Downregulation of microRNA­494 inhibits cell proliferation in lung squamous cell carcinoma via the induction of PUMA­α­mediated apoptosis.

Increased evidence has shown that abnormal microRNA (miRNA) plays pivotal roles in numerous types of cancer. However, their expression, function and mechanism in lung squamous cell carcinoma (LSCC) remains to be fully elucidated. The aim of the present study was to investigate the suppressive role of miR-494 in LSCC progression and elucidate its regulatory mechanism. By analyzing expression profiles of miRNAs in LSCC tissues using miRNA microarray, it was revealed that miR-494 was significantly upregulated in 22 pairs of LSCC tissues. Subsequently, reverse transcription-quantitative PCR was performed to determine the expression of miR-494 and p53-upregulated-modulator-of-apoptosis-α (PUMA-α). Western blot analysis was conducted to examine protein levels. Dual-luciferase reporter assay was used to confirm the binding between miR-494 and PUMA-α. Annexin V-fluoresceine isothiocyanate/propidium iodide staining and CCK-8 assays were employed to determine cell apoptosis and cell viability, respectively. It was also revealed that miR-494 was highly expressed in LSCC cell lines compared with that in 16HBE cells. Further experiments confirmed that knockdown of miR-494 reduced cell viability and induced LSCC apoptosis. Bioinformatics analysis predicted that miR-494 could potentially target PUMA-α; also known as Bcl-2-binding component 3, a pro-apoptotic factor, and an inverse correlation between the expression of miR-494 and PUMA-α mRNA levels in LSCC tissues was found. Furthermore, PUMA-α inhibition could reverse the promoting effect of miR-494 knockdown on apoptosis in LSCC cells. Taken together, these findings demonstrated that miR-494 functions as an oncogene by targeting PUMA-α in LSCC, and miR-494 may serve as a novel therapeutic target for treating LSCC.

Multiomics Analysis of Transcriptome, Epigenome, and Genome Uncovers Putative Mechanisms for Dilated Cardiomyopathy.

OBJECTIVE: Multiple genes have been identified to cause dilated cardiomyopathy (DCM). Nevertheless, there is still a lack of comprehensive elucidation of the molecular characteristics for DCM. Herein, we aimed to uncover putative molecular features for DCM by multiomics analysis. METHODS: Differentially expressed genes (DEGs) were obtained from different RNA sequencing (RNA-seq) datasets of left ventricle samples from healthy donors and DCM patients. Furthermore, protein-protein interaction (PPI) analysis was then presented. Differentially methylated genes (DMGs) were identified between DCM and control samples. Following integration of DEGs and DMGs, differentially expressed and methylated genes were acquired and their biological functions were analyzed by the clusterProfiler package. Whole exome sequencing of blood samples from 69 DCM patients was constructed in our cohort, which was analyzed the maftools package. The expression of key mutated genes was verified by three independent datasets. RESULTS: 1407 common DEGs were identified for DCM after integration of the two RNA-seq datasets. A PPI network was constructed, composed of 171 up- and 136 downregulated genes. Four hub genes were identified for DCM, including C3 (degree = 24), GNB3 (degree = 23), QSOX1 (degree = 21), and APOB (degree = 17). Moreover, 285 hyper- and 321 hypomethylated genes were screened for DCM. After integration, 20 differentially expressed and methylated genes were identified, which were associated with cell differentiation and protein digestion and absorption. Among single-nucleotide variant (SNV), C>T was the most frequent mutation classification for DCM. MUC4 was the most frequent mutation gene which occupied 71% across 69 samples, followed by PHLDA1, AHNAK2, and MAML3. These mutated genes were confirmed to be differentially expressed between DCM and control samples. CONCLUSION: Our findings comprehensively analyzed molecular characteristics from the transcriptome, epigenome, and genome perspectives for DCM, which could provide practical implications for DCM.

Multiomics Analysis of Genetics and Epigenetics Reveals Pathogenesis and Therapeutic Targets for Atrial Fibrillation.

OBJECTIVE: This study is aimed at understanding the molecular mechanisms and exploring potential therapeutic targets for atrial fibrillation (AF) by multiomics analysis. METHODS: Transcriptomics and methylation data of AF patients were retrieved from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) and differentially methylated sites between AF and normal samples were screened. Then, highly expressed and hypomethylated and lowly expressed and hypermethylated genes were identified for AF. Weighted gene coexpression network analysis (WGCNA) was presented to construct AF-related coexpression networks. 52 AF blood samples were used for whole exome sequence. The mutation was visualized by the maftools package in R. Key genes were validated in AF using independent datasets. RESULTS: DEGs were identified between AF and controls, which were enriched in neutrophil activation and regulation of actin cytoskeleton. RHOA, CCR2, CASP8, and SYNPO2L exhibited abnormal expression and methylation, which have been confirmed to be related to AF. PCDHA family genes had high methylation and low expression in AF. We constructed two AF-related coexpression modules. Single-nucleotide polymorphism (SNP) was the most common mutation type in AF, especially T > C. MUC4 was the most frequent mutation gene, followed by PHLDA1, AHNAK2, and MAML3. There was no statistical difference in expression of AHNAK2 and MAML3, for AF. PHLDA1 and MUC4 were confirmed to be abnormally expressed in AF. CONCLUSION: Our findings identified DEGs related to DNA methylation and mutation for AF, which may offer possible therapeutic targets and a new insight into the pathogenesis of AF from a multiomics perspective.