Integration of pathologic characteristics, genetic risk and lifestyle exposure for colorectal cancer survival assessment

Junyi Xin; Dongying Gu; Shuwei Li; Sangni Qian; Yifei Cheng; Wei Shao; Shuai Ben; Silu Chen; Linjun Zhu; Mingjuan Jin; Kun Chen; Zhibin Hu; Zhengdong Zhang; Mulong Du; Hongbing Shen; Meilin Wang

doi:10.1038/s41467-024-47204-9

Integration of pathologic characteristics, genetic risk and lifestyle exposure for colorectal cancer survival assessment

Nat Commun. 2024 Apr 8;15(1):3042. doi: 10.1038/s41467-024-47204-9.

Authors

Junyi Xin^#^{1

2

3}, Dongying Gu^#⁴, Shuwei Li^#^{2

3}, Sangni Qian^#^{5

6}, Yifei Cheng^{2

3}, Wei Shao^{2

3}, Shuai Ben^{2

3}, Silu Chen^{2

3}, Linjun Zhu⁷, Mingjuan Jin^{5

6}, Kun Chen^{5

6}, Zhibin Hu⁸, Zhengdong Zhang^{2

3}, Mulong Du⁹, Hongbing Shen⁸, Meilin Wang^{10

11

12}

Affiliations

¹ Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.
² Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
³ Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
⁴ Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
⁵ Department of Epidemiology and Biostatistics at School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
⁶ Cancer Institute, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
⁷ Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
⁸ Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
⁹ Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
¹⁰ Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China. mwang@njmu.edu.cn.
¹¹ Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. mwang@njmu.edu.cn.
¹² The Affiliated Suzhou Hospital of, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China. mwang@njmu.edu.cn.

^# Contributed equally.

Abstract

The development of an effective survival prediction tool is key for reducing colorectal cancer mortality. Here, we apply a three-stage study to devise a polygenic prognostic score (PPS) for stratifying colorectal cancer overall survival. Leveraging two cohorts of 3703 patients, we first perform a genome-wide survival association analysis to develop eight candidate PPSs. Further using an independent cohort with 470 patients, we identify the 287 variants-derived PPS (i.e., PPS₂₈₇) achieving an optimal prediction performance [hazard ratio (HR) per SD = 1.99, P = 1.76 × 10^-8], accompanied by additional tests in two external cohorts, with HRs per SD of 1.90 (P = 3.21 × 10^-14; 543 patients) and 1.80 (P = 1.11 × 10^-9; 713 patients). Notably, the detrimental impact of pathologic characteristics and genetic risk could be attenuated by a healthy lifestyle, yielding a 7.62% improvement in the 5-year overall survival rate. Therefore, our findings demonstrate the integrated contribution of pathologic characteristics, germline variants, and lifestyle exposure to the prognosis of colorectal cancer patients.

MeSH terms

Colorectal Neoplasms* / pathology
Humans
Life Style
Proportional Hazards Models
Risk Factors
Survival Rate

Abstract

MeSH terms

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