miR-203 is an independent molecular predictor of prognosis and treatment outcome in ovarian cancer: a multi-institutional study

Micro RNA Dysregulation in Keratinocyte Carcinomas: Clinical Evidence, Functional Impact, and Future Directions

The keratinocyte carcinomas, basal cell carcinoma (BCC), and cutaneous squamous cell carcinoma (cSCC), are the most common cancers in humans. Recently, an increasing body of literature has investigated the role of miRNAs in keratinocyte carcinoma pathogenesis, progression and their use as therapeutic agents and targets, or biomarkers. However, there is very little consistency in the literature regarding the identity of and/or role of individual miRNAs in cSCC (and to a lesser extent BCC) biology. miRNA analyses that combine clinical evidence with experimental elucidation of targets and functional impact provide far more compelling evidence than studies purely based on clinical findings or bioinformatic analyses. In this study, we review the clinical evidence associated with miRNA dysregulation in KCs, assessing the quality of validation evidence provided, identify gaps, and provide recommendations for future studies based on relevant studies that investigated miRNA levels in human cSCC and BCC. Furthermore, we demonstrate how miRNAs contribute to the regulation of a diverse network of cellular functions, and that large-scale changes in tumor cell biology can be attributed to miRNA dysregulation. We highlight the need for further studies investigating the role of miRNAs as communicators between different cell types in the tumor microenvironment. Finally, we explore the clinical benefits of miRNAs as biomarkers of keratinocyte carcinoma prognosis and treatment.

microRNA-203 Targets Insulin-Like Growth Factor Receptor 1 to Inhibit Trophoblast Vascular Remodeling to Augment Preeclampsia

OBJECTIVE

Preeclampsia (PE) is a pregnancy-specific condition featured by high blood pressure, edema, and proteinuria. Research about the role of microRNA (miR)-203 in PE remains insufficient. This experiment is designed to investigate the specific role of miR-203 in trophoblasts in PE.

STUDY DESIGN

miR-203 expression in placenta tissues of normal pregnant women and PE patients was examined to analyze the relevance between miR-203 and PE diagnostic efficiency and between miR-203 and blood pressure (systolic pressure and diastolic pressure) and proteinuria of PE patients. miR-203 expression was downregulated in hypoxia-cultured trophoblasts using miR-203 inhibitor to assess matrix metalloproteinase-9 (MMP-9) level. Then, the angiogenesis of trophoblasts with different treatments was determined. Subsequently, the target relation between miR-203 and insulin-like growth factor receptor 1 (IGF-1R) was predicted and verified. Additionally, the effect of IGF-1R in the mechanism of miR-203 modulating trophoblast vascular remodeling was detected.

RESULTS

miR-203 was overexpressed in the placenta of PE patients and it acted as a promising diagnostic indicator for PE. Moreover, miR-203 was positively associated with blood pressure (systolic pressure and diastolic pressure) and proteinuria of PE patients. miR-203 silencing in hypoxia-cultured trophoblasts enhanced trophoblast vascular remodeling. Mechanically, miR-203 bound to IGF-1R to suppress its transcription. IGF-1R downregulation counteracted the promotive effect of miR-203 silencing on trophoblast vascular remodeling.

CONCLUSION

miR-203 was overexpressed in PE, and it targeted IGF-1R to limit trophoblast vascular remodeling.

KEY POINTS

· miR-203 is overexpressed in the placenta of PE patients.. · miR-203 acts as a potential diagnostic marker for PE.. · miR-203 targets IGF-1R to reduce trophoblast vascular remodeling in PE..

Repression of miR-146a in predicting poor treatment outcome in triple-negative breast cancer

OBJECTIVES

In the era of precision medicine, the highly aggressive and heterogenous triple-negative breast cancer (TNBC) is still characterized by limited options to support personalized prognosis and guide therapeutic interventions. Thereafter, the aim of the present study has been the thorough evaluation of miR-146a as a novel molecular indicator of TNBC prognosis and treatment outcome, utilizing four independent TNBC cohorts.

DESIGN & METHODS

miR-146a levels were clinically evaluated in our screening (n = 122) and three external validation TNBC cohorts (de Rinaldis et al. 2013, n = 114; Jézéquel et al. 2015, n = 107; TCGA, n = 180). Analysis of miR-146a and validated gene targets was performed in Jézéquel et al. and TCGA validation cohorts. Patients' survival, recurrence and metastasis were determined as clinical endpoints for the survival analysis. Internal validation was performed by bootstrap analysis and clinical net benefit was evaluated by decision curve analysis.

RESULTS

Reduction of miR-146a is strongly associated with patients' poor survival and can predict post-treatment disease early-recurrence, independently of tumor size, lymph node status, histological grade and patients' age. The analysis of the external validation cohorts corroborated the unfavorable nature of miR-146a repression regarding patients' survival and, strikingly, unveiled the ability of miR-146a to predict TNBC metastasis. Combined assessment of miR-146a levels and lymph node status resulted in superior risk-stratification of TNBC patients and higher clinical benefit regarding disease prognosis and post-treatment outcome. Ultimately, miR-146a was negatively associated with EGFR and SOX2 expression in TNBC.

CONCLUSIONS

miR-146a evaluation could ameliorate personalized prognosis and support precision medicine decisions in TNBC.

tRNA-derived small RNA 3'U-tRFValCAC promotes tumour migration and early progression in ovarian cancer

INTRODUCTION

Despite recent advances in epithelial ovarian cancer (EOC) management, the highly heterogenous histological/molecular tumour background and patients' treatment response obstructs personalised prognosis and therapeutics. Herein, we have studied the role and clinical utility of the novel subclass of tRNA-derived small RNA fragments emerging via 3'-trailer processing of pre-tRNAs (3'U-tRFs) in EOC.

METHODS

SK-OV-3 and OVCAR-3 cells were used for in vitro study. Following transfection, cell growth and migration were assessed by CCK8 and wound healing assays, respectively. 3'U-tRFs levels were assessed by reverse transcription quantitative PCR (RT-qPCR), following 3'-end RNA polyadenylation. A screening (OVCAD, n = 100) and institutionally independent validation (TU Munich, n = 103) cohorts were employed for survival analysis using disease progression and patients' death as clinical end-points. Bootstrap analysis was performed for internal validation, and decision curve analysis was used to evaluate clinical benefit on disease prognosis.

RESULTS

Following primary clinical assessment, target prediction and gene ontology analyses, the 3'U-tRF^ValCAC (derived from pre-tRNA^ValCAC) was highlighted to regulate cell proliferation and adhesion, and to correlate with inferior patients' outcome. 3'U-tRF^ValCAC transfection of SK-OV-3 and OVCAR-3 cells resulted in significantly increased cell growth and migration, in a dose-dependent manner. Elevated tumour 3'U-tRF^ValCAC levels were associated with significantly higher risk for early progression and worse survival following first-line platinum-based chemotherapy, independently of patients' clinicopathological data, chemotherapy response, and residual tumour. Interestingly, 3'U-tRF^ValCAC-fitted multivariate models improved risk stratification and provided superior clinical net benefit in prediction of treatment outcome compared to disease established markers.

CONCLUSIONS

3'U-tRF^ValCAC promotes tumour cell growth and migration and supports modern risk stratification and prognosis in EOC.

A diagnostic miRNA panel to detect recurrence of ovarian cancer through artificial intelligence approaches

BACKGROUND

Ovarian Cancer (OC) is the deadliest gynecology malignancy, whose high recurrence rate in OC patients is a challenging object. Therefore, having deep insights into the genetic and molecular mechanisms of OC recurrence can improve the target therapeutic procedures. This study aimed to discover crucial miRNAs for the detection of tumor recurrence in OC by artificial intelligence approaches.

METHOD

Through the ANOVA feature selection method, we selected 100 candidate miRNAs among 588 miRNAs. For their classification, a deep-learning model was employed to validate the significance of the candidate miRNAs. The accuracy, F1-score (high-risk), and AUC-ROC of classification test data based on the 100 miRNAs were 73%, 0.81, and 0.65, respectively. Association rule mining was used to discover hidden relations among the selected miRNAs.

RESULT

Five miRNAs, including miR-1914, miR-203, miR-135a-2, miR-149, and miR-9-1, were identified as the most frequent items among high-risk association rules. The identified miRNAs may target genes/proteins involved in epithelial-mesenchymal transition (EMT), resistance to therapy, and cancer stem cells; being responsible for the heterogeneity and plasticity of the tumor. Our conclusion presents mir-1914 as the significant candidate miRNA and the most frequent item. Current knowledge indicates that the dysregulated miR-1914 may function as a tumor suppressor or oncogene in the development of cancer.

CONCLUSION

These candidate miRNAs can be considered a powerful tool in the diagnosis of OC recurrence. We hypothesize that mir-1914 might open a new line of research in the realm of managing the recurrence of OC and could be a significant factor in triggering OC recurrence.

Small Non-Coding RNAs in Human Cancer

Small non-coding RNAs are widespread in the biological world and have been extensively explored over the past decades. Their fundamental roles in human health and disease are increasingly appreciated. Furthermore, a growing number of studies have investigated the functions of small non-coding RNAs in cancer initiation and progression. In this review, we provide an overview of the biogenesis of small non-coding RNAs with a focus on microRNAs, PIWI-interacting RNAs, and a new class of tRNA-derived small RNAs. We discuss their biological functions in human cancer and highlight their clinical application as molecular biomarkers or therapeutic targets.

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.

tRNAGlyGCC-Derived Internal Fragment (i-tRF-GlyGCC) in Ovarian Cancer Treatment Outcome and Progression

Epithelial ovarian cancer (EOC) remains a highly-lethal gynecological malignancy, characterized by frequent recurrence, chemotherapy resistance and poor 5-year survival. Identifying novel predictive molecular markers remains an overdue challenge in the disease's clinical management. Herein, in silico analysis of TCGA-OV highlighted the tRNA-derived internal fragment (i-tRF-GlyGCC) among the most abundant tRFs in ovarian tumors, while target prediction and gene ontology (GO) enrichment analysis predicted its implication in key biological processes. Thereafter, i-tRF-GlyGCC levels were quantified in a screening EOC (n = 98) and an institutionally-independent serous ovarian cancer (SOC) validation cohort (n = 100, OVCAD multicenter study). Disease progression and patient death were used as clinical endpoints for the survival analysis. Internal validation was performed by bootstrap analysis and the clinical net benefit was estimated by decision curve analysis. The analysis highlighted the significant association of i-tRF-GlyGCC with advanced FIGO stages, suboptimal debulking and most importantly, with early progression and poor overall survival of EOC patients. The OVCAD validation cohort corroborated the unfavorable predictive value of i-tRF-GlyGCC in EOC. Ultimately, evaluation of i-tRF-GlyGCC with the established/clinically used prognostic markers offered superior patient risk-stratification and enhanced clinical benefit in EOC prognosis. In conclusion, i-tRF-GlyGCC assessment could aid towards personalized prognosis and support precision medicine decisions in EOC.

ITPKA induces cell senescence, inhibits ovarian cancer tumorigenesis and can be downregulated by miR-203

Overcoming senescence is a feature of ovarian cancer cells; however, the mechanisms underlying senescence regulation in ovarian cancer cells remain largely unknown. In this study, we found that ITPKA was downregulated in ovarian cancer samples, and the lower expression correlated with poor survival. Overexpression of ITPKA inhibited the anchorage-independent growth of ovarian cancer cells and induced senescence. However, knockdown of ITPKA promoted the anchorage-independent growth of ovarian cancer cells and inhibited senescence. Mechanistically, ITPKA was found to interact with MDM2, which stabilized P53, an essential regulator of senescence. Moreover, ITPKA was negatively regulated by miR-203, a microRNA that has been previously reported to be upregulated in ovarian cancer. Taken together, the results of this study demonstrated the tumor suppressive roles of ITPKA in ovarian cancer and provided a good explanation for the oncogenic roles of miR-203.

miR-181a overexpression predicts the poor treatment response and early-progression of serous ovarian cancer patients

Ovarian cancer (OC) remains a leading cause of gynecological cancer-related death worldwide, characterized by poor 5-year survival. Molecular markers could serve as crucial tools of personalized prognosis and therapy. Herein, we present miR-181a as novel predictor of OC prognosis, using five independent OC cohorts. In particular, a screening (n = 81) and an institutionally independent validation (n = 100, OVCAD multicenter study) serous OC (SOC) cohorts were analyzed. Bagnoli et al (2016) OC179 (n = 124) to OC133 (n = 100) and TCGA (n = 489) served as external validation cohorts. Patients' survival and disease progression were assessed as clinical endpoint events. Bootstrap analysis was performed for internal validation and decision curve analysis was utilized to evaluate clinical benefit. miR-181a overexpression was unveiled as powerful and independent molecular predictor of patients' poor survival and higher risk for disease progression after debulking surgery and platinum-based chemotherapy. Analysis of the OVCAD institutionally independent cohort, as well as of Bagnoli et al. and TCGA external cohorts further confirmed the unfavorable prognostic nature of miR-181a overexpression in SOC. Strikingly, multivariate prognostic models incorporating miR-181a with established disease markers clearly improved patients' risk-stratification and offered superior clinical benefit in OC prognostication. Conclusively, miR-181a evaluation could augment prognostic accuracy and support precision medicine decisions in OC.

Inflammatory Breast Carcinoma: Elevated microRNA miR-181b-5p and Reduced miR-200b-3p, miR-200c-3p, and miR-203a-3p Expression as Potential Biomarkers with Diagnostic Value

Inflammatory breast cancer (IBC) is a rare yet aggressive breast cancer variant, associated with a poor prognosis. The major challenge for IBC is misdiagnosis due to the lack of molecular biomarkers. We profiled dysregulated expression of microRNAs (miRNAs) in primary samples of IBC and non-IBC tumors using human breast cancer miRNA PCR array. We discovered that 28 miRNAs were dysregulated (10 were upregulated, while 18 were underexpressed) in IBC vs. non-IBC tumors. We identified 128 hub genes, which are putative targets of the differentially expressed miRNAs and modulate important cancer biological processes. Furthermore, our qPCR analysis independently verified a significantly upregulated expression of miR-181b-5p, whereas a significant downregulation of miR-200b-3p, miR-200c-3p, and miR-203a-3p was detected in IBC tumors. Receiver operating characteristic (ROC) curves implied that the four miRNAs individually had a diagnostic accuracy in discriminating patients with IBC from non-IBC and that miR-203a-3p had the highest diagnostic value with an AUC of 0.821. Interestingly, a combination of miR-181b-5p, miR-200b-3p, and miR-200c-3p robustly improved the diagnostic accuracy, with an area under the curve (AUC) of 0.897. Intriguingly, qPCR revealed that the expression of zinc finger E box-binding homeobox 2 (ZEB2) mRNA, the putative target of miR-200b-3p, miR-200c-3p, and miR-203a-3p, was upregulated in IBC tumors. Overall, this study identified a set of miRNAs serving as potential biomarkers with diagnostic relevance for IBC.