Identification of allelic expression imbalance genes in human hepatocellular carcinoma through massively parallel DNA and RNA sequencing

Hypertrophic cardiomyopathy MYH7 mutation R723G alters mRNA secondary structure

Point mutation R723G in the MYH7 gene causes hypertrophic cardiomyopathy (HCM). Heterozygous patients with this mutation exhibit a comparable allelic imbalance of the MYH7 gene. On average 67% of the total MYH7 mRNA are derived from the MYH7^R723G-allele and 33% from the MYH7^WT allele. Mechanisms underlying mRNA allelic imbalance are largely unknown. We suggest that a different mRNA lifetime of the alleles may cause the allelic drift in R723G patients. A potent regulator of mRNA lifetime is its secondary structure. To test for alterations in the MYH7^R723G mRNA structure we used selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) analysis. We show significantly different SHAPE reactivity of wild-type and MYH7^R723G RNA, which is in accordance with bioinformatically predicted structures. Thus, we provide the first experimental evidence for mRNA secondary structure alterations by the HCM point mutation. We assume that this may result in a prolonged lifetime of MYH7^R723G mRNA in vivo and subsequently in the determined allelic imbalance.

Comprehensive analysis of prognostic immune-related genes in the tumor microenvironment of cutaneous melanoma

Cutaneous malignant melanoma (hereafter called melanoma) is one of the most aggressive cancers with increasing incidence and mortality rates worldwide. In this study, we performed a systematic investigation of the tumor microenvironmental and genetic factors associated with melanoma to identify prognostic biomarkers for melanoma. We calculated the immune and stromal scores of melanoma patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and found that they were closely associated with patients' prognosis. Then the differentially expressed genes were obtained based on the immune and stromal scores, and prognostic immune-related genes further identified. Functional analysis and the protein-protein interaction network further revealed that these genes enriched in many immune-related biological processes. In addition, the abundance of six infiltrating immune cells was analyzed using prognostic immune-related genes by TIMER algorithm. The unsupervised clustering analysis using immune-cell proportions revealed eight clusters with distinct survival patterns, suggesting that dendritic cells were most abundant in the microenvironment and CD8⁺ T cells and neutrophils were significantly related to patients' prognosis. Finally, we validated these genes in three independent cohorts from the Gene Expression Omnibus database. In conclusion, this study comprehensively analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for melanoma.

Intrinsic MYH7 expression regulation contributes to tissue level allelic imbalance in hypertrophic cardiomyopathy

HCM, the most common inherited cardiac disease, is mainly caused by mutations in sarcomeric genes. More than a third of the patients are heterozygous for mutations in the MYH7 gene encoding for the β-myosin heavy chain. In HCM-patients, expression of the mutant and the wildtype allele can be unequal, thus leading to fractions of mutant and wildtype mRNA and protein which deviate from 1:1. This so-called allelic imbalance was detected in whole tissue samples but also in individual cells. There is evidence that the severity of HCM not only depends on the functional effect of the mutation itself, but also on the fraction of mutant protein in the myocardial tissue. Allelic imbalance has been shown to occur in a broad range of genes. Therefore, we aimed to examine whether the MYH7-alleles are intrinsically expressed imbalanced or whether the allelic imbalance is solely associated with the disease. We compared the expression of MYH7-alleles in non-HCM donors and in HCM-patients with different MYH7-missense mutations. In the HCM-patients, we identified imbalanced as well as equal expression of both alleles. Also at the protein level, allelic imbalance was determined. Most interestingly, we also discovered allelic imbalance and balance in non-HCM donors. Our findings therefore strongly indicate that apart from mutation-specific mechanisms, also non-HCM associated allelic-mRNA expression regulation may account for the allelic imbalance of the MYH7 gene in HCM-patients. Since the relative amount of mutant mRNA and protein or the extent of allelic imbalance has been associated with the severity of HCM, individual analysis of the MYH7-allelic expression may provide valuable information for the prognosis of each patient.

Weighted gene co-expression network analysis of gene modules for the prognosis of esophageal cancer

Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas (TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival (PFS) or overall survival (OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that "glycoprotein binding" was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor (PTAFR) and feline Gardner-Rasheed (FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.