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Expression pattern of m⁶A regulators is significantly correlated with malignancy and antitumor immune response of breast cancer.

ABSTRACT: More than 24 regulators have been revealed to dynamically participant in N6-methyladenosine (m⁶A) RNA methylation, and play critical roles in tumorigenesis and development of cancers. However, their functional roles have not been comprehensively clarified in breast cancer. Here we systematically analyzed the RNA sequencing data of 24 main m⁶A RNA methylation regulators in 775 breast cancer patients from The Cancer Genome Atlas dataset. Consensus clustering of the 24 m⁶A regulators was carried out and identified two patient subgroups, RNA methylation 1/2 (RM1/2). RM1 demonstrated generally lower RNA methylation modification than that of RM2, and had significantly shorter overall survival. The hallmarks of PI3K/AKT signaling in cancer, KRAS signaling and angiogenesis were significantly enriched in RM1. Moreover, the association between m⁶A regulators and antitumor immune response was also investigated in this study and revealed that RM2 was associated with significantly higher expressions of HLA-A, higher numbers of tumor-infiltrating CD8⁺ T cells, helper T cells and activated NK cells, but lower expressions of PD-L1, PD-L2, TIM3, and CCR4 than RM1. In conclusion, the expression pattern of m⁶A regulators was significantly correlated with the malignancy, prognosis and antitumor immune response in breast cancer, which might serve as potential targets and biomarkers for immunotherapy.

SUBMITTER: He X

PROVIDER: S-EPMC8057950 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: HIV-infected immunological non-responders (INRs) are characterized by their inability to reconstitute CD4+ T cell pools after antiretroviral therapy. The risk of non-AIDS-related diseases in INRs is increased, and the outcome and prognosis of INRs are inferior to that of immunological responders (IRs). However, few markers can be used to define INRs precisely. In this study, we aim to identify further potential diagnostic markers associated with INRs through bioinformatic analyses of public datasets. Methods: This study retrieved the microarray data sets of GSE106792 and GSE77939 from the Gene Expression Omnibus (GEO) database. After merging two microarray data and adjusting the batch effect, differentially expressed genes (DEGs) were identified. Gene Ontology (GO) resource and Kyoto Encyclopedia of Genes and Genomes (KEGG) resource were conducted to analyze the biological process and functional enrichment. We performed receiver operating characteristic (ROC) curves to filtrate potential diagnostic markers for INRs. Gene Set Enrichment Analysis (GSEA) was conducted to perform the pathway enrichment analysis of individual genes. Single sample GSEA (ssGSEA) was performed to assess scores of immune cells within INRs and IRs. The correlations between the diagnostic markers and differential immune cells were examined by conducting Spearman's rank correlation analysis. Subsequently, miRNA-mRNA-TF interaction networks in accordance with the potential diagnostic markers were built with Cytoscape. We finally verified the mRNA expression of the diagnostic markers in clinical samples of INRs and IRs by performing RT-qPCR. Results: We identified 52 DEGs in the samples of peripheral blood mononuclear cells (PBMC) between INRs and IRs. A few inflammatory and immune-related pathways, including chronic inflammatory response, T cell receptor signaling pathway, were enriched. FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1 were considered as potential diagnostic markers. ssGSEA results showed that the IRs had significantly higher enrichment scores of seven immune cells compared with IRs. The miRNA-mRNA-TF network was constructed with 97 miRNAs, 6 diagnostic markers, and 26 TFs, which implied a possible regulatory relationship. Conclusion: The six potential crucial genes, FAM120AOS, LTA, FAM179B, JUN, PTMA, and SH3YL1, may be associated with clinical diagnosis in INRs. Our study provided new insights into diagnostic and therapeutic targets.

Project description:IntroductionRecent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m6A methylation modification might play in the immune response of non-small cell lung cancer (NSCLC) remains vague.MethodsHerein, the gene expression, copy number variations (CNVs), and somatic mutations of 31 m6A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m6A modification patterns were identified. Correlations between m6A modification patterns and immune cell infiltration traits in the tumor immune microenvironment (TME) were systematically analyzed. Differentially expressed genes were verified and screened by random forest and cox regression analysis by comparing different m6A modification patterns. Based on the retained gene panel, a risk model was built, and m6Ascore for each sample was calculated. The function of m6Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated.ResultsConsensus clustering classified all NSCLC samples into two m6A clusters (m6A_clusterA and m6A_clusterB) according to the expression levels of 25 m6A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m6A gene clusters: m6AgeneclusterA and m6AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m6A gene clusters. Based on this, a risk score model was established. m6A modification clusters, m6A gene clusters, and m6Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m6Ascore have poor drug resistance to chemotherapy drugs (Cisplatin and Gemcitabine) and exhibit considerable therapeutic benefits and favorable clinical responses to anti-PD1 or anti-CTLA4 immunotherapy.DiscussionIn conclusion, methylation modification patterns mediated by the m6A regulators in individuals play a non-negligible role in prognosis prediction and immunotherapy response, which will facilitate personalized treatment and immunotherapeutic strategies for NSCLC patients in the future.

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Expression pattern of m⁶A regulators is significantly correlated with malignancy and antitumor immune response of breast cancer.

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Dataset Information

Expression pattern of m6A regulators is significantly correlated with malignancy and antitumor immune response of breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Expression pattern of m⁶A regulators is significantly correlated with malignancy and antitumor immune response of breast cancer.