Bioinformation Analysis Of N6-Methyladenosine-Related LncRNAs In Breast Cancer

Objective: In order to explore the interaction between m6 A modification and lnc RNA in breast cancer,to find new molecular signature of breast cancer.In this study,bioinformatics analysis methods and software will be used to screen lnc RNAs related to m6 A modification in breast cancer,establish a breast cancer prognosis risk model,and explore the potential components of breast cancer that may reflect the different m6 A modification status of lnc RNAs according to their expression levels.Methods: 1.The expression data of breast cancer samples were obtained from TCGA,and bioinformatics analysis was performed by R language to screen lnc RNAs with m6 A modification which related to prognosis of breast cancer.Then we constructed a prognostic model about m6A-related lnc RNAs for predicting the prognosis of breast cancer patients and calculate risk score basing on the model and prove its’ reliability.All the samples were divided into high-and low-risk subgroups according to the median risk score.We further explored survival difference between risk subgroups,correlations between risk scores and clinical traits,pathways enrichment and drug sensitivities in each risk subgroups.2.We clustered the samples according to the expression levels of lnc RNAs to explore the potential molecular subtype of breast cancer and predicted the pathway enrichment between subtypes through gene set enrichment analysis.3.The target mi RNAs and m RNAs of lnc RNAs were predicted and a ce RNA network was established.Gene enrichment analysis was performed on the target m RNAs.4.We collected clinical tissue specimens of patients who underwent surgical treatment in the Third Xiangya Hospital from 2019 to 2021 about 48 breast cancer and24 adjacent breast tissues,and used RT-q PCR to verify the expression level of lnc RNAs in the tissues.Results: 1.In this study,13 lnc RNAs with m6 A modification which related to prognosis of breast cancer were screened by analyzing the transcript expression data of breast cancer and normal samples from TCGA database.The formula of prognosis risk model included 10 lnc RNAs for breast cancer is obtained by LASSO-Cox analysis.Survival analysis confirmed that the high-risk group had a lower mortality rate than the low-risk group.The ROC curve showed that the model had good predictive ability for survival of breast cancer patient.Principal component analysis showed that there were significant differences between the high-and low-risk groups.Clinical correlation analysis showed that risk score was significantly associated with part of clinicopathological features.Univariate and multivariate Cox regression analysis both proved that the risk score of the model can be used as an independent prognostic factor for breast cancer.Drug sensitivity analysis suggested that the high-risk group was more sensitive to lapatinib only.The results of GSEA indicated that KEGG pathway annotation involving DNA replication,cell cycle and drug metabolism were significantly enriched in high-risk groups;mi RNAs functions in cancer and mi RNAs in RNA transport were enriched in low-risk groups.2.According to the expression levels of the 13 lnc RNAs,3 potential molecular subtypes were obtained by clustering,immune characteristics between subgroups were compared further: type I had the highest HLA genes expression levels,type II had the lowest HLA genes expression levels,and type III was in the middle;Naive B cells and CD8+ T cells infiltrated more abundantly in type I and M0 macrophages in type II as well;type II has lower immune and stromal scores but higher tumor purity;by contract,type I had higher immune and stromal scores but lower tumor purity.Therefore,it can be speculated that m6 A modification of lnc RNAs plays an indispensable role in the formation of tumor immune microenvironment of breast cancer.Results of GSEA suggested that many translation-related BPs were enriched in type I,BPs were enriched in type II which related to cell cycle and mitosis,BPs were enriched in type III which related to muscle fiber and apoptosis.3.Correlation analysis obtained a ce RNA network involving 7 target mi RNAs and further targeting 62 m RNAs of 3lnc RNAs that have a co-expression relationship with the RBM15 defined m6 A "writer".Enrichment analysis of target m RNAs suggested that they were significantly enriched in GO-BPs annotation about chemotactic activity,protein phosphatase binding,nuclear receptor activity,protein tyrosine kinase activity and multiple tumor related pathways KEGG annotations.4.Statistical analysis of RT-q PCR results of clinical tissue samples showed that the expression levels of lnc RNAs with m6 A modification which related to prognosis of breast cancer in tumor tissues were lower than those in normal breast tissues.Conclusion: A total of 13 lnc RNAs with m6 A modification which related to prognosis of breast cancer were screened,and a risk model was established basing on these lnc RNAs that could predict the prognosis of breast cancer patients.The model could be used as new molecular signature of breast cancer included 10 lnc RNAs,and the prediction ability and stability of the model have been verified.Three potential molecular subtypes of different states of lnc RNAs with m6 A modification in breast cancers was obtained at the same time.