Proteomic characterization of epithelial ovarian cancer delineates molecular signatures and therapeutic targets in distinct histological subtypes.

Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

Construction of a ferroptosis-related signature based on seven lncRNAs for prognosis and immune landscape in clear cell renal cell carcinoma.

BACKGROUND: Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are involved in regulating tumor cell ferroptosis. However, prognostic signatures based on ferroptosis-related lncRNAs (FRLs) and their relationship to the immune microenvironment have not been comprehensively explored in clear cell renal cell carcinoma (ccRCC). METHODS: In the present study, the expression profiles of ccRCC were acquired from The Cancer Genome Atlas (TCGA) database; 459 patient specimens and 69 adjacent normal tissues were randomly separated into training or validation cohorts at a 7:3 ratio. We identified 7 FRLs that constitute a prognostic signature according to the differential analysis, correlation analysis, univariate regression, and least absolute shrinkage and selection operator (LASSO) Cox analysis. To identify the independence of risk score as a prognostic factor, univariate and multivariate regression analyses were also performed. Furthermore, CIBERSORT was conducted to analyze the immune infiltration of patients in the high-risk and low-risk groups. Subsequently, the differential expression of immune checkpoint and m6A genes was analyzed in the two risk groups. RESULTS: A 7-FRLs prognostic signature of ccRCC was developed to distinguish patients into high-risk and low-risk groups with significant survival differences. This signature has great prognostic performance, with the area under the curve (AUC) for 1, 3, and 5 years of 0.713, 0.700, 0.726 in the training set and 0.727, 0.667, and 0.736 in the testing set, respectively. Moreover, this signature was significantly associated with immune infiltration. Correlation analysis showed that risk score was positively correlated with regulatory T cells (Tregs), activated CD4 memory T cells, CD8 T cells and follicular helper T cells, whereas it was inversely correlated with monocytes and M2 macrophages. In addition, the expression of fourteen immune checkpoint genes and nine m6A-related genes varied significantly between the two risk groups. CONCLUSION: We established a novel FRLs-based prognostic signature for patients with ccRCC, containing seven lncRNAs with precise predictive performance. The FRLs prognostic signature may play a significant role in antitumor immunity and provide a promising idea for individualized targeted therapy for patients with ccRCC.

Identification of miRNA-mRNA network and immune-related gene signatures in IgA nephropathy by integrated bioinformatics analysis.

BACKGROUND: IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis worldwide, and its diagnosis depends mainly on renal biopsy. However, there is no specific treatment for IgAN. Moreover, its causes and underlying molecular events require further exploration. METHODS: The expression profiles of GSE64306 and GSE93798 were downloaded from the Gene Expression Omnibus (GEO) database and used to identify the differential expression of miRNAs and genes, respectively. The StarBase and TransmiR databases were employed to predict target genes and transcription factors of the differentially expressed miRNAs (DE-miRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to predict biological functions. A comprehensive analysis of the miRNA-mRNA regulatory network was constructed, and protein-protein interaction (PPI) networks and hub genes were identified. CIBERSORT was used to examine the immune cells in IgAN, and correlation analyses were performed between the hub genes and infiltrating immune cells. RESULTS: Four downregulated miRNAs and 16 upregulated miRNAs were identified. Forty-five and twelve target genes were identified for the upregulated and downregulated DE-miRNAs, respectively. CDKN1A, CDC23, EGR1, HIF1A, and TRIM28 were the hub genes with the highest degrees of connectivity. CIBERSORT revealed increases in the numbers of activated NK cells, M1 and M2 macrophages, CD4 naive T cells, and regulatory T cells in IgAN. Additionally, HIF1A, CDC23, TRIM28, and CDKN1A in IgAN patients were associated with immune cell infiltration. CONCLUSIONS: A potential miRNA-mRNA regulatory network contributing to IgAN onset and progression was successfully established. The results of the present study may facilitate the diagnosis and treatment of IgAN by targeting established miRNA-mRNA interaction networks. Infiltrating immune cells may play significant roles in IgAN pathogenesis. Future studies on these immune cells may help guide immunotherapy for IgAN patients.

Long noncoding RNAs in gastric cancer: From molecular dissection to clinical application.

Long noncoding RNAs (lncRNAs) are important regulators of cell processes that are usually dysregulated in gastric cancer (GC). Based on their high specificity and ease of detection in tissues and body fluids, increasing attention has spurred the study of the roles of lncRNAs in GC patients. Thus, it is necessary to elucidate the molecular mechanisms and further explore the clinical applications of lncRNAs in GC. In this review, we summarize current knowledge to examine dysregulated lncRNAs in GC and their underlying molecular mechanisms and activities in GC, which involve microRNA sponging, mRNA stability, genetic variants, alternative splicing, transcription factor binding, and epigenetic modification. More significantly, the potential of lncRNAs as prognostic, circulating, and drug-resistant biomarkers for GC is also described. This review highlights the method of dissecting molecular mechanisms to explore the clinical application of lncRNAs in GC. Overall, this review offers assistance in using lncRNAs as novel candidates for molecular mechanisms and for the identification of revolutionary biomarkers for GC.

Network and Pathway-Based Integrated Analysis Identified a Novel "rs28457673-miR-15/16/195/424/497 Family-IGF1R-MAPK Signaling Pathway" Axis Associated With Post-stroke Depression.

Single-nucleotide polymorphisms (SNPs) of microRNA (miRNA) (miRSNP) are SNPs located on miRNA genes or miRNA target sites, which have been supposed to be involved in the development of central nervous system diseases by interfering with miRNA-mediated regulatory functions. However, the association of miRSNP with post-stroke depression (PSD) has not been well-investigated. In this study, we collected 54 PSD risk genes via manual literature-mining and integrated PSD-related risk pathways based on multiple public databases. Furthermore, we systematically screened candidate functional miRSNPs for PSD and integrated a miRSNP-based PSD-associated pathway network, which included 99 miRNAs that target 12 PSD risk pathways. We also reviewed the association between three risk pathways and PSD pathogenetic mechanism thoroughly. Combining literature mining and network analysis, our results proposed an underlying mechanism of "miRSNP → miRNA → risk gene → pathway" axis effects on PSD pathogenesis, especially for rs28457673 (miR-15/16/195/424/497 family) → IGF1R → hsa04010 (MAPK signaling pathway). Our studies revealed a functional role in genetic modifier at the system level in the pathogenesis of PSD, which might provide further information for the miRSNP studies in PSD.

Systematic analysis of human microRNA divergence based on evolutionary emergence.

MicroRNAs (miRNAs) play important roles in post-transcriptional gene expression control. To gain new insight into human miRNAs, we performed comprehensive sequence-based homology search for known human miRNAs to study the evolutionary distribution of human miRNAs. Furthermore, we carried out a series of studies to compare various features for different lineage-specific human miRNAs. Our results showed that major expansions of human miRNA genes coincide with the advent of vertebrates, mammals and primates. Further system-level analysis revealed significant differences in human miRNAs that arose from different evolutionary time points for a number of characteristics, implicating genetic and functional diversification for different human miRNAs during evolution. Our finds provide more useful knowledge for further exploring origins and evolution of human miRNA genes.