LncRNA MIAT Services as a Noninvasive Biomarker for Diagnosis and Correlated with Immune Infiltrates in Breast Cancer.

Background Myocardial infarction associated transcript (MIAT) is identified as a long chain non-coding RNA (lncRNA), which was associated with myocardial infarction susceptibility. While intense efforts have been made to elucidate the relationship between MIAT and carcinogenesis, the tumor immunoreaction of MIAT remains elusive. Thus, this study aimed to investigate the role of MIAT in the immunoregulation of breast cancer (BC) and further explore the better clinical significance. Methods The differential expression of MIAT between BC and normal/adjacent tissues was compared using Wilcoxon rank sum test. The diagnostic and prognostic values of elevated MIAT expression in BC tissues were unveiled via receiver operating characteristic (ROC) analysis and KM-plotter analysis. Limma and edgeR package were used to identify differentially expressed genes (DEGs) and microRNAs (DEMs) from TCGA database respectively. A co-expression dataset was constructed to comprehensively understand the relationship between MIAT and DEGs based on the Pearson correlation coefficient. Furthermore, GO and KEGG analyses were conducted to predict the potential functions of MIAT. We next intersected immune-related genes (IRGs) from ImmPort database with MIAT-co-expressed genes to obtain MIAT-co-expressed IRGs, in order to construct MIAT-microRNA (miRNA)-mRNA network. And the correlation between MIAT and tumor-infiltrating immune cells (TICs) and immunophenoscore (IPS) analysis was analyzed by TIMER and CIBERSORT. Finally, the reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was used to detect the expression profiles of MIAT in serum samples. Results The expression levels of MIAT were notably higher in BC than in normal or adjacent tissues. And MIAT expression could be used as a prognostic indicator of mortality risk in patients with BC in different aspects. Moreover, the enrichment analyses suggested that MIAT was strongly involved in BC immune response. In addition, TIMER database and CIBERSORT analyses indicated that MIAT was significantly correlated with 13 types of TICs (B cells, dendritic cells, neutrophils, CD8 T cells, CD4 memory resting T cells, CD4 memory activated T cells, gamma delta T cells, M1 macrophages, plasma cells, activated NK cells, monocytes, M2 macrophages, activated mast cells). Simultaneously, the IPS analysis implied that the higher the MIAT expression, the better the immunotherapy effect. The ROC curve analysis showed that the area under the curve (AUC) value of MIAT was 0.86 (sensitivity = 87.80%, specificity = 75.61%). And the high MIAT expression in serum was positive related to TNM stage (P = 0.032) and lymph node metastasis (P = 0.028). Conclusion MIAT may be a valuable noninvasive diagnostic biomarker for BC and is associated with tumor-infiltrating immune cells in tumor microenvironment, suggesting MIAT as a potential target for future treatment of BC.