In Silico Identification and Validation of Cuproptosis-Related LncRNA Signature as a Novel Prognostic Model and Immune Function Analysis in Colon Adenocarcinoma

Curr Oncol. 2022 Sep 15;29(9):6573-6593. doi: 10.3390/curroncol29090517.

Abstract

Background: Colon adenocarcinoma (COAD) is the most common subtype of colon cancer, and cuproptosis is a recently newly defined form of cell death that plays an important role in the development of several malignant cancers. However, studies of cuproptosis-related lncRNAs (CRLs) involved in regulating colon adenocarcinoma are limited. The purpose of this study is to develop a new prognostic CRLs signature of colon adenocarcinoma and explore its underlying biological mechanism. Methods: In this study, we downloaded RNA-seq profiles, clinical data and tumor mutational burden (TMB) data from the TCGA database, identified cuproptosis-associated lncRNAs using univariate Cox, lasso regression analysis and multivariate Cox analysis, and constructed a prognostic model with risk score based on these lncRNAs. COAD patients were divided into high- and low-risk subgroups based on the risk score. Cox regression was also used to test whether they were independent prognostic factors. The accuracy of this prognostic model was further validated by receiver operating characteristic curve (ROC), C-index and Nomogram. In addition, the lncRNA/miRNA/mRNA competing endogenous RNA (ceRNA) network and protein−protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). Results: We constructed a prognostic model based on 15 cuproptosis-associated lncRNAs. The validation results showed that the risk score of the model (HR = 1.003, 95% CI = 1.001−1.004; p < 0.001) could serve as an independent prognostic factor with accurate and credible predictive power. The risk score had the highest AUC (0.793) among various factors such as risk score, stage, gender and age, also indicating that the model we constructed to predict patient survival was better than other clinical characteristics. Meanwhile, the possible biological mechanisms of colon adenocarcinoma were explored based on the lncRNA/miRNA/mRNA ceRNA network and PPI network constructed by WGCNA. Conclusion: The prognostic model based on 15 cuproptosis-related lncRNAs has accurate and reliable predictive power to effectively predict clinical outcomes in colon adenocarcinoma patients.

Keywords: colon adenocarcinoma; cuproptosis; lncRNA; prognostic model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adenocarcinoma* / pathology
  • Apoptosis*
  • Colonic Neoplasms* / genetics
  • Colonic Neoplasms* / pathology
  • Copper
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans
  • Immunity
  • MicroRNAs* / genetics
  • MicroRNAs* / metabolism
  • Prognosis
  • RNA, Long Noncoding* / genetics
  • RNA, Long Noncoding* / metabolism
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism

Substances

  • MicroRNAs
  • RNA, Long Noncoding
  • RNA, Messenger
  • Copper

Grants and funding

This research was funded by Xinglin Scholars Discipline Talent Research Promotion Plan (Grant No. CXTD2018003) and Xinglin Scholar Research Promotion Project of Chengdu University of TCM (Grant No. 030055037).