期刊
CANCER MEDICINE
卷 12, 期 6, 页码 7603-7615出版社
WILEY
DOI: 10.1002/cam4.5420
关键词
biomarkers; clinical outcome; colon cancer; in silico system analysis; machine learning; survival prediction model
类别
This study identified genomic prognostic biomarkers for colon cancer and developed survival prediction models using machine learning and in silico system analysis. The expression of three candidate genes, RABGAP1L, MYH9, and DRD4, showed higher predictive performance for the prognosis of colon cancer patients. Functional analyses and validation with clinical data confirmed the clinical relevance of these genes. The survival prediction approach of this study can provide information on patients and aid in developing therapeutic strategies for colon cancer patients.
Background Predicting the survival of cancer patients provides prognostic information and therapeutic guidance. However, improved prediction models are needed for use in diagnosis and treatment. Objective This study aimed to identify genomic prognostic biomarkers related to colon cancer (CC) based on computational data and to develop survival prediction models. Methods We performed machine-learning (ML) analysis to screen pathogenic survival-related driver genes related to patient prognosis by integrating copy number variation and gene expression data. Moreover, in silico system analysis was performed to clinically assess data from ML analysis, and we identified RABGAP1L, MYH9, and DRD4 as candidate genes. These three genes and tumor stages were used to generate survival prediction models. Moreover, the genes were validated by experimental and clinical analyses, and the theranostic application of the survival prediction models was assessed. Results RABGAP1L, MYH9, and DRD4 were identified as survival-related candidate genes by ML and in silico system analysis. The survival prediction model using the expression of the three genes showed higher predictive performance when applied to predict the prognosis of CC patients. A series of functional analyses revealed that each knockdown of three genes reduced the protumor activity of CC cells. In particular, validation with an independent cohort of CC patients confirmed that the coexpression of MYH9 and DRD4 gene expression reflected poorer clinical outcomes in terms of overall survival and disease-free survival. Conclusions Our survival prediction approach will contribute to providing information on patients and developing a therapeutic strategy for CC patients.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据