bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Based on Improved Random Forest Defense System Against Application‐Layer DDoS Attacks
Authors: He Junjiang , Fang Wenbo , Lan Xiaolong , Yang Geying , Chen Ziyu , Chen Yang , Li Tao , Chen Jiangchuan
Published: November 2024

Application‐layer distributed denial of service (DDoS) attacks have become the main threat to Web server security. Because application‐layer DDoS attacks have strong concealability and high authenticity, intrusion detection technologies that rely solely on judging client authenticity cannot accurately detect such attacks. In addition, application‐layer DDoS attacks are periodic and repetitive, and attack targets suddenly in a short period. In this study, we propose an efficient application‐layer DDoS detection system based on improved random forest. Firstly, the Web logs are preprocessed to extract the user session characteristics. Subsequently, we propose a Session Identification based on Separation and Aggregation (SISA) method to accurately capture user sessions. Lastly, we propose an improved random forest classification algorithm based on feature weighting to address the issue of an increasing number of features leading to prolonged calculation times in the random forest algorithm, and as the feature dimension increases, there might be instances where no subfeature is related to the category to be classified. More importantly, we compare the request source IP with the malicious IP in the threat intelligence library to deal with the periodicity and repetition of application‐layer DDoS attacks. We conducted a comprehensive experiment on the publicly available Web log dataset and the threat intelligence database of the laboratory as well as the simulated generated attack log dataset in the laboratory environment. The experimental results show that the proposed detection system can control the false alarm rate and false alarm rate within a reasonable range, improving the detection efficiency further, the detection rate is 99.85%. In secondary attack detection experiments, our proposed detection method achieves a higher detection rate in a shorter time.
Incidence and Genetic Investigation of Avian Coronaviruses in Migratory Ducks From South Korea
Authors: Gim Yunhee , Jeong Song Hwi , Lee Young Ju , Jang Guehwan , Lee Changhee
Published: November 2024

Coronaviruses (CoVs) belonging to the Gamma-CoV and Delta-CoV genera are widespread in poultry and wildfowl. Migratory birds, particularly duck species, serve as hosts for CoVs and play a pivotal role in transmitting the viruses to other species, including mammals. Despite the potential risks to animals and humans, there remains a narrow knowledge of the genetic and epidemiological properties of CoVs in wild birds. The current research aimed to detect and characterize CoVs present in migratory duck species (Anas acuta, Anas platyrhynchos, and Anas poecilorhyncha) from South Korea. Employing two rounds of pan‐CoV real‐time reverse transcription‐polymerase chain reaction (RT‐PCR) and nested PCR (nPCR) assays amplifying the conserved RNA‐dependent RNA polymerase (RdRp) portion common to all known CoVs, we screened 2120 duck fecal samples collected during 2022–2023. The results indicated the presence of CoVs in 4.2% (91/2120) of samples from migratory ducks. Nucleotide sequencing of the RdRp gene revealed that all identified CoVs were clustered within the Gamma-CoV genus. Further phylogenetic analysis suggested that South Korean gamma‐CoVs belong to the Igacovirus subgenus and share similarities with those found worldwide, highlighting the critical role of migratory ducks in introducing and exporting avian CoVs. We discovered two clade VII igacovirus strains in wild ducks closely related to those in pigeons, implying potential cross infection between these avian species. Overall, our study underscores the importance of active surveillance and monitoring of avian CoVs in wild birds as a preemptive response against the forthcoming emergence of new CoV species that can threaten both animal and human health.
Supplementary Table 2 from Disparities in Cancer Stage of Diagnosis by Rurality in California, 2015 to 2019
Authors: Oh Debora L. , Wang Katarina , Goldberg Debbie , Schumacher Karen , Yang Juan , Lin Katherine , Gomez Scarlett Lin , Shariff-Marco Salma
Published: November 2024

OR for late stage diagnosis, overall
Supplementary Table 1 from Disparities in Cancer Stage of Diagnosis by Rurality in California, 2015 to 2019
Authors: Oh Debora L. , Wang Katarina , Goldberg Debbie , Schumacher Karen , Yang Juan , Lin Katherine , Gomez Scarlett Lin , Shariff-Marco Salma
Published: November 2024

Supplementary Table 1 shows covariables included in sequential models
Supplementary Data from Cancer Screening, Knowledge, and Fatalism among Chinese, Korean, and South Asian Residents of New York City
Authors: Curro Isabel I. , Teasdale Chloe A. , Wyatt Laura C. , Foster Victoria , Yusuf Yousra , Sifuentes Sonia , Chebli Perla , Kranick Julie A. , Kwon Simona C. , Trinh-Shevrin Chau , LeCroy Madison N.
Published: November 2024

Cancer-related survey questions and response options
Supplementary Table S9 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Table S9 Sensitivity analyses of the fully adjusted and stratified model for the association between dietary pattern 1 and incident overall CRC
Supplementary Table S3 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Table S3. Univariable associations with colorectal cancer
Supplementary Table S11 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Table S11. Comparison of incident colorectal cancer cases and baseline characteristics between those completing 2 vs. 3+ WebQs
Supplementary Table S10 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Table S10 Sensitivity analyses of the fully adjusted model for the association between dietary pattern 2 and incident overall CRC
Supplementary Table S1 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Table S1 Derivation of outcome, exposure of interest, model covariates, exclusion criteria, and sensitivity analysis variables from U.K. Biobank data
Supplementary Figure S2 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Figure S2 U.K. Biobank participant exclusion flow chart
Supplementary Figure S1 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

Figure S1 Directed acyclic graph of variables used in the model.
Figure 5 from Associations between Dietary Patterns and Incident Colorectal Cancer in 114,443 Individuals from the UK Biobank: A Prospective Cohort Study
Authors: Skulsky Samuel L. , Koutoukidis Dimitrios A. , Carter Jennifer L. , Piernas Carmen , Jebb Susan A. , Gao Min , Astbury Nerys M.
Published: November 2024

DP1 sensitivity analyses. The x-axis comprises HRs and associated 95% CIs and is on the log-scale. CIs presented were obtained using the floating absolute risk method. WebQ, Oxford WebQ 24-hour dietary assessment tool.
Supplemental Table 6. from Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis
Authors: Young Corey D. , Hubbard Aubrey K. , Saint-Maurice Pedro F. , Chan Irenaeus C.C. , Cao Yin , Tran Duc , Bolton Kelly L. , Chanock Stephen J. , Matthews Charles E. , Moore Steven C. , Loftfield Erikka , Machiela Mitchell J.
Published: November 2024

Supplemental Table 6. Comparison of CH Models with Significant Associations Excluding all Ever-Smokers
Supplemental Table 3. from Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis
Authors: Young Corey D. , Hubbard Aubrey K. , Saint-Maurice Pedro F. , Chan Irenaeus C.C. , Cao Yin , Tran Duc , Bolton Kelly L. , Chanock Stephen J. , Matthews Charles E. , Moore Steven C. , Loftfield Erikka , Machiela Mitchell J.
Published: November 2024

Supplemental Table 3. Relationship Between Alcohol Autosomal Mosaic Chromosomal Alterations (mCAs) and CHIP in Females
Supplemental Table 2. from Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis
Authors: Young Corey D. , Hubbard Aubrey K. , Saint-Maurice Pedro F. , Chan Irenaeus C.C. , Cao Yin , Tran Duc , Bolton Kelly L. , Chanock Stephen J. , Matthews Charles E. , Moore Steven C. , Loftfield Erikka , Machiela Mitchell J.
Published: November 2024

Supplemental Table 2. Model Output for Multivariate Analysis of Sleep, Physical Activity, Alcohol, and Social Indices
Supplemental Table 1. from Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis
Authors: Young Corey D. , Hubbard Aubrey K. , Saint-Maurice Pedro F. , Chan Irenaeus C.C. , Cao Yin , Tran Duc , Bolton Kelly L. , Chanock Stephen J. , Matthews Charles E. , Moore Steven C. , Loftfield Erikka , Machiela Mitchell J.
Published: November 2024

Supplemental Table 1. UK Biobank Field IDs for Single Metric and Summary Measure Logistic Regression Models
Table 2 from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

Five-year OS and EFS for the group of patients with PTH levels below the median (47 pg/mL) of the group (PTH− group, first column), the patients with PTH levels ≥ the median (PTH+ group, second column), the entire PTH-group (third column), the group with deficient (25OHD < 30 nmol/L) vitamin D levels (25OHD− group, fourth column), the group with sufficient vitamin D levels (25OHD+ group, last column).
Supplementary Figure 1A -B from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

Event-free and Overall Survival plots for the entire cohort and Subgroups.
Supplemental Figure 3 A-H from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

PTH and Event-free Survival of the entire group and subgroups.
Supplemental Figure 2A-H from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

PTH and Overall Survival of the entire group and subgroups.
Figure 4 from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

A–C, Multivariate Cox proportional hazard model for EFS. The variables “vitamin D deficiency” (defined by a 25 OH vitamin D level < 30 nmol/L), “higher PTH” (defined by a PTH level > 47 pg/mL), sex and age at diagnosis were investigated for EFS in the groups: embryonal malignancies (A) lymphatic malignancies (B) and malignant primary brain tumor (PBT; C).
Figure 3 from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

A–C, EFS in subgroups with PTH as a continuous variable. Visualizing of the highest measured PTH on time-to-event (as EFS) in a model assuming a linear PTH-effect in the subgroups of embryonal malignancies (A) lymphatic malignancies (B) and malignant primary brain tumor (PBT; C). For the analyses, the highest PTH at diagnosis or during the following 5-year period was used.
Figure 2 from High Parathyroid Hormone Rather than Low Vitamin D Is Associated with Reduced Event-Free Survival in Childhood Cancer
Authors: Grasemann Corinna , Höppner Jakob , Högler Wolfgang , Tippelt Stephan , Grasemann Maximilian , Grabow Desiree , Cario Gunnar , Zimmermann Martin , Schrappe Martin , Reinhardt Dirk , Schündeln Michael M.
Published: November 2024

A–C, Kaplan–Meier plots showing EFS in subgroups. The Kaplan–Meier plots show the EFS in the groups of embryonal malignancies (A) lymphatic malignancies (B) and malignant primary brain tumor (PBT; C) for patients with PTH at/above the median (47 pg/mL) of the entire group (orange line) and patients with PTH levels below the median (gray line). For the analyses, the highest PTH at diagnosis or during the following 5-year period was used. P values from paired log rank tests are provided.
Supplementary Table S5 from Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Authors: Kalia Sarah S. , Boddicker Nicholas J. , Yadav Siddhartha , Huang Hongyan , Na Jie , Hu Chunling , Ambrosone Christine B. , Yao Song , Haiman Christopher A. , Chen Fei , John Esther M. , Kurian Allison W. , Guo Boya , Lindstrӧm Sara , Auer Paul , Lacey James V. , Neuhausen Susan L. , Martinez Maria Elena , Sandler Dale P. , O’Brien Katie M. , Taylor Jack A. , Teras Lauren R. , Hodge James M. , Lori Adriana , Bodelon Clara , Trentham-Dietz Amy , Burnside Elizabeth S. , Vachon Celine M. , Winham Stacey J. , Goldgar David E. , Domchek Susan M. , Nathanson Katherine L. , Weitzel Jeffrey N. , Couch Fergus J. , Kraft Peter
Published: November 2024

Supplementary Table S5 shows discrimination of models with different combinations of risk factors with controls and invasive breast cancer cases
Supplementary Table S4 from Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Authors: Kalia Sarah S. , Boddicker Nicholas J. , Yadav Siddhartha , Huang Hongyan , Na Jie , Hu Chunling , Ambrosone Christine B. , Yao Song , Haiman Christopher A. , Chen Fei , John Esther M. , Kurian Allison W. , Guo Boya , Lindstrӧm Sara , Auer Paul , Lacey James V. , Neuhausen Susan L. , Martinez Maria Elena , Sandler Dale P. , O’Brien Katie M. , Taylor Jack A. , Teras Lauren R. , Hodge James M. , Lori Adriana , Bodelon Clara , Trentham-Dietz Amy , Burnside Elizabeth S. , Vachon Celine M. , Winham Stacey J. , Goldgar David E. , Domchek Susan M. , Nathanson Katherine L. , Weitzel Jeffrey N. , Couch Fergus J. , Kraft Peter
Published: November 2024

Supplementary Table S4 shows discrimination and fit of models with different combinations of risk factors with controls and all breast cancer cases
Supplementary Table 8 from Prostate Cancer Disparities in Clinical Characteristics and Survival among Black and Latino Patients Considering Nativity: Findings from the California Cancer Registry
Authors: Freedland Alexis R. , Sanchez Mendez Joel , Liu Lihua , Hamilton Ann S. , Zhang Juanjuan , Hwang Amie E. , Ballas Leslie , Abreu Andre Luis , Deapen Dennis , Stern Mariana C.
Published: November 2024

Prostate cancer death-specific hazard (subhazard) among non-Latino White, non-Latino White, US-born Latino, and non-US-born Latino patients in California (2004-2021).
Supplementary Table 4 from Prostate Cancer Disparities in Clinical Characteristics and Survival among Black and Latino Patients Considering Nativity: Findings from the California Cancer Registry
Authors: Freedland Alexis R. , Sanchez Mendez Joel , Liu Lihua , Hamilton Ann S. , Zhang Juanjuan , Hwang Amie E. , Ballas Leslie , Abreu Andre Luis , Deapen Dennis , Stern Mariana C.
Published: November 2024

Multivariable logistic regression models for determinants of Gleason grade upgrade, receipt of treatment, and risk of dying of prostate cancer, among non-latino White, non-Latino Black, US-born Latino, and non-US-born Latino patients in California without imputed Nativity.
Supplementary Figure S2 from Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Authors: Kalia Sarah S. , Boddicker Nicholas J. , Yadav Siddhartha , Huang Hongyan , Na Jie , Hu Chunling , Ambrosone Christine B. , Yao Song , Haiman Christopher A. , Chen Fei , John Esther M. , Kurian Allison W. , Guo Boya , Lindstrӧm Sara , Auer Paul , Lacey James V. , Neuhausen Susan L. , Martinez Maria Elena , Sandler Dale P. , O’Brien Katie M. , Taylor Jack A. , Teras Lauren R. , Hodge James M. , Lori Adriana , Bodelon Clara , Trentham-Dietz Amy , Burnside Elizabeth S. , Vachon Celine M. , Winham Stacey J. , Goldgar David E. , Domchek Susan M. , Nathanson Katherine L. , Weitzel Jeffrey N. , Couch Fergus J. , Kraft Peter
Published: November 2024

Supplementary Figure S2 shows predicted 5-year risks of breast cancer based on carrier status, PRS, and ERS
Supplementary Figure S1 from Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk
Authors: Kalia Sarah S. , Boddicker Nicholas J. , Yadav Siddhartha , Huang Hongyan , Na Jie , Hu Chunling , Ambrosone Christine B. , Yao Song , Haiman Christopher A. , Chen Fei , John Esther M. , Kurian Allison W. , Guo Boya , Lindstrӧm Sara , Auer Paul , Lacey James V. , Neuhausen Susan L. , Martinez Maria Elena , Sandler Dale P. , O’Brien Katie M. , Taylor Jack A. , Teras Lauren R. , Hodge James M. , Lori Adriana , Bodelon Clara , Trentham-Dietz Amy , Burnside Elizabeth S. , Vachon Celine M. , Winham Stacey J. , Goldgar David E. , Domchek Susan M. , Nathanson Katherine L. , Weitzel Jeffrey N. , Couch Fergus J. , Kraft Peter
Published: November 2024

Supplementary Figure S1 shows predicted lifetime risks of breast cancer based on carrier status and PRS, without and with ERS
Supplementary Table 11 from Prostate Cancer Disparities in Clinical Characteristics and Survival among Black and Latino Patients Considering Nativity: Findings from the California Cancer Registry
Authors: Freedland Alexis R. , Sanchez Mendez Joel , Liu Lihua , Hamilton Ann S. , Zhang Juanjuan , Hwang Amie E. , Ballas Leslie , Abreu Andre Luis , Deapen Dennis , Stern Mariana C.
Published: November 2024

Cancer stage of non-deceased and deceased non-Latino White, non-Latino Black, US-born Latino, and non-US-born Latino patients stratified by length of follow-up period(2004-2021).
Supplementary Figure 1 from Prostate Cancer Disparities in Clinical Characteristics and Survival among Black and Latino Patients Considering Nativity: Findings from the California Cancer Registry
Authors: Freedland Alexis R. , Sanchez Mendez Joel , Liu Lihua , Hamilton Ann S. , Zhang Juanjuan , Hwang Amie E. , Ballas Leslie , Abreu Andre Luis , Deapen Dennis , Stern Mariana C.
Published: November 2024

Cumulative distribution of prostate cancer deaths among non-Latino White, non-Latino Black, and Latino patients in California (1995-2021)
Supplementary figure S7 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Figure S7 shows Cibersort data
Supplementary Table 5 from Upgrading of Grade Group 1 Prostate Cancer at Prostatectomy: Germline Risk Factors in a Prospective Cohort
Authors: Liss Michael A. , Zeltser Nicole , Zheng Yingye , Lopez Camden , Liu Menghan , Patel Yash , Yamaguchi Takafumi N. , Eng Stefan E. , Tian Mao , Semmes Oliver J. , Lin Daniel W. , Brooks James D. , Wei John T. , Klein Eric A. , Tewari Ashutosh K. , Mosquera Juan Miguel , Khani Francesca , Robinson Brian D. , Aasad Muhammad , Troyer Dean A. , Kagan Jacob , Sanda Martin G. , Thompson Ian M. , Boutros Paul C. , Leach Robin J.
Published: November 2024

Supplementary Table 5 reports results of genetic risk of upgrading score validation in the Upgrading Reference Set.
Supplementary Table 2 from Upgrading of Grade Group 1 Prostate Cancer at Prostatectomy: Germline Risk Factors in a Prospective Cohort
Authors: Liss Michael A. , Zeltser Nicole , Zheng Yingye , Lopez Camden , Liu Menghan , Patel Yash , Yamaguchi Takafumi N. , Eng Stefan E. , Tian Mao , Semmes Oliver J. , Lin Daniel W. , Brooks James D. , Wei John T. , Klein Eric A. , Tewari Ashutosh K. , Mosquera Juan Miguel , Khani Francesca , Robinson Brian D. , Aasad Muhammad , Troyer Dean A. , Kagan Jacob , Sanda Martin G. , Thompson Ian M. , Boutros Paul C. , Leach Robin J.
Published: November 2024

Supplementary Table 2 reports demographic, clinical, and genetic summaries of the genetic analysis cohort.
Supplementary figure S2 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Figure S2 shows Bacterial analysis across sample types
Supplementary Figure 4 from Upgrading of Grade Group 1 Prostate Cancer at Prostatectomy: Germline Risk Factors in a Prospective Cohort
Authors: Liss Michael A. , Zeltser Nicole , Zheng Yingye , Lopez Camden , Liu Menghan , Patel Yash , Yamaguchi Takafumi N. , Eng Stefan E. , Tian Mao , Semmes Oliver J. , Lin Daniel W. , Brooks James D. , Wei John T. , Klein Eric A. , Tewari Ashutosh K. , Mosquera Juan Miguel , Khani Francesca , Robinson Brian D. , Aasad Muhammad , Troyer Dean A. , Kagan Jacob , Sanda Martin G. , Thompson Ian M. , Boutros Paul C. , Leach Robin J.
Published: November 2024

Supplementary Figure 4 compares carrier rates of pathogenic variants in DDR genes between the study cohort and an external cohort.
Supplementary Table S9 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S9: Genomic differential abundance between tumor and lung samples
Supplementary Table S7 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S7: Gini indices for taxa when recurrence was evaluated using a random forest classifier for different percentages of total taxa
Supplementary Table S6 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S6: Taxonomic differential abundance between recurrence and non-recurrence lung samples
Supplementary Table 1 from Occupational Benzene Exposure and Cancer Risk among Chinese Men: A Report from the Shanghai Men’s Health Study
Authors: DeMoulin Douglas , Cai Hui , Vermeulen Roel , Zheng Wei , Lipworth Loren , Shu Xiao-Ou
Published: November 2024

Supplementary Table 1 shows occupational benzene exposure in association with acute myeloid leukemia, non-Hodgkin’s lymphoma, and adenocarcinoma of the lung and stomach.
Supplementary Table S5 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S5: Taxonomic differential abundance between recurrence and non-recurrence tumor samples
Supplementary Table S3 from Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans
Authors: Williams April R. , Redding Thomas S. , Sullivan Brian A. , Baidya Robin N. , Ear Belinda , Cho Kelly , Ivey Kerry L. , Williams Christina D. , Dominitz Jason A. , Lieberman David , Hauser Elizabeth R.
Published: November 2024

Supplementary Table S3 shows model fit statistics for five different sets if nested models calculated in this study: 1) Full Cohort; 2) Over 50 years old participants only; 3) Black race participants only; 4) Those who had at least one identified colonoscopy only; and 5) Those who had no history of other cancers only.
Supplementary Table S2 from Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans
Authors: Williams April R. , Redding Thomas S. , Sullivan Brian A. , Baidya Robin N. , Ear Belinda , Cho Kelly , Ivey Kerry L. , Williams Christina D. , Dominitz Jason A. , Lieberman David , Hauser Elizabeth R.
Published: November 2024

Supplementary Table S2 shows the regression beta estimates and p-values for each e-Score risk factor for two training samples: 1) the Recalibrated MVP Male Training Sample, and 2) the GECCO Male Training Sample previously published by Jeon,5 et. al., 2018.
Supplementary Table S1 from Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans
Authors: Williams April R. , Redding Thomas S. , Sullivan Brian A. , Baidya Robin N. , Ear Belinda , Cho Kelly , Ivey Kerry L. , Williams Christina D. , Dominitz Jason A. , Lieberman David , Hauser Elizabeth R.
Published: November 2024

Supplementary Table S1 shows demographic and lifestyle characteristics for the total sample for the female participants of the Million Veteran Program with complete lifestyle data and by colorectal cancer (CRC) cases versus those without CRC.
Supplementary Table S19 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S19: Absolute loadings for the identified components integrated by microbiome (ASV) and transcriptome (genes annotated to pathways) in tumor samples without recurrence
Supplementary Table S18 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S18: Absolute loadings for the identified components integrated by microbiome (ASV) and transcriptome (genes annotated to pathways) in tumor samples with recurrence
Supplementary Table S17 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S17: Absolute loadings for the identified components integrated by microbiome (ASV) and transcriptome (genes annotated to pathways) in unaffected lung samples without recurrence
Supplementary Table S13 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S13: Cibersort analysis results showing differences between sample type and recurrence groups
Supplementary Table S12 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S12: IPA analysis showing canonical pathways based on differentially expressed genes compared between recurrence and no recurrence groups, in tumor and unaffected lung samples. Scores are based on z-score
Supplementary Table S10 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S10: Genomic differential abundance between recurrence and no recurrence tumor samples
Supplementary Table S1 from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

Supplementary Table S1: identification of possible contaminants
Data from Social, Behavioral, and Clinical Risk Factors Are Associated with Clonal Hematopoiesis
Authors: Young Corey D. , Hubbard Aubrey K. , Saint-Maurice Pedro F. , Chan Irenaeus C.C. , Cao Yin , Tran Duc , Bolton Kelly L. , Chanock Stephen J. , Matthews Charles E. , Moore Steven C. , Loftfield Erikka , Machiela Mitchell J.
Published: November 2024

AbstractBackground:
Risk factors including smoking, alcohol intake, physical activity (PA), and sleep patterns have been associated with cancer risk. Clonal hematopoiesis (CH), including mosaic chromosomal alterations and clonal hematopoiesis of indeterminate potential, is linked to increased hematopoietic cancer risk and could be used as common preclinical intermediates for the better understanding of associations of risk factors with rare hematologic malignancies.
Methods:
We analyzed cross-sectional data from 478,513 UK Biobank participants without hematologic malignancies using multivariable-adjusted analyses to assess the associations between lifestyle factors and CH types.
Results:
Smoking was reinforced as a potent modifiable risk factor for multiple CH types, with dose-dependent relationships persisting after cessation. Males in socially deprived areas of England had a lower risk of mosaic loss of chromosome Y (mLOY), females with moderate/high alcohol consumption (2–3 drinks/day) had increased mosaic loss of the X chromosome risk [OR = 1.17; 95% confidence interval (CI), 1.09–1.25; P = 8.31 × 10−6] compared with light drinkers, active males (moderate-high PA) had elevated risks of mLOY (PA category 3: OR = 1.06; 95% CI, 1.03–1.08; P = 7.57 × 10−6), and men with high body mass index (≥40) had reduced risk of mLOY (OR = 0.57; 95% CI, 0.51–0.65; P = 3.30 × 10−20). Sensitivity analyses with body mass index adjustment attenuated the effect in the mLOY–PA associations (IPAQ2: OR = 1.03; 95% CI, 1.00–1.06; P = 2.13 × 10−2 and IPAQ3: OR = 1.03; 95% CI, 1.01–1.06; P = 7.77 × 10−3).
Conclusions:
Our study reveals associations between social deprivation, smoking, and alcohol consumption and CH risk, suggesting that these exposures could contribute to common types of CH and potentially rare hematologic cancers.
Impact:
This study underscores the impact of lifestyle factors on CH frequency, emphasizing social, behavioral, and clinical influences and the importance of sociobehavioral contexts when investigating CH risk factors.
Data from Lung Microbial and Host Genomic Signatures as Predictors of Prognosis in Early-Stage Adenocarcinoma
Authors: Tsay Jun-Chieh J. , Darawshy Fares , Wang Chan , Kwok Benjamin , Wong Kendrew K. , Wu Benjamin G. , Sulaiman Imran , Zhou Hua , Isaacs Bradley , Kugler Matthias C. , Sanchez Elizabeth , Bain Alexander , Li Yonghua , Schluger Rosemary , Lukovnikova Alena , Collazo Destiny , Kyeremateng Yaa , Pillai Ray , Chang Miao , Li Qingsheng , Vanguri Rami S. , Becker Anton S. , Moore William H. , Thurston George , Gordon Terry , Moreira Andre L. , Goparaju Chandra M. , Sterman Daniel H. , Tsirigos Aristotelis , Li Huilin , Segal Leopoldo N. , Pass Harvey I.
Published: November 2024

AbstractBackground:
Risk of early-stage lung adenocarcinoma recurrence after surgical resection is significant, and the postrecurrence median survival is approximately 2 years. Currently, there are no commercially available biomarkers that predict recurrence. In this study, we investigated whether microbial and host genomic signatures in the lung can predict recurrence.
Methods:
In 91 patients with early-stage (stage IA/IB) lung adenocarcinoma with extensive follow-up, we used 16s rRNA gene sequencing and host RNA sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples.
Results:
Of 91 subjects, 23 had tumor recurrence over 5-year period. In tumor samples, lung adenocarcinoma recurrence was associated with enrichment in Dialister and Prevotella, whereas in unaffected lung samples, recurrence was associated with enrichment in Sphingomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with lung adenocarcinoma recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial–host features in the unaffected lung samples associated with recurrence, enrichment in Stenotrophomonas geniculata and Chryseobacterium was positively correlated with upregulation of IL2, IL3, IL17, EGFR, and HIF1 signaling pathways among the host transcriptome. In tumor samples, enrichment in Veillonellaceae (Dialister), Ruminococcaceae, Haemophilus influenzae, and Neisseria was positively correlated with upregulation of IL1, IL6, IL17, IFN, and tryptophan metabolism pathways.
Conclusions:
Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC = 0.83).
Impact:
This study suggests that lung adenocarcinoma recurrence is associated with distinct pathophysiologic mechanisms of microbial–host interactions in the unaffected lung rather than those present in the resected tumor.
Data from Occupational Benzene Exposure and Cancer Risk among Chinese Men: A Report from the Shanghai Men’s Health Study
Authors: DeMoulin Douglas , Cai Hui , Vermeulen Roel , Zheng Wei , Lipworth Loren , Shu Xiao-Ou
Published: November 2024

AbstractBackground:
Benzene exposure has been associated with increased risk of leukemia and other cancers; however, epidemiologic evidence is inconsistent for the latter, and confounding from smoking and alcohol was rarely adjusted.
Methods:
We investigated associations between occupational benzene exposure and risk of leukemia, lymphoma, myeloma, and lung, stomach, liver, and kidney cancers in a population-based cohort of 61,377 men, ages 40 to 74 years. A job-exposure matrix, constructed by industrial hygienists specifically for the study population, was used to derive cumulative benzene exposure from all jobs held. Cox regressions were performed to estimate adjusted HRs (aHR) and 95% confidence intervals (CI) for benzene–cancer risk associations with adjustment for potential confounders.
Results:
Over 15 years of follow-up, 1,145 lung cancer, 656 stomach cancer, 445 liver cancer, 243 kidney cancer, 100 leukemia, 124 lymphoma, and 46 myeloma cases were identified. Benzene exposure >550 mg/m3 was associated with an increased risk of leukemia (aHR = 2.3; 95% CI, 1.1–4.5), lung cancer (aHR = 1.2; 95% CI, 1.0–1.6), and stomach cancer (aHR = 1.4; 95% CI, 1.0–1.9); benzene exposure was associated with early cancer diagnosis age. The benzene–leukemia and benzene–stomach cancer associations followed a linear dose–response pattern (Plinear = 0.016 and 0.023), whereas the benzene–lung cancer association was evident at higher exposure levels (Pnonlinear = 0.027). Alcohol consumption modified the benzene–leukemia association (aHR = 3.0; 95% CI, 1.1–8.3 for drinkers and aHR = 0.9; 95% CI, 0.4–2.0 for nondrinkers, Pinteraction = 0.047).
Conclusions:
Benzene exposure was associated with an increased risk of leukemia, stomach cancer, and lung cancer. Alcohol consumption may modify the benzene–leukemia association, although estimates are imprecise.
Impact:
Our study provides additional evidence that benzene exposure increases cancer risk beyond leukemia, information important for policymakers to develop programs to mitigate cancer risk among benzene-exposed workers.
Data from Recalibrating the Genetics and Epidemiology of Colorectal Cancer Consortium Environmental Risk Score for Use in US Veterans
Authors: Williams April R. , Redding Thomas S. , Sullivan Brian A. , Baidya Robin N. , Ear Belinda , Cho Kelly , Ivey Kerry L. , Williams Christina D. , Dominitz Jason A. , Lieberman David , Hauser Elizabeth R.
Published: November 2024

AbstractBackground:
Risk for colorectal cancer may accumulate through multiple environmental factors. Understanding their effects, along with genetics, age, and family history, could allow improvements in clinical decisions for screening protocols. We aimed to extend the previous work by recalibrating an environmental risk score (e-Score) for colorectal cancer among a sample of US veteran participants of the Million Veteran Program.
Methods:
Demographic, lifestyle, and colorectal cancer data from 2011 to 2022 were abstracted from survey responses and health records of 227,504 male Million Veteran Program participants. Weighting for each environmental factor’s effect size was recalculated using Veterans Affairs training data to create a recalibrated e-Score. This recalibrated score was compared with the original weighted e-Score in a validation sample of 113,752 (n cases = 590). Nested multiple logistic regression models tested associations between quintiles for recalibrated and original e-Scores. Likelihood ratio tests were used to compare model performance.
Results:
Age (P < 0.0001), education (P < 0.0001), diabetes (P < 0.0001), physical activity (P < 0.0001), smoking (P < 0.0001), NSAID use (P < 0.0001), calcium (P = 0.015), folate (P = 0.020), and fruit consumption (P = 0.019) were significantly different between colorectal cancer case and control groups. In the validation sample, the recalibrated e-Score model significantly improved the base model performance (P < 0.001), but the original e-Score model did not (P = 0.07). The recalibrated e-Score model quintile 5 was associated with significantly higher odds for colorectal cancer compared with quintile 1 (Q5 vs. Q1: 1.79; 95% CI, 1.38–2.33).
Conclusions:
Multiple environmental factors and the recalibrated e-Score quintiles were significantly associated with colorectal cancer cases.
Impact:
A recalibrated, veteran-specific e-Score could be used to help personalize colorectal cancer screening and prevention strategies.
Cancer Epidemiology in Hispanic Populations: Needs and Opportunities
Authors: Ishibe Naoko , Elena Joanne W. , Gallicchio Lisa , Kennedy Amy E. , Akif Kaitlin E. , Hanisch Rachel , Lai Gabriel Y. , Mahabir Somdat , Martin Damali N. , Pottinger Camille A. , Yu Catherine T. , Srinivasan Shobha , Lam Tram Kim
Published: November 2024

This report provides a summary of the identified evidence gaps and a general discussion of the next steps to advance cancer epidemiology research in Hispanic/Latino (H/L) populations based partly on the workshop, “Cancer Epidemiology in Hispanic Populations,” convened by the NCI in September 2021. The cancer burden among H/L populations varies greatly by nativity and country of origin, yet this variation is not often captured due to systemic challenges in how racial/ethnic data have been collected and often reported in aggregate for this heterogeneous population. Developing culturally relevant assessment tools, increasing the representation of H/L participants, and adopting appropriate methodologic approaches are critical to enhancing cancer research. There is a variety of current funding mechanisms that may be used to address these evidence gaps and priorities, including investigator-initiated mechanisms. Cancer epidemiologic research in H/L populations should leverage existing resources where possible. New and ongoing studies should collect information on nativity status, country of origin, and related measures, use culturally specific assessment tools, engage in collaborative science, and maintain strong community engagement to build studies that will meaningfully address the cancer burden experienced by the growing H/L population.
Supplementary Table 9 from Clinical and Genomic Features of Classical and Basal Transcriptional Subtypes in Pancreatic Cancer
Authors: Singh Harshabad , Xiu Joanne , Kapner Kevin S. , Yuan Chen , Narayan Raja R. , Oberley Matthew , Farrell Alex , Surana Rishi , Huffman Brandon M. , Perez Kimberly , Cleary James M. , Jordan Alexander C. , Dias Costa Andressa , Williams Hannah L. , Raghavan Srivatsan , Weinberg Benjamin , Pishvaian Michael J. , Shroff Rachna T. , Goel Sanjay , Dougan Stephanie K. , Nowak Jonathan A. , Spetzler David , Sledge George , Wolpin Brian M. , Aguirre Andrew J.
Published: November 2024

Supplementary Table 9