Literature DB >> 30936085

Breast Cancer Risk and Insulin Resistance: Post Genome-Wide Gene-Environment Interaction Study Using a Random Survival Forest.

Su Yon Jung1, Jeanette C Papp2, Eric M Sobel2, Herbert Yu3, Zuo-Feng Zhang4.   

Abstract

Obesity-insulin connections have been considered potential risk factors for postmenopausal breast cancer, and the association between insulin resistance (IR) genotypes and phenotypes can be modified by obesity-lifestyle factors, affecting breast cancer risk. In this study, we explored the role of IR in those pathways at the genome-wide level. We identified IR-genetic factors and selected lifestyles to generate risk profiles for postmenopausal breast cancer. Using large-scale cohort data from postmenopausal women in the Women's Health Initiative Database for Genotypes and Phenotypes Study, our previous genome-wide association gene-behavior interaction study identified 58 loci for associations with IR phenotypes (homeostatic model assessment-IR, hyperglycemia, and hyperinsulinemia). We evaluated those single-nucleotide polymorphisms (SNP) and additional 31 lifestyles in relation to breast cancer risk by conducting a two-stage multimodal random survival forest analysis. We identified the most predictive genetic and lifestyle variables in overall and subgroup analyses [stratified by body mass index (BMI), exercise, and dietary fat intake]. Two SNPs (LINC00460 rs17254590 and MKLN1 rs117911989), exogenous factors related to lifetime cumulative exposure to estrogen, BMI, and dietary alcohol consumption were the most common influential factors across the analyses. Individual SNPs did not have significant associations with breast cancer, but SNPs and lifestyles combined synergistically increased the risk of breast cancer in a gene-behavior, dose-dependent manner. These findings may contribute to more accurate predictions of breast cancer and suggest potential intervention strategies for women with specific genetic and lifestyle factors to reduce their breast cancer risk. SIGNIFICANCE: These findings identify insulin resistance SNPs in combination with lifestyle as synergistic factors for breast cancer risk, suggesting lifestyle changes can prevent breast cancer in women who carry the risk genotypes. ©2019 American Association for Cancer Research.

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Year:  2019        PMID: 30936085      PMCID: PMC6522308          DOI: 10.1158/0008-5472.CAN-18-3688

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  8 in total

1.  Association Between Triglyceride Glucose Index and Non-Small Cell Lung Cancer Risk in Chinese Population.

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Review 2.  Molecular Links between Central Obesity and Breast Cancer.

Authors:  Alina-Andreea Zimta; Adrian Bogdan Tigu; Maximilian Muntean; Diana Cenariu; Ondrej Slaby; Ioana Berindan-Neagoe
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3.  Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms.

Authors:  Wei Lu; Xiang Pan; Siqi Dai; Dongliang Fu; Maxwell Hwang; Yingshuang Zhu; Lina Zhang; Jingsun Wei; Xiangxing Kong; Jun Li; Qian Xiao; Kefeng Ding
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4.  Dynein and muskelin control myosin VI delivery towards the neuronal nucleus.

Authors:  Matthias Kneussel; Noelia Sánchez-Rodríguez; Michaela Mischak; Frank F Heisler
Journal:  iScience       Date:  2021-04-09

5.  The Association Between Triglyceride-Glucose Index as a Marker of Insulin Resistance and the Risk of Breast Cancer.

Authors:  Sonar Soni Panigoro; Noorwati Sutandyo; Fiastuti Witjaksono; Nurjati Chairani Siregar; Ramadhan Ramli; Ririn Hariani; Eko Adhi Pangarsa; Yan Wisnu Prajoko; Niken Puruhita; William Hamdani; Dimas Bayu; Mardiana Madjid; Dedy Yulidar; Jane Estherina Fransiska; Retno Widyawati; Effif Syofra Tripriadi; Wiwit Ade F W; Dewi Krisna Yunda; Raymond Pranata
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6.  Integrated Analysis of RNA Binding Protein-Related lncRNA Prognostic Signature for Breast Cancer Patients.

Authors:  Shaohua Xu; Jiahui Xie; Yanjie Zhou; Hui Liu; Yirong Wang; Zhaoyong Li
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7.  Development of an Electronic Frailty Index for Predicting Mortality and Complications Analysis in Pulmonary Hypertension Using Random Survival Forest Model.

Authors:  Jiandong Zhou; Oscar Hou In Chou; Ka Hei Gabriel Wong; Sharen Lee; Keith Sai Kit Leung; Tong Liu; Bernard Man Yung Cheung; Ian Chi Kei Wong; Gary Tse; Qingpeng Zhang
Journal:  Front Cardiovasc Med       Date:  2022-07-08

8.  Haplotype analysis on correlation between transcription factor 7-like 2 gene polymorphism and breast cancer risk.

Authors:  Yang Wang; Xiaojuan Men; Yongxue Gu; Huidong Wang; Zhicai Xu
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  8 in total

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