Development and validation of a microRNA-based signature (MiROvaR) to predict early relapse or progression of epithelial ovarian cancer: a cohort study

Overexpression of miR-200s inhibits proliferation and invasion while increasing apoptosis in murine ovarian cancer cells

Women diagnosed with ovarian cancer frequently have a poor prognosis as their cancer is often diagnosed at more advanced stages when the cancer has metastasized. At this point surgery cannot remove all the tumor cells and while ovarian cancer cells often initially respond to chemotherapeutic agents like carboplatin and paclitaxel, resistance to these agents frequently occurs. Thus, novel therapies are required for the treatment of advanced stage ovarian cancer. One therapeutic option being explored is the regulation of non-coding RNAs such as microRNAs. An advantage of microRNAs is that they can regulate tens, hundreds and sometimes thousands of mRNAs in cells and thus may be more effective than chemotherapeutic agents or targeted therapies. To investigate the therapeutic potential of miR-200s in ovarian cancer, lentiviral vectors were used to overexpress both miR-200 clusters in two murine ovarian cancer cell lines, ID8 and 28-2. Overexpression of miR-200s reduced the expression of several mesenchymal genes and proteins, significantly inhibited proliferation as assessed by BrdU flow cytometry and significantly reduced invasion through Matrigel coated transwell inserts in both cell lines. Overexpression of miR-200s also increased basal apoptosis approximately 3-fold in both cell lines as determined by annexin V flow cytometry. Pathway analysis of RNA sequencing of control and miR-200 overexpressing ovarian cancer cells revealed that genes regulated by miR-200s were involved in processes like epithelial mesenchymal transition (EMT) and cell migration. Therefore, miR-200s can inhibit proliferation and increase apoptosis while suppressing tumor cell invasion and thus simultaneously target three key cancer pathways.

Integrated miRNA Profiling of Extracellular Vesicles from Uterine Aspirates, Malignant Ascites and Primary-Cultured Ascites Cells for Ovarian Cancer Screening

Extracellular vesicles (EVs) are of growing interest in the context of screening for highly informative cancer markers. We have previously shown that uterine aspirate EVs (UA EVs) are a promising source of ovarian cancer (OC) diagnostic markers. In this study, we first conducted an integrative analysis of EV-miRNA profiles from UA, malignant ascitic fluid (AF), and a conditioned medium of cultured ascites cells (ACs). Using three software packages, we identified 79 differentially expressed miRNAs (DE-miRNAs) in UA EVs from OC patients and healthy individuals. To narrow down this panel and select miRNAs most involved in OC pathogenesis, we aligned these molecules with the DE-miRNA sets obtained by comparing the EV-miRNA profiles from OC-related biofluids with the same control. We found that 76% of the DE-miRNAs from the identified panel are similarly altered (differentially co-expressed) in AF EVs, as are 58% in AC EVs. Interestingly, the set of miRNAs differentially co-expressed in AF and AC EVs strongly overlaps (40 out of 44 miRNAs). Finally, the application of more rigorous criteria for DE assessment, combined with the selection of miRNAs that are differentially co-expressed in all biofluids, resulted in the identification of a panel of 29 miRNAs for ovarian cancer screening.

Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test

Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations.

PREVENTION RELEVANCE

This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.

A novel serum m7G-harboring microRNA signature for cancer detection

Background: Emerging evidence points to the exceptional importance and value of m7G alteration in the diagnosis and prognosis of cancers. Nonetheless, a biomarker for precise screening of various cancer types has not yet been developed based on serum m7G-harboring miRNAs. Methods: A total of 20,702 serum samples, covering 12 cancer types and consisting of 7,768 cancer samples and 12,934 cancer-free samples were used in this study. A m7G target miRNA diagnostic signature (m7G-miRDS) was established through the least absolute shrinkage and selection operator (LASSO) analyses in a training dataset (n = 10,351), and validated in a validation dataset (n = 10,351). Results: The m7G-miRDS model, a 12 m7G-target-miRNAs signature, demonstrated high accuracy and was qualified for cancer detection. In the training and validation cohort, the area under the curve (AUC) reached 0.974 (95% CI 0.971-0.977) and 0.972 (95% CI 0.969-0.975), respectively. The m7G-miRDS showed superior sensitivity in each cancer type and had a satisfactory AUC in identifying bladder cancer, lung cancer and esophageal cancer. Additionally, the diagnostic performance of m7G-miRDS was not interfered by the gender, age and benign disease. Conclusion: Our results greatly extended the value of serum circulating miRNAs and m7G in cancer detection, and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as ncRNA modification.

Exosome-delivered miR-410-3p reverses epithelial-mesenchymal transition, migration and invasion of trophoblasts in spontaneous abortion

Current studies have indicated that insufficient trophoblast epithelial-mesenchymal transition (EMT), migration and invasion are crucial for spontaneous abortion (SA) occurrence and development. Exosomal miRNAs play significant roles in embryonic development and cellular communication. Hereon, we explored the roles of serum exosomes derived from SA patients on trophoblast EMT, migration and invasion. Exosomes were isolated from normal control (NC) patients with abortion for unplanned pregnancy and SA patients, then characterized by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and western blotting. Exosomal miRNA profiles were identified by miRNA sequencing. The effects of serum exosomes on trophoblast migration and invasion were detected by scratch wound healing and transwell assays, and other potential mechanisms were revealed by quantitative real-time PCR (RT-PCR), western blotting and dual-luciferase reporter assay. Finally, animal experiments were used to explore the effects of exosomal miR-410-3p on embryo absorption in mice. The serum exosomes from SA patients inhibited trophoblast EMT and reduced their migration and invasion ability in vitro. The miRNA sequencing showed that miR-410-3p was upregulated in SA serum exosomes. The functional experiments showed that SA serum exosomes restrained trophoblast EMT, migration and invasion by releasing miR-410-3p. Mechanistically, SA serum exosomal miR-410-3p inhibited trophoblast cell EMT, migration and invasion by targeting TNF receptor-associated factor 6 (TRAF6) at the post-transcriptional level. Besides, SA serum exosomal miR-410-3p inhibited the p38 MAPK signalling pathway by targeting TRAF6 in trophoblasts. Moreover, milk exosomes loaded with miR-410-3p mimic reached the maternal-fetal interface and aggravated embryo absorption in female mice. Clinically, miR-410-3p and TRAF6 expression were abnormal and negatively correlated in the placental villi of SA patients. Our findings indicated that exosome-derived miR-410-3p plays an important role between SA serum and trophoblasts in intercellular communication, suggesting a novel mechanism by which serum exosomal miRNA regulates trophoblasts in SA patients.

Transcriptomic analyses of ovarian clear-cell carcinoma with concurrent endometriosis

Introduction

Endometriosis, a benign inflammatory disease whereby endometrial-like tissue grows outside the uterus, is a risk factor for endometriosis-associated ovarian cancers. In particular, ovarian endometriomas, cystic lesions of deeply invasive endometriosis, are considered the precursor lesion for ovarian clear-cell carcinoma (OCCC).

Methods

To explore this transcriptomic landscape, OCCC from women with pathology-proven concurrent endometriosis (n = 4) were compared to benign endometriomas (n = 4) by bulk RNA and small-RNA sequencing.

Results

Analysis of protein-coding genes identified 2449 upregulated and 3131 downregulated protein-coding genes (DESeq2, P< 0.05, log2 fold-change > |1|) in OCCC with concurrent endometriosis compared to endometriomas. Gene set enrichment analysis showed upregulation of pathways involved in cell cycle regulation and DNA replication and downregulation of pathways involved in cytokine receptor signaling and matrisome. Comparison of pathway activation scores between the clinical samples and publicly-available datasets for OCCC cell lines revealed significant molecular similarities between OCCC with concurrent endometriosis and OVTOKO, OVISE, RMG1, OVMANA, TOV21G, IGROV1, and JHOC5 cell lines. Analysis of miRNAs revealed 64 upregulated and 61 downregulated mature miRNA molecules (DESeq2, P< 0.05, log2 fold-change > |1|). MiR-10a-5p represented over 21% of the miRNA molecules in OCCC with endometriosis and was significantly upregulated (NGS: log2fold change = 4.37, P = 2.43e-18; QPCR: 8.1-fold change, P< 0.05). Correlation between miR-10a expression level in OCCC cell lines and IC50 (50% inhibitory concentration) of carboplatin in vitro revealed a positive correlation (R2 = 0.93). MiR-10a overexpression in vitro resulted in a significant decrease in proliferation (n = 6; P< 0.05) compared to transfection with a non-targeting control miRNA. Similarly, the cell-cycle analysis revealed a significant shift in cells from S and G2 to G1 (n = 6; P< 0.0001). Bioinformatic analysis predicted that miR-10a-5p target genes that were downregulated in OCCC with endometriosis were involved in receptor signaling pathways, proliferation, and cell cycle progression. MiR-10a overexpression in vitro was correlated with decreased expression of predicted miR-10a target genes critical for proliferation, cell-cycle regulation, and cell survival including [SERPINE1 (3-fold downregulated; P< 0.05), CDK6 (2.4-fold downregulated; P< 0.05), and RAP2A (2-3-fold downregulated; P< 0.05)].

Discussion

These studies in OCCC suggest that miR-10a-5p is an impactful, potentially oncogenic molecule, which warrants further studies.

Non-coding RNAs in radiotherapy resistance: Roles and therapeutic implications in gastrointestinal cancer

Radiotherapy has become an indispensable and conventional means for patients with advanced solid tumors including gastrointestinal cancer. However, innate or acquired radiotherapy resistance remains a significant challenge and greatly limits the therapeutic effect, which results in cancer relapse and poor prognosis. Therefore, it is an urgent need to identify novel biomarkers and therapeutic targets for clarify the biological characteristics and mechanism of radiotherapy resistance. Recently, lots of studies have revealed that non-coding RNAs (ncRNAs) are the potential indicators and regulators of radiotherapy resistance via the mediation of various targets/pathways in different cancers. These findings may serve as a potential therapeutic strategy to overcome radiotherapy resistance. In this review, we will shed light on the recent findings regarding the functions and regulatory mechanisms of ncRNAs following radiotherapy, and comprehensively discuss their potential as biomarkers and therapeutic targets in radiotherapy resistance of gastrointestinal cancer.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

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.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Impairment of RAD17 Functions by miR-506-3p as a Novel Synthetic Lethal Approach Targeting DNA Repair Pathways in Ovarian Cancer

Epithelial ovarian cancer (EOC) remains the most lethal gynecological cancer and development of chemo-resistance is a major factor in disease relapse. Homologous recombination (HR) is a critical pathway for DNA double strand break repair and its deficiency is associated to a better response to DNA damage-inducing agents. Strategies to inhibit HR-mediated DNA repair is a clinical need to improve patients’ outcome. MicroRNA (miRNAs) affect most of cellular processes including response to cancer treatment. We previously showed that miR-506-3p targets RAD51, an essential HR component. In this study we demonstrated that: i) another HR component, RAD17, is also a direct target of miR-506-3p and that it is involved in mediating miR-506-3p phenotypic effects; ii) the impairment of miR-506-3p binding to RAD17 3’ UTR reverted the miR-506-3p induced platinum sensitization; iii) miR-506-3p/RAD17 axis reduces the ability of EOC cell to sense DNA damage, abrogates the G2/M cell cycle checkpoint thus delaying the G2/M cell cycle arrest likely allowing the entry into mitosis of heavily DNA-damaged cells with a consequent mitotic catastrophe; iv) RAD17 expression, regulated by miR-506-3p, is synthetically lethal with inhibitors of cell cycle checkpoint kinases Chk1 and Wee1 in platinum resistant cell line. Overall miR-506-3p expression may recapitulate a BRCAness phenotype sensitizing EOC cells to chemotherapy and helping in selecting patients susceptible to DNA damaging drugs in combination with new small molecules targeting DNA-damage repair pathway.

Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is a highly lethal gynecologic cancer, in part due to resistance to platinum-based chemotherapy reported among 20% of patients. This study aims to generate novel hypotheses of the biological mechanisms underlying chemotherapy resistance, which remain poorly understood. Differential expression analyses of mRNA- and microRNA-sequencing data from HGSOC patients of The Cancer Genome Atlas identified 21 microRNAs associated with angiogenesis and 196 mRNAs enriched for adaptive immunity and translation. Coexpression network analysis identified three microRNA networks associated with chemotherapy response enriched for lipoprotein transport and oncogenic pathways, as well as two mRNA networks enriched for ubiquitination and lipid metabolism. These network modules were replicated in two independent ovarian cancer cohorts. Moreover, integrative analyses of the mRNA/microRNA sequencing and single-nucleotide polymorphisms (SNPs) revealed potential regulation of significant mRNA transcripts by microRNAs and SNPs (expression quantitative trait loci). Thus, we report novel transcriptional networks and biological pathways associated with resistance to platinum-based chemotherapy in HGSOC patients. These results expand our understanding of the effector networks and regulators of chemotherapy response, which will help to improve the management of ovarian cancer.

The Progress of the Specific and Rapid Genetic Detection Methods for Ovarian Cancer Diagnosis and Treatment

Cancer is a public health problem that threatens human health. Due to the lack of specific and rapid diagnosis and treatment methods, the 5-year survival rate of patients has not been effectively improved in the past 10 years. Abnormal gene expression is closely related to the occurrence and development of cancer. Cancer diagnosis and treatment methods based on genetic testing have received extensive attention in recent years. It is essential to explore specific and rapid cancer genetic testing methods. Taking ovarian cancer as an example, we reviewed the progress of specific and rapid nucleic acid detection methods related to cancer risk assessment, low-abundance mutation detection, and methylation detection, to provide new strategies and ideas for related research.

Validation of MiROvaR, a microRNA-based predictor of early relapse in early stage epithelial ovarian cancer as a new strategy to optimise patients' prognostic assessment

AIM

Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but unpredictable recurrence. Accurate prediction of risk of relapse is still a major concern, essentially to avoid overtreatment. Our robust tissue-based miRNA signature named MiROvaR, predicting early EOC recurrence in mostly advanced-stage EOC patients, is here challenged in an independent cohort to extend its classifying ability in the early-stage EOC setting.

METHODS

We retrospectively selected patients who underwent comprehensive surgical staging at our institution including stages from IA to IIB. miRNA expression profile was analysed in 89 cases and MiROvaR algorithm was applied using the previously validated cut-off for patients' classification. The primary endpoint was progression-free survival (PFS) at 5 years. Complete follow-up time (median = 112 months) was also considered as secondary analysis.

RESULTS

MiROvaR was assessable on 87 cases (19 events of disease progression) and classified 68 (78%) low-risk and 19 (22%) high-risk patients. Recurrence rate at primary end-point was 39% for high-risk patients as compared to 9.5% for low-risk ones. Accordingly, their Kaplan-Meier PFS curves were significantly different at both primary and secondary analysis (p = 0.0006 and p = 0.03, respectively). While none of the prominent clinical variables had prognostic relevance, MiROvaR significantly predicted disease recurrence at the 5-year assessment (primary endpoint analysis; HR:5.43, 95%CI:1.82-16.1, p = 0.0024; AUC = 0.78, 95%CI:0.53-0.82) and at complete follow-up time (HR:2.67, 95%CI:1.04-6.8, p = 0.041; AUC:0.68, 95%CI:0.52-0.82).

CONCLUSIONS

We validated MiROvaR performance in identifying at diagnosis eEOC patients' at higher risk of early relapse thus enabling selection of the most effective therapeutic approach.

A CT-based radiomics nomogram for predicting early recurrence in patients with high-grade serous ovarian cancer

PURPOSE

To develop and validate a radiomics nomogram for predicting early recurrence in high-grade serous ovarian cancer (HGSOC) patients.

MATERIALS AND METHODS

From May 2008 to December 2019, 256 eligible HGSOC patients were enrolled and divided into training (n = 179) and test cohorts (n = 77) in a 7:3 ratio. A radiomics signature (Radscore) was selected by using recursive feature elimination based on a support vector machine (SVM-RFE) and building a radiomics model for recurrence prediction. Independent clinical risk factors were generated by univariable and multivariable Cox regression analyses. A combined model was developed based on the Radscore and independent clinical risk factors and presented as a radiomics nomogram. Its performance was assessed by AUC, Kaplan-Meier survival analysis and decision curve analysis.

RESULTS

Seven radiomics features were selected. The radiomics model yielded AUCs of 0.715 (95% CI: 0.640, 0.790) and 0.717 (95% CI: 0.600, 0.834) in the training and test cohorts, respectively. The clinical model (FIGO stage and residual disease) yielded AUCs of 0.632 and 0.691 in the training and test cohorts, respectively. The combined model demonstrated AUCs of 0.749 (95% CI: 0.678, 0.821) and 0.769 (95% CI: 0.662, 0.877) in the training and test cohorts, respectively. In the combined model, PFS was significantly shorter in the high-risk group than in the low-risk group (P < 0.0001).

CONCLUSIONS

The radiomics nomogram performed well for early individualized recurrence prediction in patients with HGSOC and can also be used to differentiate high-risk patients from low-risk patients.

Ovarian cancer: epigenetics, drug resistance, and progression

Ovarian cancer (OC) is one of the most common malignant tumors in women. OC is associated with the activation of oncogenes, the inactivation of tumor suppressor genes, and the activation of abnormal cell signaling pathways. Moreover, epigenetic processes have been found to play an important role in OC tumorigenesis. Epigenetic processes do not change DNA sequences but regulate gene expression through DNA methylation, histone modification, and non-coding RNA. This review comprehensively considers the importance of epigenetics in OC, with a focus on microRNA and long non-coding RNA. These types of RNA are promising molecular markers and therapeutic targets that may support precision medicine in OC. DNA methylation inhibitors and histone deacetylase inhibitors may be useful for such targeting, with a possible novel approach combining these two therapies. Currently, the clinical application of such epigenetic approaches is limited by multiple obstacles, including the heterogeneity of OC, insufficient sample sizes in reported studies, and non-optimized methods for detecting potential tumor markers. Nonetheless, the application of epigenetic approaches to OC patient diagnosis, treatment, and prognosis is a promising area for future clinical investigation.

Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer

Ovarian cancer is a major cause of fatality due to a gynecological malignancy. This lethality is largely due to the unspecific clinical manifestations of ovarian cancer, which lead to late detection and to high resistance to conventional therapies based on platinum. In recent years, we have advanced our understanding of the mechanisms provoking tumor relapse, and the advent of so-called omics technologies has provided exceptional tools to evaluate molecular mechanisms leading to therapy resistance in ovarian cancer. Here, we review the contribution of genomics, transcriptomics, and epigenomics techniques to our knowledge about the biology and molecular features of ovarian cancers, with a focus on therapy resistance. The use of these technologies to identify molecular markers and mechanisms leading to chemoresistance in these tumors is discussed, as well as potential further applications.

Integrated microRNA and mRNA signatures associated with overall survival in epithelial ovarian cancer

Ovarian cancer (OC), the eighth-leading cause of cancer-related death among females worldwide, is mainly represented by epithelial OC (EOC) that can be further subdivided into four subtypes: serous (75%), endometrioid (10%), clear cell (10%), and mucinous (3%). Major reasons for high mortality are the poor biological understanding of the OC mechanisms and a lack of reliable markers defining each EOC subtype. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression primarily by targeting messenger RNA (mRNA) transcripts. Their aberrant expression patterns have been associated with cancer development, including OC. However, the role of miRNAs in tumorigenesis is still to be determined, mainly due to the lack of consensus regarding optimal methodologies for identification and validation of miRNAs and their targets. Several tools for computational target prediction exist, but false interpretations remain a problem. The experimental validation of every potential miRNA-mRNA pair is not feasible, as it is laborious and expensive. In this study, we analyzed the correlation between global miRNA and mRNA expression patterns derived from microarray profiling of 197 EOC patients to identify the signatures of miRNA-mRNA interactions associated with overall survival (OS). The aim was to investigate whether these miRNA-mRNA signatures might have a prognostic value for OS in different subtypes of EOC. The content of our cohort (162 serous carcinomas, 15 endometrioid carcinomas, 11 mucinous carcinomas, and 9 clear cell carcinomas) reflects a real-world scenario of EOC. Several interaction pairs between 6 miRNAs (hsa-miR-126-3p, hsa-miR-223-3p, hsa-miR-23a-5p, hsa-miR-27a-5p, hsa-miR-486-5p, and hsa-miR-506-3p) and 8 mRNAs (ATF3, CH25H, EMP1, HBB, HBEGF, NAMPT, POSTN, and PROCR) were identified and the findings appear to be well supported by the literature. This indicates that our study has a potential to reveal miRNA-mRNA signatures relevant for EOC. Thus, the evaluation on independent cohorts will further evaluate the performance of such findings.

Multi-Omics Data Fusion for Cancer Molecular Subtyping Using Sparse Canonical Correlation Analysis

It is now clear that major malignancies are heterogeneous diseases associated with diverse molecular properties and clinical outcomes, posing a great challenge for more individualized therapy. In the last decade, cancer molecular subtyping studies were mostly based on transcriptomic profiles, ignoring heterogeneity at other (epi-)genetic levels of gene regulation. Integrating multiple types of (epi)genomic data generates a more comprehensive landscape of biological processes, providing an opportunity to better dissect cancer heterogeneity. Here, we propose sparse canonical correlation analysis for cancer classification (SCCA-CC), which projects each type of single-omics data onto a unified space for data fusion, followed by clustering and classification analysis. Without loss of generality, as case studies, we integrated two types of omics data, mRNA and miRNA profiles, for molecular classification of ovarian cancer (n = 462), and breast cancer (n = 451). The two types of omics data were projected onto a unified space using SCCA, followed by data fusion to identify cancer subtypes. The subtypes we identified recapitulated subtypes previously recognized by other groups (all P- values < 0.001), but display more significant clinical associations. Especially in ovarian cancer, the four subtypes we identified were significantly associated with overall survival, while the taxonomy previously established by TCGA did not (P- values: 0.039 vs. 0.12). The multi-omics classifiers we established can not only classify individual types of data but also demonstrated higher accuracies on the fused data. Compared with iCluster, SCCA-CC demonstrated its superiority by identifying subtypes of higher coherence, clinical relevance, and time efficiency. In conclusion, we developed an integrated bioinformatic framework SCCA-CC for cancer molecular subtyping. Using two case studies in breast and ovarian cancer, we demonstrated its effectiveness in identifying biologically meaningful and clinically relevant subtypes. SCCA-CC presented a unique advantage in its ability to classify both single-omics data and multi-omics data, which significantly extends the applicability to various data types, and making more efficient use of published omics resources.

Prognostic implications of tumour-infiltrating lymphocytes for recurrence in epithelial ovarian cancer

The recurrence of patients with epithelial ovarian cancer (EOC) is largely attributed to tumour cells escaping from the surveillance of immune cells. However, to date there is a lack of studies that have systematically evaluated the associations between the infiltration fraction of immune cells and the recurrence risk of EOC. Based on the micro-ribonucleic acid (microRNA) expression profiles of 441 EOC patients, we constructed a microRNA-based panel with recurrence prediction potential using non-negative matrix factorization consensus clustering. Then, we evaluated the association between recurrence risk and infiltration proportions among 10 immune cell types by CIBERSORT and a multivariable Cox regression model. As a result, we identified a 72-microRNA-based panel that could stratify patients into high and low risk of recurrence. The infiltration of plasma cells and M1 macrophages was consistently significantly associated with the risk of recurrence in patients with EOC. Plasma cells were significantly associated with a decreased risk of relapse [hazard ratio (HR) = 0.58, p = 0.006), while M1 macrophages were associated with an increased risk of relapse (HR = 1.59, p = 0.003). Therefore, the 72-microRNA-based panel, M1 macrophages and plasma cells may hold potential to serve as recurrence predictors of EOC patients in clinical practice.

MicroRNA characteristics in epithelial ovarian cancer

The purpose of the current study was to clarify differences in microRNA expression according to clinicopathological characteristics, and to investigate if miRNA profiles could predict cytoreductive outcome in patients with FIGO stage IIIC and IV ovarian cancer. Patients enrolled in the Pelvic Mass study between 2004 and 2010, diagnosed and surgically treated for epithelial ovarian cancer, were used for investigation. MicroRNA was profiled from tumour tissue with global microRNA microarray analysis. Differences in miRNA expression profiles were analysed according to histologic subtype, FIGO stage, tumour grade, type I or II tumours and result of primary cytoreductive surgery. One microRNA, miR-130a, which was found to be associated with serous histology and advanced FIGO stage, was also validated using data from external cohorts. Another seven microRNAs (miR-34a, miR-455-3p, miR-595, miR-1301, miR-146-5p, 193a-5p, miR-939) were found to be significantly associated with the clinicopathological characteristics (p ≤ 0.001), in our data, but mere not similarly significant when tested against external cohorts. Further validation in comparable cohorts, with microRNA profiled using newest and similar methods are warranted.

The Value of Immune-Related Genes Signature in Osteosarcoma Based on Weighted Gene Co-expression Network Analysis

Background. Osteosarcoma (OS) is a serious malignant tumor that is more common in adolescents or children under 20 years of age. This study is aimed at obtaining immune-related genes (IRGs) associated with the progression and prognosis of OS. Method. Expression profiling data and clinical data for OS were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. ESTIMATE calculates immune scores and stromal scores of samples and performs the prognostic analysis. Weighted gene coexpression network analysis (WGCNA) was used to find modules correlated with immune and stromal scores. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to explore IRGs associated with OS prognosis and construct and validate a hazard score model. Finally, we verified the expression and function of EVI2B in OS. Results. WGCNA selected twenty-eight IRGs, 10 of which were associated with OS prognosis, and LASSO further obtained three key prognostic genes. A prognostic model of EVI2B was constructed, and according to the risk score model, patients in the high-risk group had a worse prognosis than those in the low-risk group, and the prognosis was statistically significant in the high- and low-risk groups. Receiver operating characteristic (ROC) curves were used to assess the prognostic model’s accuracy and externally validate the independent GSE21257 cohort. The results of immunohistochemical staining and qPCR showed that EVI2B was a tumor suppressor gene. The differential genes in the high- and low-risk groups were analyzed by enrichment analysis of GO and KEGG, indicating that the EVI2B model is associated with immune response. Conclusion. In this study, IRG EVI2B is closely related to OS’s prognosis and can be used as a potential biomarker for prognosis and treatment of OS.

Identification of the miRNA signature associated with survival in patients with ovarian cancer

Ovarian cancer is a major gynaecological malignant tumor associated with a high mortality rate. Identifying survival-related variants may improve treatment and survival in patients with ovarian cancer. In this work, we proposed a support vector regression (SVR)-based method called OV-SURV, which is incorporated with an inheritable bi-objective combinatorial genetic algorithm for feature selection to identify a miRNA signature associated with survival in patients with ovarian cancer. There were 209 patients with miRNA expression profiles and survival information of ovarian cancer retrieved from The Cancer Genome Atlas database. OV-SURV achieved a mean correlation coefficient of 0.77±0.01and a mean absolute error of 0.69±0.02 years using 10-fold cross-validation. Analysis of the top ranked miRNAs revealed that the miRNAs, hsa-let-7f, hsa-miR-1237, hsa-miR-98, hsa-miR-933, and hsa-miR-889, were significantly associated with the survival in patients with ovarian cancer. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that four of these miRNAs, hsa-miR-182, hsa-miR-34a, hsa-miR-342, and hsa-miR-1304, were highly enriched in fatty acid biosynthesis, and the five miRNAs, hsa-let-7f, hsa-miR-34a, hsa-miR-342, hsa-miR-1304, and hsa-miR-24, were highly enriched in fatty acid metabolism. The prediction model with the identified miRNA signature consisting of prognostic biomarkers can benefit therapeutic decision making of ovarian cancer.

Development of Aptamer-Based Molecular Tools for Rapid Intraoperative Diagnosis and In Vivo Imaging of Serous Ovarian Cancer

Diagnosis and treatment of ovarian cancer are based on intraoperative pathology and debulking surgery. The development of a novel molecular tool is significant for rapid intraoperative pathologic diagnosis, which instructs the decision-making on excision surgery and effective chemotherapy. In this work, we represent a DNA aptamer named mApoc46, which is generated from cell-SELEX by targeting patient-derived primary serous ovarian cancer (pSOC) cells. An average dissociation constant (K_d) was determined to be 0.15 ± 0.05 μM by flow cytometry. The mApoc46 aptamer displays a robust specificity to pSOC cells. Labeled with FAM, mApoc46 can selectively stain living pSOC cells in 30 min without staining commercial OC cell lines and cell lines associated with other cancers. Interestingly, FAM-mApoc46 displayed superb selectivity toward high-grade serous ovarian cancer (HG-SOC) tissues in frozen sections against low-grade SOC, ovarian borderline tumor, other nonepithelial ovarian tumors, and healthy ovarian tissue. These results lead to a potential application in the identification of OCs' histological subtypes during operation. In the patient-derived tumor xenograft NCG mice model, Cy5-labeled mApoc46 was found to accumulate at the tumor area and served as an in vivo imaging probe. The mApoc46 probe shows a robust and stable performance to visualize SOC tumors in the body. Therefore, aptamer mApoc46 holds great potential in rapid intraoperative detection, pathological diagnosis, fluorescence image-guided cancer surgery, and targeted drug delivery and therapy.

Prognostic Evidence of the miRNA-Based Ovarian Cancer Signature MiROvaR in Independent Datasets

Simple Summary

Epithelial ovarian cancers (EOC) have an unpredictable frequent recurrence often associated with incurable chemo-resistant disease. Basing on the miRNA expression profile of 892 EOC patients, we previously developed a 35 miRNA-based classifier, MiROvaR, able to predict EOC risk of early relapse. Further independent analysis of prediction accuracy represents a crucial step in the test-validation phase. Here we exploited an external and independently collected, handled and profiled EOC cohort, to challenge MirovaR accuracy. Our analysis confirmed the MiROvaR prognostic power, thus opening the way to its prospective validation as a clinical grade assay entering into clinical practice to help in the refinement of therapeutic intervention for high risk EOC patients.

Abstract

Epithelial ovarian cancer (EOC) remains the second most common cause of gynecological cancer deaths. To improve patients’ outcomes, we still need reliable biomarkers of early relapse, of which external independent validation is a crucial process. Our previously established prognostic signature, MiROvaR, including 35 microRNAs (miRNA) able to stratify EOC patients for their risk of relapse, was challenged on a new independent cohort of 197 EOC patients included in the Pelvic Mass Study whose miRNA profile was made publically available, thus resulting in the only accessible database aside from the EOC TCGA collection. Following accurate data matrix adjustment to account for the use of different miRNA platforms, MiROvaR confirmed its ability to discriminate early relapsing patients. The model’s original cutoff separated 156 (79.2%) high- and 41 (20.8%) low-risk patients with median progression free survival (PFS) of 16.3 months and not yet reached (NYR), respectively (hazard ratio (HR): 2.42–95% Confidence Interval (CI) 1.49–3.93; Log-rank p = 0.00024). The MiROvaR predictive accuracy (area under the curve (AUC) = 0.68; 95% Cl 0.57–0.79) confirms its prognostic value. This external validation in a totally independently collected, handled and profiled EOC cohort suggests that MiROvaR is a strong and reliable biomarker of EOC early relapse, warranting prospective validation.

Blood-based biomarkers of human papillomavirus-associated cancers: A systematic review and meta-analysis

BACKGROUND

Despite the significant societal burden of human papillomavirus (HPV)-associated cancers, clinical screening interventions for HPV-associated noncervical cancers are not available. Blood-based biomarkers may help close this gap in care.

METHODS

Five databases were searched, 5687 articles were identified, and 3631 unique candidate titles and abstracts were independently reviewed by 2 authors; 702 articles underwent a full-text review. Eligibility criteria included the assessment of a blood-based biomarker within a cohort or case-control study.

RESULTS

One hundred thirty-seven studies were included. Among all biomarkers assessed, HPV-16 E seropositivity and circulating HPV DNA were most significantly correlated with HPV-associated cancers in comparison with cancer-free controls. In most scenarios, HPV-16 E6 seropositivity varied nonsignificantly according to tumor type, specimen collection timing, and anatomic site (crude odds ratio [cOR] for p16+ or HPV+ oropharyngeal cancer [OPC], 133.10; 95% confidence interval [CI], 59.40-298.21; cOR for HPV-unspecified OPC, 25.41; 95% CI, 8.71-74.06; cOR for prediagnostic HPV-unspecified OPC, 59.00; 95% CI, 15.39-226.25; cOR for HPV-unspecified cervical cancer, 12.05; 95% CI, 3.23-44.97; cOR for HPV-unspecified anal cancer, 73.60; 95% CI, 19.68-275.33; cOR for HPV-unspecified penile cancer, 16.25; 95% CI, 2.83-93.48). Circulating HPV-16 DNA was a valid biomarker for cervical cancer (cOR, 15.72; 95% CI, 3.41-72.57). In 3 cervical cancer case-control studies, cases exhibited unique microRNA expression profiles in comparison with controls. Other assessed biomarker candidates were not valid.

CONCLUSIONS

HPV-16 E6 antibodies and circulating HPV-16 DNA are the most robustly analyzed and most promising blood-based biomarkers for HPV-associated cancers to date. Comparative validity analyses are warranted. Variations in tumor type-specific, high-risk HPV DNA prevalence according to anatomic site and world region highlight the need for biomarkers targeting more high-risk HPV types. Further investigation of blood-based microRNA expression profiling appears indicated.

Plasma cells shape the mesenchymal identity of ovarian cancers through transfer of exosome-derived microRNAs

Ovarian cancer represents a highly lethal disease that poses a substantial burden for females, with four main molecular subtypes carrying distinct clinical outcomes. Here, we demonstrated that plasma cells, a subset of antibody-producing B cells, were enriched in the mesenchymal subtype of high-grade serous ovarian cancers (HGSCs). Plasma cell abundance correlated with the density of mesenchymal cells in clinical specimens of HGSCs. Coculture of nonmesenchymal ovarian cancer cells and plasma cells induced a mesenchymal phenotype of tumor cells in vitro and in vivo. Phenotypic switch was mediated by the transfer of plasma cell–derived exosomes containing miR-330-3p into nonmesenchymal ovarian cancer cells. Exosome-derived miR-330-3p increased expression of junctional adhesion molecule B in a noncanonical fashion. Depletion of plasma cells by bortezomib reversed the mesenchymal characteristics of ovarian cancer and inhibited in vivo tumor growth. Collectively, our work suggests targeting plasma cells may be a novel approach for ovarian cancer therapy.

A 4-gene signature predicts prognosis of uterine serous carcinoma

Background

Uterine serous carcinoma (USC) is an aggressive type of endometrial cancer that accounts for up to 40% of endometrial cancer deaths, creating an urgent need for prognostic biomarkers.

Methods

USC RNA-Seq data and corresponding patients’ clinical records were obtained from The Cancer Genome Atlas and Genotype-Tissue Expression datasets. Univariate cox, Lasso, and Multivariate cox regression analyses were conducted to forge a prognostic signature. Multivariable and univariable cox regression analysis and ROC curve evaluated the prediction efficiency both in the training and testing sets.

Results

We uncovered 1385 genes dysregulated in 110 cases of USC tissue relative to 113 cases of normal uterine tissue. Functional enrichment analysis of these genes revealed the involvement of various cancer-related pathways in USC. A novel 4-gene signature (KRT23, CXCL1, SOX9 and ABCA10) of USC prognosis was finally forged by serial regression analyses. Overall patient survival (OS) and recurrence-free survival (RFS) were significantly lower in the high-risk group relative to the low-risk group in both the training and testing sets. The area under the ROC curve of the 4-gene signature was highest among clinicopathological features in predicting OS and RFS. The 4-gene signature was found to be an independent prognostic indicator in USC and was a superior predictor of OS in early stage of USC.

Conclusions

Our findings highlight the potential of the 4-gene signature as a guide for personalized USC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07834-4.

Sphingolipids as multifaceted mediators in ovarian cancer

Ovarian cancer is the most lethal gynaecological malignancy. It is commonly diagnosed at advanced stage when it has metastasised to the abdominal cavity and treatment becomes very challenging. While current standard therapy involving debulking surgery and platinum + taxane-based chemotherapy is associated with high response rates initially, the large majority of patients relapse and ultimately succumb to chemotherapy-resistant disease. In order to improve survival novel strategies for early detection and therapeutics against treatment-refractory disease are urgently needed. A promising new target against ovarian cancer is the sphingolipid pathway which is commonly hijacked in cancer to support cell proliferation and survival and has been shown to promote chemoresistance and metastasis in a wide range of malignant neoplasms. In particular, the sphingosine kinase 1-sphingosine 1-phosphate receptor 1 axis has been shown to be altered in ovarian cancer in multiple ways and therefore represents an attractive therapeutic target. Here we review the roles of sphingolipids in ovarian cancer progression, metastasis and chemoresistance, highlighting novel strategies to target this pathway that represent potential avenues to improve patient survival.

Extracellular miRNAs as Predictive Biomarkers for Glypican-3-Derived Peptide Vaccine Therapy Response in Ovarian Clear Cell Carcinoma

Ovarian clear cell carcinoma (OCCC) has been treated with surgery and chemotherapy; however, the prognosis remains poor because of chemoresistance. Therefore, immunotherapies are attracting attention, including the GPC3 peptide vaccine, which improves overall survival. However, the response rate is limited and there are no sufficient predictive biomarkers that can identify responders before treatment. Our purpose was to identify circulating serum miRNAs as predictive biomarkers for response to GPC3 peptide vaccine. Eighty-four patients in a phase II trial of a GPC3 peptide vaccine were enrolled and miRNA sequencing was performed on their serum samples. Candidate miRNAs were selected from a group of 14 patients for whom treatment was responsive and validated in an independent group of 10 patients for whom treatment was responsive. Three markedly upregulated miRNAs, miR-375-3p, miR-193a-5p, and miR-1228-5p, were identified, and the combination of those miRNAs demonstrated high value in the prediction of the response. The origin of these miRNAs was assessed by referring to OCCC tissue miRNA profiles, and they were not identified as cancer tissue-related miRNAs. Functional annotation analysis suggested that they were associated with interferon-related pathways. The miRNAs identified herein have great potential to allow the realization of liquid biopsy for predicting the immunotherapy response and precision medicine.

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.

The Therapeutic Potential of MicroRNAs in Cancer: Illusion or Opportunity?

The functional involvement of microRNAs in human neoplasia has raised in the last years an increasing interest in the scientific community toward the potential application in clinics as therapeutic tools. Indeed, the possibility to modulate their expression to re-establish a lost equilibrium and counteract tumor growth and dissemination, and/or to improve responsiveness to standard therapies, is promising and fascinating. However, several issues need to be taken into account such as factors related to miRNA stability in the blood, tissue penetration and potential off-target effects, which might affect safety, tolerability and efficacy of an miRNA-based therapy. Here we describe the most relevant challenges related to miRNA-based therapy, review the delivery strategies exploited to date and the on-going clinical trials.

Targeting endothelin 1 receptor-miR-200b/c-ZEB1 circuitry blunts metastatic progression in ovarian cancer

Identification of regulatory mechanisms underlying the poor prognosis of ovarian cancer is necessary for diagnostic and therapeutic implications. Here we show that endothelin A receptor (ET_AR) and ZEB1 expression is upregulated in mesenchymal ovarian cancer and correlates with poor prognosis. Notably, the expression of ET_AR and ZEB1 negatively correlates with miR-200b/c. These miRNAs, besides targeting ZEB1, impair ET_AR expression through the 3’UTR binding. ZEB1, in turn, restores ET_AR levels by transcriptionally repressing miR-200b/c. Activation of ET_AR drives the expression of ZEB1 integrating the miR-200/ZEB1 double negative feedback loop. The ET_AR-miR-200b/c-ZEB1 circuit promotes epithelial-mesenchymal transition, cell plasticity, invasiveness and metastasis. Of therapeutic interest, ET_AR blockade with macitentan, a dual ET_AR and ET_BR antagonist, increases miR-200b/c and reduces ZEB1 expression with the concomitant inhibition of metastatic dissemination. Collectively, these findings highlight the reciprocal network that integrates ET_AR and ZEB1 axes with the miR-200b/c regulatory circuit to favour metastatic progression in ovarian cancer.

Rosanna Sestito et al. report a miR-200b/c-mediated regulatory circuit that drives ovarian cancer metastasis via the endothelin A receptor (ET_AR). They show that blockade of ET_AR increases miR-200b/c expression and subsequently reduces ZEB1 expression, thereby inhibiting further metastatic progression.

Construction of a new tumor immunity-related signature to assess and classify the prognostic risk of ovarian cancer

Ovarian cancer is associated with a high mortality rate. In this study, we established a new immune-related signature that can stratify ovarian cancer patients. First, we obtained immune-related genes through IMMUPORT, and DEGs (Differential Expression Genes) by analyzing the GSE26712 dataset. The APP (Antigen Processing and Presentation) and DEG signatures were established using univariate and multivariate Cox models. Kaplan-Meier analysis revealed the signatures' prognostic value in training and validation cohorts (HR: 0.379 VS. 0.450; 0.333 VS. 0.327). Nomogram analysis was used to assess the signatures' ability to predict the 30-month prognosis, which was evaluated using the calibration curve and time-dependent ROC curve (30-month AUC: 0.665 VS. 0.743). Time-dependent ROC, Decision Curve Analysis (DCA) and Integrated discrimination improvement (IDI) was used to compare the new model to previously published gene signatures. 30-month AUC composite variable (0.736) was higher than 9-gene signature (0.657), and composite variable had a larger net benefit and a higher IDI (+2.436%) relative to the 9-gene signature. Tumor immune infiltration and tumor microenvironment scores of the 2 groups separated by APP signature were compared. GSEA was used to identify enriched KEGG pathways. Conclusively, the proposed signature can stratify ovarian cancer patients by risk-score and guide clinical decisions.

Development and Validation of a 6-miRNA Prognostic Signature in Spinal Chordoma

BACKGROUND

Published data have suggested a critical role for microRNA (miRNA) expression in chordoma progression. However, most of these studies focus on single miRNA and no multi-miRNA prognostic signature has been currently established for chordoma. In this study, we sought to develop and validate a 6-miRNA risk score (miRscore) model for survival prediction.

METHODS

Medline, Embase, and Google scholar searches (from inception to July 20, 2018) were conducted to identify candidate miRNAs with prognostic value as per predefined criteria. Quantitative RT-PCR was used to measure miRNA levels in 114 spinal chordoma (54 in the training and 60 in the validation cohort) and 20 control specimens. Subsequently, the miRscore was built based on miRNAs data.

RESULTS

Literature searches identified six prognostic miRNAs (miR-574-3p, miR-1237-3p, miR-140-3p, miR-1, miR-155, and miR-1290) with differential expression in tumor tissues. Bioinformatical analysis revealed an important regulatory role for miR-574-3p/EGFR signaling in chordoma and showed that the target genes of these prognostic miRNAs were mainly enriched in transcription regulation, protein binding and cancer-related pathways. In both cohorts, the miRscore was associated with surrounding muscle invasion by tumor and/or other aggressive features. The miRscore model well predicted local recurrence-free survival and overall survival, which remained after adjusting for other relevant covariates. Further time-dependent receiver operating characteristics analysis in the two cohorts found that the miRscore classifier had stronger prognostic power than known clinical predictors and improved the ability of Enneking staging to predict outcomes. Importantly, recursive-partitioning analysis of both samples combined separated patients into four prognostically distinct risk subgroups for recurrence and survival (both P < 0.001).

CONCLUSIONS

These data suggest the miRscore as a useful prognostic stratification tool in spinal chordoma and may represent an important step toward future personalized treatment of patients.

The role of non-coding RNA on macrophage modification in tuberculosis infection

Tuberculosis (TB), a serious disease caused by Mycobacterium tuberculosis (Mtb), remains the world's top infectious killer. It is well-established that TB can circumvent the host's immune response for long-term survival. Macrophages serve as the major host cells for TB growth and persistence and their altered functions are critical for the response of the host defense against TB exposure (elimination, latency, reactivation, and bacillary dissemination). Noncoding RNAs are crucial posttranscriptional regulators of macrophage discrimination. Therefore, this review highlights the regulatory mechanism underlying the relationship between noncoding RNAs and macrophages in TB infection, which may facilitate the identification of potential therapeutic targets and effective diagnosis biomarkers for TB disease.

Bioinformatic gene analysis for potential therapeutic targets of Huntington's disease in pre-symptomatic and symptomatic stage

Background

Huntington’s disease (HD) is a neurodegenerative disorder characterized by psychiatric symptoms, serious motor and cognitive deficits. Certain pathological changes can already be observed in pre-symptomatic HD (pre-HD) patients; however, the underlying molecular pathogenesis is still uncertain and no effective treatments are available until now. Here, we reanalyzed HD-related differentially expressed genes from the GEO database between symptomatic HD patients, pre-HD individuals, and healthy controls using bioinformatics analysis, hoping to get more insight in the pathogenesis of both pre-HD and HD, and shed a light in the potential therapeutic targets of the disease.

Methods

Pre-HD and symptomatic HD differentially expressed genes (DEGs) were screened by bioinformatics analysis Gene Expression Omnibus (GEO) dataset GSE1751. A protein–protein interaction (PPI) network was used to select hub genes. Subsequently, Gene Ontology (GO) enrichment analysis of DEGs and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of hub genes were applied. Dataset GSE24250 was downloaded to verify our hub genes by the Kaplan–Meier method using Graphpad Prism 5.0. Finally, target miRNAs of intersected hub genes involved in pre-HD and symptomatic HD were predicted.

Results

A total of 37 and 985 DEGs were identified in pre-HD and symptomatic HD, respectively. The hub genes, SIRT1, SUZ12, and PSMC6, may be implicated in pre-HD, and the hub genes, FIS1, SIRT1, CCNH, SUZ12, and 10 others, may be implicated in symptomatic HD. The intersected hub genes, SIRT1 and SUZ12, and their predicted target miRNAs, in particular miR-22-3p and miR-19b, may be significantly associated with pre-HD.

Conclusion

The PSMC6, SIRT1, and SUZ12 genes and their related ubiquitin-mediated proteolysis, transcriptional dysregulation, and histone metabolism are significantly associated with pre-HD. FIS1, CCNH, and their related mitochondrial disruption and transcriptional dysregulation processes are related to symptomatic HD, which might shed a light on the elucidation of potential therapeutic targets in HD.

Circulating and Tissue microRNAs as Biomarkers for Ovarian Cancer Prognosis

Ovarian cancer (OC) is one of the most common cancers globally with a high rate of cancer- associated mortality. OC may be classified into epithelial cell neoplasms, germ cell neoplasms and stromal cell neoplasms. The five-year survival in the early and advanced stages of disease is approximately 90% and 15%, respectively. microRNAs are short, single-stranded, non-coding ribonucleic acid (RNA). miRNAs play critical roles in post transcriptionally regulations of gene expression. miRNAs are found in different tissues and body fluids. In carcinogenesis the expression of miRNAs are altered. Recent studies have revealed that there is a relationship between alteration of miRNAs expression and the prognosis of patients with OC. The aim of this review was to summarize the findings of recent studies that have investigated the expression of circulating and tissue miRNAs as novel biomarkers in the prognosis of OC.

LncRNA KCNQ1OT1 regulates the invasion and migration of hepatocellular carcinoma by acting on S1PR1 through miR-149

The aim of this study was to investigate the effect of lncRNA KCNQ1OT1 on HCC and to explore the possible underlying mechanisms. The expression levels of KCNQ1OT1, miR-149 and S1PR1 were detected by qRT-PCR assay. A dual luciferase reporter assay was used to detect the interaction between KCNQ1OT1 and miR-149, as well as miR-149 and S1PR1. The interaction between KCNQ1OT1 and miR-149 was further investigated by RNA pull-down assay. Wound healing assays and Transwell assays were carried out to determine cell migration and invasion. A xenograft tumour assay was used to validate the role of KCNQ1OT1 in vivo. KCNQ1OT1 and S1PR1 were significantly increased, but miR-149 was decreased in HCC cells. Luciferase reporter assays and RNA pull-down assays revealed that KCNQ1OT1 directly targeted miR-149. In addition, miR-149 bound to the 3'-UTR of S1PR1. Knockdown of KCNQ1OT1 or overexpression of miR-149 inhibited the invasion and migration of HCC cells. However, suppression of miR-149 could abrogate the effect of KCNQ1OT1 knockdown on the invasion and migration abilities of HCC cells. In vivo assays showed that KCNQ1OT1 knockdown suppressed tumour growth. This work suggests that lncRNA KCNQ1OT1 might act as a potential therapeutic target in HCC.

Predictive Relevance of Circulating miR-622 in Patients with Newly Diagnosed and Recurrent High-Grade Serous Ovarian Carcinoma

BACKGROUND

Identifying patients with high-grade serous ovarian cancer (HGSOC) who will respond to treatment remains a clinical challenge. We focused on miR-622, a miRNA involved in the homologous recombination repair (HRR) pathway, and we assessed its predictive value in serum prior to first-line chemotherapy and at relapse.

METHODS

Serum miR-622 expression was assessed in serum prior to first-line platinum-based chemotherapy in a prospective multicenter study (miRNA Serum Analysis, miRSA, NCT01391351) and a retrospective cohort (Biological Resource Center, BRC), and was also studied at relapse. Progression-free survival (PFS) and overall survival (OS) were used as primary and secondary endpoints prior to first-line chemotherapy and OS as a primary endpoint at relapse.

RESULTS

The group with high serum miR-622 expression was associated with a significantly lower PFS (15.4 versus 24.4 months; adjusted HR 2.11, 95% CI 1.2 3.8, P = 0.015) and OS (29.7 versus 40.6 months; adjusted HR 7.68, 95% CI 2.2-26.2, P = 0.0011) in the miRSA cohort. In the BRC cohort, a high expression of miR-622 was also associated with a significantly lower OS (22.8 versus 35.9 months; adjusted HR 1.98, 95% CI 1.1-3.6, P = 0.026). At relapse, high serum miR-622 was associated with a significantly lower OS (7.9 versus 20.6 months; adjusted HR 3.15, 95% CI 1.4-7.2, P = 0.0062). Serum miR-622 expression is a predictive independent biomarker of response to platinum-based chemotherapy for newly diagnosed and recurrent HGSOC.

CONCLUSIONS

These results may open new perspectives for HGSOC patient stratification and monitoring of resistance to platinum-based and poly(ADP-ribose)-polymerase-inhibitor-maintenance therapies, facilitating better and personalized treatment decisions.

Designer Self-Assembling Peptide Hydrogels to Engineer 3D Cell Microenvironments for Cell Constructs Formation and Precise Oncology Remodeling in Ovarian Cancer

Designer self-assembling peptides form the entangled nanofiber networks in hydrogels by ionic-complementary self-assembly. This type of hydrogel has realistic biological and physiochemical properties to serve as biomimetic extracellular matrix (ECM) for biomedical applications. The advantages and benefits are distinct from natural hydrogels and other synthetic or semisynthetic hydrogels. Designer peptides provide diverse alternatives of main building blocks to form various functional nanostructures. The entangled nanofiber networks permit essential compositional complexity and heterogeneity of engineering cell microenvironments in comparison with other hydrogels, which may reconstruct the tumor microenvironments (TMEs) in 3D cell cultures and tissue-specific modeling in vitro. Either ovarian cancer progression or recurrence and relapse are involved in the multifaceted TMEs in addition to mesothelial cells, fibroblasts, endothelial cells, pericytes, immune cells, adipocytes, and the ECM. Based on the progress in common hydrogel products, this work focuses on the diverse designer self-assembling peptide hydrogels for instructive cell constructs in tissue-specific modeling and the precise oncology remodeling for ovarian cancer, which are issued by several research aspects in a 3D context. The advantages and significance of designer peptide hydrogels are discussed, and some common approaches and coming challenges are also addressed in current complex tumor diseases.

Ovarian Cancer Translational Activity of the Multicenter Italian Trial in Ovarian Cancer (MITO) Group: Lessons Learned in 10 Years of Experience

Ovarian cancer is the most lethal gynecological cancer, and despite years of research, with the exception of a BRCA mutation driving the use of PARP inhibitors, no new prognostic/predictive biomarkers are clinically available. Improvement in biomarker selection and validation may derive from the systematic inclusion of translational analyses into the design of clinical trials. In the era of personalized medicine, the prospective centralized collection of high-quality biological material, expert pathological revision, and association to well-controlled clinical data are important or even essential added values to clinical trials. Here, we present the academic experience of the MITO (Multicenter Italian Trial in Ovarian Cancer) group, including gynecologists, pathologists, oncologists, biostatisticians, and translational researchers, whose effort is dedicated to the care and basic/translational research of gynecologic cancer. In our ten years of experience, we have been able to collect and process, for translational analyses, formalin-fixed, paraffin-embedded blocks from more than one thousand ovarian cancer patients. Standard operating procedures for collection, shipping, and processing were developed and made available to MITO researchers through the coordinating center’s web-based platform. Clinical data were collected through dedicated electronic case report forms hosted in a web-based electronic platform and stored in a central database at the trial’s coordinating center, which performed all the analyses related to the proposed translational researches. During this time, we improved our strategies of block management from retrospective to prospective collection, up to the design of a prospective collection with a quality check for sample eligibility before patients’ accrual. The final aim of our work is to share our experience by suggesting a guideline for the process of centralized collection, revision processing, and storing of formalin-fixed, paraffin-embedded blocks for translational purposes.

Expression profiles of PRKG1, SDF2L1 and PPP1R12A are predictive and prognostic factors for therapy response and survival in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGS-EOCs) is generally sensitive to front-line platinum (Pt)-based chemotherapy although most patients at an advanced stage relapse with progressive resistant disease. Clinical or molecular data to identify primary resistant cases at diagnosis are not yet available. HGS-EOC biopsies from 105 Pt-sensitive (Pt-s) and 89 Pt-resistant (Pt-r) patients were retrospectively selected from two independent tumor tissue collections. Pathway analysis was done integrating miRNA and mRNA expression profiles. Signatures were further validated in silico on a cohort of 838 HGS-EOC cases from a published dataset. In all, 131 mRNAs and 5 miRNAs belonging to different functionally related molecular pathways distinguish Pt-s from Pt-r cases. Then, 17 out of 23 selected elements were validated by orthogonal approaches (SI signature). As resistance to Pt is associated with a short progression-free survival (PFS) and overall survival (OS), the prognostic role of the SI signature was assessed, and 14 genes associated with PFS and OS, in multivariate analyses (SII signature). The prognostic value of the SII signature was validated in a third extensive cohort. The expression profiles of SDF2L1, PPP1R12A and PRKG1 genes (SIII signature) served as independent prognostic biomarkers of Pt-response and survival. The study identified a prognostic molecular signature based on the combined expression profile of three genes which had never been associated with the clinical outcome of HGS-EOC. This may lead to early identification, at the time of diagnosis, of patients who would not greatly benefit from standard chemotherapy and are thus eligible for novel investigational approaches.

Serum MicroRNA Signature as a Diagnostic and Therapeutic Marker in Patients with Psoriatic Arthritis

OBJECTIVE

MicroRNA (miRNA) are small endogenous regulatory RNA molecules that have emerged as potential therapeutic targets and biomarkers in autoimmunity. Here, we investigated serum miRNA levels in patients with psoriatic arthritis (PsA) and further assessed a serum miRNA signature in therapeutic responder versus nonresponder PsA patients.

METHODS

Serum samples were collected from healthy controls (HC; n = 20) and PsA patients (n = 31), and clinical demographics were obtained. To examine circulatory miRNA in serum from HC and PsA patients, a focused immunology miRNA panel was analyzed utilizing a miRNA Fireplex assay (FirePlex Bioworks Inc.). MiRNA expression was further assessed in responders versus nonresponders according to the European League Against Rheumatism response criteria.

RESULTS

Six miRNA (miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, miR-26a-5p, and miR-21-5p) were significantly higher in PsA compared to HC (all P < 0.05), with high specificity and sensitivity determined by receiver-operating characteristic curve analysis. Analysis of responder versus nonresponders demonstrated higher baseline levels of miR-221-3p, miR-130a-3p, miR-146a-5p, miR-151-5p, and miR-26a-5p were associated with therapeutic response.

CONCLUSION

This study identified a 6-serum microRNA signature that could be attractive candidates as noninvasive markers for PsA and may help to elucidate the disease pathogenesis.

Recurrence-Associated Multi-RNA Signature to Predict Disease-Free Survival for Ovarian Cancer Patients

Ovarian cancer (OvCa) is an intractable gynecological malignancy due to the high recurrence rate. Several molecular biomarkers have been previously screened for early identifying patients with a high recurrence risk and poor prognosis. However, all the known studies focused on a single type of RNAs, not integrating various types. This study was to construct a new multi-RNA-based model to predict the recurrence and prognosis for OvCa patients by using the messenger RNA (mRNA, including long noncoding RNA (lncRNA)) and microRNA (miRNA) sequencing data of The Cancer Genome Atlas database. After univariate Cox regression and least absolute shrinkage and selection operator analyses, a multi-RNA-based signature (2 miRNAs: hsa-miR-508, hsa-miR-506; 1 lncRNA: TM4SF1-AS1; 11 mRNAs: MAGI3, SLAMF7, GLI2, PDK1, ARID3A, PLEKHG4B, TNFAIP8L3, C1QTNF3, NDUFAF1, CH25H, TMEM129) was generated and used to establish a risk score model. The high- and low-risk patients classified by the median risk score exhibited significantly different recurrence risks (89% versus 61%, p < 0.001) and survival time (the area under the receiver operating characteristic curve (AUC) = 0.901 for 5-year disease-free survival (DFS)). This risk model was independent of other clinical features and superior to pathologic staging for DFS prediction (AUC, 0.906 versus 0.524; C-index, 0.633 versus 0.510). Furthermore, some new interaction axes were revealed to explain the possible functions of these RNAs (competing endogenous RNA: TM4SF1-AS1-miR-186-STEAP2, LINC00536-miR-508-STEAP2, LINC00475-miR-506-TMEM129; coexpression: LINC00598-PLEKHG4B). In conclusion, this multi-RNA-based risk model may be clinically useful to stratify OvCa patients with different recurrence risks and survival outcomes and included RNAs may be potential therapeutic targets.

Comprehensive analysis of mRNA-level and miRNA-level subpathway activities for identifying robust ovarian cancer prognostic signatures

Ovarian cancer (OvCa) causes the highest mortality among all gynaecologic cancers. A large number of mRNA‐ or miRNA‐based signatures were identified for OvCa patient prognosis. However, the comprehensive analysis of function‐level prognostic signatures is currently not considered in OvCa. In the present study, we respectively inferred subpathway activities from mRNA and miRNA levels based on high‐throughput expression profiles and reconstructed subpathways. Firstly, the activities of two tumour pathways were calculated and the difference between normal and tumour samples were analysed using multiple tumour types. Then, we calculated subpathway activities for OvCa based on the expression profiles from both mRNA and miRNA levels. Furthermore, based on these subpathway activity matrices, we performed bootstrap analysis to obtain sub‐training sets and utilized univariate method to identify robust OvCa prognostic subpathways. A comprehensive comparison of subpathway results between these two levels was performed. As a result, we observed subpathway mutual exclusion trend between the levels of mRNA and miRNA, which indicated the necessary of combining mRNA‐miRNA levels. Finally, by using ICGC data as testing sets, we utilized two strategies to verify survival predictive power of the mRNA‐miRNA combined subpathway signatures and performed comparisons with results from individual levels. It was confirmed that our framework displayed application to identify robust and efficient prognostic signatures for OvCa, and the combined signatures indeed exhibited advantages over individual ones. In the study, we took a step forward in relevant novel integrated functional signatures for OvCa prognosis.

The miR-34 family and its clinical significance in ovarian cancer

The tumor suppressor miR-34 family is transcriptionally induced by p53. Clinical significance of the various miR-34 family members has not been studied in ovarian cancer. In 228 ovarian cancers and in 19 non-neoplastic fallopian tube samples we analysed miR-34 a/b/c expression in relation to clinicopathological characteristics and clinical outcome. We found significantly lower levels of miR-34 a/b/c in ovarian cancers as compared to control-tissues (P=0.002, P<0.001, P<0.001, respectively). Expression of miR-34 b/c revealed an inverse correlation with BRCA1/2 mRNA-expression (BRCA1: miR34 b/c P=0.002 each; BRCA2: miR-34 b/c P<0.001 each), the same was true for miR-34a and BRCA2 mRNA-expression (P<0.001). The miR-34 family expression was found to be significantly lower in type 2 in comparison to type 1 cancers (P<0.001) and in TP53-mutated compared with TP53-wild-type ovarian cancers (P<0.001, P=0.002, P=0.004, respectively). When low grade serous ovarian cancers were compared with high grade serous cancers the respective miR-34 a/b/c expression was 2.6-, 40.8- and 32.3-fold higher. The expression of each of the miR-34 family members was revealed to be of independent prognostic relevance regarding progression free survival (PFS); miR-34a: HR 0.6, P=0.033; miR-34b: HR 0.2, P=0.001 and miR-34c: HR 0.3, P=0.002, respectively). For overall survival (OS) independency of the prognostic value was confined to miR-34b (HR 0.4, P=0.016) and miR-34c (HR 0.6, P=0.049). The independency of the prognostic value of our identified thresholds was confirmed for PFS for miR-34c in a publicly available dataset (NCBI Gene Expression Omnibus GSE73582). Our findings suggest that downregulation of miR-34 family is a crucial part in ovarian cancer development. Low miR-34 levels are linked to a worse overall survival and progression free survival and may indicate a more aggressive disease.

Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer

To identify the novel, noninvasive biomarkers to assess the outcome and prognosis of breast cancer (BC), patients with high sensitivity and specificity are greatly desired. Herein, the miRNA expression profile and matched clinical features of BC patients were extracted from The Cancer Genome Atlas (TCGA) database. The preliminary candidates were screened out by the univariate Cox regression test. Then, with the help of LASSO Cox regression analysis, the hsa-let-7b, hsa-mir-101-2, hsa-mir-135a-2, hsa-mir-22, hsa-mir-30a, hsa-mir-31, hsa-mir-3130-1, hsa-mir-320b-1, hsa-mir-3678, hsa-mir-4662a, hsa-mir-4772, hsa-mir-493, hsa-mir-556, hsa-mir-652, hsa-mir-6733, hsa-mir-874, and hsa-mir-9-3 were selected to construct the overall survival (OS) predicting signature, while the hsa-mir-130a, hsa-mir-204, hsa-mir-217, hsa-mir-223, hsa-mir-24-2, hsa-mir-29b-1, hsa-mir-363, hsa-mir-5001, hsa-mir-514a-1, hsa-mir-624, hsa-mir-639, hsa-mir-659, and hsa-mir-6892 were adopted to establish the recurrence-free survival (RFS) predicting signature. Referring to the median risk scores generated by the OS and RFS formulas, respectively, subgroup patients with high risk were strongly related to a poor OS and RFS revealed by Kaplan-Meier (K-M) plots. Meanwhile, receiver operating curve (ROC) analysis validated the accuracy and stability of these two signatures. When stratified by clinical features, such as tumor stage, age, and molecular subtypes, we found that the miRNA-based OS and RFS classifiers were still significant in predicting OS/RFS and showed the best predictive values than any other features. Besides, functional prediction analyses showed that these targeted genes of the enrolled miRNAs were enriched in cancer-associated pathways, such as MAPK/RTK, Ras, and PI3K-Akt signaling pathways. In summary, our observations demonstrate that the novel miRNA-based OS and RFS signatures are independent prognostic indicators for BC patients and worthy to be validated by further prospective studies.