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.

ALKBH5 modulates macrophages polarization in tumor microenvironment of ovarian cancer.

BACKGROUND: Macrophages play an essential role in regulating ovarian cancer immune microenvironment. Studies have shown that m6A methylation could influence immune microenvironment in cancer. In this study, we investigated the roles of m6A demethylase ALKBH5 and m6A recognition protein IGF2BP2 played in regulating macrophages polarization in ovarian cancer. METHODS: In this study, we first explored the differentially expressed m6A methylation enzymes in M0 and M2 macrophages according to two independent GEO datasets. TIMER2.0 and GSCA database were used to explore the immune analysis of ALKBH5 and IGF2BP2 in ovarian cancer. K-M plotter and TIMER2.0 databases were used to evaluate the prognostic role of ALKBH5 and IGF2BP2 in ovarian cancer. For CNV mutation analysis of ALKBH5 and IGF2BP2, cBioPortal and GSCA databases were used. For single-cell analysis, sc-TIME and HPA softwares were used to analyze the roles of ALKBH5 and IGF2BP2 played in immune cells in ovarian cancer. To identify the role of ALKBH5 played in macrophage polarization, RT-PCR was used to verify the macrophage polarization related markers in vitro study. The function of ALKBH5 played in ovarian cancer was further analyzed through GO and KEGG analysis. FINDINGS: In this study, we found that ALKBH5 and IGF2BP2 were up-regulated in M2 macrophages, which showed closely correlation with immune cells expressions in ovarian cancer, especially with macrophages. Ovarian cancer patients with higher expression of ALKBH5 and IGF2BP2 showed worse prognosis, possibly because of their close correlation with immune response. ALKBH5 also correlated with macrophage phenotypes in single-cell levels analysis. However, the expression level of IGF2BP2 in ovarian cancer immune microenvironment was very low. The results of RT-PCR indicated the potential role of ALKBH5 in M2 polarization of macrophages. INTERPRETATION: ALKBH5 participated in regulating macrophage M2 polarization in ovarian cancer immune microenvironment.

Tim4 enables large peritoneal macrophages to cross-present tumor antigens at early stages of tumorigenesis.

Receptors controlling the cross-presentation of tumor antigens by macrophage subsets in cancer tissues are poorly explored. Here, we show that TIM4+ large peritoneal macrophages efficiently capture and cross-present tumor-associated antigens at early stages of peritoneal infiltration by ovarian cancer cells. The phosphatidylserine (PS) receptor TIM4 promotes maximal uptake of dead cells or PS-coated artificial targets and triggers inflammatory and metabolic gene programs in combination with cytoskeletal remodeling and upregulation of transcriptional signatures related to antigen processing. At the cellular level, TIM4-mediated engulfment induces nucleation of F-actin around nascent phagosomes, delaying the recruitment of vacuolar ATPase, acidification, and cargo degradation. In vivo, TIM4 deletion blunts induction of early anti-tumoral effector CD8 T cells and accelerates the progression of ovarian tumors. We conclude that TIM4-mediated uptake drives the formation of specialized phagosomes that prolong the integrity of ingested antigens and facilitate cross-presentation, contributing to immune surveillance of the peritoneum.

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.

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer.

BACKGROUND: Ovarian cancer (OC) is a gynecological malignancy tumor with high recurrence and mortality rates. Programmed cell death (PCD) is an essential regulator in cancer metabolism, whose functions are still unknown in OC. Therefore, it is vital to determine the prognostic value and therapy response of PCD-related genes in OC. METHODS: By mining The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Genecards databases, we constructed a prognostic PCD-related genes model and performed Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic (ROC) curve for its predictive ability. A nomogram was created via Cox regression. We validated our model in train and test sets. Quantitative real-time PCR (qRT-PCR) was applied to identify the expression of our model genes. Finally, we analyzed functional analysis, immune infiltration, genomic mutation, tumor mutational burden (TMB) and drug sensitivity of patients in low- and high-risk group based on median scores. RESULTS: A ten-PCD-related gene signature including protein phosphatase 1 regulatory subunit 15 A (PPP1R15A), 8-oxoguanine-DNA glycosylase (OGG1), HECT and RLD domain containing E3 ubiquitin protein ligase family member 1 (HERC1), Caspase-2.(CASP2), Caspase activity and apoptosis inhibitor 1(CAAP1), RB transcriptional corepressor 1(RB1), Z-DNA binding protein 1 (ZBP1), CD3-epsilon (CD3E), Clathrin heavy chain like 1(CLTCL1), and CCAAT/enhancer-binding protein beta (CEBPB) was constructed. Risk score performed well with good area under curve (AUC) (AUC3 - year =0.728, AUC5 - year = 0.730). The nomogram based on risk score has good performance in predicting the prognosis of OC patients (AUC1 - year =0.781, AUC3 - year =0.759, AUC5 - year = 0.670). Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the erythroblastic leukemia viral oncogene homolog (ERBB) signaling pathway and focal adhesion were enriched in the high-risk group. Meanwhile, patients with high-risk scores had worse OS. In addition, patients with low-risk scores had higher immune-infiltrating cells and enhanced expression of checkpoints, programmed cell death 1 ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO-1) and lymphocyte activation gene-3 (LAG3), and were more sensitive to A.443,654, GDC.0449, paclitaxel, gefitinib and cisplatin. Finally, qRT-PCR confirmed RB1, CAAP1, ZBP1, CEBPB and CLTCL1 over-expressed, while PPP1R15A, OGG1, CASP2, CD3E and HERC1 under-expressed in OC cell lines. CONCLUSION: Our model could precisely predict the prognosis, immune status and drug sensitivity of OC patients.

ATF3 characterizes aggressive drug-tolerant persister cells in HGSOC.

High-grade serous ovarian cancer (HGSOC) represents the most common and lethal subtype of ovarian cancer. Despite initial response to platinum-based standard therapy, patients commonly suffer from relapse that likely originates from drug-tolerant persister (DTP) cells. We generated isogenic clones of treatment-naïve and cisplatin-tolerant persister HGSOC cells. In addition, single-cell RNA sequencing of barcoded cells was performed in a xenograft model with HGSOC cell lines after platinum-based therapy. Published single-cell RNA-sequencing data from neo-adjuvant and non-treated HGSOC patients and patient data from TCGA were analyzed. DTP-derived cells exhibited morphological alterations and upregulation of epithelial-mesenchymal transition (EMT) markers. An aggressive subpopulation of DTP-derived cells showed high expression of the stress marker ATF3. Knockdown of ATF3 enhanced the sensitivity of aggressive DTP-derived cells to cisplatin-induced cell death, implying a role for ATF3 stress response in promoting a drug tolerant persister cell state. Furthermore, single cell lineage tracing to detect transcriptional changes in a HGSOC cell line-derived xenograft relapse model showed that cells derived from relapsed solid tumors express increased levels of EMT and multiple endoplasmic reticulum (ER) stress markers, including ATF3. Single cell RNA sequencing of epithelial cells from four HGSOC patients also identified a small cell population resembling DTP cells in all samples. Moreover, analysis of TCGA data from 259 HGSOC patients revealed a significant progression-free survival advantage for patients with low expression of the ATF3-associated partial EMT genes. These findings suggest that increased ATF3 expression together with partial EMT promote the development of aggressive DTP, and thereby relapse in HGSOC patients.

Targeting the GPI transamidase subunit GPAA1 abrogates the CD24 immune checkpoint in ovarian cancer.

CD24 is frequently overexpressed in ovarian cancer and promotes immune evasion by interacting with its receptor Siglec10, present on tumor-associated macrophages, providing a "don't eat me" signal that prevents targeting and phagocytosis by macrophages. Factors promoting CD24 expression could represent novel immunotherapeutic targets for ovarian cancer. Here, using a genome-wide CRISPR knockout screen, we identify GPAA1 (glycosylphosphatidylinositol anchor attachment 1), a factor that catalyzes the attachment of a glycosylphosphatidylinositol (GPI) lipid anchor to substrate proteins, as a positive regulator of CD24 cell surface expression. Genetic ablation of GPAA1 abolishes CD24 cell surface expression, enhances macrophage-mediated phagocytosis, and inhibits ovarian tumor growth in mice. GPAA1 shares structural similarities with aminopeptidases. Consequently, we show that bestatin, a clinically advanced aminopeptidase inhibitor, binds to GPAA1 and blocks GPI attachment, resulting in reduced CD24 cell surface expression, increased macrophage-mediated phagocytosis, and suppressed growth of ovarian tumors. Our study highlights the potential of targeting GPAA1 as an immunotherapeutic approach for CD24+ ovarian cancers.

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.

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.

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.

Olaparib not cost-effective as maintenance therapy for platinum-sensitive, BRCA1/2 germline-mutated metastatic pancreatic cancer.

OBJECTIVE: To assess the cost-effectiveness and budget impact of olaparib as a maintenance therapy in platinum-responsive, metastatic pancreatic cancer patients harboring a germline BRCA1/2 mutation, using the Swiss context as a model. METHODS: Based on data from the POLO trial, published literature and local cost data, we developed a partitioned survival model of olaparib maintenance including full costs for BRCA1/2 germline testing compared to FOLFIRI maintenance chemotherapy and watch-and-wait. We calculated the incremental cost-effectiveness ratio (ICER) for the base case and several scenario analyses and estimated 5-year budget impact. RESULTS: Comparing olaparib with watch-and wait and maintenance chemotherapy resulted in incremental cost-effectiveness ratios of CHF 2,711,716 and CHF 2,217,083 per QALY gained, respectively. The 5-year costs for the olaparib strategy in Switzerland would be CHF 22.4 million, of which CHF 11.4 million would be accounted for by germline BRCA1/2 screening of the potentially eligible population. This would amount to a budget impact of CHF 15.4 million (USD 16.9 million) versus watch-and-wait. CONCLUSIONS: Olaparib is not a cost-effective maintenance treatment option. Companion diagnostics are an equally important cost driver as the drug itself.

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.

TCEB3 initiates ovarian cancer apoptosis by mediating ubiquitination and degradation of MCL-1.

Platinum resistance remains a major contributor to the poor prognosis of ovarian cancer. Anti-apoptotic protein myeloid cell leukemia-1 (MCL-1) has emerged as a promising target for overcoming drug resistance, but different cancer cells utilize distinct protein degradation pathways to alter MCL-1 level. We systematically investigated E3 ligases to identify novel candidates that mediate platinum resistance in ovarian cancer. Transcription Elongation Factor B (TCEB3) has been identified as a novel E3 ligase recognition subunit that targets MCL-1 in the cytoplasm during platinum treatment other than its traditional function of targeting the Pol II in the nuclear compartment. TCEB3 expression is downregulated in platinum-resistant cell lines and this low expression is associated with poor prognosis. The ubiquitination of MCL-1 induced by TCEB3 leads to cell death in ovarian cancer. Moreover, platinum treatment increased the cytoplasm proportion of TCEB3, and the cytoplasm localization of TCEB3 is important for its targeting of MCL-1. This study emphasizes the dual function of TCEB3 in homeostasis maintenance and in cell fate determination under different conditions, and provides a new insight into drug resistance in ovarian cancer.

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.

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.