Development of the expression and prognostic significance of m5C‐related LncRNAs in breast cancer. (4th December 2022) - Xu, Gaoran; Li, Chengxin; Di, Ziyang; Yang, Yalong; Liang, Leilei; Yuan, Qianqian; Yang, Qian; Dong, Xingxing; Xu, Siguang; Wu, Gaosong
Abstract: Background: 5‐Methylcytosine (m5C) methylation is a major epigenetic RNA modification and is closely related to tumorigenesis in various cancers. This study aimed to explore the prognostic value of m5C‐related lncRNAs in breast cancer. Methods: Clinical characteristics and RNA‐seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. First, we performed differentially expressed gene (DEG) analysis and constructed a PPI network for the 12 m5C regulators. Then, we identified the m5C‐related LncRNAs by the "cor. test." An m5C‐related lncRNA prognostic risk signature was developed using univariate Cox regression and Lasso‐penalized Cox regression analyses. The model's performance was determined using Kaplan–Meier (KM) survival analysis and ROC curves. Finally, a nomogram was constructed for clinical application in evaluating patients with BRCA. We also researched the drug sensitivity of signature lncRNAs and immune cell infiltration. Finally, we validated the expression of the signature lncRNAs through qRT–PCR in a breast cancer cell line and a breast epithelial cell line. Results: Overall, we constructed an 11‐lncRNA risk score signature based on the lncRNAs associated with m5C regulators. According to the median risk score, we divided BRCA patients into high‐ and low‐risk groups. The prognostic risk signature displayed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of immune cell subtypes. Drug sensitivity proved that our prognostic risk signature potentially has therapeutic value. Conclusions: The m5C‐related lncRNA signature reliably predicted the prognosis of breast cancer patients and may provide new insight into the breast cancer tumor immune microenvironment. Abstract : By RNA‐seq and TCGA, an 11‐lncRNA risk score signature was constructed based on lncRNAs associated with m5C regulators, which could reliably predict the prognosis of breast cancer patients. Immune cell infiltration assays and drug susceptibility assays demonstrate their value for studying the tumor immune microenvironment in breast cancer.