High-grade serous ovarian carcinoma (HGSOC) is associated with a high risk of postoperative recurrence, and the timing of recurrence is closely related to patient survival outcomes and subsequent treatment strategies. However, current postoperative surveillance primarily relies on clinical indicators and routine imaging examinations, which offer limited predictive accuracy. Although deep learning–based image analysis has shown promise in capturing tumor heterogeneity and improving prognostic assessment, studies integrating preoperative contrast-enhanced computed tomography (CE-CT) and ultrasound imaging for recurrence risk prediction in HGSOC remain limited. This single-center retrospective study enrolled 293 patients with pathologically confirmed HGSOC, who were randomly assigned to a training cohort and an internal validation cohort. Separate two-dimensional deep learning survival models were developed using preoperative CE-CT and ultrasound images. A Cox partial likelihood–based time-to-event loss function was applied to generate modality-specific deep learning scores (DL-scores). Independent clinical predictors were identified through univariate and multivariate Cox regression analyses and were integrated with CT-DL and US-DL scores to construct a multimodal Cox prognostic model, which was visualized using a nomogram. Model performance was assessed using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, Kaplan–Meier survival analysis, calibration curves, and decision curve analysis. Bootstrap resampling was performed to evaluate model robustness, and Gradient-weighted Class Activation Mapping (Grad-CAM) was used to visualize model attention. The multimodal integrated model demonstrated superior prognostic performance, achieving C-index values of 0.840 in the training cohort and 0.722 in the internal validation cohort. Time-dependent ROC analysis showed that the combined model achieved areas under the curve (AUCs) of 0.880, 0.890, and 0.892 for predicting 1-, 2-, and 3-year recurrence-free survival (RFS) in the training cohort, and 0.864, 0.781, and 0.772 in the validation cohort, respectively. Kaplan–Meier survival analysis revealed a significant separation between high- and low-risk groups (log-rank test, all P < 0.001). Calibration and decision curve analyses indicated good agreement between predicted and observed outcomes and a higher net clinical benefit. Bootstrap resampling further confirmed the robustness of the multimodal model. Grad-CAM visualizations suggested that the model primarily focused on tumor and peritumoral regions. This study proposes a multimodal prognostic framework integrating deep learning features from CE-CT and ultrasound with clinical variables for preoperative prediction of postoperative recurrence risk in HGSOC. Using routinely acquired imaging data, the model shows consistent interpretability and performance, supporting its use as an exploratory decision-support and risk-stratification tool. Prospective, multicenter validation is required before clinical implementation.

To investigate the differences in lipid metabolism and obesity between patients with ovarian endometrioid carcinoma (OEC) and ovarian clear cell carcinoma (OCCC), both of which are classified as endometriosis-associated Type I ovarian cancers. This retrospective study included 133 patients who underwent surgery for OEC (n = 50) or OCCC (n = 83) between 2010 and 2022. Preoperative serum lipid markers (total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) and body mass index (BMI) were compared between the two groups. Associations with menopausal status and disease stage were examined, and independent predictors were evaluated by multivariate logistic regression. Patients with OEC had significantly higher TC (215 vs. 199.5 mg/dL, p = 0.040), LDL-C (139 vs. 120.6 mg/dL, p = 0.026), and BMI (22.1 vs. 20.4 kg/m2, p = 0.020) compared with those with OCCC. No significant differences were observed for HDL-C. In premenopausal women, TC and LDL-C were significantly higher in patients with OEC, whereas no intergroup differences were found in postmenopausal women. Among patients with OEC, those with advanced-stage disease had higher TC and LDL-C, whereas no stage-related differences were observed in patients with OCCC. Multivariate analysis identified BMI and LDL-C as independent factors associated with OEC. Lipid metabolism abnormalities and obesity were more strongly associated with OEC than with OCCC, suggesting subtype-specific metabolic mechanisms of carcinogenesis and progression. These findings highlight the importance of metabolic factors in OEC, warranting further prospective studies.

A series of five zinc(II) complexes containing two 4(1H)-quinolinone-based ligands (Hqui), with the composition of [Zn(H2O)(qui)2] (1–5), was prepared and characterised. The X-ray structure of complex (3·3EtOH) revealed a distorted square-pyramidal geometry with the O5 donor set, originating from two bidentate-coordinated qui ligands and a coordinated water molecule. Hirshfeld surface analysis showed that the crystal structure is primarily stabilised by O–H···O and N–H···O hydrogen bonds, supported by C–H···O and C–H···Cl contacts, and distinct π–π stacking between quinolinone units. The shape-index and curvedness maps indicated π–π stacking and planar packing features, whilst the fingerprint plots revealed H···H, H···C/C···H, and H···O/O···H contacts as the main contributors to the intermolecular landscape, emphasising the roles of hydrogen bonding and dispersion forces in stabilising the crystal packing. The complexes were tested for their in vitro antitumour activity on human osteosarcoma (HOS), breast adenocarcinoma (MCF7), ovarian carcinoma (A2780), androgen-sensitive prostate adenocarcinoma (LNCaP), and Caucasian prostate adenocarcinoma (PC3) cancer cell lines. The limited solubility of the complexes in cell culture media prevented cytotoxicity testing at concentrations above 10 µM (or above 20 µM), and unfortunately, the exact IC50 values could not be determined under these conditions, although a decrease in cancer cell viability with increasing concentrations of the complexes was observed in some cases.

High-grade serous ovarian carcinoma (HGSOC) is characterized by profound genomic instability and spatial heterogeneity. Liquid biopsy, utilizing circulating tumor DNA (ctDNA), offers a non-invasive approach to capture the comprehensive mutational landscape of the disease. This pilot study evaluated the concordance of genomic alterations between cell-free DNA (cfDNA) and matched tumor tissue in patients with HGSOC. Twelve patients with HGSOC undergoing primary cytoreductive surgery were enrolled. Using the Macrogen® Axen™ Cancer Panel 2 with unique molecular identifier (UMI) technology for error suppression, we achieved a theoretical limit of detection of ~0.36% VAF. The mean cfDNA concentration was 107.3 ng/mL, showing a significant positive correlation with FIGO stage (p = 0.016). While the sensitivity of cfDNA to detect tissue-confirmed mutations was 57.6%, the overall gene-level concordance was 95.3%, largely driven by negative agreement in wild-type genes. Liquid biopsy revealed a significantly broader mutational spectrum (mean 9.67 alterations/patient) compared to tissue (5.50/patient). Crucially, concordant mutations exhibited high variant allele frequencies (VAFs) (mean 41.4%), whereas plasma-unique discordant mutations showed significantly lower VAFs (mean 7.31%, p < 0.001). These preliminary findings suggest that while tissue biopsy likely reflects the dominant clonal population, liquid biopsy may serve as a potential molecular mirror, capturing subclonal variants from spatially distinct metastatic sites and hypoxic niches.

Background/Objectives: Low-grade serous ovarian carcinoma (LGSOC) is known as an uncommon subtype of cancer with poor response to standard chemotherapy, so novel targets are required. The current study aims to highlight the Human Epidermal Growth Factor Receptor-2 (HER2/neu) immunohistochemical (IHC) expression in LGSOCs. Methods: The study was conducted using 33 cases of LGSOCs from the calendar years 2017-2024. IHC staining was performed using antibody anti-HER2/neu (clone 4B5). HER2/neu scoring was performed based on the American Society of Clinical Oncology and the College of American Pathologists (ASCO/CAP) criteria for breast carcinoma. Results: The mean age of the 33 patients was 46.5 years. International Federation of Gynecology and Obstetrics (FIGO) stage data for patients revealed a predominance of advanced disease: 82.7% (24/29) were in advanced stages. Early stages comprised 17.3% (5/29) of cases. The study did not find HER2/neu overexpression in all cases. In 3.0% of samples (1/33), HER2/neu IHC staining was scored as 1+, and in 6.1% (2/33) of all LGSOCs, ultralow phenotype was observed. Of 23 cases in the HER2-negative group, 6 patients were alive with progressive disease, 1 patient died in 5 months, and 16 were alive with no evidence of disease. Of two patients with the HER2-ultralow phenotype, one was alive with no evidence of disease at 16 months follow-up. Conclusions: The results support the idea that HER2/neu overexpression is exceptionally rare in LGSOC; nevertheless, future trials are essential to fully characterize the spectrum of HER2/neu alterations in LGSOC and to determine definitively whether the rare cases with mutations or ultralow expression could represent a small subgroup that might benefit from specific targeted agents.

Epithelial ovarian cancer (EOC) is the deadliest gynecologic cancer, due to asymptomatic early stages, vague symptoms in later stages, and limited clinical tools. Despite distinct clinicopathologic features, all EOC histotypes typically receive identical primary treatment, and are often studied as a single entity. We analyzed the proteome of 244 patients and identified differentially abundant proteins (DAPs) with and without stage specificity across histotypes and constructed panels of DAPs to distinguish histotypes in both early and late stages. Survival analysis was performed to find proteins associated with clinical outcomes, and enrichment analysis was conducted to reveal biological processes connected to prognosis and the proteins involved. Here we find DAPs without (e.g. S100A1, AGR2, CTH) and with (TSPYL, VWA2, GPC6, S100P) stage-specificity for each histotype. Survival analysis revealed histotype- and stage-specific prognostic markers (e.g., EXO3CL2, PPIL6, GYG1, GAPDH), while biological process enrichment highlighted pathways underlying clinical outcomes. Our findings provide novel diagnostic and prognostic biomarker candidates and insights into mechanisms driving EOC progression with histotype- and stage-specificity. This may aid the development of improved clinical tools for detection, patient stratification, and targeted therapies in EOC.

Ovarian clear cell carcinoma (CCC) is an aggressive subtype of ovarian cancer that is resistant to conventional chemotherapy, resulting in poor prognosis. CCC develops from endometriosis, which exposes tumor cells to a hypoxic microenvironment, thereby highlighting the critical role of hypoxia in ovarian CCC progression. Thus, identifying novel therapeutic targets, particularly those associated with hypoxia, is important. Hypoxia-inducible factor 2A (HIF2A) is a key regulator of hypoxic responses, but its role in ovarian CCC remains unclear. This study assessed the prognostic and functional significance of HIF2A in ovarian CCC and investigated its potential as a therapeutic target. Inhibiting HIF2A significantly suppressed ovarian CCC tumor growth through a genetic knockdown cell line as well as pharmacological inhibition using a novel HIF2A inhibitor, NKT2152. In vitro experiments showed that HIF2A suppression enhanced mitochondrial respiration and increased mitochondrial reactive oxygen species production alongside the downregulation of HIF2A target genes. Moreover, treatment with NKT2152 significantly reduced tumor growth in both cell line-derived and patient-derived xenograft models. In conclusion, our findings provide novel insights into the prognostic and functional role of HIF2A in ovarian CCC and underscore its potential as a promising therapeutic target.

Objective: To investigate the differences in clinicopathological and molecular characteristics between pure ovarian endometrioid carcinoma (POEC) and synchronous endometrial and ovarian endometrioid carcinoma (SEOEC), aiming to provide a basis for their differential diagnosis and individualized treatment. Methods: Clinical and pathological data were collected from ovarian endometrioid carcinoma patients and they were divided into POEC group (219 cases) and SEOEC group (169 cases) according to whether they had endometrioid endometrial carcinoma or not. Clinical data including the age at onset, reasons for medical consultation, maximum diameter of ovarian tumors and pathological examination results such as histologic grading of the lesions were collected. Additionally, follow-up outcomes and survival status of the patients were also recorded. Molecular subtyping results were obtained from 108 cases of POEC group and 109 cases of SEOEC group patients. Large-scale targeted sequencing using next-generation sequencing was performed on 76 POEC group samples (32 with matched peripheral blood) and 51 SEOEC group samples (46 with matched peripheral blood/normal tissue). The prognosis of POEC group and SEOEC group were analyzed. Moreover, SEOEC group were further stratified to high-risk group and low-risk group according to 2020 WHO classification of tumors and 2023 International Federation of Gynecology and Obstetrics (FIGO) staging of endometrial cancer. Results: (1) Clinicopathological characteristics: compared to the SEOEC group, POEC group patients exhibited the following characteristics: younger age at diagnosis (50.0 years vs 38.0 years, P<0.001), higher proportion presenting with typical ovarian cancer symptoms (45.7% vs 92.1%, P<0.001), higher detection rates of ovarian endometriosis (14.9% vs 56.2%, P<0.001) and uterine adenomyosis (23.0% vs 37.0%, P=0.021), higher proportion of low grade tumors (78.7% vs 95.4%, P<0.001), lower proportion of mismatch repair deficiency subtype (23.9% vs 3.7%, P<0.001). (2) Gene mutation profile: although the driver gene mutation profiles were similar between the two groups, POEC group patients had a significantly lower PTEN (22.4% vs 64.0%, P<0.001) and CTNNB1 (22.4% vs 48.0%, P=0.014) mutation rates compared to SEOEC group. Also, POEC group had a higher KRAS mutation rate than SEOEC group patients (50.0% vs 28.0%, P=0.055). (3)Prognosis: survival analysis revealed that POEC group patients had a significantly shater progression free survival time compared to the low-risk SEOEC group patients(P=0.046). However, their long-term survival outcomes (both overall survival and disease specific survival) were significantly better than those of the high-risk SEOEC group patients (P=0.018 and P=0.046, respectively). Conclusions: POEC and SEOEC represent two distinct tumor entities with significantly different clinical, pathological and molecular features. Accurate differential diagnosis is crucial for correct clinical decision-making.

This study utilized a novel Proximity Barcoding Assay to perform high-resolution proteomic profiling of individual plasma extracellular vesicles from 85 patients with advanced high-grade serous ovarian carcinoma (OC) and 95 healthy controls (HC). Single-EV analysis identified 119 differentially expressed proteins and 17 distinct EV subpopulations. Cluster 7 (enriched in integrins ITGB3, ITGB1, and ITGA6) was significantly elevated in OC plasma (4.47% in HC vs. 14.79-15.82% in OC). Machine learning (SVM-RFE, LASSO, Random Forest) identified a diagnostic panel (ITGA6, ITGB2, ILK) achieving exceptional accuracy in distinguishing OC from HC (AUC = 0.999 training; 1.000 validation). Furthermore, risk models incorporating specific protein signatures effectively stratified patients by platinum sensitivity/resistance (9-protein panel: ILK, CDCP1, CD86, CLDN4, CLEC1B, CDHR5, CLDN11, JAM2, FOLH1), lymph node metastasis status (7-protein panel: APOE, CD28, CLDN4, FOLH1, ITGAL, JAML, ULBP3), and post-surgical residual disease burden (4-protein panel: CD44, CLMP, ITGA4, AMIGO1), with Cluster 13 (ITGB1-high) also significantly associated with residual disease. This work demonstrates the power of single-EV proteomics combined with machine learning for non-invasive diagnosis and clinical outcome assessment in advanced ovarian cancer, though the absence of early-stage patients limits its applicability for early detection.

PD-L1 expression in Ovarian Carcinoma and its Correlation with Clinico—Pathological Features: An Experience at a Tertiary Care Hospital in North India

BACKGROUND: Given the considerable morphological heterogeneity of invasive epithelial ovarian cancer, characterized by differences in clinical course and rates of progression, investigation of predictors specific to each histological type is of particular relevance. AIM: This work aimed to identify the predictive significance of hereditary and phenotypic factors modulating the risk of developing different histological types of invasive epithelial ovarian cancer. METHODS: A total of 620 patients with invasive epithelial ovarian cancer of various histological types were examined in the main group: serous carcinoma (57.7%), endometrioid carcinoma (23.1%), clear cell carcinoma (11.6%), and mucinous ovarian carcinoma (7.6%). The control group consisted of 226 women without cancer. Information on risk factors was obtained from medical records. Comparative analysis of the frequency characteristics of the studied variables between the main and control groups was performed using the Pearson chi-square (χ2) test. The strength of association was assessed using Cramér’s V coefficient. RESULTS: Compared with the control group, the main group showed higher frequencies of ovarian cancer (7.7% vs. 0%; p 0.001) and breast cancer (5.0% vs. 0%; p 0.001) in first-degree relatives; obesity in childhood (11.3% vs. 5.3%; p = 0.002), obesity in adolescence (10.6% vs. 3.5%; p = 0.001), and obesity at the time of primary diagnosis (47.1% vs. 21.7%; p 0.001). The main group more frequently reported the use of postmenopausal hormone replacement therapy (45.0% vs. 33.6%; p = 0.003) and endometriosis (13.4% vs. 7.5%; p = 0.02), whereas full-term pregnancy (p 0.001), breastfeeding (p 0.001), and oral contraceptive use (p 0.001) were less frequent. For the development of advanced serous ovarian carcinoma, the most substantial predictors were hereditary factors, obesity at the time of diagnosis, and postmenopausal hormone replacement therapy. In comparison with serous carcinoma, the distinguishing predictors were endometriosis, late menopause, and obesity in childhood and adolescence for endometrioid carcinoma; endometriosis for clear cell carcinoma; and obesity in adolescence and smoking for mucinous ovarian carcinoma. CONCLUSION: In rare histological types of invasive epithelial ovarian cancer, compared with serous carcinoma, the predictive significance of endometriosis, late menopause, smoking, and obesity in childhood and adolescence increases substantially.

Serous effusions, including pleural effusion and ascites, commonly occur in advanced cancers like lung and ovarian carcinomas. Detecting tumor cells in these effusions is crucial for assessing cancer metastasis. However, clinical methods mainly include cytological examination, which has limited sensitivity, and complex cell block technology that requires large volumes of serous effusion. Surface-enhanced Raman spectroscopy (SERS), with its high sensitivity and noninvasive nature, has emerged as a crucial tool for liquid biopsies. Building on this technology, a novel SERS bioprobe was specifically designed for the precise identification and capture of tumor cells in serous effusions, utilizing a composite material. The SERS bioprobes offer strong SERS enhancement, excellent spectral reproducibility, and molecular targeting, thereby enhancing detection specificity. Furthermore, SERS classification models were established to categorize samples based on tumor cell concentrations in serous effusions, enabling semiquantitative diagnostic capability. Notably, machine learning-assisted analysis enables rapid processing and classification of numerous Raman spectra and thorough feature extraction and greatly improves the SERS bioprobe's diagnostic accuracy. Consequently, the combination of SERS bioprobes and machine learning provides a rapid and effective detection method that overcomes the low sensitivity of conventional cytological detection in serous effusions and enables assessment of tumor cell concentration ranges within these fluids.

BackgroundA deep learning (DL) model based on preoperative computed tomography (CT) has been proposed for estimating recurrence in patients with ovarian cancer. However, the inherent opacity of DL models complicates the interpretation of their output, limiting their clinical applicability. The aim of this study was thus to generate histopathologic evidence supporting such DL prediction models and to construct a clustering-based analytical framework for identifying patients with risk factors for ovarian cancer.MethodsA retrospective study was conducted in which preoperative CT data were collected from patients with high-grade serous ovarian cancer treated with radical tumor resection from January 2013 to December 2019 at three tertiary care centers. Unsupervised clustering was performed with 1,280 DL model-driven features, and the associations between clusters and histopathological features were analyzed. Multivariate regression was used to investigate the added value of DL outputs for histopathologic correlations.ResultsA total of 418 patients [median age 55 years, interquartile range (IQR), 30–77 years] were evaluated. Unsupervised clusters 3 and 4 were associated with the positive status of P53, P16, and Ki-67, along with invasion of the omentum, rectum, and pelvic wall (P<0.05). In the multivariate logistic regression, the DL output, when adjusted for International Federation of Gynecology and Obstetrics (FIGO) stage, was independently associated with P53 [odd ratios (OR) 1.9642; 95% confidence interval (CI): 1.2412–3.1082; P=0.0039], P16 (OR 2.3446; 95% CI: 1.5445–3.5592; P=0.0001), Ki-67 (OR 10.0433; 95% CI: 5.3525–18.8450; P<0.001), invasion of the omentum (OR 2.5995; 95% CI: 1.7175–3.9342; P<0.001), invasion of the rectum (OR 2.3568; 95% CI: 1.5614–3.5574; P<0.001), and pelvic wall effusion (OR 2.0779; 95% CI: 1.3769–3.1360; P=0.0005). Unsupervised cluster 4 and patients with lower principal component analysis (PCA) scores were associated with worse survival (P<0.0001).ConclusionsThe DL model could effectively extract histopathological features of high-grade serous ovarian cancer from CT images.

Epithelial ovarian cancer (EOC) is often diagnosed at advanced stages, with metastasis driven by spheroid dissemination within the peritoneal cavity. We previously demonstrated that autophagy supports spheroid cell survival and suggest that it contributes to chemoresistance. Unc-51-like autophagy activating kinase 1 (ULK1), a key regulator of autophagy, has emerged as a promising therapeutic target. Here, we evaluated the effects of ULK1 inhibition via MRT68921, alone and in combination with afatinib-a tyrosine kinase inhibitor (TKI) known to induce pro-survival autophagy-in EOC. High-grade serous (HGSOC) and ovarian clear cell carcinoma (OCCC) cell lines were cultured under adherent and spheroid conditions. Immunoblotting confirmed on-target effects and modulation of autophagy. Autophagic flux was assessed using mCherry-eGFP-LC3 reporter assays. We assessed 96 dose combinations of MRT68921 and afatinib using drug combination matrices, with synergy evaluated via Synergy Finder. Promising combinations were evaluated across multiple EOC spheroid models and patient ascites-derived organoids. MRT68921 inhibited ULK1 activity and reduced autophagic flux in a context-dependent manner while afatinib alone induced autophagy. Their combination produced synergistic effects at select concentrations, impairing spheroid reattachment and viability. However, MRT68921 alone significantly reduced viability across multiple EOC models, including patient ascites-derived organoids. This study is the first to evaluate the combined effects of MRT68921 and afatinib in epithelial ovarian cancer. Our findings demonstrate that ULK1 inhibition via MRT68921 consistently reduces cell viability across multiple ovarian cancer models, supporting ULK1 as a promising therapeutic target. In contrast, combination with afatinib produced limited and context-dependent effects, indicating that further investigation is needed to identify optimal combination strategies for ULK1-targeted therapies.

BackgroundSingle-cell-based analyses of high-grade serous ovarian carcinoma (HGSOC) survival have largely ignored adipocytes, which are fragile and under-represented in single-cell references. Adipocytes are known active components of the tumor microenvironment in many cancers, and HGSOC tumors frequently metastasize to the omentum, a lining of adipose tissue.MethodsWe created a composite reference that combines single-nucleus adipose profiles with published HGSOC single-cell data to deconvolve 588 bulk RNA-seq tumours from theSchildkrautcohorts. We used stage-stratified Cox models to quantify the association between intratumoural adipocyte fractions and overall survival while adjusting for age, body mass index (BMI), race, and residual disease. We also evaluated associations with deconvolved immune, stromal, and epithelial cell groups.ResultsA 10% increase in estimated tumor adipocyte content was associated with a 41% increase in the hazard of death (HR = 1.41, 95% CI 1.18-1.70, p = 0.0002) after adjusting for age, BMI and race (n=566). A 10% increase in immune cell proportion was associated with favorable survival (HR = 0.82, 95% CI 0.69-0.97, p = 0.024). Stromal and epithelial macro-fractions were not associated with survival. Associations with adipocyte and immune cell type proportions were unchanged in models additionally controlling the other cell type proportions. Results were similar after additionally adjusting for residual disease after debulking surgery.ConclusionsAdipocytes may be a tumor-intrinsic factor associated with adverse outcomes in HGSOC. Quantifying adipocyte burden using bulk RNA-seq could enhance risk stratification and guide the development of adipocyte-targeted therapies.

Ovarian cancer is a 2nd most common cancer of the female reproductive system and high-grade serous carcinoma is the most common and aggressive type of ovarian cancer. Accounting for most deaths from this disease. It’s characterised by its rapid growth, tendency to spread (metastasize) and resistance to chemotherapy. A case of postmenopausal hypertensive female patient of high-grade serous carcinoma was presented with ascites. Patient was treated with Shunthi Churna, Mishri, Tab Sutshekhar, Syrup M-liv, Tab Shankhavati, Yavakshar, Sarjikshar, Swetparpati, Raktaprasadak Heem, Kamdudha Rasa, Pittantak Churna, Muktashukti Bhasma, Tapyadi Louha, Swarnavasantmalti Rasa, Vaikrant Bhasma, Heerak Bhasma, Drakshaavleha, Tab Amylcure DS. The Ayurvedic treatment was given in between the conventional therapy. The tumor marker CA-125 has been come down from1860 U/ml to normal range. Mild ascites was reduced and clinical gradation came down too.

Elucidation of the molecular mechanism underlying metastatic dissemination in patients with high-grade serous ovarian carcinoma (HG-SOC) has the potential to affect patient outcome. This study explores the role of gasdermins (GSDMs) in HG-SOC, focusing on novel pyroptosis-independent nuclear functions of GSDME, which are integrated with the endothelin-1 (ET-1)/ET-1 receptor A (ETAR) signaling to sustain metastatic progression. In this tumor, GSDME upregulation is correlated to epithelial-mesenchymal transition (EMT) and ETAR expression. ET-1 signaling fuels GSDME expression by inducing its transcription via the core EMT factors, ZEB1 and ZEB2. GSDME, in turn, translocates to the nucleus to engage ZEB1 and transcriptionally regulate genes coupled with EMT and inflammatory signals, such as E-cadherin, vimentin and interleukin (IL)-6. GSDME depletion, similarly to ZEB1 and ETAR blockade, restrains ET-1-induced EMT phenotypic plasticity and inflammatory cytokine release. Clinically relevant, ET-1 receptor (ET-1R) antagonist, by depleting the nuclear reservoir of the GSDME/ZEB1 transcriptional complex, hinders the metastatic traits of HG-SOC. The intertwined ETAR/GSDME/ZEB1 circuitry characterizes mesenchymal HG-SOC patients and associates with a high-risk of poor survival. Together, these findings unveil GSDME as a key transcriptional regulator of aggressive behaviors and worse prognosis in HG-SOC patients, in an ET-1-driven alliance with ZEB1, which could be targeted by ET-1R antagonist to reduce the metastatic burden of this tumor.

Neuroinflammation is a key driver of cognitive deficits after surgical menopause, a state commonly triggered by oophorectomy for oncological purposes. This intervention is routinely performed in premenopausal patients with hormone receptor-positive (HR+) breast cancer, constitutes foundational therapy for epithelial ovarian carcinoma, and is indicated for risk reduction in carriers of hereditary mutations such as breast cancer susceptibility gene 1/2 (BRCA1/2). As highly efficient immune cells, microglia play a central role in the onset of neurodegenerative diseases. Our study explored the role of thioredoxin-1 (Trx-1) in suppressing microglial activation and its potential for ameliorating postmenopausal cognitive decline. Female C57BL/6J mice underwent ovariectomy (OVX) to model tumor-therapeutic oophorectomy. They were intraperitoneally injected with recombinant human Trx-1 (rhTrx-1) at a dose of 200 μg/30 g or PBS once weekly for five weeks following OVX. A Y-maze active avoidance task and trace fear conditioning were used to assess cognitive function. Levels of neuroinflammation were evaluated through immunofluorescence, enzyme-linked immunosorbent assay (ELISA), and real-time polymerase chain reaction (PCR). Trx-1 levels in the hippocampus of OVX mice were measured by western blot and immunohistochemical analysis. Furthermore, the impact of Trx-1 on microglial activation was assessed in vitro. OVX induced the production of inflammatory factors and microglial activation in the brain, resulting in cognitive deficits in mice. However, intraperitoneal injection of rhTrx-1 inhibited these effects by improving cognitive function, reducing inflammatory cytokines, and promoting microglial polarization. In vitro studies also showed that rhTrx-1 attenuated lipopolysaccharide (LPS)-stimulated microglial activation through mitogen-activated protein kinase (MAPK) pathway signaling. Due to its inhibitory effect on neuroinflammation and microglial activation, Trx-1 may represent a promising therapeutic candidate for managing cancer therapy-related cognitive impairment, particularly in patients undergoing estrogen-deprivation therapies such as oophorectomy.

Background: Cytoreductive surgery (CRS) with hyperthermic intraperitoneal chemotherapy (HIPEC) is established for peritoneal metastases, but managing pleural metastases remains challenging. Hyperthermic intrathoracic chemotherapy (HITHOC) is an emerging modality. The combined procedure (CRS+HIPEC+HITHOC) presents profound anaesthetic challenges. We report the successful anaesthetic management of a patient undergoing this combined procedure.Case Presentation: A 51-year-old female with advanced ovarian carcinoma and biopsy-proven pleural metastases underwent complete CRS followed by HIPEC (cisplatin, 43°C, 90 min) and right-sided HITHOC (cisplatin/doxorubicin, 60 min) in a single sitting. Anaesthetic management included invasive hemodynamic monitoring, dual epidural catheters, goal-directed fluid therapy, and aggressive electrolyte correction. Sodium thiosulfate was used for nephroprotection. Key challenges included managing hemodynamic instability during HITHOC, temperature fluctuations, and chemotherapy-related toxicity.Conclusion: The combination of CRS, HIPEC, and HITHOC is a high-risk procedure necessitating a meticulous, multidisciplinary approach. Vigilant anaesthetic management focusing on advanced monitoring, precise fluid and vasopressor titration, temperature control, and organ protection is crucial for patient safety and positive outcomes. This case demonstrates that with expert management, such complex procedures can be performed successfully, offering a potential therapeutic option for selected patients.

Late detection and tumor recurrence are major factors driving the lethality of high-grade serous ovarian carcinoma (HGSOC). PARP inhibitors (PARPi) have achieved significant clinical efficacy by selectively targeting DNA repair deficiencies in HGSOC patients with BRCA mutations and homologous recombination deficiency (HRD). However, a subset of patients ultimately develops resistance to PARPi, necessitating alternative effective treatment options. The mutational signatures of APOBEC3 family of DNA deaminases are widespread across a broad array of cancer types. Here, we report that cancer stem cell (CSC)-like tumorspheres exhibit reduced A3B expression compared to non-CSC adherent counterparts. Importantly, inhibition of A3B leads to PARPi resistance, elevated frequency of CSCs, and enhanced expression of stemness factors. In addition, we found that high A3B-expressing cells are under strong replication stress and thus synergize efficiently with PARPi. These studies reveal the important role A3B plays in regulating PARPi response.