Effects of silencing hsa_circ_0015326 on proliferation, migration, invasion, and apoptosis of epithelial ovarian cancer cells.

Although the treatment of ovarian cancer has made great progress, there are still many patients who are not timely detected and given targeted therapy due to unknown pathogenesis. Recent studies have found that hsa_circ_0015326 is upregulated in ovarian cancer and is involved in the proliferation, invasion, and migration of ovarian cancer cells. However, whether hsa_circ_0015326 can be used as a new target of ovarian cancer needs further investigation. Therefore, the effect of hsa_circ_0015326 on epithelial ovarian cancer was investigated in this study. At first, si-hsa_circ_0015326 lentivirus was transfected into epithelial ovarian cancer cells. Then real-time fluorescence quantitative PCR (qRT-PCR) was used to detect hsa_circ_0015326 level. The proliferation of ovarian cancer cells was detected by CCK-8 assay. The horizontal and vertical migration abilities of the cells were detected by wound-healing assay and Transwell assay, respectively. Transwell assay was also used to determine the invasion rate. As for the apoptosis rate, it was assessed by flow cytometry. As a result, the expression level of hsa_circ_0015326 in A2780 and SKOV3 was found to be higher than that in IOSE-80. However, after transfecting si-hsa_circ_0015326 and si-NC into the cells, the proliferation, migration, and invasion abilities of A2780 and SKOV3 cells in the si-hsa_circ_0015326 group were significantly reduced in comparison to those in the si-NC and mock groups, while their apoptosis rates were elevated. Collectively, silencing hsa_circ_0015326 bears the capability of inhibiting the proliferation, migration, and invasion of ovarian cancer cells while increasing apoptosis rate. It can be concluded that hsa_circ_0015326 promotes the malignant biological activities of epithelial ovarian cancer cells.

Evaluating homologous recombination activity in tissues to predict the risk of hereditary breast and ovarian cancer and olaparib sensitivity.

Homologous recombination (HR) repairs DNA damage including DNA double-stranded breaks and alterations in HR-related genes results in HR deficiency. Germline alteration of HR-related genes, such as BRCA1 and BRCA2, causes hereditary breast and ovarian cancer (HBOC). Cancer cells with HR deficiency are sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors and DNA-damaging agents. Thus, accurately evaluating HR activity is useful for diagnosing HBOC and predicting the therapeutic effects of anti-cancer agents. Previously, we developed an assay for site-specific HR activity (ASHRA) that can quantitatively evaluate HR activity and detect moderate HR deficiency. HR activity in cells measured by ASHRA correlates with sensitivity to the PARP inhibitor, olaparib. In this study, we applied ASHRA to lymphoblastoid cells and xenograft tumor tissues, which simulate peripheral blood lymphocytes and tumor tissues, respectively, as clinically available samples. We showed that ASHRA could be used to detect HR deficiency in lymphoblastoid cells derived from a BRCA1 pathogenic variant carrier. Furthermore, ASHRA could quantitatively measure the HR activity in xenograft tumor tissues with HR activity that was gradually suppressed by inducible BRCA1 knockdown. The HR activity of xenograft tumor tissues quantitatively correlated with the effect of olaparib. Our data suggest that ASHRA could be a useful assay for diagnosing HBOC and predicting the efficacy of PARP inhibitors.

Long non-coding RNA RAD51-AS1 promotes the tumorigenesis of ovarian cancer by elevating EIF5A2 expression.

PURPOSE: The present study aims to determine the molecular mechanism mediated by RAD51 antisense RNA 1 (RAD51-AS1) in ovarian cancer (OvCA). METHODS: The data associated with RAD51-AS1 in OvCA were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Relative expression of RAD51-AS1 was detected. Determination of cell proliferation, metastasis, and invasion was performed by cell counting, colony formation, would-healing, and transwell invasion assays. Protein levels were detected by western blotting. The molecular mechanism mediated by RAD51-AS1 was predicted by bioinformatics analysis and verified by dual-luciferase reporter assays. Subcutaneous tumorigenesis models were used to confirm the function of RAD51-AS1 in vivo. RESULTS: Data from TCGA and GEO showed that RAD51-AS1 was associated with poor prognosis in OvCA patients and DNA repair, cell cycle, focal adhesion, and apoptosis in SKOV3.ip cells. High levels of RAD51-AS1 were detected in OvCA cells. Overexpressing RAD51-AS1 enhanced the proliferative, invading, and migratory capabilities of OvCA cells in vitro while silencing RAD51-AS1 exhibited the opposite effects. Mechanically, RAD51-AS1 elevated eukaryotic initiation factor 5A2 (EIF5A2) expression as a sponge for microRNA (miR)-140-3p. Finally, the role of RAD51-AS1 was verified by subcutaneous tumorigenesis models. CONCLUSION: RAD51-AS1 promoted OvCA progression by the regulation of the miR-140-3p/EIF5A2 axis, which illustrated the potential therapeutic target for OvCA.

Machine learning developed a fibroblast-related signature for predicting clinical outcome and drug sensitivity in ovarian cancer.

Ovarian cancer (OC) is the leading cause of gynecological cancer death. Cancer-associated fibroblasts (CAF) is involved in wound healing and inflammatory processes, tumor occurrence and progression, and chemotherapy resistance in OC. GSE184880 dataset was used to identify CAF-related genes in OC. CAF-related signature (CRS) was constructed using integrative 10 machine learning methods with the datasets from the Cancer Genome Atlas, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082. The performance of CRS in predicting immunotherapy benefits was verified using 3 immunotherapy datasets (GSE91061, GSE78220, and IMvigor210) and several immune calculating scores. The Lasso + StepCox[forward] method-based predicting model having a highest average C index of 0.69 was referred as the optimal CRS and it had a stable and powerful performance in predicting clinical outcome of OC patients, with the 1-, 3-, and 5-year area under curves were 0.699, 0.708, and 0.767 in the Cancer Genome Atlas cohort. The C index of CRS was higher than that of tumor grade, clinical stage, and many developed signatures. Low CRS score demonstrated lower tumor immune dysfunction and exclusion score, lower immune escape score, higher PD1&CTLA4 immunophenoscore, higher tumor mutation burden score, higher response rate and better prognosis in OC, suggesting a better immunotherapy response. OC patients with low CRS score had a lower half maximal inhibitory concentration value of some drugs (Gemcitabine, Tamoxifen, and Nilotinib, etc) and lower score of some cancer-related hallmarks (Notch signaling, hypoxia, and glycolysis, etc). The current study developed an optimal CRS in OC, which acted as an indicator for the prognosis, stratifying risk and guiding treatment for OC patients.

Germline mutations in BRCA1 and BRCA2 among Brazilian women with ovarian cancer treated in the Public Health System.

BACKGROUND: Germline mutations in BRCA1 and BRCA2 genes are among the main causes of hereditary ovarian cancer. Identifying these mutations may reduce cancer risk, facilitate early detection, and enable personalized treatment. However, genetic testing is limited in the Brazilian Public Health System, and data regarding germline mutations in many regions are scarce. Therefore, the study aimed to investigate the prevalence of germline mutations in BRCA1 and BRCA2 in women with ovarian cancer treated in the Public Health System in Pernambuco, Brazil. METHODS: A cross-sectional study was conducted in the Hereditary Cancer Program from two reference oncological centers in Pernambuco. Women (n = 45) with high-grade serous ovarian cancer underwent genetic counseling and DNA sequencing for BRCA1 and BRCA2 genes. RESULTS: The prevalence of deleterious mutations in the BRCA1 and BRCA2 genes was 33%. Of the 15 germline mutations found, 13 were in BRCA1 and 2 in BRCA2; two mutations of unknown clinical significance were also found in BRCA2. Mutations c.5266dupC and c.2215 A > T were the most frequent; each was mutation observed in three patients. Additionally, the mutations c.7645dupT and c.921dupT were reported for the first time. CONCLUSION: One in three women showed a pathogenic mutation, demonstrating a significant prevalence of germline mutations in this sample. Additionally, the small sample revealed an interesting number of mutations, indicating the need to explore more regions of the country.

Human epidermal growth factor receptor-2 expression and subsequent dynamic changes in patients with ovarian cancer.

Human epidermal growth factor receptor-2 (HER2)-targeting drugs are increasingly being incorporated into therapeutic paradigms for non-breast cancers, yet studies on HER2 expression in ovarian cancer (OC) are inadequate. Here, we studied the HER2 status and dynamic changes in OC by reviewing the records of patients who underwent HER2 testing at a single institution. Clinical parameters, including histology, BRCA status, and immunohistochemistry (IHC), were evaluated alongside HER2 expression, timing, and anatomical location. Among 200 patients, 28% and 6% exhibited expression scores of 2+ and 3+, respectively. HER2 3+ scores were observed in 23%, 11%, 9%, and 5% of mucinous, endometrioid, clear cell, and high-grade serous tumors, respectively, and were exclusively identified in BRCA-wildtype, mismatch repair-proficient, or PD-L1-low-expressing tumors. The TP53 mutation rate was low, whereas ARID1A, KRAS, and PIK3CA mutations were relatively more prevalent with HER2 scores of 2+ or 3+ than with 0 or 1+. Four of the five tumors with an HER2 3+ score exhibited ERBB2 amplification. Among 19 patients who underwent multiple time-lagged biopsies, 11 showed increased HER2 expression in subsequent biopsies. Patients with HER2-overexpressing OC exhibited distinct histological, IHC, and genomic profiles. HER2-targeting agents are potential options for BRCA-wildtype patients, particularly as later lines of treatment.

Construction and analysis of competitive endogenous RNA networks and prognostic models associated with ovarian cancer based on the exoRBase database.

OBJECTIVE: To construct a competitive endogenous RNA (ceRNA) regulatory network in blood exosomes of patients with ovarian cancer (OC) using bioinformatics and explore its pathogenesis. METHODS: The exoRbase2.0 database was used to download blood exosome gene sequencing data from patients OC and normal controls and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were detected independently using R language for differential expression analysis. TargetScan and miRanda databases were combined for the prediction and differential expression of mRNA-binding microRNAs (miRNA). The miRcode and starBase databases were used to predict miRNAs that bind to differentially expressed lncRNAs and circRNAs repectively. The relevant mRNA, circRNA, lncRNA and their corresponding miRNA prediction data were imported into Cytoscape software for visualization of the ceRNA network. The R language and KEGG Orthology-based Annotation System (KOBAS) were used to execute and illustrate the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Hub genes were identified using The CytoHubba plugin. RESULTS: Thirty-one differentially expressed mRNAs, 17 differentially expressed lncRNAs, and 24 differentially expressed circRNAs were screened. Cytoscape software was used to construct the ceRNA network with nine mRNA nodes, two lncRNA nodes, eight circRNA nodes, and 51 miRNA nodes. Both GO and KEGG were focused on the Spliceosome pathway, indicating that spliceosomes are closely linked with the development of OC, while heterogenous nuclear ribonucleoprotein K and RNA binding motif protein X-linked genes were the top 10 score Hub genes screened by Cytoscape software, including two lncRNAs, four mRNAs, and four circRNAs. In patients with OC, the expression of eukaryotic translation initiation factor 4 gamma 2 (EIF4G2), SERPINE 1 mRNA binding protein 1 (SERBP1), ribosomal protein L15 (RPL15) and human leukocyte antigen complex P5 (HCP5) was significantly higher whereas that of testis expressed transcript, Y-linked 15 and DEAD-box helicase 3 Y-linked genes was lower compared to normal controls Immunocorrelation scores revealed that SERBP1 was significantly and negatively correlated with endothelial cells and CD4+ T cells and positively correlated with natural killer (NK) cells and macrophages, respectively; RPL15 was significantly positively correlated with macrophages and endothelial cells and negatively correlated with CD8+ T cells and uncharacterized cells, respectively. EIF4G2 was significantly and negatively correlated with endothelial cells and CD4+ T cells, and positively correlated with uncharacterized cells, respectively. Based on the survival data and the significant correlation characteristics derived from the multifactorial Cox analysis (P < 0.05), the survival prediction curves demonstrated that the prognostic factors associated with 3-year survival in patients with OC were The prognostic factors associated with survival were Macrophage, RPL15. CONCLUSION: This study successfully constructs a ceRNA regulatory network in blood exosomes of OV patients, which provides the specific targets for diagnosis and treatment of OC.

The evaluation of miR-1181 and miR-4314 as serum microRNA biomarkers for epithelial ovarian cancer diagnosis and prognosis.

AIM: Epithelial ovarian cancer (EOC) is the most ominous tumor of gynecological cancers due to its poor early detection rate and unfavorable prognosis. To date, there is no reliable screening method for the diagnosis of ovarian cancer at an early stage. MiRNAs are small non-coding RNA molecules, and their main function is to regulate gene expression. The present study compared the serum miR-1181 and miR-4314 levels in patients with EOC and healthy controls to measure the diagnostic and prognostic value as candidate biomarkers. MATERIALS AND METHODS: We collected serum samples from a total of 135 participants (69 patients with EOC and 66 healthy controls). Relative expressions of miR-1181 and miR-4314 were measured by quantitative real-time polymerase chain reaction assay (qPCR). RESULTS: The present study revealed that both serum miR-1181 and miR-4314 levels in patients with EOC were significantly increased compared to healthy controls for each marker. In addition, there was a significant relationship between miR-1181 and miR-4314 overexpressions and the stage and prognosis of the disease. Finally, patients with high expression levels of miR-1181 and miR-4314 had significantly shorter survival rates than those with low expression levels. CONCLUSION: The current study proposed that serum miR-1181 and miR-4314 could discriminate the EOC patients from healthy controls. In addition, both miR-1181 and miR-4314 may be predictive biomarkers for ovarian cancer prognosis. Further studies are needed to confirm the findings of the present study.

A Study on the Retrospective Reinterpretation of BRCA1 and BRCA2 Variants.

BACKGROUND: Hereditary breast/ovarian cancer is associated with BRCA gene mutations. As large volumes of clinical data on BRCA variants are continuously updated, their clinical interpretation may change, leading to their reclassification. This study analyzed the class and proportion of the changed clinical interpretations of BRCA variants to validate the need for periodic reviews of these variants. METHODS: This retrospective study reinterpreted previously reported BRCA1 and BRCA2 exon variants according to the 2015 American College of Medical Genetics and Genomics guidelines and the clinical significance of the recent public genomic database. Reanalyzed results were obtained for patients tested for BRCA genetic mutation for 10 years and 4 months. RESULTS: We included data from 4,058 patients, with 595 having at least one pathogenic variant (P), likely pathogenic variant (LP), or variant of uncertain significance (VUS) at a detection rate of 14.66%. The numbers of exon and intron variants were 562 (87.81%) and 78 (12.19%), respectively. BRCA1 exhibited a significantly higher P/LP detection rate of 6.96% compared to that of BRCA2 at 6.89% (p < 0.001). Conversely, BRCA2 demonstrated a significantly higher VUS rate of 10.38% compared to that of BRCA1 at 5.08% (p < 0.001). Among BRCA1 mutations, substitutions were the most prevalent in P/LP and VUS. Among BRCA2 mutations, deletions were most prevalent in P/LP, and substitutions were most prevalent in VUS. Among the 131 patients with P/LP in BRCA1 exons, the clinical interpretation was reclassified in two cases (1.53%), one VUS and one benign/likely benign (B/LB), and 48 cases (48.00%) with VUS were reclassified; one to P/LP and 47 to B/LB. Among the 138 patients with P/LP in BRCA2 exons, the clinical interpretation was reclassified in six (4.35%), five to VUS, and one to B/LB, and all 74 with VUS were reclassified to B/LB. CONCLUSIONS: We determined the class and proportion of reclassified BRCA variants. In conclusion, reviews are required to provide clinical guidance, such as determining treatment direction and preventive measures in the future.

MATN2 overexpression suppresses tumor growth in ovarian cancer via PTEN/PI3K/AKT pathway.

The incidence rate of developing ovarian cancer decreases over the years; however, mortality ranks top among malignancies of women, mainly metastasis through local invasion. Matrilin-2 (MATN2) is a member of the matrilin family that plays an important role in many cancers. However, its relationship with ovarian cancer remains unknown. Our study aimed to explore the function and possible mechanism of MATN2 in ovarian cancer. Human ovarian cancer tissue microarrays were used to detect the MATN2 expression in different types of ovarian cancer using immunohistochemistry (IHC). CCK-8, wound scratch healing assay, transwell assay, and flow cytometry were used to detect cell mobility. Gene and protein expression were detected using quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. MATN2 interacts with phosphatase, and the tensin homolog (PTEN) deleted on chromosome 10 was analyzed using TCGA database and co-immunoprecipitation (Co-IP). In vivo experiments were conducted using BALB/c nude mice, and tumor volume and weight were recorded. Tumor growth was determined using hematoxylin and eosin (H&E) and IHC staining. MATN2 was significantly downregulated in ovarian cancer cells. The SKOV3 and A2780 cell mobility was significantly inhibited by MATN2 overexpression, while the cell apoptosis rate was significantly increased. MATN2 overexpression decreased transplanted tumor size in vivo. These results were reversed by inhibiting MATN2. Furthermore, we found that PTEN closely interacted with MATN2 using bioinformatics and Co-IP. MATN2 overexpression significantly inhibited the PI3K/AKT pathway, however, PTEN suppression reversed this effect of MATN2 overexpression. These results indicated that MATN2 may play a critical role in ovarian cancer development by inhibiting cells proliferation and migration. The mechanism was related to interacting with PTEN, thus inhibiting downstream effectors in the PI3K/AKT pathway, which may be a novel target for treating ovarian cancer.

Ginger inhibits the invasion of ovarian cancer cells SKOV3 through CLDN7, CLDN11 and CD274 m6A methylation modifications.

BACKGROUND: Ginger is a common aromatic vegetable with a wide range of functional ingredients and considerable medicinal and nutritional properties. Numerous studies have shown that ginger and its active ingredients have suppressive effects on manifold tumours, including ovarian cancer (OC). However, the molecular mechanism by which ginger inhibits OC is not clear. The aim of this study was to investigate the function and mechanism of ginger in OC. METHODS: The estimation of n6-methyladenosine (m6A) levels was performed using the m6A RNA Methylation Quantification Kit, and RT-qPCR was used to determine the expression of m6A-related genes and proteins. The m6A methylationome was detected by MeRIP-seq, following analysis of the data. Differential methylation of genes was assessed utilizing RT-qPCR and Western Blotting. The effect of ginger on SKOV3 invasion in ovarian cancer cells was investigated using the wound healing assay and transwell assays. RESULTS: Ginger significantly reduced the m6A level of OC cells SKOV3. The 3'UTR region is the major site of modification for m6A methylation, and its key molecular activities include Cell Adhesion Molecules, according to meRIP-seq results. Moreover, it was observed that Ginger aids significantly in downregulating the CLDN7, CLDN11 mRNA, and protein expression. The results of wound healing assay and transwell assay showed that ginger significantly inhibited the invasion of OC cells SKOV3. CONCLUSIONS: Ginger inhibits ovarian cancer cells' SKOV3 invasion by regulating m6A methylation through CLDN7, CLDN11, and CD274.

Anti-cancer effects of alpha lipoic acid, cisplatin and paclitaxel combination in the OVCAR-3 ovarian adenocarcinoma cell line.

BACKGROUND: Ovarian cancer is the leading cause of gynecological cancer deaths. One of the major challenges in treating ovarian cancer with chemotherapy is managing the resistance developed by cancer cells to drugs, while also minimizing the side effects caused by these agents In the present study, we aimed to examine the effects of a combination of alpha lipoic acid (ALA), with cisplatin and paclitaxel in ovarian cancer(OVCAR-3). METHODS: The cytotoxic effects of ALA, cisplatin and paclitaxel on OVCAR-3 cells were determined. Four groups were formed: Control, ALA, Cisplatin + Paclitaxel, ALA + Cisplatin + Paclitaxel. The effects of single and combined therapy on cell migration, invasion and colony formation were analyzed. Changes in the expression of genes related to apoptosis, cell adhesion and cell cycle were analyzed with Real-time polymerase chain reaction(RT-PCR). The oxidative stress index and The Annexin V test were performed. RESULTS: The reduction in rapamycin-insensitive companion of mTOR(RICTOR) expression in the ALA + Cisplatin + Paclitaxel group was found statistically significant(p < 0.05). The decrease in MMP-9 and - 11 expressions the ALA + Cisplatin + Paclitaxel group was statistically significant(p < 0.05). The lowest values for mitogen-activated protein kinase(MAPK) proteins were found in the ALA + Cisplatin + Paclitaxel group. No colony formation was observed in the Cisplatin + Paclitaxel and ALA + Cisplatin + Paclitaxel groups. The lowest wound healing at 24 h was seen in the ALA + Cisplatin + Paclitaxel group. CONCLUSIONS: This study is the first one to investigate the combined treatment of ALA, Cisplatin, Paclitaxel on OVCAR-3. While ALA alone was not effective, combined therapy with ALA, has been found to reduce cell invasion, especially wound healing in the first 24 h, along with tumor cell adhesion.

Sensitive circulating tumor DNA-based residual disease detection in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is one of the leading causes of cancer-related death in women worldwide, and is characterized by a high rate of recurrence after surgery and chemotherapy. We sought to implement a circulating tumor DNA (ctDNA)-based blood test for more accurate post-operative surveillance of this disease. We analyzed 264 plasma samples collected between June 2016 and September 2021 from 63 EOC patients using tumor-guided plasma cell-free DNA analysis to detect residual disease after treatment. Assay specificity was verified using cross-patient analysis of 1,195 control samples. ctDNA was detected in 51 of 55 (93%) samples at diagnosis, and 18 of 18 (100%) samples at progression. Positive ctDNA in the last on-treatment sample was associated with rapid progression (median 1.02 versus 3.38 yr, HR = 5.63, P < 0.001) and reduced overall survival (median 2.31 versus NR yr, HR = 8.22, P < 0.001) in patients with high-grade serous cancer. In the case of 12 patients, ctDNA assays detected progression earlier than standard surveillance, with a median lead time of 5.9 mo. To approach the physical limits of ctDNA detection, five patients were analyzed using ultra-sensitive assays interrogating 479-1,856 tumor mutations, capable of tracking ctDNA fractions down to 0.0004%. Our results demonstrate that ctDNA assays achieve high sensitivity and specificity in detecting post-operative residual disease in EOC.

Functional analysis and validation of oncodrive gene AP3S1 in ovarian cancer through filtering of mutation data from whole-exome sequencing.

BACKGROUND: High-grade serous ovarian carcinoma (HGSOC) is the most aggressive and prevalent subtype of ovarian cancer and accounts for a significant portion of ovarian cancer-related deaths worldwide. Despite advancements in cancer treatment, the overall survival rate for HGSOC patients remains low, thus highlighting the urgent need for a deeper understanding of the molecular mechanisms driving tumorigenesis and for identifying potential therapeutic targets. Whole-exome sequencing (WES) has emerged as a powerful tool for identifying somatic mutations and alterations across the entire exome, thus providing valuable insights into the genetic drivers and molecular pathways underlying cancer development and progression. METHODS: Via the analysis of whole-exome sequencing results of tumor samples from 90 ovarian cancer patients, we compared the mutational landscape of ovarian cancer patients with that of TCGA patients to identify similarities and differences. The sequencing data were subjected to bioinformatics analysis to explore tumor driver genes and their functional roles. Furthermore, we conducted basic medical experiments to validate the results obtained from the bioinformatics analysis. RESULTS: Whole-exome sequencing revealed the mutational profile of HGSOC, including BRCA1, BRCA2 and TP53 mutations. AP3S1 emerged as the most weighted tumor driver gene. Further analysis of AP3S1 mutations and expression demonstrated their associations with patient survival and the tumor immune response. AP3S1 knockdown experiments in ovarian cancer cells demonstrated its regulatory role in tumor cell migration and invasion through the TGF-ß/SMAD pathway. CONCLUSION: This comprehensive analysis of somatic mutations in HGSOC provides insight into potential therapeutic targets and molecular pathways for targeted interventions. AP3S1 was identified as being a key player in tumor immunity and prognosis, thus providing new perspectives for personalized treatment strategies. The findings of this study contribute to the understanding of HGSOC pathogenesis and provide a foundation for improved outcomes in patients with this aggressive disease.

MicroRNA Expression Profiles in Human Samples and Cell Lines Revealed Nine miRNAs Associated with Cisplatin Resistance in High-Grade Serous Ovarian Cancer.

Metastasis and drug resistance are major contributors to cancer-related fatalities worldwide. In ovarian cancer (OC), a staggering 70% develop resistance to the front-line therapy, cisplatin. Despite proposed mechanisms, the molecular events driving cisplatin resistance remain unclear. Dysregulated microRNAs (miRNAs) play a role in OC initiation, progression, and chemoresistance, yet few studies have compared miRNA expression in OC samples and cell lines. This study aimed to identify key miRNAs involved in the cisplatin resistance of high-grade-serous-ovarian-cancer (HGSOC), the most common gynecological malignancy. MiRNA expression profiles were conducted on RNA isolated from formalin-fixed-paraffin-embedded human ovarian tumor samples and HGSOC cell lines. Nine miRNAs were identified in both sample types. Targeting these with oligonucleotide miRNA inhibitors (OMIs) reduced proliferation by more than 50% for miR-203a, miR-96-5p, miR-10a-5p, miR-141-3p, miR-200c-3p, miR-182-5p, miR-183-5p, and miR-1206. OMIs significantly reduced migration for miR-183-5p, miR-203a, miR-296-5p, and miR-1206. Molecular pathway analysis revealed that the nine miRNAs regulate pathways associated with proliferation, invasion, and chemoresistance through PTEN, ZEB1, FOXO1, and SNAI2. High expression of miR-1206, miR-10a-5p, miR-141-3p, and miR-96-5p correlated with poor prognosis in OC patients according to the KM plotter database. These nine miRNAs could be used as targets for therapy and as markers of cisplatin response.

The Clinicopathological Significance of the Cyclin D1/E1-Cyclin-Dependent Kinase (CDK2/4/6)-Retinoblastoma (RB1/pRB1) Pathway in Epithelial Ovarian Cancers.

Cyclin-dependent kinases (CDK2, CDK4, CDK6), cyclin D1, cyclin E1 and phosphorylated retinoblastoma (pRB1) are key regulators of the G1/S cell cycle checkpoint and may influence platinum response in ovarian cancers. CDK2/4/6 inhibitors are emerging targets in ovarian cancer therapeutics. In the current study, we evaluated the prognostic and predictive significance of the CDK2/4/6-cyclin D1/E1-pRB1 axis in clinical ovarian cancers (OC). The CDK2/4/6, cyclin D1/E1 and RB1/pRB1 protein expression were investigated in 300 ovarian cancers and correlated with clinicopathological parameters and patient outcomes. CDK2/4/6, cyclin D1/E1 and RB1 mRNA expression were evaluated in the publicly available ovarian TCGA dataset. We observed nuclear and cytoplasmic staining for CDK2/4/6, cyclins D1/E1 and RB1/pRB1 in OCs with varying percentages. Increased nuclear CDK2 and nuclear cyclin E1 expression was linked with poor progression-free survival (PFS) and a shorter overall survival (OS). Nuclear CDK6 was associated with poor OS. The cytoplasmic expression of CDK4, cyclin D1 and cyclin E1 also has predictive and/or prognostic significance in OCs. In the multivariate analysis, nuclear cyclin E1 was an independent predictor of poor PFS. Tumours with high nuclear cyclin E1/high nuclear CDK2 have a worse PFS and OS. Detailed bioinformatics in the TCGA cohort showed a positive correlation between cyclin E1 and CDK2. We also showed that cyclin-E1-overexpressing tumours are enriched for genes involved in insulin signalling and release. Our data not only identified the prognostic/predictive significance of these key cell cycle regulators but also demonstrate the importance of sub-cellular localisation. CDK2 targeting in cyclin-E1-amplified OCs could be a rational approach.

Comprehensive analysis of the interaction of antigen presentation during anti-tumour immunity and establishment of AIDPS systems in ovarian cancer.

There are hundreds of prognostic models for ovarian cancer. These genes are based on different gene classes, and there are many ways to construct the models. Therefore, this paper aims to build the most stable prognostic evaluation system known to date through 101 machine learning strategies. We combined 101 algorithm combinations with 10 machine learning algorithms to create antigen presentation-associated genetic markers (AIDPS) with outstanding precision and steady performance. The inclusive set of algorithms comprises the elastic network (Enet), Ridge, stepwise Cox, Lasso, generalized enhanced regression model (GBM), random survival forest (RSF), supervised principal component (SuperPC), Cox partial least squares regression (plsRcox), survival support vector machine (Survival-SVM). Then, in the train cohort, the prediction model was fitted using a leave-one cross-validation (LOOCV) technique, which involved 101 different possible combinations of prognostic genes. Seven validation data sets (GSE26193, GSE26712, GSE30161, GSE63885, GSE9891, GSE140082 and ICGC_OV_AU) were compared and analysed, and the C-index was calculated. Finally, we collected 32 published ovarian cancer prognostic models (including mRNA and lncRNA). All data sets and prognostic models were subjected to a univariate Cox regression analysis, and the C-index was calculated to demonstrate that the antigen presentation process should be the core criterion for evaluating ovarian cancer prognosis. In a univariate Cox regression analysis, 22 prognostic genes were identified based on the expression profiles of 283 genes involved in antigen presentation and the intersection of genes (p < 0.05). AIDPS were developed by our machine learning-based integration method, which was applied to these 22 genes. One hundred and one prediction models are fitted using the LOOCV framework, and the C-index is calculated for each model across all validation sets. Interestingly, RSF + Lasso was the best model overall since it had the greatest average C-index and the highest C-index of any combination of models tested on the validated data sets. In comparing external cohorts, we found that the C-index correlated AIDPS method using the RSF + Lasso method in 101 prediction models was in contrast to other features. Notably, AIDPS outperformed the vast majority of models across all data sets. Antigen-presenting anti-tumour immune pathways can be used as a representative gene set of ovarian cancer to track the prognosis of patients with cancer. The antigen-presenting model obtained by the RSF + Lasso method has the best C-INDEX, which plays a key role in developing antigen-presenting targeted drugs in ovarian cancer and improving the treatment outcome of patients.

Genetically identification of endometriosis and cancers risk in women through a two-sample Mendelian randomization study.

Endometriosis is a prevalent and chronic inflammatory gynecologic disorder affecting approximately 6-10% of women globally, and has been associated with an increased risk of cancer. Nevertheless, previous studies have been hindered by methodological limitations that compromise the validity and robustness of their findings. In this study we conducted a comprehensive two-sample Mendelian randomization analysis to explore the genetically driven causal relationship between endometriosis and the risk of cancer. We conducted the analysis via the inverse variance weighted method, MR Egger method, and weighted median method utilizing publicly available genome-wide association study summary statistics. Furthermore, we implemented additional sensitivity analyses to assess the robustness and validity of the causal associations identified. We found strong evidence of a significant causal effect of endometriosis on a higher risk of ovarian cancer via inverse-variance weighted method (OR = 1.19, 95% CI 1.11-1.29, p < 0.0001), MR-Egger regression, and weighted median methodologies. Remarkably, our findings revealed a significant association between endometriosis and an increased risk of clear cell ovarian cancer (OR = 2.04, 95% CI 1.66-2.51, p < 0.0001) and endometrioid ovarian cancer (OR = 1.45, 95% CI 1.27-1.65, p < 0.0001). No association between endometriosis and other types of cancer was observed. We uncovered a causal relationship between endometriosis and an elevated risk of ovarian cancer, particularly clear cell ovarian cancer and endometrioid ovarian cancer. No significant associations between endometriosis and other types of cancer could be identified.

Spotlight on New Hallmarks of Drug-Resistance towards Personalized Care for Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Despite the latest advances, a major clinical issue in EOC is the disappointing prognosis related to chemoresistance in almost one-third of cases. Drug resistance relies on heterogeneous cancer stem cells (CSCs), endowed with tumor-initiating potential, leading to relapse. No biomarkers of chemoresistance have been validated yet. Recently, major signaling pathways, micro ribonucleic acids (miRNAs), and circulating tumor cells (CTCs) have been advocated as putative biomarkers and potential therapeutic targets for drug resistance. However, further investigation is mandatory before their routine implementation. In accordance with the increasing rate of therapeutic efforts in EOC, the need for biomarker-driven personalized therapies is growing. This review aims to discuss the emerging hallmarks of drug resistance with an in-depth insight into the underlying molecular mechanisms lacking so far. Finally, a glimpse of novel therapeutic avenues and future challenges will be provided.