Integrative analysis from multi‐centre studies identifies a function‐derived personalized multi‐gene signature of outcome in colorectal cancer. Issue 8 (29th May 2019)

• Record Type: Journal Article
• Authors: Sun, Jie; Zhao, Hengqiang; Lin, Shuting; Bao, Siqi; Zhang, Yan; Su, Jianzhong; Zhou, Meng
• Is Part Of: Journal of cellular and molecular medicine. Volume 23:Issue 8(2019)
• Page Start: 5270
• Page End: 5281
• Publication Date: 2019-05-29
• Subjects: colorectal cancer -- integrative analysis -- personalized gene signature; Cytology; Medicine; Molecular Biology; Cytologie -- Périodiques; Médecine -- Périodiques; Biologie moléculaire -- Périodiques; Cytology -- Periodicals; Medicine -- Periodicals; Molecular biology -- Periodicals; 611.01805
• DOI: 10.1111/jcmm.14403
• Languages: English
• ISSNs: 1582-1838

Abstract

Abstract: Colorectal cancer (CRC) is highly heterogeneous leading to variable prognosis and treatment responses. Therefore, it is necessary to explore novel personalized and reproducible prognostic signatures to aid clinical decision‐making. The present study combined large‐scale gene expression profiles and clinical data of 1828 patients with CRC from multi‐centre studies and identified a personalized gene prognostic signature consisting of 46 unique genes (called function‐derived personalized gene signature [FunPGS]) from an integrated statistics and function‐derived perspective. In the meta‐training and multiple independent validation cohorts, the FunPGS effectively discriminated patients with CRC with significantly different prognosis at the individual level and remained as an independent factor upon adjusting for clinical covariates in multivariate analysis. Furthermore, the FunPGS demonstrated superior performance for risk stratification with respect to other recently reported signatures and clinical factors. The complementary value of the molecular signature and clinical factors was further explored, and it was observed that the composite signature called IMCPS greatly improved the predictive performance of survival estimation relative to molecular signatures or clinical factors alone. With further prospective validation in clinical trials, the FunPGS may become a promising and powerful personalized prognostic tool for stratifying patients with CRC in order to achieve an optimal systemic therapy.