A prognostic index based on an eleven gene signature to predict systemic recurrences in colorectal cancer

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A prognostic index based on an eleven gene signature to predict systemic recurrences in colorectal cancer
Seon-Kyu KimSeon-Young Kim; C W Kim; S A Roh; Y J Ha; J L Lee; H Heo; D H Cho; J S Lee; Yong Sung Kim; J C Kim
Bibliographic Citation
Experimental and Molecular Medicine, vol. 51, no. 10, pp. 115-115
Publication Year
Approximately half of colorectal cancer (CRC) patients experience disease recurrence and metastasis, and these individuals frequently fail to respond to treatment due to their clinical and biological diversity. Here, we aimed to identify a prognostic signature consisting of a small gene group for precisely predicting CRC heterogeneity. We performed transcriptomic profiling using RNA-seq data generated from the primary tissue samples of 130 CRC patients. A prognostic index (PI) based on recurrence-associated genes was developed and validated in two larger independent CRC patient cohorts (n=795). The association between the PI and prognosis of CRC patients was evaluated using Kaplan?Meier plots, log-rank tests, a Cox regression analysis and a RT-PCR analysis. Transcriptomic profiling in 130 CRC patients identified two distinct subtypes associated with systemic recurrence. Pathway enrichment and RT-PCR analyses revealed an eleven gene signature incorporated into the PI system, which was a significant prognostic indicator of CRC. Multivariate and subset analyses showed that PI was an independent risk factor (HR=1.812, 95% CI=1.342-2.448, P<0.001) with predictive value to identify low-risk stage II patients who responded the worst to adjuvant chemotherapy. Finally, a comparative analysis with previously reported Consensus Molecular Subgroup (CMS), high-risk patients classified by the PI revealed a distinct molecular property similar to CMS4, associated with a poor prognosis. This novel PI predictor based on an eleven gene signature likely represents a surrogate diagnostic tool for identifying high-risk CRC patients and for predicting the worst responding patients for adjuvant chemotherapy.
Springer-Nature Pub Group
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Division of Biomedical Research > Personalized Genomic Medicine Research Center > 1. Journal Articles
Korea Bioinformation Center > 1. Journal Articles
Division of Biomedical Research > Genome Editing Research Center > 1. Journal Articles
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