MiRNA expression patterns are associated with tumor mutational burden in lung adenocarcinoma

Abstract

Background: Tumor mutational burden (TMB) has emerged as an independent biomarker to predict patient responses to treatment with immune checkpoint inhibitors (ICIs) for lung adenocarcinoma (LUAD). MicroRNAs (miRNAs) have a crucial role in the regulation of anticancer immune responses, but the association of miRNA expression patterns and TMB is not clear in LUAD. Methods: Differentially expressed miRNAs in samples with high TMB and low TMB samples were screened in the LUAD dataset in The Cancer Genome Atlas. The least absolute shrinkage and selection operator (LASSO) method was applied to develop a miRNA-based signature classifier for predicting TMB levels in the training set. An test set was used to validate this classifier. The correlation between the miRNA-based classifier index and the expression of three immune checkpoints (PD-1, PD-L1, and CTLA-4) were explored. Functional enrichment analysis was carried out of the miRNAs included in the miRNAbased signature classifier. Results: Twenty-five differentially expressed miRNAs were used to establish a miRNA-based signature classifier for predicting TMB level. The accuracy of the 25-miRNA-based signature classifier was 0.850 in the training set, 0.810 in the test set and 0.840 in the total set. This miRNA-based signature classifier index showed a low correlation with PD-1 and PD-L1, and no correlation with CTLA-4. Enrichment analysis for these 25 miRNA revealed they are involved in many immune-related biological processes and cancer-related pathways. Conclusion: MiRNA expression patterns are associated with tumor mutational burden and a miRNAbased signature classifier may serve as a biomarker for prediction of TMB levels in LUAD.

A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

“…We obtained tumor mutation data of LUAD from TCGA database. 10 mutations per megabyte (MB) was used as the threshold of high and low TMB ( Hellmann et al, 2018 ; Lv et al, 2019 ). A high TMB level was defined as >10 mutations per MB, and below that threshold was a low TMB level.…”

Integrative modeling of multi-omics data for predicting tumor mutation burden in lung cancer patients

“…miRNAs expression in the tumor microenvironment plays a crucial role in mediating and controlling several immune and cell interactions, and convolute in the regulation of immune checkpoints, PD1 and PD-L1 [63]. It was reported that a 25 miRNA-based signature classi er could predict the TMB level with high accuracy [64]. A cluster of highly expressed miRNA including hsa-miR-492, hsa-miR-498, hsa-miR-320 were found to be correlated with tumorigenesis of retinoblastoma [65].…”

Immunotherapy in Non-Small-Cell Lung Cancer: from Targeted Molecules to Resistance Patterns

“…More recently, a significant association between somatic RYR2 (ryanodine receptor 2) mutations and high TMB was defined as a potential prognostic marker for lung adenocarcinoma [9]. Other authors have developed a 25 miRNA-based signature classifier, involved in immune-related biological processes and in cancer-related pathways, as a potential biomarker to predict TMB levels in lung adenocarcinoma [10]. High TMB can increase neo-antigen expression linked to T-cell recruitment [4].…”