Abstract
BackgroundThe pathological stage of colon cancer cannot accurately predict recurrence, and to date, no gene expression characteristics have been demonstrated to be reliable for prognostic stratification in clinical practice, perhaps because colon cancer is a heterogeneous disease. The purpose was to establish a comprehensive molecular classification and prognostic marker for colon cancer based on invasion-related expression profiling.MethodsFrom the Gene Expression Omnibus (GEO) database, we collected two microarray datasets of colon cancer samples, and another dataset was obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) further underwent univariate analysis, least absolute shrinkage, selection operator (LASSO) regression analysis, and multivariate Cox survival analysis to screen prognosis-associated feature genes, which were further verified with test datasets.ResultsTwo molecular subtypes (C1 and C2) were identified based on invasion-related genes in the colon cancer samples in TCGA training dataset, and C2 had a good prognosis. Moreover, C1 was more sensitive to immunotherapy. A total of 1,514 invasion-related genes, specifically 124 downregulated genes and 1,390 upregulated genes in C1 and C2, were identified as DEGs. A four-gene prognostic signature was identified and validated, and colon cancer patients were stratified into a high-risk group and a low-risk group. Multivariate regression analyses and a nomogram indicated that the four-gene signature developed in this study was an independent predictive factor and had a relatively good predictive capability when adjusting for other clinical factors.ConclusionThis research provided novel insights into the mechanisms underlying invasion and offered a novel biomarker of a poor prognosis in colon cancer patients.
Highlights
Colon cancer, which is a malignant tumor of the digestive tract derived from the mucosal epithelium of the colon or rectum, has become the third most frequent cancer among men and the second most frequent cancer among women worldwide (Arnold et al, 2017; Althobaiti and Jradi, 2019)
Univariate Cox survival analysis was performed on the expression profiles of 1,132 invasion-related genes using the Coxph function of the R package survival (V3.1–12), and 56 genes were identified to be associated with the prognosis of colon cancer (p < 0.01)
The 56 prognostic genes were used to cluster TCGA samples with the R package NMF (K = 2–10), and TCGA samples were classified into a C1 or C2 category according to the clustering results (Figure 2A)
Summary
Colon cancer, which is a malignant tumor of the digestive tract derived from the mucosal epithelium of the colon or rectum, has become the third most frequent cancer among men and the second most frequent cancer among women worldwide (Arnold et al, 2017; Althobaiti and Jradi, 2019). Progresses rapidly, and has a poor prognosis and Invasion-Related Genes in CRC high mortality rate. There are many treatments available to prolong the survival of patients with advanced disease, and surgery is the main treatment for colon cancer, but the 5-year survival rate is 50% (Zhai et al, 2017). Biomarkers have been used as common tools for disease detection and prognosis management in colon cancer patients (Juo et al, 2014). The pathological stage of colon cancer cannot accurately predict recurrence, and to date, no gene expression characteristics have been demonstrated to be reliable for prognostic stratification in clinical practice, perhaps because colon cancer is a heterogeneous disease. The purpose was to establish a comprehensive molecular classification and prognostic marker for colon cancer based on invasionrelated expression profiling
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
