Construction of Prognostic Risk Model of 5-Methylcytosine-Related Long Non-Coding RNAs and Evaluation of the Characteristics of Tumor-Infiltrating Immune Cells in Breast Cancer

Abstract

Purpose: The role of 5-methylcytosine-related long non-coding RNAs (m5C-lncRNAs) in breast cancer (BC) remains unclear. Here, we aimed to investigate the prognostic value, gene expression characteristics, and correlation between m5C-lncRNA risk model and tumor immune cell infiltration in BC.Methods: The expression matrix of m5C-lncRNAs in BC was obtained from The Cancer Genome Atlas database, and the lncRNAs were analyzed using differential expression analysis as well as univariate and multivariate Cox regression analysis to eventually obtain BC-specific m5C-lncRNAs. A risk model was developed based on three lncRNAs using multivariate Cox regression and the prognostic value, accuracy, as well as reliability were verified. Gene set enrichment analysis (GSEA) was used to analyze the Kyoto Encyclopedia of Genes and Genomes signaling pathway enrichment of the risk model. CIBERSORT algorithm and correlation analysis were used to explore the characteristics of the BC tumor-infiltrating immune cells. Finally, reverse transcription-quantitative polymerase chain reaction was performed to detect the expression level of three lncRNA in clinical samples.Results: A total of 334 differential m5C-lncRNAs were identified, and three BC-specific m5C-lncRNAs were selected, namely AP005131.2, AL121832.2, and LINC01152. Based on these three lncRNAs, a highly reliable and specific risk model was constructed, which was proven to be closely related to the prognosis of patients with BC. Therefore, a nomogram based on the risk score was built to assist clinical decisions. GSEA revealed that the risk model was significantly enriched in metabolism-related pathways and was associated with tumor immune cell infiltration based on the analysis with the CIBERSORT algorithm.Conclusion: The efficient risk model based on m5C-lncRNAs associated with cancer metabolism and tumor immune cell infiltration could predict the survival prognosis of patients, and AP005131.2, AL121832.2, and LINC01152 could be novel biomarkers and therapeutic targets for BC.

The Value of m5C-Related lncRNAs in the Prognostic Assessment and Immunotherapy of Stomach Adenocarcinoma

“…Upregulation of the m5C methyltransferase NSUN2 has been shown to contribute to the malignant advancement of gastric cancer cells [ 11 ]. Bioinformatics studies illustrated that the levels of m5C genes correlated with the prognosis of patients with breast cancer and colon carcinoma [ 12 , 13 ]. Currently, there is a lack of comprehensive understanding of the value of m5C-related lncRNAs in the prognostic assessment of STAD.…”

Exploration of Potential Roles of m5C-Related Regulators in Colon Adenocarcinoma Prognosis

“…Previous studies have shown that m 6 A RNA modification not only plays a critical role in the tumorigenesis and progression of CRC, but also has powerful significance in the diagnosis and prognosis of CRC patients ( Li et al, 2021 ). Additionally, a growing body of evidence shows that m 5 C-related regulators could be latent predictive biomarkers in a variety of cancer ( Huang et al, 2021a ; Huang et al, 2021b ; Pan et al, 2021 ). However, the literature on CRC and m 5 C has largely focused on DNA methylation ( Zhu et al, 2018 ).…”

Diagnostic and prognostic value of m5C regulatory genes in hepatocellular carcinoma

“…Ongoing studies have showed that RNA modification contributes to tumorigenesis and tumor progression, and there is growing evidence that m5C regulator genes may serve as potential biomarkers for cancer prediction ( Huang et al, 2021a ; Huang et al, 2021b ; Cui et al, 2021 ; Xue et al, 2021 ). It has been suggested that 5 mC methylation influences the development of HCC including clinical stage, progression, and prognosis ( Villanueva et al, 2015 ; Hlady et al, 2019 ), but the relationship between m5C-related RNA modification and HCC is still poorly understood.…”