The ferroptosis-related long non-coding RNAs signature predicts biochemical recurrence and immune cell infiltration in prostate cancer

Abstract

Abstract Background Findings from numerous studies have revealed that ferroptosis is closely related to tumorigenesis and immune cell infiltration. Long non-coding RNAs (lncRNAs) are reportedly involved in the progression of various cancers, including prostate cancer (PCa). This study was designed to establish a ferroptosis-related lncRNA (frlncRNA) signature to predict PCa prognosis. Methods The frlncRNAs were identified by studying their expression by Pearson’s correlation analysis. Differentially expressed prognosis related frlncRNAs were identified by the Wilcoxon test and univariate Cox regression analysis. The LASSO Cox regression model was used to build a model to predict biochemical recurrence (BCR) based on frlncRNAs. The GSEA software (version 4.1.0) was used to explore the enriched pathways in high- and low- risk groups. Patients with PCa were clustered into different subgroups by unsupervised clustering based on the frlncRNAs considered in the prognostic model. Real-time PCR and CCK8 assays were performed to verify the expression and function of frlncRNAs. Results We identified 35 differentially expressed prognosis related frlncRNAs based on data on PCa from TCGA. A risk signature based on five frlncRNAs (AP006284.1, AC132938.1, BCRP3, AL360181.4 and AL135999.1), was confirmed to perform well in predicting BCR. The high-risk group had higher disease grades and a greater number of infiltrating immune cells. Besides this, we found that the five frlncRNAs were connected with typical immune checkpoints. With respect to molecular mechanisms, several metabolic pathways were found to enriched in the low-risk group. Furthermore, patients could be classified into different subtypes with different PSA-free times using the five frlncRNAs. Notably, AP006284.1, AC132938.1, BCRP3 and AL135999.1 were upregulated in PCa cells and tissues, whereas AL360181.4 exhibited the opposite trend. The downregulation of BCRP3 and AP006284.1 impaired the proliferation of 22RV1 cells. Conclusion We generated a prognostic model based on five frlncRNAs, with clinical usefulness, and thus provided a novel strategy for predicting the BCR of patients with PCa.