RNA-Binding Motif Protein 11 (RBM11) Serves as a Prognostic Biomarker and Promotes Ovarian Cancer Progression

Genome-wide association study (GWAS) identified PCOS susceptibility variants and replicates reported risk variants

BACKGROUND

Genetic predisposition and environmental factors are considered risk factors for polycystic ovary syndrome (PCOS). Genome-wide association studies (GWAS) have been reported from various subpopulations to evaluate SNPs associated with PCOS risk. No PCOS-associated GWAS study has been reported from India so far.

PURPOSE

The current study was conducted to identify the PCOS-susceptible loci among the North Indian population and to validate the significant loci reported by previous GWAS studies.

METHODS

A total of 272 participants with 134 PCOS patients and 138 age-matched healthy controls were recruited. Genomic DNA was isolated and genotyped by using Infinium Global Screening Array v3.0 microchip considering HWE 10e-5 statistically significant.

RESULTS

A total of fifteen markers have been identified as candidate PCOS risk factors. Only two SNPs, namely rs17186366 and rs11171739 have been identified through replication analysis while comparing the previously reported PCOS GWAS data. In-silico analysis was performed to study the functional impact of identified significant genes for gene ontology, pathways related to gene set, and cluster analysis to determine protein-protein interaction among genes or gene products.

CONCLUSION

The study suggests that multiple variants play an important role in PCOS pathogenesis and emphasizes the importance of further genetic studies among Indian subpopulations. The study also validates two previously reported SNPs in the Indian population. What this study adds to clinical work Study summarizes the importance of candidate gene markers validated by replication and in-silico functional study, significantly involved in PCOS pathogenesis in the studied population. These markers can be used in the future as diagnostic markers for clinical phenotype identification.

Comprehensive bioinformatics analysis of a RBM family-based prognostic signature with experiment validation in hepatocellular carcinoma

BACKGROUND

Although some RBM proteins family members play important roles in hepatocellular carcinoma (HCC) development, their value of prognosis and tumor treatment is not clear. To reveal the expression patterns and clinical significance of RBM family members in HCC, we constructed a RBM family-based prognosis signature.

METHOD

We collected the data of HCC patients from TCGA and ICGC database. The prognostic signature was constructed in TCGA and verified using ICGC cohort. Based on this model, risk score was calculated and patients were divided into high- and low-risk group. Comparison of immune cell infiltration, the response to immunotherapy, and IC50 of chemotherapeutic drugs were employed between different risk subgroups. Besides, CCK-8 and EdU assays were performed to investigate the role of RBM45 in HCC.

RESULT

Among 19 differential expression RBM protein family genes, 7 prognostic genes were picked out. Through LASSO Cox regression, a 4-gene prognostic model was successfully constructed, which included RBM8A, RBM19, RBM28 and RBM45. Results of validation and estimation suggested this model could be applied for prognostic prediction in HCC patients with a well predictive value. Risk score was shown to be an independent predictor and high-risk patients had poor prognosis. High-risk patients had an immunosuppressive tumor microenvironment while patients with low risk could benefit more from ICI therapy and sorafenib treatment. In addition, knockdown of RBM45 inhibited the proliferation of HCC.

CONCLUSION

This prognostic signature based on RBM family had a great value for predicting OS of HCC patients. Low-risk patients were more suitable for receiving immunotherapy and sorafenib treatment. The RBM family members made of the prognostic model might promote the progression of HCC.

Microglial Extracellular Vesicles as Modulators of Brain Microenvironment in Glioma

Microglial cells represent the resident immune elements of the central nervous system, where they exert constant monitoring and contribute to preserving neuronal activity and function. In the context of glioblastoma (GBM), a common type of tumor originating in the brain, microglial cells deeply modify their phenotype, lose their homeostatic functions, invade the tumoral mass and support the growth and further invasion of the tumoral cells into the surrounding brain parenchyma. These modifications are, at least in part, induced by bidirectional communication among microglial and tumoral cells through the release of soluble molecules and extracellular vesicles (EVs). EVs produced by GBM and microglial cells transfer different kinds of biological information to receiving cells, deeply modifying their phenotype and activity and could represent important diagnostic markers and therapeutic targets. Recent evidence demonstrates that in GBM, microglial-derived EVs contribute to the immune suppression of the tumor microenvironment (TME), thus favoring GBM immune escape. In this review, we report the current knowledge on EV formation, biogenesis, cargo and functions, with a focus on the effects of microglia-derived EVs in GBM. What clearly emerges from this analysis is that we are at the beginning of a full understanding of the complete picture of the biological effects of microglial-derived EVs and that further investigations using multidisciplinary approaches are necessary to validate their use in GBM diagnosis and therapy.

Iodoacetic acid exposure alters the transcriptome in mouse ovarian antral follicles

Iodoacetic acid (IAA) is an unregulated water disinfection byproduct that is an ovarian toxicant. However, the mechanisms of action underlying IAA toxicity in ovarian follicles remain unclear. Thus, we determined whether IAA alters gene expression in ovarian follicles in mice. Adult female mice were dosed with water or IAA (10 or 500 mg/L) in the water for 35-40 days. Antral follicles were collected for RNA-sequencing analysis and sera were collected to measure estradiol. RNA-sequencing analysis identified 1063 differentially expressed genes (DEGs) in the 10 and 500 mg/L IAA groups (false discovery rate FDR < 0.1), respectively, compared to controls. Gene Ontology Enrichment analysis showed that DEGs were involved with RNA processing and regulation of angiogenesis (10 mg/L) and the cell cycle and cell division (500 mg/L). Pathway Enrichment analysis showed that DEGs were involved in the phosphatidylinositol 3-kinase and protein kinase B (PI3K-Akt), gonadotropin-releasing hormone (GnRH), estrogen, and insulin signaling pathways (10 mg/L). Pathway Enrichment analysis showed that DEGs were involved in the oocyte meiosis, GnRH, and oxytocin signaling pathways (500 mg/L). RNA-sequencing analysis identified 809 DEGs when comparing the 500 and 10 mg/L IAA groups (FDR < 0.1). DEGs were related to ribosome, translation, mRNA processing, oxidative phosphorylation, chromosome, cell cycle, cell division, protein folding, and the oxytocin signaling pathway. Moreover, IAA exposure significantly decreased estradiol levels (500 mg/L) compared to control. This study identified key candidate genes and pathways involved in IAA toxicity and can help to further understand the molecular mechanisms of IAA toxicity in ovarian follicles.

Clinical Characteristics in the Prediction of Posttreatment Survival of Patients with Ovarian Cancer

Objective

To determine the efficacy of clinical characteristics in the prediction of prognosis in patients with ovarian cancer.

Methods

Clinical data were collected from 3 datasets from TCGA database, including 1680 cases of ovarian serous cystadenocarcinoma, and were analyzed. Patients with ovarian cancer admitted to our hospital in 2016 were retrieved and followed up for prognosis analysis.

Results

From the datasets, for patients > 75 years old at the time of diagnosis, histologic grade and mutation count were good predictors for disease-free survival, while for patients > 50 years old at the time of diagnosis, histologic grade, race, fraction genome altered, and mutation count were good predictors for overall survival. In the patients (n = 38) retrieved from our hospital, the longest dimension of lesion (cm) and body weight at admission were good predictors for overall survival.

Conclusions

Those clinical factors, together with the two predictive equations, could be used to comprehensively predict the long-term prognosis of patients with ovarian cancer.

RNA-binding proteins in ovarian cancer: a novel avenue of their roles in diagnosis and treatment

Ovarian cancer (OC), an important cause of cancer-related death in women worldwide, is one of the most malignant cancers and is characterized by a poor prognosis. RNA-binding proteins (RBPs), a class of endogenous proteins that can bind to mRNAs and modify (or even determine) the amount of protein they can generate, have attracted great attention in the context of various diseases, especially cancers. Compelling studies have suggested that RBPs are aberrantly expressed in different cancer tissues and cell types, including OC tissues and cells. More specifically, RBPs can regulate proliferation, apoptosis, invasion, metastasis, tumorigenesis and chemosensitivity and serve as potential therapeutic targets in OC. Herein, we summarize what is currently known about the biogenesis, molecular functions and potential roles of human RBPs in OC and their prospects for application in the clinical treatment of OC.

The RNA-Binding Motif Protein Family in Cancer: Friend or Foe?

The RNA-binding motif (RBM) proteins are a class of RNA-binding proteins named, containing RNA-recognition motifs (RRMs), RNA-binding domains, and ribonucleoprotein motifs. RBM proteins are involved in RNA metabolism, including splicing, transport, translation, and stability. Many studies have found that aberrant expression and dysregulated function of RBM proteins family members are closely related to the occurrence and development of cancers. This review summarizes the role of RBM proteins family genes in cancers, including their roles in cancer occurrence and cell proliferation, migration, and apoptosis. It is essential to understand the mechanisms of these proteins in tumorigenesis and development, and to identify new therapeutic targets and prognostic markers.