High-grade Serous Carcinoma Research Articles

Lymph node metastasis in grossly apparent early-stage epithelial ovarian cancer: A retrospective clinical study at a tertiary institute.

This study aimed to evaluate the incidence and predict the risk factors of lymph node (LN) metastasis among patients with grossly apparent early-stage epithelial ovarian cancer (EOC). We retrospectively reviewed the clinicopathologic data and follow-up information of 266 patients who underwent LN dissection for apparent early-stage EOC between January 2018 and September 2022 at the Obstetrics and Gynecology Hospital of Fudan University. Among 266 patients, 44 (16.5%) showed LN metastasis, of which 65.9% and 59.1% presented in the pelvic region and para-aortic region, respectively. Univariate analysis revealed higher LN positivity in patients with high-grade serous carcinoma (HGSC), preoperative imaging suggestive of LN metastasis, bilateral adnexal involvement, lymphovascular space invasion (LVSI), positive peritoneal cytology, and clinical stage IIA. LN metastases were identified in 7.9%, 10.2%, and 39.7% of clinical stage IA/B, IC, and IIA disease cases, respectively. Multivariate analysis confirmed significantly higher LN positivity rates in patients with HGSC, LVSI, and clinical stage IIA. In clinical stage IIA EOC, the 3-year progression-free survival (PFS) rates were 65.8% and 77.4% (P = 0.360) for LN-negative and LN-positive groups, respectively. In clinical stage I EOC, the 3-year PFS rates were 93.5% and 59.4% (P < 0.001) for LN-negative and LN-positive groups, respectively. High-grade serous histology, LVSI, and clinical stage IIA disease are predictive factors for LN involvement in early-stage EOC. In addition, LN metastasis appears to be associated with worse PFS in clinical stage I EOC compared with clinical stage IIA EOC.

Tumor-Intrinsic Activity of Chromobox 2 Remodels the Tumor Microenvironment in High-grade Serous Carcinoma.

CBX2 expression correlates with the TIME. CBX2 modulation shifts the macrophage population, potentially leading to an immunosuppressive microenvironment, highlighting CBX2 as a target to improve efficacy of immunotherapy.

Deep Learning-Based Ovarian Cancer Subtype Classification Using VGG16 and MobileNetV2 with Squeeze-and-Excitation Blocks

Background: Ovarian carcinoma remains one of the deadliest gynecological malignancies due to its heterogeneity and late-stage detection. Accurate classification of its subtypes—High-Grade Serous Carcinoma (HGSC), Clear-Cell Carcinoma (CC), Endometrioid Carcinoma (EC), Low-Grade Serous Carcinoma (LGSC), and Mucinous Carcinoma (MC)—is essential for tailored treatments, yet traditional histopathological methods often lack precision. This study aimed to develop a deep learning (DL) model to enhance ovarian cancer subtype classification using histopathological images. Methods: Histopathological images were collected from medical repositories, and data augmentation techniques were applied to increase dataset diversity. Two convolutional neural network (CNN) architectures, VGG16 and MobileNetV2, were fine-tuned using transfer learning to classify the subtypes. The models were pre-trained on the ImageNet dataset and evaluated through accuracy, precision, recall, F1-score, and ROC-AUC, with K-fold cross-validation ensuring robustness. Results: Results indicated that VGG16 improved classification over baseline CNN models, while MobileNetV2, with Squeeze-and-Excitation (SE) blocks, achieved the highest performance, offering greater accuracy and computational efficiency. MobileNetV2’s lightweight architecture captured intricate tissue patterns more effectively, making it the superior model. Conclusion: This study highlights the potential of advanced DL models, particularly MobileNetV2 with SE block attention, for improving ovarian cancer subtype classification. These findings offer promising implications for clinical practice and personalized treatment approaches. Future research should focus on larger datasets and integrating multimodal data for further advancements.

Single-cell transcriptomics reveals tumor landscape in ovarian carcinosarcoma.

The present study used single-cell RNA sequencing (scRNA-seq) to characterize the cellular composition of ovarian carcinosarcoma (OCS) and identify its molecular characteristics. scRNA-seq was performed in resected primary OCS for an in-depth analysis of tumor cells and the tumor microenvironment. Immunohistochemistry staining was used for validation. The scRNA-seq data of OCS were compared with those of high-grade serous ovarian carcinoma (HGSOC) tumors and other OCS tumors. Both malignant epithelial and malignant mesenchymal cells were observed in the OCS patient of this study. We identified four epithelial cell subclusters with different biological roles. Among them, epithelial subcluster 4 presented high levels of breast cancer type 1 susceptibility protein homolog (BRCA1) and DNA topoisomerase 2-α (TOP2A) expression and was related to drug resistance and cell cycle. We analyzed the interaction between epithelial and mesenchymal cells and found that fibroblast growth factor (FGF) and pleiotrophin (PTN) signalings were the main pathways contributing to communication between these cells. Moreover, we compared the malignant epithelial and mesenchymal cells of this OCS tumor with our previous published HGSOC scRNA-seq data and OCS data. All the epithelial subclusters in the OCS tumor could be found in the HGSOC samples. Notably, the mesenchymal subcluster C14 exhibited specific expression patterns in the OCS tumor, characterized by elevated expression of cytochrome P450 family 24 subfamily A member 1 (CYP24A1), collagen type XXIII α1 chain (COL23A1), cholecystokinin (CCK), bone morphogenetic protein 7 (BMP7), PTN, Wnt inhibitory factor 1 (WIF1), and insulin-like growth factor 2 (IGF2). Moreover, this subcluster showed distinct characteristics when compared with both another previously published OCS tumor and normal ovarian tissue. This study provides the single-cell transcriptomics signature of human OCS, which constitutes a new resource for elucidating OCS diversity.

Changes in the tumour microenvironment mark the transition from serous borderline tumour to low-grade serous carcinoma.

Low-grade serous ovarian carcinoma (LGSC) is a rare and lethal subtype of ovarian cancer. LGSC is pathologically, biologically, and clinically distinct from the more common high-grade serous ovarian carcinoma (HGSC). LGSC arises from serous borderline ovarian tumours (SBTs). The mechanism of transformation for SBTs to LGSC remains poorly understood. To better understand the biology of LGSC, we performed whole proteome profiling of formalin-fixed, paraffin-embedded tissue blocks of LGSC (n = 11), HGSC (n = 19), and SBTs (n = 26). We identified that the whole proteome is able to distinguish between histotypes of the ovarian epithelial tumours. Proteins associated with the tumour microenvironment were differentially expressed between LGSC and SBTs. Fibroblast activation protein (FAP), a protein expressed in cancer-associated fibroblasts, is the most differentially abundant protein in LGSC compared with SBT. Multiplex immunohistochemistry (IHC) for immune markers (CD20, CD79a, CD3, CD8, and CD68) was performed to determine the presence of B cells, T cells, and macrophages. The LGSC FAP+ stroma was associated with greater abundance of Tregs and M2 macrophages, features not present in SBTs. Our proteomics cohort reveals that there are changes in the tumour microenvironment in LGSC compared with its putative precursor lesion, SBT. These changes suggest that the tumour microenvironment provides a supportive environment for LGSC tumourigenesis and progression. Thus, targeting the tumour microenvironment of LGSC may be a viable therapeutic strategy. © 2024 The Pathological Society of Great Britain and Ireland.

Targeted Nanocarrier-Based Drug Delivery Strategies for Improving the Therapeutic Efficacy of PARP Inhibitors against Ovarian Cancer.

The current focus of ovarian cancer (OC) research is the improvement of treatment options through maximising drug effectiveness. OC remains the fifth leading cause of cancer-induced mortality in women worldwide. In recent years, nanotechnology has revolutionised drug delivery systems. Nanoparticles may be utilised as carriers in gene therapy or to overcome the problem of drug resistance in tumours by limiting the number of free drugs in circulation and thereby minimising undesired adverse effects. Cell surface receptors, such as human epidermal growth factor 2 (HER2), folic acid (FA) receptors, CD44 (also referred to as homing cell adhesion molecule, HCAM), and vascular endothelial growth factor (VEGF) are highly expressed in ovarian cancer cells. Generation of active targeting nanoparticles involves modification with ligands that recognise cell surface receptors and thereby promote internalisation by cancer cells. Several poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are currently used for the treatment of high-grade serous ovarian carcinomas (HGSOC) or platinum-sensitive relapsed OC. However, PARP resistance and poor drug bioavailability are common challenges, highlighting the urgent need to develop novel, effective strategies for ovarian cancer treatment. This review evaluates the utility of nanoparticles in ovarian cancer therapy, with a specific focus on targeted approaches and the use of PARPi nanocarriers to optimise treatment outcomes.

Cell-intrinsic platinum response and associated genetic and gene expression signatures in ovarian cancer cell lines and isogenic models.

Ovarian cancers are still largely treated with platinum-based chemotherapy as the standard of care, yet few biomarkers of clinical response have had an impact on clinical decision making as of yet. Two particular challenges faced in mechanistically deciphering platinum responsiveness in ovarian cancer have been the suitability of cell line models for ovarian cancer subtypes and the availability of information on comparatively how sensitive ovarian cancer cell lines are to platinum. We performed one of the most comprehensive profiles to date on 36 ovarian cancer cell lines across over seven subtypes and integrated drug response and multiomic data to improve on our understanding of the best cell line models for platinum responsiveness in ovarian cancer. RNA-seq analysis of the 36 cell lines in a single batch experiment largely conforms with the currently accepted subtyping of ovarian cancers, further supporting other studies that have reclassified cell lines and demonstrate that commonly used cell lines are poor models of high-grade serous ovarian carcinoma. We performed drug dose response assays in the 32 of these cell lines for cisplatin and carboplatin, providing a quantitative database of IC 50 s for these drugs. Our results demonstrate that cell lines largely fall either well above or below the equivalent dose of the clinical maximally achievable dose (C max ) of each compound, allowing designation of cell lines as sensitive or resistant. We performed differential expression analysis for high-grade serous ovarian carcinoma cell lines to identify gene expression correlating with platinum-response. Further, we generated two platinum-resistant derivatives each for OVCAR3 and OVCAR4, as well as leveraged clinically-resistant PEO1/PEO4/PEO6 and PEA1/PEA2 isogenic models to perform differential expression analysis for seven total isogenic pairs of platinum resistant cell lines. While gene expression changes overall were heterogeneous and vast, common themes were innate immunity/STAT activation, epithelial to mesenchymal transition and stemness, and platinum influx/efflux regulators. In addition to gene expression analyses, we performed copy number signature analysis and orthogonal measures of homologous recombination deficiency (HRD) scar scores and copy number burden, which is the first report to our knowledge applying field-standard copy number signatures to ovarian cancer cell lines. We also examined markers and functional readouts of stemness that revealed that cell lines are poor models for examination of stemness contributions to platinum resistance, likely pointing to the fact that this is a transient state. Overall this study serves as a resource to determine the best cell lines to utilize for ovarian cancer research on certain subtypes and platinum response studies, as well as sparks new hypotheses for future study in ovarian cancer.

Comparative Analysis of Gene Expression Analysis Methods for RNA in Situ Hybridization Images

Gene expression analysis is pivotal in cancer research and clinical practice. While traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, RNAscope score, RT-droplet digital PCR (RT-ddPCR), and automated QuantISH and QuPath were employed for quantifying RNA-ISH expression values from formalin-fixed paraffin-embedded samples. The methods were compared using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. The findings demonstrate good concordance between automated methods and RNAscope, with RT-ddPCR showing less concordance. Additionally, QuantISH exhibits robust performance, even for low-expressed genes like CCNE1, showcasing its modular design and enhancing accessibility as a viable alternative for gene expression analysis.

Deep fine-KNN classification of ovarian cancer subtypes using efficientNet-B0 extracted features: a comprehensive analysis

This study presents a robust approach for the classification of ovarian cancer subtypes through the integration of deep learning and k-nearest neighbor (KNN) methods. The proposed model leverages the powerful feature extraction capabilities of EfficientNet-B0, utilizing its deep features for subsequent fine-grained classification using the fine-KNN approach. The UBC-OCEAN dataset, encompassing histopathological images of five distinct ovarian cancer subtypes, namely, high-grade serous carcinoma (HGSC), clear-cell ovarian carcinoma (CC), endometrioid carcinoma (EC), low-grade serous carcinoma (LGSC), and mucinous carcinoma (MC), served as the foundation for our investigation. With a dataset comprising 725 images, divided into 80% for training and 20% for testing, our model exhibits exceptional performance. Both the validation and testing phases achieved 100% accuracy, underscoring the efficacy of the proposed methodology. In addition, the area under the curve (AUC), a key metric for evaluating the model’s discriminative ability, demonstrated high performance across various subtypes, with AUC values of 0.94, 0.78, 0.69, 0.92, and 0.94 for MC. Furthermore, the positive likelihood ratios (LR+) were indicative of the model’s diagnostic utility, with notable values for each subtype: CC (27.294), EC (9.441), HGSC (12.588), LGSC (17.942), and MC (17.942). These findings demonstrate the effectiveness of the model in distinguishing between ovarian cancer subtypes, positioning it as a promising tool for diagnostic applications. The demonstrated accuracy, AUC values, and LR+ values underscore the potential of the model as a valuable diagnostic tool, contributing to the advancement of precision medicine in the field of ovarian cancer research.

Concurrent RB1 Loss and BRCA Deficiency Predicts Enhanced Immunologic Response and Long-term Survival in Tubo-ovarian High-grade Serous Carcinoma.

The purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC). RB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss. RB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1. Co-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

PARK2 suppresses the proliferation of high-grade serous ovarian carcinoma via inducing the proteasomal degradation of ZNF703.

High-grade serous ovarian cancer (HGSC) is an aggressive disease with poor prognosis. The oncoprotein ZNF703 is implicated in driving HGSC pathogenesis, but factors regulating its abundance remain unclear. In this study, we aim to investigate the potential connection between ZNF703 dysregulation and ubiquitin-mediated protein degradation in HGSC. Bioinformatics prediction was performed using BioGRID database. HGSC representative cell lines were utilized for in vitro and in vivo studies. Results showed that ZNF703 protein was stabilized upon proteasome inhibition, suggesting a regulation via ubiquitination. The ubiquitin E3 ligase PARK2 was found to interact with ZNF703 in a dose-dependent manner, promoting its polyubiquitination and subsequent proteasomal degradation. Re-expression of PARK2 in HGSC cells led to reduced ZNF703 levels together with decreased Cyclin D1/E1 abundance and G1 cell cycle arrest. ZNF703 overexpression alone increased S phase cells, Cyclin D1/E1 levels, and xenograft tumor growth, while co-expression with PARK2 mitigated these oncogenic effects. Collectively, our findings identify ZNF703 as a bona fide substrate of PARK2, reveal a tumor suppressive function for PARK2 in attenuating ZNF703-mediated G1/S transition and HGSC growth through instigating its degradation. This study elucidates a pivotal PARK2-ZNF703 axis with therapeutic implications for targeted intervention in HGSC.

Artificial Intelligence-Based Histopathological Subtyping of High-Grade Serous Ovarian Cancer

Four subtypes of ovarian high-grade serous carcinoma (HGSC) have previously been identified, each with different prognoses and drug sensitivities. However, the accuracy of the classification depended on the assessor’s experience. This study aimed to develop a universal algorithm for HGSC-subtype classification using deep learning techniques. An artificial intelligence (AI)-based classification algorithm, which replicates the consensus diagnosis of pathologists, was formulated to analyze the morphological patterns and tumor-infiltrating lymphocyte counts for each tile extracted from whole slide images of ovarian HGSC available in The Cancer Genome Atlas (TCGA) dataset. The accuracy of the algorithm was determined using the validation set from the Japanese Gynecologic Oncology Group 3022A1 (JGOG3022A1) and Kindai and Kyoto University (Kindai/Kyoto) cohorts. The algorithm classified the four HGSC-subtypes with mean accuracies of 0.933, 0.910, and 0.862 for the TCGA, JGOG3022A1, and Kindai/Kyoto cohorts, respectively. To compare Mesenchymal Transition (MT) with non-MT groups, overall survival analysis was performed in the TCGA dataset. The AI-based prediction of HGSC-subtype classification in TCGA cases showed that the MT group had a worse prognosis than the non-MT group (p = 0.017). Furthermore, Cox proportional hazard regression analysis identified AI-based MT subtype classification prediction as a contributing factor along with residual disease after surgery, stage, and age. In conclusion, a robust AI-based HGSC-subtype classification algorithm was established using virtual slides of ovarian HGSC.

Targeted proteomics of plasma extracellular vesicles uncovers MUC1 as combinatorial biomarker for the early detection of high-grade serous ovarian cancer

BackgroundThe five-year prognosis for patients with late-stage high-grade serous carcinoma (HGSC) remains dismal, underscoring the critical need for identifying early-stage biomarkers. This study explores the potential of extracellular vesicles (EVs) circulating in blood, which are believed to harbor proteomic cargo reflective of the HGSC microenvironment, as a source for biomarker discovery.ResultsWe conducted a comprehensive proteomic profiling of EVs isolated from blood plasma, ascites, and cell lines of patients, employing both data-dependent (DDA) and data-independent acquisition (DIA) methods to construct a spectral library tailored for targeted proteomics. Our investigation aimed at uncovering novel biomarkers for the early detection of HGSC by comparing the proteomic signatures of EVs from women with HGSC to those with benign gynecological conditions. The initial cohort, comprising 19 donors, utilized DDA proteomics for spectral library development. The subsequent cohort, involving 30 HGSC patients and 30 control subjects, employed DIA proteomics for a similar purpose. Support vector machine (SVM) classification was applied in both cohorts to identify combinatorial biomarkers with high specificity and sensitivity (ROC-AUC > 0.90). Notably, MUC1 emerged as a significant biomarker in both cohorts when used in combination with additional biomarkers. Validation through an ELISA assay on a subset of benign (n = 18), Stage I (n = 9), and stage II (n = 9) plasma samples corroborated the diagnostic utility of MUC1 in the early-stage detection of HGSC.ConclusionsThis study highlights the value of EV-based proteomic analysis in the discovery of combinatorial biomarkers for early ovarian cancer detection.

Neoadjuvant and adjuvant pembrolizumab in advanced high-grade serous carcinoma: the randomized phase II NeoPembrOV clinical trial

This open-label, non-comparative, 2:1 randomized, phase II trial (NCT03275506) in women with stage IIIC/IV high-grade serous carcinoma (HGSC) for whom upfront complete resection was unachievable assessed whether adding pembrolizumab (200 mg every 3 weeks) to standard-of-care carboplatin plus paclitaxel yielded a complete resection rate (CRR) of at least 50%. Postoperatively patients continued assigned treatment for a maximum of 2 years. Postoperative bevacizumab was optional. The primary endpoint was independently assessed CRR at interval debulking surgery. Secondary endpoints were Completeness of Cytoreduction Index (CCI) and peritoneal cancer index (PCI) scores, objective and best response rates, progression-free survival, overall survival, safety, postoperative morbidity, and pathological complete response. The CRR in 61 pembrolizumab-treated patients was 74% (one-sided 95% CI = 63%), exceeding the prespecified ≥50% threshold and meeting the primary objective. The CRR without pembrolizumab was 70% (one-sided 95% CI = 54%). In the remaining patients CCI scores were ≥3 in 27% of the standard-of-care group and 18% of the investigational group and CC1 in 3% of the investigational group. PCI score decreased by a mean of 9.6 in the standard-of-care group and 10.2 in the investigational group. Objective response rates were 60% and 72%, respectively, and best overall response rates were 83% and 90%, respectively. Progression-free survival was similar with the two regimens (median 20.8 versus 19.4 months in the standard-of-care versus investigational arms, respectively) but overall survival favored pembrolizumab-containing therapy (median 35.3 versus 49.8 months, respectively). The most common grade ≥3 adverse events with pembrolizumab-containing therapy were anemia during neoadjuvant therapy and infection/fever postoperatively. Pembrolizumab was discontinued prematurely because of adverse events in 23% of pembrolizumab-treated patients. Combining pembrolizumab with neoadjuvant chemotherapy is feasible for HGSC considered not completely resectable; observed activity in some subgroups justifies further evaluation to improve understanding of the role of immunotherapy in HGSC.

YAP1 Suppression by ZDHHC7 Is Associated with Ferroptosis Resistance and Poor Prognosis in Ovarian Clear Cell Carcinoma.

Ovarian clear cell carcinoma (OCCC), which has unique clinical characteristics, arises from benign endometriotic cysts, forming an oxidative stress environment because of excess iron accumulation, and exhibits poor prognosis, particularly in advanced stages owing to resistance to conventional therapeutics. Ferroptosis is an iron-dependent form of programmed cell death induced by lipid peroxidation and controlled by Hippo signaling. We hypothesized that overcoming ferroptosis resistance is an attractive strategy because OCCC acquires oxidative stress resistance during its development and exhibits chemoresistant features indicative of ferroptosis resistance. This study aimed to determine whether OCCC is resistant to ferroptosis and clarify the mechanism underlying resistance. Unlike ovarian high-grade serous carcinoma cells, OCCC cells were exposed to oxidative stress. However, OCCC cells remained unaffected by lipid peroxidation. Cell viability assays revealed that OCCC cells exhibited resistance to the ferroptosis inducer erastin. Moreover, Samroc analysis showed that the Hippo signaling pathway was enriched in OCCC cell lines and clinical samples. Furthermore, patients with low expression of nuclear yes-associated protein 1 (YAP1) exhibited a significantly poor prognosis of OCCC. Moreover, YAP1 activation enhanced ferroptosis in OCCC cell lines. Furthermore, suppression of zinc finger DHHC-type palmitoyltransferase 7 (ZDHHC7) enhanced ferroptosis by activating YAP1 in OCCC cell lines. Mouse xenograft models demonstrated that ZDHHC7 inhibition suppressed tumor growth via YAP1 activation by erastin treatment. In conclusion, YAP1 activation regulated by ZDHHC7 enhanced ferroptosis in OCCC. Thus, overcoming ferroptosis resistance is a potential therapeutic strategy for OCCC.

The genomic trajectory of ovarian high-grade serous carcinoma can be observed in STIC lesions.

Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as p53 signatures, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinoma (STIC) lesions, which in turn progress into invasive HGSC, which readily spreads to the ovary and disseminates around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole-genome duplication (WGD) observed in late-stage disease were determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded (FFPE) samples from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole-genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next-generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was a strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of WGD, arises early in HGSC and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Human peritoneal fluid exerts ovulation- and nonovulation-sourced oncogenic activities on transforming fallopian tube epithelial cells

Secretory cells in the fallopian tube fimbria epithelium (FTE) are regarded as the main cells of origin of ovarian high-grade serous carcinoma (HGSC). Ovulation is the main cause of FTE oncogenesis, which proceeds through a sequence of TP53 mutations, chromosomal instability due to Rb/cyclin E aberration, in situ carcinoma (STIC), and metastasis to the ovary and peritoneum (metastatic HGSC). Previously, we have identified multiple oncogenic activities of the ovulatory follicular fluid (FF), which exerts the full spectrum of transforming activity on FTE cells at different stages of transformation. After ovulation, the FF is transfused into the peritoneal fluid (PF), in which the FTE constantly bathes. We wondered whether PF exerts the same spectrum of oncogenic activities as done by FF and whether these activities are derived from FF. By using a panel of FTE cell lines with p53 mutation (FT282-V), p53/CCNE1 aberrations (FT282-CCNE1), and p53/Rb aberrations plus spontaneous transformation, and peritoneal metastasis (FEXT2), we analyzed the changes of different transformation phenotypes after treating with FF and PF collected before or after ovulation. Similar to effects exhibited by FF, we found that, to a lesser extent, PF promoted anchorage-independent growth (AIG), migration, anoikis resistance, and peritoneal attachment in transforming FTE cells. The more transformed cells were typically more affected. Among the transforming activities exhibited by PF treatment, AIG, Matrigel invasion, and peritoneal attachment growth were higher with luteal-phase PF treatment than with the proliferative-phase PF treatment, suggesting an ovulation source. In contrast, changes in anoikis resistance and migration activities were similar in response to treatment with PF collected before and after ovulation, suggesting an ovulation-independent source. The overall transforming activity of luteal-phase PF was verified in an i.p. co-injection xenograft mouse model. Co-injection of Luc-FEXT2 cells with either FF or luteal-phase PF supported early peritoneal implantation, whereas co-injection with follicular-phase PF did not. This study, for the first time, demonstrates that PF from ovulating women can promote different oncogenic phenotypes in FTE cells at different stages of malignant transformation. Most of these activities, other than anoikis resistance and cell migration, are sourced from ovulation.

Cutaneous Metastasis of Ovarian Tumor after Hysterectomy and Bilateral Salpingo-oophorectomy: A Case Report

OBJECTIVES Cutaneous metastases are a very rare presentation of ovarian tumors (OV). They occur in about 3.5 percent of cases. The prognosis of cutaneous metastases is not good despite recent treatment modalities. Researchers are looking for much more personalized treatments. The patient had a history of ovarian tumor, for which she had a hysterectomy and bilateral salpingo-oophorectomy. She presented with multiple cutaneous eruptions. The histopathology shows high-grade serous carcinoma of the ovaries. Immunochemistry is positive for cytokeratin 7, WT1, and CAX. She had developed left leg swelling, generalized edema, and complaints of dysuria and difficulty defecating. Many targeted therapies have been developed, such as inhibiting growth factor receptors and immunological treatments that induce cell death, opening the door to precision medicine.

Chromosomal copy number and mutational status are required to authenticate ovarian cancer cell lines as appropriate cell models

BackgroundThe mutational status of ovarian cancer cell line IGROV-1 is inconsistent across the literature, suggestive of multiple clonal populations of the cell line. IGROV-1 has previously been categorised as an inappropriate model for high-grade serous ovarian cancer.MethodsIGROV-1 cells were obtained from the Netherlands Cancer Institute (IGROV-1-NKI) and the MD Anderson Cancer Centre (IGROV-1-MDA). Cell lines were STR fingerprinted and had their chromosomal copy number analysed and BRCA1/2 genes sequenced. Mutation status of ovarian cancer-related genes were extracted from the literature.ResultsThe IGROV-1-NKI cell line has a tetraploid chromosomal profile. In contrast, the IGROV-1-MDA cell line has pseudo-normal chromosomes. The IGROV-1-NKI and IGROV-MDA are both STR matches (80.7% and 84.6%) to the original IGROV-1 cells isolated in 1985. However, IGROV-1-NKI and IGROV-1-MDA are not an STR match to each other (78.1%) indicating genetic drift. The BRCA1 and BRCA2 gene sequences are 100% identical between IGROV-1-MDA and IGROV-1-NKI, including a BRCA1 heterozygous deleterious mutation. The IGROV-1-MDA cells are more resistant to cisplatin and olaparib than IGROV-1-NKI. IGROV-1 has a mutational profile consistent with both Type I (PTEN, PIK3CA and ARID1A) and Type II ovarian cancer (BRCA1, TP53) and is likely to be a Type II high-grade serous carcinoma of the SET (Solid, pseudo-Endometroid and Transitional cell carcinoma-like morphology) subtype.ConclusionsRoutine testing of chromosomal copy number as well as the mutational status of ovarian cancer related genes should become the new standard alongside STR fingerprinting to ensure that ovarian cancer cell lines are appropriate models.

High-grade serous carcinoma of the fallopian tube in a young woman with chromosomal 4q abnormality: A case report

BACKGROUND Few studies have reported an association between an increased risk of acquiring cancers and survival in patients with 4q deletion syndrome. This study presents a rare association between chromosome 4q abnormalities and fallopian tube high-grade serous carcinoma (HGSC) in a young woman. CASE SUMMARY A 35-year-old woman presented with acute dull abdominal pain and a known chromosomal abnormality involving 4q13.3 duplication and 4q23q24 deletion. Upon arrival at the emergency room, her abdomen appeared ovoid and distended with palpable shifting dullness. Ascites were identified through abdominal ultrasound, and computed tomography revealed an omentum cake and an enlarged bilateral adnexa. Blood tests showed elevated CA-125 levels. Paracentesis was conducted, and immunohistochemistry indicated that the cancer cells favored an ovarian origin, making us suspect ovarian cancer. The patient underwent debulking surgery, which led to a diagnosis of stage IIIC HGSC of the fallopian tube. Subsequently, the patient received adjuvant chemotherapy with carboplatin and paclitaxel, resulting in stable current condition. CONCLUSION This study demonstrates a rare correlation between a chromosome 4q abnormality and HGSC. UBE2D3 may affect crucial cancer-related pathways, including P53, BRCA, cyclin D, and tyrosine kinase receptors, thereby possibly contributing to cancer development. In addition, ADH1 and DDIT4 may be potential influencers of both carcinogenic and therapeutic responses.