Based on cuproptosis-related lncRNAs, a novel prognostic signature for colon adenocarcinoma prognosis, immunotherapy, and chemotherapy response

Chong Li; Keqian Zhang; Yuzhu Gong; Qinan Wu; Yanyan Zhang; Yan Dong; Dejia Li; Zhe Wang

doi:10.3389/fphar.2023.1200054

Based on cuproptosis-related lncRNAs, a novel prognostic signature for colon adenocarcinoma prognosis, immunotherapy, and chemotherapy response

Front Pharmacol. 2023 Jun 12:14:1200054. doi: 10.3389/fphar.2023.1200054. eCollection 2023.

Authors

Chong Li^{1

2}, Keqian Zhang³, Yuzhu Gong³, Qinan Wu⁴, Yanyan Zhang², Yan Dong³, Dejia Li¹, Zhe Wang³

Affiliations

¹ Department of Occupational and Environmental Health, School of Public Health, Wuhan University, Wuhan, China.
² Department of Oncology, Dazu Hospital of Chongqing Medical University, Chongqing, China.
³ Department of Oncology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
⁴ Endocrinology Department, Dazu Hospital of Chongqing Medical University, Chongqing, China.

Abstract

Introduction: Colon adenocarcinoma (COAD) is a special pathological subtype of colorectal cancer (CRC) with highly heterogeneous solid tumors with poor prognosis, and novel biomarkers are urgently required to guide its prognosis. Material and methods: RNA-Seq data of COAD were downloaded through The Cancer Genome Atlas (TCGA) database to determine cuproptosis-related lncRNAs (CRLs) using weighted gene co-expression network analysis (WGCNA). The scores of the pathways were calculated by single-sample gene set enrichment analysis (ssGSEA). CRLs that affected prognoses were determined via the univariate COX regression analysis to develop a prognostic model using multivariate COX regression analysis and LASSO regression analysis. The model was assessed by applying Kaplan-Meier (K-M) survival analysis and receiver operating characteristic curves and validated in GSE39582 and GSE17538. The tumor microenvironment (TME), single nucleotide variants (SNV), and immunotherapy response/chemotherapy sensitivity were assessed in high- and low-score subgroups. Finally, the construction of a nomogram was adopted to predict survival rates of COAD patients during years 1, 3, and 5. Results: We found that a high cuproptosis score reduced the survival rates of COAD significantly. A total of five CRLs affecting prognosis were identified, containing AC008494.3, EIF3J-DT, AC016027.1, AL731533.2, and ZEB1-AS1. The ROC curve showed that RiskScore could perform well in predicting the prognosis of COAD. Meanwhile, we found that RiskScore showed good ability in assessing immunotherapy and chemotherapy sensitivity. Finally, the nomogram and decision curves showed that RiskScore would be a powerful predictor for COAD. Conclusion: A novel prognostic model was constructed using CRLs in COAD, and the CRLs in the model were probably a potential therapeutic target. Based on this study, RiskScore was an independent predictor factor, immunotherapy response, and chemotherapy sensitivity for COAD, providing a new scientific basis for COAD prognosis management.

Keywords: TCGA; colon adenocarcinoma; cuproptosis; immunotherapy response; lncRNA; prognostic.

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (81472698) and Natural Science Foundation of Chongqing CSTC (CSTB2022NSCQ-MSX0212).