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Purpose: Exploring new understanding of genetic factors can help reveal the etiology of MPM and improve the survival rate of patients with MPM. Methods: We explored the expression pattern in MPM across GEO, DAVID, HMDD, and miRNet. The PPI networks of the intersection targets were constructed by STRING and Cytoscape, and the hub genes were selected by plugin cytoHubba. The survival analysis of hub genes was also carried out based on the GEPIA and UALCAN database. The immune subtype and infiltration analyses were performed using TISTDB and TIMER database. Results: A total of 251 DEGs were detected. GO and KEGG pathway analysis revealed that DEGs were significantly enriched in extracellular matrix organization, ECM-receptor interaction. The PPI network was assessed, and the top 10 hub genes were identified by evaluating degrees. High expression level of CDH2, COL3A1, CAV1 was associated with worse prognostic value in MPM. For different immune subtypes, significant connection with CDH2/COL3A1/CAV1 expression existed in MPM. The correlation between immune cells and hub genes showed that CAV1 was positively correlated with Dendritic cells, CDH2 was positively correlated with Dendritic cells, while it was negatively correlated with Neutrophil. COL3A1 expression was positively associated with infiltration levels of Macrophages, whereas negative association with Neutrophil. Furthermore, Neutrophil and CDH2 was significantly correlated with the clinical outcomes of MPM. Conclusion: CDH2, COL3A1, and CAV1 may serve as a promising prognostic biomarker in MPM, in particular, the correlation between CDH2 and Neutrophil is one of the critical factors affecting MPM prognosis.

Objectives NIHL is a disease with irreversible damage caused by multi-factor interaction, and the STAT3 is an essential protein with signal transduction and transcription functions. This study is aimed to explore the effect of STAT3 polymorphism on individual susceptibility to NIHL individuals, and to further examine the interaction between lifestyles and NIHL in the dominant model . Methods This study was designed a case-control study and included 609 NIHL cases and 611 healthy hearing controls from the Jiangsu province of China. By collecting the lifestyle and demographic information of the study participants, genotyping the collected blood samples, and performing Real-time Quantitative PCR (qRT-PCR) to analyze and investigate the potential association between STAT3 SNPs and NIHL. Results Statistical analysis results show that individuals carrying the C allele of rs1053023 and rs1053005 were more likely to develop NIHL than individuals carrying the T allele (OR = 1.367, 95% CI = 1.148–1.628, P = 0.0001 and OR = 1.37, 95% CI = 1.147–1.636, P = 0.001). In the dominant model (TC/CC genotype and TT genotype), stratified analysis of lifestyle, we found that people who smoke regularly are more likely to suffer from NIHL than non-smokers or occasional smokers. Besides, the expression of STAT3 was higher in NIHL cases by real-time quantitative PCR. Conclusion Gene polymorphisms, rs1053023 and rs1053005, from STAT3, are associated with NIHL and C alleles of rs1053023 and rs1053005 within STAT3 may become biomarkers for workers exposed to noise.

Objective We aim to investigate whether genetic mutations in three important base excision repair genes (OGG1, APEX1, and XRCC1) may influence susceptibility to noise-induced hearing loss. Methods Three SNPs in OGG1, APEX1, and XRCC1 were genotyped from noise exposed workers who were classified into susceptible and resistant individuals. Results: Results showed that the rs1799782 TT genotype located in the XRCC1 coding region and rs1130409 GG/GT in the APEX1 coding region were associated with increased risk for noise-induced hearing loss. Compared to the rs1799782 C allele frequency, the T allele frequency increased in the sensitive group (OR = 1.51). Rs1130409 G allele frequency also increased in the sensitive group compared to the resistant group (OR = 1.59). Conclusions XRCC1 rs1799782 and APEX1 rs1130409 may have potential as biomarkers for screening susceptibility to NIHL in workers exposed severe noise.