CoSMeD

CoSMeD estimates 5-year survival probability for left-sided and right-sided colorectal cancer patients using molecular data.


Key Features:

  • Multi-Omics Data Integration: Integrates gene expression, DNA methylation, and microRNA expression data from The Cancer Genome Atlas (TCGA).
  • Prognostic Biomarker Identification: Identifies side-specific prognostic biomarkers (6 for left-sided and 28 for right-sided colorectal cancer) using specificity measures and robust likelihood-based survival analysis to predict 5-year survival.
  • External Validation: Validates the prognostic value of identified side-specific genes using additional datasets from the Gene Expression Omnibus (GEO).
  • Integration with Clinical Data: Combines molecular biomarkers with clinical data to improve discriminatory ability and calibration of side-specific 5-year survival predictions.

Scientific Applications:

  • Survival Prognostication: Provides molecularly informed 5-year survival probability estimates for left- and right-sided colorectal cancer patients.
  • Side-Specific Biomarker Research: Enables investigation of molecular differences between left-sided and right-sided colorectal cancer through identified gene sets.
  • Personalized Treatment Stratification: Supports development of individualized treatment protocols by integrating side-specific molecular biomarkers with clinical information.

Methodology:

Integrates TCGA gene expression, DNA methylation, and microRNA expression data; applies specificity measures and robust likelihood-based survival analysis to identify prognostic biomarkers; validates prognostic genes using GEO datasets.

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
11/23/2021
Last Updated:
11/23/2021

Operations

Publications

Xin J, Wu Y, Ben S, Li S, Chu H, Wang M, Wang M, Song M, Du M, Zhang Z. CoSMeD: a user-friendly web server to estimate 5-year survival probability of left-sided and right-sided colorectal cancer patients using molecular data. Bioinformatics. 2021;38(1):278-281. doi:10.1093/bioinformatics/btab523. PMID:34260718.

PMID: 34260718
Funding: - Natural Science Foundation of Jiangsu Province: BK20181371 - Natural Science Foundation of the Jiangsu Higher Education Institutions of China: 17KJB330003