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Approved Research

Investigating the genetic, environmental and clinical determinants and their interactions on cancer risk, and developing risk prediction and prognosis models for common cancer types

Principal Investigator: Dr Xue Li
Approved Research ID: 66354
Approval date: January 12th 2021

Lay summary

Cancer has caused a considerable burden worldwide, accounting for about 1 in every 6 deaths worldwide. It is urgently important to develop the early prevention and control of common cancer risk. It has been recognized that complex mechanisms driven by a combination of genetic, environmental and lifestyle factors contribute to the etiology of diverse cancer risk. The extensive information from the large dataset on both environmental exposures and genomics data could be very helpful for individual risk prediction and early intervention for cancers prevention. Additionally, the baseline clinical characteristics, treatment choice, environmental factors, and individual genetic variations may result in the different prognosis of cancer.

We proposed this study  to address a series of research questions in relation to cancer risk, prognosis and survival. This specific aims include: 1) to fill in gaps in knowledge about factors related to cancer etiology, prognosis and survival, including genetic predisposition, environmental exposures such as smoking, physical and sedentary activity, diet, alcohol, excess body weight,  circadian rhythm disruption, pollutants, etc., and other predictors including medical conditions and common medications; 2) to improve understanding of the molecular epidemiology of cancer, with a focus on breast, colorectal, lung, pancreatic and prostate cancers, through studies of circulating biomarkers, genetic factors and gene-environmental interactions, and tumor heterogeneity; 3) to apply machine learning algorithms and employ the identified contributable risk factors to develop risk prediction and prognosis models for common cancer types. Our study would be beneficial for population screening and personalized treatment through comprehensively investigating the risk factors associated with the cancer risk and prognosis.