» Articles » PMID: 36135086

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

Overview
Journal Curr Oncol
Publisher MDPI
Specialty Oncology
Date 2022 Sep 22
PMID 36135086
Authors
Affiliations
Soon will be listed here.
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.

Citing Articles

Subtype cluster analysis unveiled the correlation between m6A- and cuproptosis-related lncRNAs and the prognosis, immune microenvironment, and treatment sensitivity of esophageal cancer.

Zhang M, Su Y, Wen P, Shao X, Yang P, An P Front Immunol. 2025; 16:1539630.

PMID: 40034693 PMC: 11872909. DOI: 10.3389/fimmu.2025.1539630.


High expression levels of S1PR3 and PDGFRB indicates unfavorable clinical outcomes in colon adenocarcinoma.

Yu M, Zhang K, Wang S Heliyon. 2024; 10(15):e35532.

PMID: 39170287 PMC: 11336742. DOI: 10.1016/j.heliyon.2024.e35532.


Construction and validation of a novel lysosomal signature for hepatocellular carcinoma prognosis, diagnosis, and therapeutic decision-making.

Chen J, Gao G, He Y, Zhang Y, Wu H, Dai P Sci Rep. 2023; 13(1):22624.

PMID: 38114725 PMC: 10730614. DOI: 10.1038/s41598-023-49985-3.


Cuproptosis: mechanisms and links with cancers.

Xie J, Yang Y, Gao Y, He J Mol Cancer. 2023; 22(1):46.

PMID: 36882769 PMC: 9990368. DOI: 10.1186/s12943-023-01732-y.


Machine learning and bioinformatics-based insights into the potential targets of saponins in smith against non-small cell lung cancer.

Wang Y, Huang X, Xian B, Jiang H, Zhou T, Chen S Front Genet. 2022; 13:1005896.

PMID: 36386821 PMC: 9649596. DOI: 10.3389/fgene.2022.1005896.

References
1.
von Mering C, Huynen M, Jaeggi D, Schmidt S, Bork P, Snel B . STRING: a database of predicted functional associations between proteins. Nucleic Acids Res. 2003; 31(1):258-61. PMC: 165481. DOI: 10.1093/nar/gkg034. View

2.
Pita-Fernandez S, Gonzalez-Saez L, Lopez-Calvino B, Seoane-Pillado T, Rodriguez-Camacho E, Pazos-Sierra A . Effect of diagnostic delay on survival in patients with colorectal cancer: a retrospective cohort study. BMC Cancer. 2016; 16:664. PMC: 4994409. DOI: 10.1186/s12885-016-2717-z. View

3.
Li J, Xiang R, Song W, Wu J, Kong C, Fu T . A Novel Ferroptosis-Related LncRNA Pair Prognostic Signature Predicts Immune Landscapes and Treatment Responses for Gastric Cancer Patients. Front Genet. 2022; 13:899419. PMC: 9250987. DOI: 10.3389/fgene.2022.899419. View

4.
Qian X, Jiang C, Zhu Z, Han G, Xu N, Ye J . Long non-coding RNA LINC00511 facilitates colon cancer development through regulating microRNA-625-5p to target WEE1. Cell Death Discov. 2022; 8(1):233. PMC: 9046421. DOI: 10.1038/s41420-021-00790-9. View

5.
Jeggari A, Marks D, Larsson E . miRcode: a map of putative microRNA target sites in the long non-coding transcriptome. Bioinformatics. 2012; 28(15):2062-3. PMC: 3400968. DOI: 10.1093/bioinformatics/bts344. View