Survival analysis

Machine learning

Cancer

Internal medicine

World Wide Web

Oncology

Multivariate statistics

Univariate

Lasso (programming language)

Computer science

Proportional hazards model

Colorectal cancer

Receiver operating characteristic

Computational biology

Medicine

Biology

Frontiers in Immunology

Background Ferroptosis is a newly defined form of programmed cell death that plays an important role in many cancers. However, ferroptosis-related lncRNAs (FRLs) involved in the regulation of colon cancer are not thoroughly understood. This study aimed to identify a prognostic FRL signature in colon cancer and explore its potential molecular function. Methods RNA-seq data and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database, and a list of ferroptosis-related genes was extracted from the FerrDb website. Analysis of differentially expressed FRLs was performed using the ‘limma’ package in R software. By implementing coexpression analysis and univariate Cox analysis, we then identified prognostic FRLs. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 4 FRLs. We evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis and receiver operating characteristic (ROC) curve analysis. Moreover, the relationships between the signature and immune landscape, somatic mutation and drug sensitivity were explored. Finally, in vitro experiments were conducted to validate the functions of AP003555.1 and AC000584.1. Results A 4-FRL signature was constructed. Two risk groups were classified based on the risk score calculated by this signature. The signature-based risk score exhibited a more powerful capacity for survival prediction than traditional clinicopathological features in colon patients. Additionally, we observed a significant difference in immune cells, such as CD4+ and CD8+ T cells and macrophages, between the two groups. Moreover, the high-risk group exhibited lower IC50 values for certain chemotherapy drugs, such as cisplatin, docetaxel, bleomycin or axitinib. Finally, the in vitro experiments showed that ferroptosis processes were suppressed after AP003555.1 and AC000584.1 knockdown. Conclusion The proposed 4-FRL signature is a promising biomarker to predict clinical outcomes and therapeutic responses in colon cancer patients.

Identification and Validation of Ferroptosis-Related LncRNA Signatures as a Novel Prognostic Model for Colon Cancer