durations longer than 3 years.
Conclusions:
Our findings suggest that the observed association between PPIs and gastric cancer might be mainly due to reverse causality.
Impact:
The results of this study suggest that PPIs are a safe therapeutic choice regarding their effect on the occurrence of gastric cancer.

See related commentary by Richman and Leiman, p. 1127