Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Proteomic and Phosphoproteomic Reprogramming in Epithelial Ovarian Cancer Metastasis.

Epithelial ovarian cancer (EOC) is a high-risk cancer presenting with heterogeneous tumors. The high incidence of EOC metastasis from primary tumors to nearby tissues and organs is a major driver of EOC lethality. We used cellular models of spheroid formation and readherence to investigate cellular signaling dynamics in each step toward EOC metastasis. In our system, adherent cells model primary tumors, spheroid formation represents the initiation of metastatic spread, and readherent spheroid cells represent secondary tumors. Proteomic and phosphoproteomic analyses show that spheroid cells are hypoxic and show markers for cell cycle arrest. Aurora kinase B abundance and downstream substrate phosphorylation are significantly reduced in spheroids and readherent cells, explaining their cell cycle arrest phenotype. The proteome of readherent cells is most similar to spheroids, yet greater changes in the phosphoproteome show that spheroid cells stimulate Rho-associated kinase 1 (ROCK1)-mediated signaling, which controls cytoskeletal organization. In spheroids, we found significant phosphorylation of ROCK1 substrates that were reduced in both adherent and readherent cells. Application of the ROCK1-specific inhibitor Y-27632 to spheroids increased the rate of readherence and altered spheroid density. The data suggest ROCK1 inhibition increases EOC metastatic potential. We identified novel pathways controlled by Aurora kinase B and ROCK1 as major drivers of metastatic behavior in EOC cells. Our data show that phosphoproteomic reprogramming precedes proteomic changes that characterize spheroid readherence in EOC metastasis.

Mass Spectrometry-Based Proteomics of Epithelial Ovarian Cancers: A Clinical Perspective.

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery of proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990 and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Serum Exosomes From Epithelial Ovarian Cancer Patients Contain LRP1, Which Promotes the Migration of Epithelial Ovarian Cancer Cell.

Ovarian cancer is a gynecological tumor with extremely high mortality and poor prognosis. Exosomes derived from tumor cells contain abundant proteins that may influence tumor metastasis. The purpose of our study was to explore the proteomic profile of serum exosomes from epithelial ovarian cancer (EOC) patients and to find potential diagnostic markers for EOC. We obtained purified exosomes from serum using ultracentrifugation. Migration assay was used to evaluate the effects of exosomes on the migration of EOC cells. Proteomic profile of serum exosomes was analyzed by liquid chromatogram-tandem mass spectrometry. The levels of low-density lipoprotein receptor-related protein 1 (LRP1) in serum and serum exosomes were determined by enzyme-linked immunosorbent assay. Western blot and Immunohistochemistry were used to determine the level of LRP1 in tissues. Moreover, we performed small-interfering RNA-mediated knockdown of LRP1 in EOC cells to obtain SI-LRP1-Exos and SI-NC-Exos. The detailed mechanisms by which exosomal LRP1 affected the migration of EOC cells in vitro and in vivo were also explored. We found that serum exosomes from EOC patients contributed to the migration of EOC cells. The level of serum exosomal LRP1 of EOC patients was significantly upregulated compared with that of healthy volunteers, which was consistent with the result of enzyme-linked immunosorbent assay. We found that exosomal LRP1 regulated the expression of MMP2 and MMP9 through ERK signaling pathway and affected the migration of EOC cells in vitro and in vivo. Therefore, we propose that exosomal LRP1 contributes to the migration of EOC and may act as an important diagnostic and prognostic biomarker of EOC.

Prevalence and outcomes of germline pathogenic variants of homologous recombination repair genes in ovarian cancer.

Germline pathogenic variants (PVs) are pivotal in gynecological oncology. We focused on the prevalence, clinicopathological features, and survival impact of homologous recombination repair (HRR) PVs in patients with epithelial ovarian cancer (EOC). This was a multicenter retrospective cohort study, and 1248 patients with EOC were registered. Eligible patients (n = 1112) underwent germline DNA analysis for 26 cancer predisposition genes, including nine HRR-related genes, such as BRCA1/2, BRIP1, PALB2, RAD51C/D, and ATM. The associations between clinicopathological factors and HRR-related PVs were examined. Kaplan-Meier and Cox regression analyses were conducted. Among 1091 analyzed patients, 153 (14.0%) carried PVs and 140 (12.8%) were HRR-related. HRR-PV-positive status significantly correlated with serous carcinoma (22.9% vs. 4.8%, P < 0.0001) and advanced disease (18.5% vs. 5.9%, P < 0.0001). The HRR-PV-positive group exhibited higher prevalence of personal breast (12.9%) and familial breast/ovarian (29.2%) cancer history. HRR status independently improved overall survival in stage III/IV disease (P = 0.04) but not progression-free survival. HRR-related germline PVs exhibit distinct clinicopathological features with survival implications. Variants were significantly associated with serous carcinoma and advanced disease, underscoring the importance of genetic testing to develop individualized EOC treatment strategies. Considering the study period (2000-2019), the limited use of bevacizumab and poly (ADP-ribose) polymerase inhibitors as maintenance therapy should be recognized.

USP43 impairs cisplatin sensitivity in epithelial ovarian cancer through HDAC2-dependent regulation of Wnt/ß-catenin signaling pathway.

Epithelial ovarian cancer (EOC) is the leading cause of cancer death all over the world. USP43 functions as a tumor promoter in various malignant cancers. Nevertheless, the biological roles and mechanisms of USP43 in EOC remain unknown. In this study, USP43 was highly expressed in EOC tissues and cells, and high expression of USP43 were associated with a poor prognosis of EOC. USP43 overexpression promoted EOC cell proliferation, enhanced the ability of migration and invasion, decreased cisplatin sensitivity and inhibited apoptosis. Knockdown of USP43 in vitro effectively retarded above malignant progression of EOC. In vivo xenograft tumors, silencing USP43 slowed tumor growth and enhanced cisplatin sensitivity. Mechanistically, USP43 inhibited HDAC2 degradation and enhanced HDAC2 protein stability through its deubiquitylation function. USP43 diminished the sensitivity of EOC cells to cisplatin through activation of the Wnt/ß-catenin signaling pathway mediated by HDAC2. Taken together, the data in this study revealed the functions of USP43 in proliferation, migration, invasion, chemoresistance of EOC cells, and the mechanism of HDAC2-mediated Wnt/ß-catenin signaling pathway. Thus, USP43 might serve as a potential target for the control of ovarian cancer progression.

NLRP12 is a prognostic biomarker and correlated with immune infiltrates in epithelial ovarian cancer.

BACKGROUND: NLRP12 is a member of the intracellular Nod-like receptor (NLR) family, suggesting it is an innate immune receptor for the initiation and progression of several cancers. However, its role on prognosis and immune infiltrates in epithelial ovarian cancer (EOC) is still unknown. The present study aimed to evaluate its prognostic value and its association with immune infiltrates in EOC. METHODS: The mRNA expression of NLRP12 of EOC from The Cancer Genome Atlas (TCGA) was analyzed. The association between NLRP12 and clinicopathological characters was evaluated with logistic regression. The association between NLRP12 expression and survival was analyzed by Cox regression and Kaplan-Meier analyses. A nomogram was used to predict the impact of NLRP12 on prognosis. Gene Ontology term analysis and gene set enrichment analysis (GSEA) were performed to identify the signaling pathways related to NLRP12 expression. Immune cells infiltration for NLRP12 was analyzed using single-sample GSEA. The relationship between NLRP12 and tumor-infiltrating immune cells (TICs) was investigated by a Wilcoxon rank sum test. The expression of NLRP12 were also further verified in EOC tissues and cell lines. Additionally, we confirmed the biological function of NLRP12 in vitro. RESULTS: NLRP12 was highly expressed in patients with EOC from TCGA. High NLRP12 expression correlated with poor disease-specific survival (p < 0.001) and overall survival (p < 0.001). Multivariate analysis revealed that NLRP12 expression was an independent prognostic marker for overall survival (p = 0.042). The C-indexes and calibration plots of the nomogram based on multivariate analysis indicated an effective predictive performance for EOC patients. GSEA showed enrichment of cell adhesion, tumorigenesis and immune response in the NLRP12 high expression group. Increased NLRP12 expression correlated positively with several TICs, including macrophages, neutrophils, T effector memory cells and immature dendritic cells (p < 0.001). In addition, NLRP12 silencing inhibited cell proliferation and migration in EOC cells. CONCLUSIONS: In conclusion, increased NLRP12 expression correlated significantly with poor survival and immune infiltration in EOC.

sB7-H4 is a diagnostic biomarker in epithelial ovarian cancer and correlates to platinum resistance.

Ovarian cancer, with its high mortality rate among gynecological cancers, is often diagnosed late due to the lack of early diagnostic symptoms and biomarkers. The tumor immune microenvironment has become a focal point in cancer diagnostic and therapeutic research. Among these, B7-H4, a checkpoint protein, plays a crucial role in immune regulation and tumor suppression, contributing to immune evasion within the tumor microenvironment. This study aims to identify the concentration of soluble B7-H4(sB7-H4) in the plasma of patients with ovarian cancer and to evaluate its clinical significance. Through a comprehensive analysis involving enzyme-linked immunosorbent assay, immunohistochemistry, and multicolor immunofluorescence, we quantified sB7-H4 levels in patient plasma and ascites, correlating these findings with tissue expression and clinical outcomes. Results indicated a strong association between high sB7-H4 levels and advanced disease, surgical outcomes, lymphatic metastasis, and platinum resistance. When compared with traditional biomarkers CA125 and HE4, sB7-H4, especially in conjunction with these markers, enhances the diagnostic accuracy for epithelial ovarian cancer, offering insights into disease progression and therapeutic efficacy. This comprehensive analysis suggests that sB7-H4 is a promising biomarker for EOC, providing valuable insights into diagnosis, stage differentiation, treatment effectiveness, and prognosis.

ZSWIM4 inhibition improves chemosensitivity in epithelial ovarian cancer cells by suppressing intracellular glycine biosynthesis.

BACKGROUND: Zinc finger SWIM-type containing 4 (ZSWIM4) induces drug resistance in breast cancer cells. However, its role in epithelial ovarian cancer (EOC) remains unknown. In this study, we aimed to investigate the clinical significance of ZSWIM4 expression in EOC and develop new clinical therapeutic strategies for EOC. METHODS: ZSWIM4 expression in control and EOC tumor tissues was examined using immunohistochemistry. Lentiviral transduction, Cell Counting Kit-8 assay, tumorsphere formation assay, flow cytometry, western blotting, and animal xenograft model were used to assess the role of ZSWIM4 in chemotherapy. Cleavage Under Targets and Tagmentation (CUT&Tag) assays, chromatin immunoprecipitation assays, and luciferase reporter assays were used to confirm FOXK1-mediated upregulation of ZSWIM4 expression. The mechanism by which ZSWIM4 inhibition improves chemosensitivity was evaluated using RNA-sequencing. A ZSWIM4-targeting inhibitor was explored by virtual screening and surface plasmon resonance analysis. Patient-derived organoid (PDO) models were constructed from EOC tumor tissues with ZSWIM4 expression. RESULTS: ZSWIM4 was overexpressed in EOC tumor tissues and impaired patient prognoses. Its expression correlated positively with EOC recurrence. ZSWIM4 expression was upregulated following carboplatin treatment, which, in turn, contributed to chemoresistance. Silencing ZSWIM4 expression sensitized EOC cells to carboplatin treatment in vitro and in vivo. FOXK1 could bind to the GTAAACA sequence of the ZSWIM4 promoter region to upregulate ZSWIM4 transcriptional activity and FOXK1 expression increased following carboplatin treatment, leading to an increase in ZSWIM4 expression. Mechanistically, ZSWIM4 knockdown downregulated the expression of several rate-limiting enzymes involved in glycine synthesis, causing a decrease in intracellular glycine levels, thus enhancing intracellular reactive oxygen species production induced by carboplatin treatment. Compound IPN60090 directly bound to ZSWIM4 protein and exerted a significant chemosensitizing effect in both EOC cells and PDO models. CONCLUSIONS: ZSWIM4 inhibition enhanced EOC cell chemosensitivity by ameliorating intracellular glycine metabolism reprogramming, thus providing a new potential therapeutic strategy for EOC.

Functional genetic variants of GEN1 predict overall survival of Chinese epithelial ovarian cancer patients.

BACKGROUND: Inherited variations in DNA double-strand break (DSB) repair pathway are known to influence ovarian cancer occurrence, progression and treatment response. Despite its significance, survival-associated genetic variants within the DSB pathway remain underexplored. METHODS: In the present study, we performed a two-phase analysis of 19,290 single-nucleotide polymorphisms (SNPs) in 199 genes in the DSB repair pathway from a genome-wide association study (GWAS) dataset and explored their associations with overall survival (OS) in 1039 Han Chinese epithelial ovarian carcinoma (EOC) patients. After utilizing multivariate Cox regression analysis with bayesian false-discovery probability for multiple test correction, significant genetic variations were identified and subsequently underwent functional prediction and validation. RESULTS: We discovered a significant association between poor overall survival and the functional variant GEN1 rs56070363 C > T (CT + TT vs. TT, adjusted hazard ratio (HR) = 2.50, P < 0.001). And the impact of GEN1 rs56070363 C > T on survival was attributed to its reduced binding affinity to hsa-miR-1287-5p and the resultant upregulation of GEN1 mRNA expression. Overexpression of GEN1 aggregated EOC cell proliferation, invasion and migration presumably by influencing the expression of immune inhibitory factors, thereby elevating the proportion of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and then constructing an immunosuppressive tumor microenvironment. CONCLUSIONS: In conclusion, GEN1 rs56070363 variant could serve as a potential predictive biomarker and chemotherapeutic target for improving the survival of EOC patients.

Synergistic antitumor effect of liposomal-based formulations of olaparib and topotecan in primary epithelial ovarian cancer cells.

BACKGROUND: Olaparib is a PARP inhibitor inducing synthetic lethality in tumors with deficient homologous recombination (HRD) caused by BRCA1/2 mutations. The FDA has approved monotherapy for first-line platinum-sensitive, recurrent high-grade epithelial ovarian cancer. Combination therapy alongside DNA-damaging therapeutics is a promising solution to overcome the limited efficacy in patients with HRD. The present study was designed to develop topotecan- and olaparib-loaded liposomes (TLL and OLL) and assess the effectiveness of their combination in patient-derived ovarian cancer samples. METHODS: We used HEOC, four clear-cell tumors (EOC 1-4), malignant ascites, and an OCI-E1p endometrioid primary ovarian cancer cell line and performed NGS analysis of BRCA1/2 mutation status. Antiproliferative activity was determined with the MTT assay. The Chou-Talalay algorithm was used to investigate the in vitro pharmacodynamic interactions of TLLs and OLLs. RESULTS: The OLL showed significantly higher efficacy in all ovarian cancer types with wild-type BRCA1/2 than a conventional formulation, suggesting potential for increased in vivo efficacy. The TLL revealed substantially higher toxicity to EOC 1, EOC 3, ascites and lower toxicity to HEOC than the standard formulation, suggesting better therapeutic efficacy and safety profile. The combination of studied compounds showed a higher reduction in cell viability than drugs used individually, demonstrating a synergistic antitumor effect at most of the selected concentrations. CONCLUSIONS: The concentration-dependent response of different ovarian cancer cell types to combination therapy confirms the need for in vitro optimization to maximize drug cytotoxicity. The OLL and TLL combination is a promising formulation for further animal studies, especially for eliminating epithelial ovarian cancer with wild-type BRCA1/2.

The anti-tumor effects of AZD4547 on ovarian cancer cells: differential responses based on c-Met and FGF19/FGFR4 expression.

BACKGROUND: The FGF/FGFR signaling pathway plays a critical role in human cancers. We analyzed the anti-tumor effect of AZD4547, an inhibitor targeting the FGF/FGFR pathway, in epithelial ovarian cancer (EOC) and strategies on overcoming AZD4547 resistance. METHODS: The effect of AZD4547 on cell viability/migration was evaluated and in vivo experiments in intraperitoneal xenografts using EOC cells and a patient-derived xenograft (PDX) model were performed. The effect of the combination of AZD4547 with SU11274, a c-Met-specific inhibitor, FGF19-specific siRNA, or an FGFR4 inhibitor was evaluated by MTT assay. RESULTS: AZD4547 significantly decreased cell survival and migration in drug-sensitive EOC cells but not drug-resistant cells. AZD4547 significantly decreased tumor weight in xenograft models of drug-sensitive A2780 and SKOV3ip1 cells and in a PDX with drug sensitivity but not in models with drug-resistant A2780-CP20 and SKOV3-TR cells. Furthermore, c-Met expression was high in SKOV3-TR and HeyA8-MDR cells, and co-administration of SU11274 and AZD4547 synergistically induced cell death. In addition, expressions of FGF19 and FGFR4 were high in A2780-CP20 cells. Combining AZD4547 with FGF19 siRNA or with a selective FGFR4 inhibitor led to significantly reduced cell proliferation in A2780-CP20 cells. CONCLUSIONS: This study showed that AZD4547 has significant anti-cancer effects in drug-sensitive cells and PDX models but not in drug-resistant EOC cells. In drug-resistant cells, the expression level of c-Met or FGF19/FGFR4 may be a predictive biomarker for AZD4547 treatment response, and a combination strategy of drugs targeting c-Met or FGF19/FGFR4 together with AZD4547 may be an effective therapeutic strategy for EOC.

Pan-immune-inflammation value: a new prognostic index in epithelial ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is one of the deadliest gynaecological malignancies worldwide. The aim of this retrospective study was to create a predictive scoring model based on simple immunological and inflammatory parameters to predict overall survival (OS) and progression-free survival (PFS) in patients with EOC. METHODS: We obtained 576 EOC patients and randomly assigned them to the training set (n = 405) and the validation set (n = 171) in a ratio of 7:3. We retrospectively evaluated the association between PIV and OS and PFS using a novel immunoinflammatory marker, according to the optihmal treshold of PIV, we divided the patients into two different subgroups, high PIV (PIV > 254.9) and low PIV (PIV ≤ 254.9). Pan-immune Inflammatory Value (PIV) was computed as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). Then developed a simple score prediction model based on several independent prognostic parameters using Cox regression analysis. We used receiver operator characteristic (ROC) curves, calibration plots, and decision analysis (DCA) curves to evaluate the performance of the model. Finally, we used Kaplan-Meier curves to ensure that the model could distinguish well between low- and high-risk groups. RESULTS: There was a significant difference in survival outcomes between high PIV (PIV > 310.2) and low PIV (PIV ≤ PIV310.2) (3-year survival rates of 61.34% and 76.71%, respectively); 5-year OS, 25.21% and 51.14%, respectively; 3-year PFS, 40.90% and 65.30%; 5-year PFS, 19.33% and 39.73%, respectively). Column plots of OS and PFS were constructed using independent prognostic factors. In the training module, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.713, 0.796, 0.839, and 0.730, 0.799, 0.826, respectively.In the validation cohort, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.676, 0.803, 0.685, and 0.700, respectively, 0.754, 0.727. The calibration curves showed good agreement between predicted survival and actual observations. The decision analysis curves also showed that the current model has good accuracy and clinical applicability. 3-year OS was 61.34% and 76.71%, respectively; 5-year OS was 25.21% and 51.14%, respectively; 3-year PFS was 40.90% and 65.30%, respectively; 5-year PFS was 19.33% and 39.73%, respectively. CONCLUSIONS: We constructed and validated a PIV-based nomogram to predict OS and PFS in EOC patients, with a view to helping gynaecologists converge on oncologists in their treatment and follow-up expertise in epithelial ovarian cancer.

Contrast-enhanced CT radiomics for preoperative prediction of stage in epithelial ovarian cancer: a multicenter study.

BACKGROUND: Preoperative prediction of International Federation of Gynecology and Obstetrics (FIGO) stage in patients with epithelial ovarian cancer (EOC) is crucial for determining appropriate treatment strategy. This study aimed to explore the value of contrast-enhanced CT (CECT) radiomics in predicting preoperative FIGO staging of EOC, and to validate the stability of the model through an independent external dataset. METHODS: A total of 201 EOC patients from three centers, divided into a training cohort (n = 106), internal (n = 46) and external (n = 49) validation cohorts. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used for screening radiomics features. Five machine learning algorithms, namely logistic regression, support vector machine, random forest, light gradient boosting machine (LightGBM), and decision tree, were utilized in developing the radiomics model. The optimal performing algorithm was selected to establish the radiomics model, clinical model, and the combined model. The diagnostic performances of the models were evaluated through receiver operating characteristic analysis, and the comparison of the area under curves (AUCs) were conducted using the Delong test or F-test. RESULTS: Seven optimal radiomics features were retained by the LASSO algorithm. The five radiomics models demonstrate that the LightGBM model exhibits notable prediction efficiency and robustness, as evidenced by AUCs of 0.83 in the training cohort, 0.80 in the internal validation cohort, and 0.68 in the external validation cohort. The multivariate logistic regression analysis indicated that carcinoma antigen 125 and tumor location were identified as independent predictors for the FIGO staging of EOC. The combined model exhibited best diagnostic efficiency, with AUCs of 0.95 in the training cohort, 0.83 in the internal validation cohort, and 0.79 in the external validation cohort. The F-test indicated that the combined model exhibited a significantly superior AUC value compared to the radiomics model in the training cohort (P < 0.001). CONCLUSIONS: The combined model integrating clinical characteristics and radiomics features shows potential as a non-invasive adjunctive diagnostic modality for preoperative evaluation of the FIGO staging status of EOC, thereby facilitating clinical decision-making and enhancing patient outcomes.

The up-regulation of PAK2 indicates unfavorable prognosis in patients with serous epithelial ovarian cancer and contributes to paclitaxel resistance in ovarian cancer cells.

BACKGROUND: The main challenge in treating ovarian cancer is chemotherapy resistance. Previous studies have shown that PAK2 is highly expressed in various cancers. This research investigates whether increased PAK2 expression contributes to chemo-resistance and poor prognosis in ovarian cancer. METHODS: Initially, bioinformatics analysis was used to assess the importance of PAK2 mRNA up-regulation in ovarian cancer. This was then validated using tissue microarray to confirm PAK2 protein expression and localization in clinical samples. Univariate and multivariate logistic regression analyses were carried out to identify potential risk factors for chemo-resistance in serous epithelial ovarian cancer (EOC), while multivariate Cox regression and Kaplan-Meier analysis were conducted to ascertain prognostic factors for overall survival (OS) and disease-free survival (DFS) in patients with serous EOC. In vitro experiments were conducted to verify if inhibiting PAK2 expression could increase A2780/Taxol cells' sensitivity to paclitaxel, as shown by evaluating cell proliferation, apoptosis, transwell, and clone formation. Additionally, the interaction between PAK2, lnc-SNHG1, and miR-216b-5p was verified using RIP and luciferase reporter assays. Rescue experiments were undertaken to examine the influence of the lnc-SNHG1/miR-216b-5p/PAK2 axis on the development of paclitaxel resistance in A2780/Taxol cells. RESULTS: The bioinformatics analysis indicated a notable increase in PAK2 expression in ovarian malignant tumors compared to adjacent tissues, particularly in patients with stage III-IV disease compared to those with stage I-II disease (P = 0.0056). Elevated levels of PAK2 were linked to reduced OS in ovarian cancer patients, although no significant association was observed with DFS. Immunohistochemistry findings further supported these results, showing positive PAK2 protein expression in chemo-resistant serous EOC tissues, predominantly localized in the cytoplasm, which correlated with poorer OS and DFS outcomes. In vitro experiments demonstrated that the downregulation of PAK2 in A2780/Taxol cells led to a reduction in colony formation, an increase in apoptosis, and a diminished capacity for cell invasion. Subsequent analysis confirmed that lnc-SNHG1 functions as a competitive endogenous RNA (ceRNA) by interacting with miR-216b-5p and regulating PAK2 expression. Rescue experiments demonstrated that lnc-SNHG1 induces resistance to paclitaxel in A2780/Taxol cells by modulating the miR-216b-5p/PAK2 axis. CONCLUSIONS: PAK2 shows promise as a predictor of chemotherapy resistance and poor outcomes in ovarian cancer, indicating its potential use as a treatment target to overcome this resistance.

Peritumoral MRI Radiomics Features Increase the Evaluation Efficiency for Response to Chemotherapy in Patients With Epithelial Ovarian Cancer.

BACKGROUND: It remains unclear whether extracting peritumoral volume (PTV) radiomics features are useful tools for evaluating response to chemotherapy of epithelial ovarian cancer (EOC). PURPOSE: To evaluate MRI radiomics signatures (RS) capturing subtle changes of PTV and their added evaluation performance to whole tumor volume (WTV) for response to chemotherapy in patients with EOC. STUDY TYPE: Retrospective. POPULATION: 219 patients aged from 15 to 79 years were enrolled. FIELD STRENGTH/SEQUENCE: 3.0 or 1.5T, axial fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (CE-T1WI). ASSESSMENT: MRI features were extracted from the four axial sequences and six different volumes of interest (VOIs) (WTV and WTV + PTV (WPTV)) with different peritumor sizes (PS) ranging from 1 to 5 mm. Those features underwent preprocessing, and the most informative features were selected using minimum redundancy maximum relevance and least absolute shrinkage and selection operator to construct the RS. The optimal RS, with the highest area under the curve (AUC) of receiver operating characteristic was then integrated with independent clinical characteristics through multivariable logistic regression to construct the radiomics-clinical model (RCM). STATISTICAL TESTS: Mann-Whitney U test, chi-squared test, DeLong test, log-rank test. P < 0.05 indicated a significant difference. RESULTS: All the RSs constructed on WPTV exhibited higher AUCs (0.720-0.756) than WTV (0.671). Of which, RS with PS = 2 mm displayed a significantly better performance (AUC = 0.756). International Federation of Gynecology and Obstetrics (FIGO) stage was identified as the exclusive independent clinical evaluation characteristic, and the RCM demonstrated higher AUC (0.790) than the RS, but without statistical significance (P = 0.261). DATA CONCLUSION: The radiomics features extracted from PTV could increase the efficiency of WTV radiomics for evaluating the chemotherapy response of EOC. The cut-off of 2 mm PTV was a reasonable value to obtain effective evaluation efficiency. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

What is the most pertinent definition of malnutrition in epithelial ovarian cancer to assess morbidity and mortality?

INTRODUCTION: Malnutrition is common in ovarian cancer and is a major cause of morbidity and mortality. We aimed to define the most pertinent way to assess malnutrition in patients with epithelial ovarian cancer (EOC) in order to study its impact on morbidity (intra and post-operative complications) and survival (OS, overall survival and RFS, recurrence-free survival). METHODS: We retrospectively included all patients with EOC from 2003 to 2020. Nutritional status was assessed using the weight loss at diagnosis (more or <5%), albuminemia, the Nutritional Risk Index (NRI), and the Malnutrition Universal Screening Tool (MUST). RESULTS: Six hundred and fifteen patients were included. Among them, 34% declared having lost >5% of their usual weight, 58% had an albuminemia <35 g/L, 86% presented an abnormal NRI and 29% an abnormal MUST score. After univariate analysis, weight loss>5% appeared to be significantly associated with RFS. An abnormal NRI or MUST score were significantly associated with a decrease in OS in univariate analysis. None of the markers of malnutrition studied were correlated with morbidity. CONCLUSION: We were not able to reach a consensus concerning the most accurate definition to define malnutrition and predict morbidity and mortality in EOC. However, this modifiable prognosis factor must be systematically assessed and managed accordingly.

Distribution and prognostic role of BRCA status in elderly ovarian cancer patients.

OBJECTIVE: In the era of target therapy and personalized medicine, BRCA mutational status has a major influence on survival in ovarian cancer patients. Our aim is to verify if the poorer prognosis of elderly ovarian cancer patients can be related to the biology of the tumor beyond their own morbidities and/or suboptimal treatments. METHODS: This is a retrospective single-institution study evaluating prognosis of patients with a diagnosis of ovarian cancer and known BRCA status. We collected clinical and surgical characteristics and the distribution of BRCA mutational status according to age groups. RESULTS: 1840 patients were included in the analysis. The rate of BRCA mutated decreased over age-range from 49.7% in patients aged <50 years to 18.8% in ≥80 years old women. The prognostic role of BRCA status on survival is maintained when focusing on the elderly population, with improved Disease Free Survival (27.2 months vs 16.5 months for BRCA mutated and wild type respectively, p = 0.001) and Cancer Specific Survival (117.6 months vs 43.1 months for BRCA mutated and wild type respectively, p = 0.001) for BRCAmut compared to BRCAwt patients. In the multivariable analysis, among elderly women, upfront surgery and BRCA mutation are independent factors affecting survival. CONCLUSIONS: Elderly patients experiment a poorer prognosis due to multiple factors that include both their medical condition and comorbidities, under-treatment and most importantly disease characteristics. We found that beyond disparities, BRCA mutation is still the strongest independent prognostic factor affecting both the risk of recurrence and death due to disease.

Has time to chemotherapy from primary debulking surgery in advanced ovarian cancer an impact on survival? - A population-based nationwide SweGCG study.

OBJECTIVE: The aim of the study was to investigate if time to start chemotherapy (TTC) after primary debulking surgery (PDS) impacted relative survival (RS) in advanced epithelial ovarian/fallopian tube/primary peritoneal cancer (EOC). METHODS: Nationwide population-based study of women with EOC FIGO stages IIIC-IV, registered 2008-2018 in the Swedish Quality Register for Gynecologic Cancer, treated with PDS and chemotherapy. TTC was categorized into; ≤21 days, 22-28 days, 29-35 days, 36-42 days and > 42 days. Relative survival (RS) was estimated using the Pohar-Perme estimate of net survival. Multivariable analyses of excess mortality rate ratios (EMRRs) were estimated by Poisson regression models. RESULTS: In total, 1694 women were included. The median age was 65.0 years. Older age and no residual disease were more common in TTC >42 days than 0-21 days. The RS at 5-years was 37.9% and did not differ between TTC groups. In the R0 (no residual disease) cohort (n = 806), 2-year RS was higher in TTC ≤21 days (91.6%) and 22-28 days (91.4%) than TTC >42 days (79.1%). TTC >42 days (EMRR 2.33, p = 0.026), FIGO stage IV (EMRR 1.83, p = 0.007) and non-serous histology (EMRR 4.20, p < 0.001) were associated with 2-year worse excess mortality compared to TTC 0-21 days, in the R0 cohort. TTC was associated with 2-year survival in the R0 cohort in FIGO stage IV but not in stage IIIC. TTC was not associated with RS in patients with residual disease. CONCLUSIONS: For the entire cohort, stage IV, non-serous morphology and residual disease, but not TTC, influenced 5-year relative survival. However, longer TTC was associated with a poorer 2-year survival for those without residual disease after PDS.

Relationship between frailty and nutrition: Refining predictors of mortality after primary cytoreductive surgery for ovarian cancer.

OBJECTIVE: We aimed to examine the interplay between frailty and nutritional status on 90-day mortality after primary cytoreductive surgery (PCS) for ovarian cancer (OC). METHODS: Patients with OC who underwent PCS from 1/2/2006-4/30/2018 at a single institution were identified. Frailty index (FI) includes 30 items and is calculated summing across all the item scores and dividing by the total; frailty was defined as FI ≥0.15. Nutritional status was considered impaired when preoperative serum albumin was <3.5 g/dL. Logistic regression was used to analyze the association between FI (continuous) and albumin status (binary) and 90-day postoperative mortality. RESULTS: A total of 533 patients (mean age, 64.4 years) were included, the majority were stage IIIC disease and serous histology. Albumin was <3.5 g/dL in 87 patients (16.3%) and 113 patients (21.2%) were considered frail. Median FI was 0.07 (IQR 0.03, 0.13). Postoperative 90-day mortality occurred in 24 patients (4.5%). Mortality within 90 days was higher amongst patients with low albumin (12/87, 13.8%), regardless of frailty status (13.8% [9/65] non-frail and 13.6% [3/22] frail patients). Ninety-day mortality in patients with normal albumin (n = 446) was over twice as likely in frail versus non-frail patients (5.5% [5/91] vs. 2.0% [7/355], respectively, p = 0.08). A model to assess 90-day mortality that included both FI and low albumin significantly improved the overall discrimination compared to low albumin alone (AUC 0.76 vs. 0.68 p = 0.03). CONCLUSION: Our findings suggest that frailty and nutrition are both related to 90-day mortality. Preoperative interventions to improve functional and nutritional characteristics are needed.