Frontiers in Genetics (Jul 2021)

Identification and Validation of a Four-Long Non-coding RNA Signature Associated With Immune Infiltration and Prognosis in Colon Cancer

  • Yanbo Wang,
  • Jing Liu,
  • Fenghai Ren,
  • Yanjie Chu,
  • Binbin Cui

DOI
https://doi.org/10.3389/fgene.2021.671128
Journal volume & issue
Vol. 12

Abstract

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The emerging evidence has demonstrated the critical roles of long non-coding RNAs (lncRNAs) as regulators in the tumor immune microenvironment (TIME). However, the tumor immune infiltration-associated lncRNAs and their clinical significance in colon cancer have not yet been thoroughly investigated. This study performed an integrative analysis of lncRNA expression profiles and immune cell infiltration profiles and identified 258 immune infiltration-associated lncRNAs. Of them, four lncRNAs (AC008494.3, LINC00926, AC022034.1, and SNHG26) were significantly and independently associated with the patient’s overall survival. Finally, we developed a tumor immune infiltration-associated lncRNA signature (TIILncSig) comprising of these four lncRNAs, which can divide colon cancer patients of The Cancer Genome Atlas (TCGA) into high-risk and low-risk groups with a significantly different outcome [Hazard ratio (HR) = 2.718, 95% CI = 1.955–3.779, p < 0.001]. Prognostic performance of the TIILncSig was further validated in another independent colon cancer cohort (HR = 1.832, 95% CI = 1.045–3.21, p = 0.034). Results of multivariate Cox regression and stratification analysis demonstrated that the TIILncSig is an independent predictive factor from other clinical features (HR = 2.687, 95% CI = 1.912–3.776, p < 0.001 for TCGA cohort and HR = 1.837, 95% CI = 1.047–3.223, p = 0.034 for GSE17538 cohort). Literature analysis provided experimental evidence supporting roles of the TIILncSig in cancer carcinogenesis and progression and immune regulation. Summary, our study will help to understand the mechanisms of lncRNAs in immune regulation in the tumor microenvironment and provide novel biomarkers or targets for prognosis prediction and therapy decision-making for patients with colon cancer.

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