miR-206 as a prognostic and sensitivity biomarker for platinum chemotherapy in epithelial ovarian cancer

Perspective and Therapeutic Potential of the Noncoding RNA-Connexin Axis

Noncoding RNAs (ncRNAs) are a class of nucleotide sequences that cannot be translated into peptides. ncRNAs can function post-transcriptionally by splicing complementary sequences of mRNAs or other ncRNAs or by directly engaging in protein interactions. Over the past few decades, the pervasiveness of ncRNAs in cell physiology and their pivotal roles in various diseases have been identified. One target regulated by ncRNAs is connexin (Cx), a protein that forms gap junctions and hemichannels and facilitates intercellular molecule exchange. The aberrant expression and misdistribution of connexins have been implicated in central nervous system diseases, cardiovascular diseases, bone diseases, and cancer. Current databases and technologies have enabled researchers to identify the direct or indirect relationships between ncRNAs and connexins, thereby elucidating their correlation with diseases. In this review, we selected the literature published in the past five years concerning disorders regulated by ncRNAs via corresponding connexins. Among it, microRNAs that regulate the expression of Cx43 play a crucial role in disease development and are predominantly reviewed. The distinctive perspective of the ncRNA-Cx axis interprets pathology in an epigenetic manner and is expected to motivate research for the development of biomarkers and therapeutics.

Post-transcriptional regulation of myogenic transcription factors during muscle development and pathogenesis

The transcriptional regulation of skeletal muscle (SKM) development (myogenesis) has been documented for over 3 decades and served as a paradigm for tissue-specific cell type determination and differentiation. Myogenic stem cells (MuSC) in embryos and adult SKM are regulated by the transcription factors Pax3 and Pax7 for their stem cell characteristics, while their lineage determination and terminal differentiation are both dictated by the myogenic regulatory factors (MRF) that comprise Mrf4, Myf5, Myogenin, and MyoD. The myocyte enhancer factor Mef2c is activated by MRF during terminal differentiation and collaborates with them to promote myoblast fusion and differentiation. Recent studies have found critical regulation of these myogenic transcription factors at mRNA level, including subcellular localization, stability, and translational regulation. Therefore, the regulation of Pax3/7, MRFs and Mef2c mRNAs by RNA-binding factors and non-coding RNAs (ncRNA), including microRNAs and long non-coding RNAs (lncRNA), will be the focus of this review and the impact of this regulation on myogenesis will be further addressed. Interestingly, the stem cell characteristics of MuSC has been found to be critically regulated by ncRNAs, implying the involvement of ncRNAs in SKM homeostasis and regeneration. Current studies have further identified that some ncRNAs are implicated in the etiology of some SKM diseases and can serve as valuable tools/indicators for prediction of prognosis. The roles of ncRNAs in the MuSC biology and SKM disease etiology will also be discussed in this review.

Non-coding RNAs in gynecologic cancer

The term "gynecologic cancer" pertains to neoplasms impacting the reproductive tissues and organs of women encompassing the endometrium, vagina, cervix, uterus, vulva, and ovaries. The progression of gynecologic cancer is linked to various molecular mechanisms. Historically, cancer research primarily focused on protein-coding genes. However, recent years have unveiled the involvement of non-coding RNAs (ncRNAs), including microRNAs, long non-coding RNAs (LncRNAs), and circular RNAs, in modulating cellular functions within gynecological cancer. Substantial evidence suggests that ncRNAs may wield a dual role in gynecological cancer, acting as either oncogenic or tumor-suppressive agents. Numerous clinical trials are presently investigating the roles of ncRNAs as biomarkers and therapeutic agents. These endeavors may introduce a fresh perspective on the diagnosis and treatment of gynecological cancer. In this overview, we highlight some of the ncRNAs associated with gynecological cancers.

MicroRNA-206 in human cancer: Mechanistic and clinical perspectives

MicroRNAs (miRNAs), small non-coding RNAs approximately 20-25 nt in length, play important roles via directly binding to the corresponding 3' UTR of target mRNAs. Recent research has shown that miRNAs cover a wide range of diseases, including several types of cancer. It is interesting to note that miR-206 operates as a tumor suppressor and is downregulated in abundant cancer types, such as breast cancer, lung cancer, colorectal cancer, and so forth. Interestingly, a growing number of studies have also reported that miR-206 could function as an oncogene and promote tumor cell proliferation. Thereby, miR-206 may act as either oncogenes or tumor suppressors under certain conditions. In addition, it was widely acknowledged that restoring tumor-suppressor miR-206 has emerged as an unconventional cancer therapy strategy. Therefore, miR-206 might be a newfangled procedure for achieving a more significant treatment outcome for cancer patients. This review summarizes the role of miR-206 in several cancer types and the contributions made between miR-206 and the diagnosis, treatment, and drug resistance of solid tumors.

Emerging roles and mechanisms of miR-206 in human disorders: a comprehensive review

As a member of the miR-1 family, miR-206 is located between IL-17 and PKHD1 genes in human. This miRNA has been shown to be involved in the pathogenic processes in a variety of human disorders including cancers, amyotrophic lateral sclerosis, Alzheimer's disease, atherosclerosis, bronchopulmonary dysplasia, coronary artery disease, chronic obstructive pulmonary disease, epilepsy, nonalcoholic fatty liver disease, Hirschsprung disease, muscular dystrophies, pulmonary arterial hypertension, sepsis and ulcerative colitis. In the current review, we summarize the role of miR-206 in both malignant and non-malignant situations and explain its possible therapeutic implications.

The Potential of MicroRNAs as Clinical Biomarkers to Aid Ovarian Cancer Diagnosis and Treatment

Ovarian cancer is a commonly diagnosed malignancy in women. When diagnosed at an early stage, survival outcomes are favourable for the vast majority, with up to 90% of ovarian cancer patients being free of disease at 5 years follow-up. Unfortunately, ovarian cancer is typically diagnosed at an advanced stage due to the majority of patients remaining asymptomatic until the cancer has metastasised, resulting in poor outcomes for the majority. While the molecular era has facilitated the subclassification of the disease into distinct clinical subtypes, ovarian cancer remains managed and treated as a single disease entity. MicroRNAs (miRNAs) are small (19-25 nucleotides), endogenous molecules which are integral to regulating gene expression. Aberrant miRNA expression profiles have been described in several cancers, and have been implicated to be useful biomarkers which may aid cancer diagnostics and treatment. Several preliminary studies have identified candidate tumour suppressor and oncogenic miRNAs which may be involved in the development and progression of ovarian cancer, highlighting their candidacy as oncological biomarkers; understanding the mechanisms by which these miRNAs regulate the key processes involved in oncogenesis can improve our overall understanding of cancer development and identify novel biomarkers and therapeutic targets. This review highlights the potential role of miRNAs which may be utilised to aid diagnosis, estimate prognosis and enhance therapeutic strategies in the management of primary ovarian cancer.

Recent advances of non-coding RNAs in ovarian cancer prognosis and therapeutics

Ovarian cancer (OC) is the third most common gynecological malignancy with the highest mortality worldwide. OC is usually diagnosed at an advanced stage, and the standard treatment is surgery combined with platinum or paclitaxel chemotherapy. However, chemoresistance inevitably appears coupled with the easy recurrence and poor prognosis. Thus, early diagnosis, predicting prognosis, and reducing chemoresistance are of great significance for controlling the progression and improving treatment effects of OC. Recently, much insight has been gained into the non-coding RNA (ncRNA) that is employed for RNAs but does not encode a protein, and many types of ncRNAs have been characterized including long-chain non-coding RNAs, microRNAs, and circular RNAs. Accumulating evidence indicates these ncRNAs play very active roles in OC progression and metastasis. In this review, we briefly discuss the ncRNAs as biomarkers for OC prognosis. We focus on the recent advances of ncRNAs as therapeutic targets in preventing OC metastasis, chemoresistance, immune escape, and metabolism. The novel strategies for ncRNAs-targeted therapy are also exploited for improving the survival of OC patients.

Identification of an Immune Gene-Based Cisplatin Response Model and CD27 as a Therapeutic Target against Cisplatin Resistance for Ovarian Cancer

Objective. Evidence demonstrates that the immune microenvironment is extensively associated with chemotherapy response of ovarian cancer (OV). Herein, this study is aimed at establishing a cisplatin response prediction model for OV on the basis of immune genes. Methods. The expression profiles of cisplatin-sensitive and cisplatin-resistant OV specimens were integrated from multiple public datasets. The abundance scores of 22 immune cells were estimated with CIBERSORT algorithm. Differentially expressed immune genes (DEGs) were determined between cisplatin-sensitive and cisplatin-resistant groups. Thereafter, a cisplatin response model was constructed based on prognostic DEGs with logistic regression analysis. The prediction performance was validated in independent cohorts. The possible relationships between the model and immunotherapy were then assessed. Results. Treg scores were significantly decreased in cisplatin-resistant than cisplatin-sensitive OV specimens, with the opposite results for naïve B cells and activated dendritic cells. Fourteen prognostic DEGs were identified and used to develop a cisplatin-response model. The response scores, estimated by the model, showed favorable performance in discriminating cisplatin-response and nonresponse samples. The response scores also presented significantly negative correlations with three well-known cisplatin-resistant pathways and a positive correlation with the expression of CD274 (PD-L1). Moreover, the decreased CD27 expression was observed in cisplatin-resistant groups, and OV specimens with higher CD27 expressions were more sensitive to cisplatin treatment. Conclusion. Altogether, our findings proposed a cisplatin response prediction model and identified CD27 that might be involved in cisplatin resistance. Further investigations suggested that CD27 could be a promising immunotherapeutic target for cisplatin-resistant subset of OV.

Establish of an Initial Platinum-Resistance Predictor in High-Grade Serous Ovarian Cancer Patients Regardless of Homologous Recombination Deficiency Status

Backgrounds

Ovarian cancer (OC) is still the leading aggressive and lethal disease of gynecological cancers, and platinum-based regimes are the standard treatments. However, nearly 20%–30% of patients with OC are initial platinum resistant (IPR), and there is a lack of valid tools to predict whether they will be primary platinum resistant or not prior to chemotherapy.

Methods

Transcriptome data from The Cancer Genome Atlas (TCGA) was downloaded as the training data, and transcriptome data of GSE15622, GSE102073, GSE19829, and GSE26712 were retrieved from Gene Expression Omnibus (GEO) as the validation cohorts. Differentially expressed genes (DEGs) were selected between platinum-sensitive and platinum-resistant patients from the training cohort, and multiple machine-learning algorithms [including random forest, XGboost, and least absolute shrinkage and selection operator (LASSO) regression] were utilized to determine the candidate genes from DEGs. Then, we applied logistic regression to establish the IPR signature based on the expression. Finally, comprehensive clinical, genomic, and survival feature were analyzed to understand the application value of the established IPR signature.

Results

A total of 532 DEGs were identified between platinum-resistant and platinum-sensitive samples, and 11 of them were shared by these three-machine learning algorithms and utilized to construct an IPR prediction signature. The area under receiver operating characteristic curve (AUC) was 0.841 and 0.796 in the training and validation cohorts, respectively. Notably, the prediction capacity of this signature was stable and robust regardless of the patients’ homologous recombination deficiency (HRD) and mutation burden status. Meanwhile, the genomic feature was concordant between samples with high- or low-IPR signature, except a significantly higher prevalence of gain at Chr19q.12 (regions including CCNE1) in the high-IPR signature samples. The efficacy of prediction of platinum resistance of IPR signature successfully transferred to the precise survival prediction, with the AUC of 0.71, 0.72, and 0.66 to predict 1-, 3-, and 5-year survival, respectively. At last, we found a significantly different tumor-infiltrated lymphocytes feature, including lower abundance of CD4+ naive T cells in the samples with high-IPR signature. A relatively lower tumor immune dysfunction and exclusion (TIDE) value and more sensitivity to multiple therapies including Gefitinib may suggest the potency to transfer from platinum-based therapy to immunotherapy or target therapies in patients with high-IPR signature.

Conclusion

Our study established an IPR signature based on the expression of 11 genes that could stably and robustly distinguish OC patients with IPR and/or poor outcomes, which may guide therapeutic regimes tailoring.

SIAH1 reverses chemoresistance in epithelial ovarian cancer via ubiquitination of YBX-1

Chemoresistance is a severe outcome among patients with epithelial ovarian cancer (EOC) that leads to a poor prognosis. YBX-1 has been shown to cause treatment failure and cancer progression in EOC. However, strategies that directly target YBX-1 are not yet conceivable. Here, we identified that SIAH1 which was downregulated in chemoresistant EOC samples and cell lines functioned as novel E3 ligases to trigger degradation of YBX-1 at cytoplasm by RING finger domain. Mechanistic studies show that YBX-1 was ubiquitinated by SIAH1 at lys304 that lead to the instability of its target m5C-modified mRNAs, thus sensitized EOC cells to cDDP. Overexpression of SIAH1 enhanced the antitumor efficacy of cisplatin in vitro and in vivo, which were partially impaired by ectopic expression of YBX-1 or depletion of YBX-1 ubiquitination. In summary, our data identify the SIAH1/YBX-1 interaction as a therapeutic target for overcoming EOC chemoresistance.

Recognition of the Possible miRNA-mRNA Controlling Network in Stroke by Bioinformatics Examination

BACKGROUND

Based on the latest research of WHO, it has been revealed that more than 15 million people suffer from stroke every year worldwide. Of these 15 million people, 6 million succumb to death, and 5 million get permanently disabled. This is the prime reason for the substantial economic burden on all parts of the world.

METHODS

These data have been obtained from the GEO database, and the GEO2R tool was used to find out the differentially expressed miRNAs (DEMs) between the stroke and normal patients' blood. FunRich and miRNet were considered to find potential upstream transcription factors and downstream target genes of candidate EMRs. Next, we use GO annotation and KEGG pathway enrichment. Target genes were analyzed with the help of the R software. Then, the STRING database and Cytoscape software were used to conduct PPI and DEM-hub gene networks. Finally, GSE58294 was used to estimate the hub gene expressions.

RESULTS

Six DEMs in total were selected out from GSE95204 and GSE117064 datasets. 663 DEMs' target genes were predicted, and NRF1, EGR1, MYC, YY1, E2F1, SP4, and SP1 were predicted as an upstream transcription factor for DEMs' target genes. Target genes of DEMs were primarily augmented in the PI3K-Akt signaling pathway and p53 signaling pathway. The network construction of DEM hygiene is potentially modulated by hsa-miR-3591-5p, hsa-miR-548as-3p, hsa-miR-206, and hsa-miR-4503 hub genes which were found among the top 10 of the hub genes. Among the top 10 hub genes, justification of CTNNB1, PTEN, ESR1, CCND1, KRAS, AKT1, CCND2, CDKN1B, and MYCN was constant with that in the GSE58294 dataset.

CONCLUSION

In summary, our research first constructs the miRNA-mRNA network in stroke, which probably renders an awakening purview into the pathogenesis and cure of stroke.

Epigenetic Mechanisms and Therapeutic Targets in Chemoresistant High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an important area of research, as the major obstacle to the treatment of HGSOC is the development of resistance to platinum chemotherapy. The cause of chemoresistance is still largely unknown and may be due to epigenetics modifications that are driving HGSOC metastasis and treatment resistance. The identification of epigenetic changes in chemoresistant HGSOC enables the development of epigenetic modulating drugs that may be used to improve outcomes. Several epigenetic modulating drugs have displayed promise as drug targets for HGSOC, such as demethylating agents azacitidine and decitabine. Others, such as histone deacetylase inhibitors and miRNA-targeting therapies, demonstrated promising preclinical results but resulted in off-target side effects in clinical trials. This article reviews the epigenetic modifications identified in chemoresistant HGSOC and clinical trials utilizing epigenetic therapies in HGSOC.

Predictive value of RAD51 on the survival and drug responsiveness of ovarian cancer

Background

Ovarian cancer has greatly endangered and deteriorated female health conditions worldwide. Refinement of predictive biomarkers could enable patient stratification and help optimize disease management.

Methods

RAD51 expression profile, target-disease associations, and fitness scores of RAD51 were analyzed in ovarian cancer using bioinformatic analysis. To further identify its role, gene enrichment analysis was performed, and a regulatory network was constructed. Survival analysis and drug sensitivity assay were performed to evaluate the effect of RAD51 expression on ovarian cancer prognosis. The predictive value of RAD51 was then confirmed in a validation cohort immunohistochemically.

Results

Ovarian cancer expressed more RAD51 than normal ovary. RAD51 conferred ovarian cancer dependency and was associated with ovarian cancer. RAD51 had extensive target-disease associations with various diseases, including ovarian cancer. Genes that correlate with and interact with RAD51 were involved in DNA damage repair and drug responsiveness. High RAD51 expression indicated unfavorable survival outcomes and resistance to platinum, taxane, and PARP inhibitors in ovarian cancer. In the validation cohort (126 patients), high RAD51 expression indicated platinum resistance, and platinum-resistant patients expressed more RAD51. Patients with high RAD51 expression had shorter OS (HR = 2.968, P < 0.0001) and poorer PFS (HR = 2.838, P < 0.0001). RAD51 expression level was negatively correlated with patients’ survival length.

Conclusions

Ovarian cancer had pronounced RAD51 expression and RAD51 conferred ovarian cancer dependency. High RAD51 expression indicated poor survival and decreased drug sensitivity. RAD51 has predictive value in ovarian cancer and can be exploited as a predictive biomarker.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01953-5.