Continuation of Novel Dietary Index for Gut Microbiota and Associations with Colorectal Cancer and Breast Cancer Risk PLCO-730
Principal Investigator
Name
Susan Steck
Degrees
Ph.D., M.P.H.
Institution
University of South Carolina
Position Title
Professor
Email
ssteck@sc.edu
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-2029
Initial CDAS Request Approval
Mar 4, 2026
Title
Continuation of Novel Dietary Index for Gut Microbiota and Associations with Colorectal Cancer and Breast Cancer Risk PLCO-730
Summary
Background: Recent studies show that disturbances in the gut microbiota, microorganisms in the human intestine, are a link through which modifiable risk factors induce carcinogenesis of both the colon and breast.1–4 Disturbed gut microbiota, termed dysbiosis, increases the risk for colorectal and breast cancer through effects on inflammation, adiposity, oxidative stress, and estrogen metabolism.5,6 Diet is among the prominent determinants of gut microbiota composition and several health promoting and deleterious effects of diet are mediated by the gut microbiota.7–9 Although studies have investigated specific food components that promote or disturb gut microbiota diversity and balance,10–14 there is lack of dietary patterns or indices that define the ideal metabolic requirements of the gut microbiota, which, when met, could result in a suppression of colorectal and breast cancer risk. We developed a novel dietary index for gut microbiota (DI-GM) based on extensive literature review that scores an individual’s diet quality based on its potential to increase gut microbiota diversity and minimize dysbiosis. Our aim is to utilize the data from PLCO to examine the association of the novel DI-GM and risk of colorectal and breast cancers. Since gut microbiota are involved in estrogen metabolism, we will also explore the association between the DI-GM and serum estrogen metabolite levels among the subset of PLCO female participants with these data.
Method: The main exposure, the DI-GM will be calculated using dietary data from the PLCO diet history questionnaire (DHQ) along with existing dietary indices (Healthy Eating Index (HEI) and Mediterranean Diet Score (MDS)). The primary outcomes will be incident colorectal cancer and incident breast cancer. We will examine both continuous DI-GM and categorical DI-GM variables, exploring quartiles of DI-GM. Cox proportional hazards models will be used to estimate HRs and 95% confidence intervals (CIs) to evaluate the relationships of DI-GM with colorectal and breast cancer risk. Subgroup analyses will be conducted to explore whether associations differ by breast cancer subtypes. Linear regression will be used to examine the association between the DI-GM and estrogen metabolite levels. Adjustment will be done for potential confounders.
Significance: The findings can lay groundwork for future intervention studies that focus on dietary modulation of gut microbiota to prevent and improve prognosis of colorectal and breast cancers.
Reference
1. Chen J, et al. Breast Cancer Res Treat. 2019;178(3):493-496.
2. Mani S. In: Progress in Molecular Biology and Translational Science. Vol 151. Elsevier B.V.; 2017:217-229.
3. Yang J, Yu J. Protein Cell. 2018;9(5):474-487.
4. Borges-Canha M, et al. Rev Esp Enfermedades Dig. 2015;107(11):659-671.
5. Gagnière J, et al. World J Gastroenterol. 2016;22(2):501-518.
6. Komorowski AS, Pezo RC. Breast Cancer Res Treat. 2020;179(2):287-300. doi:10.1007/s10549-019-05472-w
7. O’Keefe SJD. Nat Rev Gastroenterol Hepatol. 2016;13(12):691-706.
8. Vipperla K, O’Keefe SJ. Food Funct. 2016;7(4):1731-1740.
9. Power SE, et al. Br J Nutr. 2014;111(3):387-402.
10. Tindall AM, et al. J Nutr. 2018;148(9):1402-1407.
11. Hasan N, Yang H. PeerJ. 2019;2019(8).
12. Valdes AM, et al. BMJ. 2018;361:36-44.
13. O’Keefe SJD, et al. Nat Commun. 2015;6.
14. Nguyen LH, et al. Gastroenterology. 2020;158(5):1313-1325.
Aims
1. Calculate the DI-GM, Healthy Eating Index, Mediterranean Diet Score, using food frequency questionnaire data in the PLCO.
2. Examine the association of the dietary patterns/indices and risk of colorectal cancer. Cox proportional hazards models will be used to estimate HRs and 95% confidence intervals to evaluate the relationships of the dietary patterns/indices with colorectal cancer risk.
3. Examine the association of the dietary patterns/indices and risk of breast cancer. Cox proportional hazards models will be used to estimate HRs and 95% confidence intervals to evaluate the relationships of the dietary patterns/indices with breast cancer risk.
3a. Examine whether the association between the DI-GM and breast cancer risk vary by breast cancer subtypes
3b. Investigate the association between the DI-GM and blood level of estrogen metabolites
Collaborators
Bezawit Kase South Carolina Department of Public Health