The Prognostic Value Of M7G-related LncRNAs In Patients With Breast Cancer Based On Bioinformatics

Background:Breast cancer has become the most newly diagnosed cancer in the world,and it still has a high risk of recurrence and metastasis.At present,lncRNAs are potential new biomarkers and therapeutic targets of cancer.As a new type of RNA methylation,7-methylguanine(m7G)RNA methylation is another hotspot of epigenetic transcriptome after m6A modification.Objective:In this study,we analyzed the differential expression of m7G related lncRNAs in breast cancer and looked for biomarkers closely related to the prognosis of breast cancer,preliminarily explored them,and established a prognostic risk prediction model.Method:In this study,transcriptome data and clinical information data of breast cancer samples obtained from the TCGA database were combined with m7G-related genes in the Gene Ontology database to screen out lncRNAs that may be related to m7G modification,and univariate Cox regression analysis was used to obtain prognostic m7G-related lncRNAs.After the classification of prognostic m7G-related lncRNAs by cluster analysis,the immune cell infiltration analysis,tumor microenvironment analysis and the correlation with METTL1 gene were preliminarily explored.The TCGA dataset was divided into training sets and test sets to construct and validate the prognostic risk models,respectively.Lasso regression and crossvalidation were used to further screen lncRNAs associated with prognosis and establish a prognostic risk model.Risk scores were calculated according to the model formula,and breast cancer patients were divided into two groups with high and low scores for analysis and verification.Results:A total of 29 prognosis m7G-related lncRNAs were identified.The results of cluster analysis showed that there was a statistical difference in prognosis among different clusters,while there were no statistical differences in METTL1 gene expression.Primitive B cells,Plasma cells,T cells CD8,T cells CD4 memory activated,T cell follicular helper,T cells regulatory and NK cells activated infiltrated significantly in the classification with good prognosis,while Macrophages M0,Macrophages M2 and Dendritic cells resting infiltrated significantly in the classification with poor prognosis.The content of stromal cells in the cluster with poor prognosis was higher than that with good prognosis.In addition,the study screened 15 lncRNAs from prognosis m7G-related lncRNAs to establish a risk prediction model.The patients were divided into two groups according to the risk score.K-M survival curve showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group(P<0.05).15-lncRNAs based risk score showed a higher prognostic value for breast cancer patients.Independent prognostic analysis of the risk score(P<0.05)indicated that the risk score could be used as an independent prognostic factor.Conclusion:We established a prognostic risk prediction model for breast cancer based on m7G-related lncRNAs,which can score the risk of breast cancer patients and preliminarily predict the prognosis of patients,which is conducive to the identification of high-risk patients.In addition,our study suggests that m7G may be involved in the regulation of tumor metabolism,immune cell infiltration,and tumor microenvironment,providing a possible new idea to further explore the regulatory mechanism of m7G modification in the development of breast cancer.