Dataset Information

A nineteen gene-based risk score classifier predicts prognosis of colorectal cancer patients.

ABSTRACT: Colorectal cancer (CRC) patients frequently experience disease recurrence and distant metastasis. This study aimed to identify prognostic indicators, including individual responses to chemotherapy, in CRC patients. RNA-seq data was generated using 54 samples (normal colon, primary CRC, and liver metastases) from 18 CRC patients and genes associated with CRC aggressiveness were identified. A risk score based on these genes was developed and validated in four independent CRC patient cohorts (n = 1063). Diverse statistical methods were applied to validate the risk scoring system, including a generalized linear model likelihood ratio test, Kaplan-Meier curves, a log-rank test, and the Cox model. TREM1 and CTGF were identified as two activated regulators associated with CRC aggressiveness. A risk score based on 19 genes regulated by TREM1 or CTGF activation (TCA19) was a significant prognostic indicator. In multivariate and subset analyses based on pathological staging, TCA19 was an independent risk factor (HR = 1.894, 95% CI = 1.227-2.809, P = 0.002). Subset stratification in stage III patients revealed that TCA19 had prognostic potential and identified patients who would benefit from adjuvant chemotherapy, regardless of age. The TCA19 predictor represents a novel diagnostic tool for identifying high-risk CRC patients and possibly predicting the response to adjuvant chemotherapy.

SUBMITTER: Kim SK

PROVIDER: S-EPMC5528589 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A nineteen gene-based risk score classifier predicts prognosis of colorectal cancer patients.

Kim Seon-Kyu SK Kim Seon-Young SY Kim Jeong-Hwan JH Roh Seon Ae SA Cho Dong-Hyung DH Kim Yong Sung YS Kim Jin Cheon JC

Molecular oncology 20140704 8

Colorectal cancer (CRC) patients frequently experience disease recurrence and distant metastasis. This study aimed to identify prognostic indicators, including individual responses to chemotherapy, in CRC patients. RNA-seq data was generated using 54 samples (normal colon, primary CRC, and liver metastases) from 18 CRC patients and genes associated with CRC aggressiveness were identified. A risk score based on these genes was developed and validated in four independent CRC patient cohorts (n = 1 ...[more]

PMID: 25049118

Similar Datasets

Project description:Objective: Immunity plays a vital role in the human papilloma virus (HPV) persistent infection, and closely associates with occurrence and development of cervical squamous cell carcinoma (CSCC). Herein, we performed an integrated bioinformatics analysis to establish an immune-gene signature and immune-associated nomogram for predicting prognosis of CSCC patients. Methods: The list of immunity-associated genes was retrieved from ImmPort database. The gene and clinical information of CSCC patients were obtained from The Cancer Genome Atlas (TCGA) website. The immune gene signature for predicting overall survival (OS) of CSCC patients was constructed using the univariate Cox-regression analysis, random survival forests, and multivariate Cox-regression analysis. This signature was externally validated in GSE44001 cohort from Gene Expression Omnibus (GEO). Then, based on the established signature and the TCGA cohort with the corresponding clinical information, a nomogram was constructed and evaluated via Cox regression analysis, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots and decision curve analyses (DCAs). Results: A 5-immune-gene prognostic signature for CSCC was established. Low expression of ICOS, ISG20 and high expression of ANGPTL4, SBDS, LTBR were risk factors for CSCC prognosis indicating poor OS. Based on this signature, the OS was significantly worse in high-risk group than in low-risk group (p-value < 0.001), the area under curves (AUCs) for 1-, 3-, 5-years OS were, respectively, 0.784, 0.727, and 0.715. A nomogram incorporating the risk score of signature and the clinical stage was constructed. The C-index of this nomogram was 0.76. AUC values were 0.811, 0.717, and 0.712 for 1-, 3-, 5-years OS. The nomogram showed good calibration and gained more net benefits than the 5-immune-gene signature and the clinical stage. Conclusion: The 5-immune-gene signature may serve as a novel, independent predictor for prognosis in patients with CSCC. The nomogram incorporating the signature risk score and clinical stage improved the predictive performance than the signature and clinical stage alone for predicting 1-year OS.

Dataset Information

A nineteen gene-based risk score classifier predicts prognosis of colorectal cancer patients.

Publications

A nineteen gene-based risk score classifier predicts prognosis of colorectal cancer patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets