Roles of Embryonic Lethal Abnormal Vision-Like RNA Binding Proteins in Cancer and Beyond

ZBTB7A regulates LncRNA HOTAIR-mediated ELAVL1/SOX17 axis to inhibit malignancy and angiogenesis in endometrial carcinoma

BACKGROUND

Endometrial cancer (EC) is the sixth most frequent cancer in women worldwide and has higher fatality rates. The pathophysiology of EC is complex, and there are currently no reliable methods for diagnosing and treating the condition. Long non-coding RNA (lncRNA), according to mounting evidence, is vital to the pathophysiology of EC. HOTAIR is regarded as a significant prognostic indicator of EC. ZBTB7A decreased EC proliferation and migration, according to recent studies, however the underlying mechanism still needs to be clarified.

METHODS

The research utilized RT-qPCR to measure HOTAIR expression in clinical EC tissues and various EC cell lines. Kaplan-Meier survival analysis was employed to correlate HOTAIR levels with patient prognosis. Additionally, the study examined the interaction between ZBTB7A and HOTAIR using bioinformatics tools and ChIP assays. The experimental approach also involved manipulating the expression levels of HOTAIR and ZBTB7A in EC cell lines and assessing the impact on various cellular processes and gene expression.

RESULTS

The study found significantly higher levels of HOTAIR in EC tissues compared to adjacent normal tissues, with high HOTAIR expression correlating with poorer survival rates and advanced cancer characteristics. EC cell lines like HEC-1 A and KLE showed higher HOTAIR levels compared to normal cells. Knockdown of HOTAIR in these cell lines reduced proliferation, angiogenesis, and migration. ZBTB7A was found to be inversely correlated with HOTAIR, and its overexpression led to a decrease in HOTAIR levels and a reduction in malignant cell behaviors. The study also uncovered that HOTAIR interacts with ELAVL1 to regulate SOX17, which in turn activates the Wnt/β-catenin pathway, promoting malignant behaviors in EC cells.

CONCLUSION

HOTAIR is a critical regulator in EC, contributing to tumor growth and poor prognosis. Its interaction with ZBTB7A and regulation of SOX17 via the Wnt/β-catenin pathway underlines its potential as a therapeutic target.

Unravelling driver genes as potential therapeutic targets in ovarian cancer via integrated bioinformatics approach

Target-driven cancer therapy is a notable advancement in precision oncology that has been accompanied by substantial medical accomplishments. Ovarian cancer is a highly frequent neoplasm in women and exhibits significant genomic and clinical heterogeneity. In a previous publication, we presented an extensive bioinformatics study aimed at identifying specific biomarkers associated with ovarian cancer. The findings of the network analysis indicate the presence of a cluster of nine dysregulated hub genes that exhibited significance in the underlying biological processes and contributed to the initiation of ovarian cancer. Here in this research article, we are proceeding our previous research by taking all hub genes into consideration for further analysis. GEPIA2 was used to identify patterns in the expression of critical genes. The KM plotter analysis indicated that the out of all genes 5 genes are statistically significant. The cBioPortal platform was further used to investigate the frequency of genetic mutations across the board and how they affected the survival of the patients. Maximum mutation was reported by ELAVL2. In order to discover viable therapeutic candidates after competitive inhibition of ELAVL2 with small molecular drug complex, high throughput screening and docking studies were used. Five compounds were identified. Overall, our results suggest that the ELAV-like protein 2-ZINC03830554 complex was relatively stable during the molecular dynamic simulation. The five compounds that have been found can also be further examined as potential therapeutic possibilities. The combined findings suggest that ELAVL2, together with their genetic changes, can be investigated in therapeutic interventions for precision oncology, leveraging early diagnostics and target-driven therapy.

A network-based drug prioritization and combination analysis for the MEK5/ERK5 pathway in breast cancer

BACKGROUND

Prioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic perspective for preclinical drug evaluation. In the current study, a network-based approach was proposed and applied to prioritize plant polyphenols and identify potential drug combinations in breast cancer. We focused on MEK5/ERK5 signalling pathway genes, a recently identified potential drug target in cancer with roles spanning major carcinogenesis processes.

RESULTS

By constructing and identifying perturbed protein-protein interaction networks for luminal A breast cancer, plant polyphenols and drugs from transcriptome data, we first demonstrated their systemic effects on the MEK5/ERK5 signalling pathway. Subsequently, we applied a pathway-specific network pharmacology pipeline to prioritize plant polyphenols and potential drug combinations for use in breast cancer. Our analysis prioritized genistein among plant polyphenols. Drug combination simulations predicted several FDA-approved drugs in breast cancer with well-established pharmacology as candidates for target network synergistic combination with genistein. This study also highlights the concept of target network enhancer drugs, with drugs previously not well characterised in breast cancer being prioritized for use in the MEK5/ERK5 pathway in breast cancer.

CONCLUSION

This study proposes a computational framework for drug prioritization and combination with the MEK5/ERK5 signaling pathway in breast cancer. The method is flexible and provides the scientific community with a robust method that can be applied to other complex diseases.

The molecular genetics of nELAVL in brain development and disease

Embryonic development requires tight control of gene expression levels, activity, and localisation. This control is coordinated by multiple levels of regulation on DNA, RNA and protein. RNA-binding proteins (RBPs) are recognised as key regulators of post-transcriptional gene regulation, where their binding controls splicing, polyadenylation, nuclear export, mRNA stability, translation rate and decay. In brain development, the ELAVL family of RNA binding proteins undertake essential functions across spatiotemporal windows to help regulate and specify transcriptomic programmes for cell specialisation. Despite their recognised importance in neural tissues, their molecular roles and connections to pathology are less explored. Here we provide an overview of the neuronal ELAVL family, noting commonalities and differences amongst different species, their molecular characteristics, and roles in the cell. We bring together the available molecular genetics evidence to link different ELAVL proteins to phenotypes and disease, in both the brain and beyond, including ELAVL2, which is the least studied ELAVL family member. We find that ELAVL-related pathology shares a common neurological theme, but different ELAVL proteins are more strongly connected to different phenotypes, reflecting their specialised expression across time and space.

The Prognostic Role of HuR Varies Between Different Subtypes of Breast Cancer Patients: Data Mining and Retrospective Analysis

Objective

Human-antigen R (HuR) is an RNA-binding protein, which regulates the expression of several oncogenes and tumor suppressor genes through post-transcriptional mechanisms. But the role of HuR in breast cancer remains controversial. The aim of this study was to verify the association between cytoplasmic HuR level and prognosis of breast cancer patients.

Methods

Data mining from the Human Protein Atlas (HPA) and Kaplan-Meier Plotter (KMP) databases was performed. Then, 394 patients with stage I-III primary breast cancer were enrolled between January 2005 and December 2016. We investigated the association between cytoplasmic HuR level and clinicopathological characteristics or survival of these patients. Immunohistochemical analysis was performed to determine HuR expression level. SPSS 21.0 statistical software was used for analysis.

Results

In the HPA and KMP datasets, HuR protein and mRNA expression level were not significantly associated with overall survival of all breast cancer patients enrolled. Results from our 394 patients indicated that higher expression level of cytoplasmic HuR was associated with larger tumor size, lymph node positive, ER negative and triple-negative subtype. For all patients enrolled, the results indicated that compared with HuR negative patients, the DFS (disease-free survival) of HuR 1+ was longer (60.5% vs 78.8, P=0.053, HR=0.616, 95% CI: 0.378-1.005), the P value was borderline. In the triple-negative breast cancer (TNBC) subgroup, HuR positive patients had significantly longer DFS than HuR negative patients (65.5% vs 30.8%, P=0.001, HR=0.345, 95% CI: 0.180-0.658). In the HR+HER2- subgroup, HuR low (0~1+) patients had significantly longer OS than HuR high (2+~3+) patients (97.0% vs 89.5%, P=0.033, HR=2.482, 95% CI: 1.074-5.736).

Conclusion

In conclusion, our results revealed that higher expression level of HuR was related to aggressive biological characteristics which supported the findings from previous researches. In the HR+HER2- subgroup, lower HuR expression level patients had better survival time, while in the TNBC subgroup we got the opposite results. Our work indicated that HuR might play different roles in different breast cancer subtypes.

EIF4A3 induced circABCA5 promotes the gastric cancer progression by SPI1 mediated IL6/JAK2/STAT3 signaling

Gastric cancer is one of the most common malignancies of the digestive system with high mortality rates. Recent studies have demonstrated that circRNAs are novel noncoding RNAs that play vital roles in the tumorigenesis and development of gastric cancer. Our study found a novel circRNA, namely, hsa_circ_0107595 (also called circABCA5), that is overexpressed in gastric cancer based on circRNA sequencing. qPCR demonstrated its overexpression in gastric cancer specimens. The overexpression or knockdown of circABCA5 in gastric cancer cell lines was achieved by lentiviral-mediated transfection. All MTS, EdU, Transwell and migration assays and xenograft experiments demonstrated that circABCA5 could promote gastric cancer proliferation, invasion, and migration in vitro and in vivo. Mechanistically, both RIP and RNA pulldown assays confirmed that circABCA5 could bind to the SPI1 protein, upregulate SPI1 expression, and promote its nuclear translocation. SPI1 could further promote the malignant phenotype of gastric cancer by activating IL6/JAK2/STAT3 signaling. In addition, EIF4A3 could directly bind to circABCA5, promoting its stability and expression. Our study reveals that circABCA5 plays a vital role in the diagnosis and prognosis of gastric cancer and may even be developed as a molecular target for the treatment of gastric cancer.

CircKPNB1 mediates a positive feedback loop and promotes the malignant phenotypes of GSCs via TNF-α/NF-κB signaling

Glioma stem cells (GSCs) are a special kind of cells in GBM showing tumor initiation, self-renewal, and multi-lineage differentiation abilities. Finding novel circRNAs related to GSCs is of great significance for the study of glioma. qPCR, western blotting, and immunohistochemistry were used to detect the expression levels of circKPNB1, SPI1, DGCR8, and TNF-α. The expression of these molecules in GSCs was regulated by lentiviral-based infection. RNA immunoprecipitation assay, RNA pull-down, dual-luciferase reporter, and chromatin immunoprecipitation assays were used to study the direct regulation mechanisms among these molecules. All the MTS, EDU, transwell, neurosphere formation assays, ELDA assays, and xenograft experiments were used to detect the malignant phenotype of GSCs. We found a novel circRNA circKPNB1 was overexpressed in GBM and associated with GBM patients' poor prognosis. CircKPNB1 overexpression can promote the cell viabilities, proliferation, invasion, neurospheres formation abilities, and stemness of GSCs. Mechanistically, circKPNB1 regulates the protein stability and nuclear translocation of SPI1. SPI1 promotes the malignant phenotype of GSCs via TNF-α mediated NF-κB signaling. SPI1 can also transcriptionally upregulate DGCR8 expression, and the latter can maintain the stability of circKPNB1 and forms a positive feedback loop among DGCR8, circKPNB1 and SPI1. Our study found circKPNB1 was a novel oncogene in GBM and of great significance in the diagnosis and prognosis prediction of GBM and maybe a novel target for molecular targeted therapy.