Literature DB >> 30649085

The effects of genetic variants related to insulin metabolism pathways and the interactions with lifestyles on colorectal cancer risk.

Su Yon Jung1, Zuo-Feng Zhang2.   

Abstract

OBJECTIVES: Genetic variants in metabolic signaling pathways may interact with lifestyle factors, such as dietary fatty acids, influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood.
METHODS: In this study, we examined 54 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I/insulin traits and their signaling pathways and lifestyle factors in relation to postmenopausal CRC, using data from 6,539 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies. By employing a two-stage random survival forest analysis, we evaluated the SNPs and lifestyle factors by ranking them according to their predictive value and accuracy for CRC.
RESULTS: We identified four SNPs (IRS1 rs1801123, IRS1 rs1801278, AKT2 rs3730256, and AKT2 rs7247515) and two lifestyle factors (age and percentage calories from saturated fatty acids) as the top six most influential predictors for CRC risk. We further examined interactive effects of those factors on cancer risk. In the individual SNP analysis, no significant association was observed, but the combination of the four SNPs, age, and percentage calories from saturated fatty acid (≥11% per day) significantly increased the risk of CRC in a gene and lifestyle dose-dependent manner.
CONCLUSIONS: Our findings provide insight into gene-lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. Our study suggests the careful use of data on potential genetic targets in clinical trials for cancer prevention to reduce the risk for CRC in postmenopausal women.

Entities:  

Year:  2019        PMID: 30649085      PMCID: PMC7035960          DOI: 10.1097/GME.0000000000001301

Source DB:  PubMed          Journal:  Menopause        ISSN: 1072-3714            Impact factor:   2.953


  43 in total

1.  Machine learning models in breast cancer survival prediction.

Authors:  Mitra Montazeri; Mohadeseh Montazeri; Mahdieh Montazeri; Amin Beigzadeh
Journal:  Technol Health Care       Date:  2016       Impact factor: 1.285

2.  Evaluating Random Forests for Survival Analysis using Prediction Error Curves.

Authors:  Ulla B Mogensen; Hemant Ishwaran; Thomas A Gerds
Journal:  J Stat Softw       Date:  2012-09       Impact factor: 6.440

3.  Single nucleotide polymorphisms in the IGF-IRS pathway are associated with outcome in mCRC patients enrolled in the FIRE-3 trial.

Authors:  Marta Schirripa; Wu Zhang; Volker Heinemann; Shu Cao; Satoshi Okazaki; Dongyun Yang; Fotios Loupakis; Martin D Berger; Yan Ning; Yuji Miyamoto; Mitsukuni Suenaga; Roel F Gopez; Jordan D West; Diana Hanna; Afsaneh Barzi; Alfredo Falcone; Sebastian Stintzing; Heinz-Josef Lenz
Journal:  Int J Cancer       Date:  2017-05-10       Impact factor: 7.396

4.  A longitudinal study of the metabolic syndrome and risk of colorectal cancer in postmenopausal women.

Authors:  Geoffrey C Kabat; Mimi Y Kim; Ulrike Peters; Marcia Stefanick; Lifang Hou; Jean Wactawski-Wende; Catherine Messina; James M Shikany; Thomas E Rohan
Journal:  Eur J Cancer Prev       Date:  2012-07       Impact factor: 2.497

Review 5.  Insulin-like growth factor 2 in development and disease: a mini-review.

Authors:  Daniel Bergman; Matilda Halje; Matilda Nordin; Wilhelm Engström
Journal:  Gerontology       Date:  2012-12-20       Impact factor: 5.140

6.  Association between insulin receptor substrate 1 Gly972Arg polymorphism and cancer risk.

Authors:  Hongtuan Zhang; Andi Wang; Hui Ma; Yong Xu
Journal:  Tumour Biol       Date:  2013-05-25

7.  Insulin, insulin-like growth factor-I, endogenous estradiol, and risk of colorectal cancer in postmenopausal women.

Authors:  Marc J Gunter; Donald R Hoover; Herbert Yu; Sylvia Wassertheil-Smoller; Thomas E Rohan; JoAnn E Manson; Barbara V Howard; Judith Wylie-Rosett; Garnet L Anderson; Gloria Y F Ho; Robert C Kaplan; Jixin Li; Xiaonan Xue; Tiffany G Harris; Robert D Burk; Howard D Strickler
Journal:  Cancer Res       Date:  2008-01-01       Impact factor: 12.701

8.  Modification of the associations between lifestyle, dietary factors and colorectal cancer risk by APC variants.

Authors:  Evropi Theodoratou; Harry Campbell; Albert Tenesa; Geraldine McNeill; Roseanne Cetnarskyj; Rebecca A Barnetson; Mary E Porteous; Malcolm G Dunlop; Susan M Farrington
Journal:  Carcinogenesis       Date:  2008-03-28       Impact factor: 4.944

9.  Body size, physical activity, early-life energy restriction, and associations with methylated insulin-like growth factor-binding protein genes in colorectal cancer.

Authors:  Colinda C J M Simons; Piet A van den Brandt; Coen D A Stehouwer; Manon van Engeland; Matty P Weijenberg
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-06-27       Impact factor: 4.254

10.  Novel insulin receptor substrate 1 and 2 variants in breast and colorectal cancer.

Authors:  Diana Liberata Esposito; Fabio Verginelli; Sonia Toracchio; Sandra Mammarella; Laura De Lellis; Cinzia Vanni; Antonio Russo; Renato Mariani-Costantini; Alessandro Cama
Journal:  Oncol Rep       Date:  2013-07-18       Impact factor: 3.906

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  4 in total

1.  Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review.

Authors:  Luke McGeoch; Catherine L Saunders; Simon J Griffin; Jon D Emery; Fiona M Walter; Deborah J Thompson; Antonis C Antoniou; Juliet A Usher-Smith
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-07-10       Impact factor: 4.254

2.  Therapeutic Efficacy Evaluation of Pegylated Liposome Encapsulated With Vinorelbine Plus 111In Repeated Treatments in Human Colorectal Carcinoma With Multimodalities of Molecular Imaging.

Authors:  Yi-Chun Chien; Ying-Hsiang Chou; Wei-Hsun Wang; John Chun-Hao Chen; Wen-Shin Chang; Chia-Wen Tsai; DA-Tian Bau; Jeng-Jong Hwang
Journal:  Cancer Genomics Proteomics       Date:  2020 Jan-Feb       Impact factor: 4.069

3.  Night-Shift Work Duration and Risk of Colorectal Cancer According to IRS1 and IRS2 Expression.

Authors:  Yan Shi; Li Liu; Eva S Schernhammer; Reiko Nishihara; Xuehong Zhang; Tsuyoshi Hamada; Jonathan A Nowak; Marios Giannakis; Yanan Ma; Mingyang Song; Daniel Nevo; Keisuke Kosumi; Mancang Gu; Sun A Kim; Teppei Morikawa; Kana Wu; Jing Sui; Kyriaki Papantoniou; Molin Wang; Andrew T Chan; Charles S Fuchs; Jeffrey A Meyerhardt; Edward Giovannucci; Shuji Ogino
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-10-30       Impact factor: 4.254

4.  Polygenic risk prediction models for colorectal cancer: a systematic review.

Authors:  Michele Sassano; Marco Mariani; Gianluigi Quaranta; Roberta Pastorino; Stefania Boccia
Journal:  BMC Cancer       Date:  2022-01-15       Impact factor: 4.430

  4 in total

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