Search Results (109)

Background/Objectives: The effects of combining chemotherapy with hormonal therapy based on hormone receptor (HR) expression in epithelial ovarian, fallopian tube, or primary peritoneal (EOC) remain unclear. This study evaluated the efficacy and safety of physician-chosen chemotherapy combined with hormonal therapy in patients with heavily pretreated advanced EOC, stratified by HR expression. Methods: This phase II, multicenter, pilot study included patients with heavily pretreated advanced EOC, allocated to estrogen receptor (ER)-dominant or progesterone receptor (PR)-dominant arms. Patients in the ER-dominant arm received tamoxifen plus physician-selected chemotherapy, while those in the PR-dominant arm received megestrol acetate (MA) plus chemotherapy. The primary outcome was the best objective response rate (ORR) for six months, assessed using an optimal two-stage Simon design. Results: Among 33 ER-dominant patients with high-grade serous carcinoma (HGSC), the six-month best ORR was 27.3% (3% complete response, 24.2% partial response). The six-month ORR and clinical benefit rate (CBR) were 18.8% and 37.5%, respectively, with 62.5% experiencing progressive disease (PD). Among three PR-dominant patients (two clear cell carcinoma and one HGSC), the six-month best ORR was 0%. The six-month ORR and CBR were also 0%, and all experienced PD within six months. No unacceptable toxicity related to tamoxifen or MA was encountered. Conclusions: In heavily pretreated advanced HGSC patients with ER-dominant expression, chemotherapy combined with tamoxifen showed encouraging clinical activity with favorable safety. While limited by the study design, these findings suggest a potential role for tailored hormonal therapy combined with chemotherapy based on HR expression in heavily pretreated advanced EOC. Clinical Trial Registration: KCT0004571 Full article

Background/Objectives: Tumor-infiltrating lymphocytes (TILs) and inflammation status are emerging prognostic markers in various cancers, but their significance in high-grade serous ovarian carcinoma (HGSC) remains unclear. Our objective was to evaluate different TIL subtypes and inflammation status in relation to progression-free survival (PFS) in primary HGSC. Methods: CD3⁺/CD4⁺/CD8⁺/PD-1+ stromal TILs (sTILs) and intraepithelial TILs (iTILs) were evaluated by manual assessment and digital image analysis (DIA), following TIL Working Group recommendations. Inflammation status was evaluated through the following scores: systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), CA125, and lactate dehydrogenase (LDH). Results: CD8⁺ TILs were the most prevalent subtype in both iTILs and sTILs. However, sTILs were significantly more abundant than iTILs (p < 0.001) among all subsets, except for PD-1+ cells. DIA results of TIL assessments were in agreement with manual assessments. High stromal CD3⁺ and CD8⁺ TILs, PIV, CA125, and LDH, were associated with improved PFS. Potential independent prognostic factors for PFS in manual assessment were PIV (HR = 0.32, CI 95% = 0.12–0.82) and CD8⁺ sTILs (HR = 0.30, CI 95% = 0.12–0.79), whereas in DIA assessment they were CD3⁺ sTILs (HR = 0.31, CI 95% = 0.15–0.67), PIV (HR = 0.35, 95% CI 0.13–0.96), and residual disease (HR = 0.21 95% CI 0.08–0.53). Conclusions: CD3⁺/CD8⁺ sTILs and PIV are promising prognostic indicators in HGSC; however, further research is needed to confirm their clinical utility. Full article

Background: HRD is a key biomarker in ovarian cancer, predicting response to PARP inhibitors. However, it remains unclear whether HRD-positive patients differ from HRD-negative patients in terms of clinical characteristics in PARP inhibitor-naïve populations. This study aims to evaluate platinum-sensitive PARP-inhibitor naïve ovarian cancer patients’ clinical characteristics and survival outcomes based on HRD status. Secondly, to investigate whether platinum-resistant patients with homologous recombination repair (HRR) gene mutations are HRD-positive. Methods: Two distinct HRD algorithms—an in-house genomic instability score (GIS) and the normalized large-scale state transitions score (nLST)—were used to stratify patients as HRD-positive or HRD-negative. Clinical data and survival in PARP inhibitor-naïve, platinum-sensitive HGSC patients were analyzed. Results: A total of 71 platinum-sensitive PARP-inhibitor naïve patients were analyzed. By in-house GIS, 37 patients (52%) were classified as HRD-positive and 34 (48%) as HRD-negative. Using nLST, 43 (61%) were HRD-positive and 28 (39%) were HRD-negative. Our analysis revealed no significant differences in clinical parameters or survival between HRD-positive and HRD-negative platinum-sensitive patients. The only observed difference was that somatic BRCA1/2-mutated patients were younger. In the subgroup of six platinum-resistant patients harboring HRR gene mutations, four patients (67%) were classified as HRD positive. Conclusions: Our findings suggest that HRD status does not significantly influence clinical characteristics or survival outcomes in platinum-sensitive, PARP inhibitor-naïve HGSC patients. As some platinum-resistant patients with HRR gene mutations were HRD positive; this subgroup may benefit from further investigation into the potential effect of PARP inhibitors. Full article

Ovarian cancer is a lethal malignancy, with most patients initially responding to chemotherapy but frequently experiencing recurrence. Previous studies primarily examined tumor characteristics using limited genetic markers or bulk RNA sequencing. Here, we used spatial transcriptomics via the GeoMx^® platform, alongside multispectral immune cell immunofluorescence (IF), to identify biomarkers associated with disease progression following first-line treatment of high-grade serous carcinoma (HGSC). We identified several spatial biomarkers linked to non-recurrence, including elevated NKG7 expression in CD45+ immune cell regions (p = 0.0011) and higher TFPI2 and PIGR expression in tumor areas (p = 2.09 × 10⁻⁶), both associated with improved progression-free survival. Multispectral IF revealed significantly higher regulatory T cell (Treg) to CD8+ T cell ratios in the tumor nests and stroma of recurrent patients (p = 0.016, 0.048). Tregs were also found closer to cancer cells or macrophages than CD8+ T cells in recurrent tumors (p = 0.048), correlating with poor survival. Integrated analysis showed that immune cell density and immune pathway scores in the recurrent group positively correlated with cancer pathway scores, except for NF-κB. This comprehensive analysis revealed clues to interactions between different immune cells and identified biomarkers that may be useful for predicting recurrence of HGSC. Full article

Cancer stem cells (CSCs) significantly contribute to heterogeneity, malignancy, and therapy resistance in ovarian cancer. Recent studies emphasize the role of the vitamin D receptor (VDR) in regulating cell differentiation and stemness in various types of cancer. This study aims to determine the expression levels of CD44, CD133, and VDR in epithelial ovarian tumors (EOTs) and to compare these levels across different tumor types, including benign, atypical proliferative tumors, and five types of malignant phenotypes, in order to evaluate their potential as diagnostic tools for malignancy. Tissue samples from 218 patients diagnosed with EOT were analyzed. Clinical and histopathologic parameters were recorded. Quantitative immunohistochemical tissue microarray analysis was used to assess the expression levels of CD44, CD133, and VDR using two different scoring systems. Comparisons were made between benign tumors (n = 45), atypical proliferative tumors (n = 42), and ovarian carcinomas (n = 131), including high-grade serous (HGSC) and non-HGSC subtypes. Ovarian cancer, especially HGSC, showed a significantly higher expression of CD44 and VDR (p < 0.05) compared to atypical proliferative tumors and benign tumors. The expression of CD133 was highest in atypical proliferative tumors (p < 0.05). A moderate positive correlation was found between CD44, CD133, and VDR in all groups, with significant correlations with tumor grade and FIGO stage in ovarian cancer (p < 0.05). The increased expression of CD44 and VDR in aggressive ovarian cancer, along with elevated CD133 levels in atypical proliferative tumors, highlights the complexity of tumor biology. These markers may serve as valuable targets for the diagnosis of ovarian cancer. Full article

Background: Endocrine therapy is the standard-of-care maintenance treatment for estrogen receptor (ER)-positive breast cancers and is increasingly used in low-grade serous ovarian cancer. However, its therapeutic role in the early maintenance setting for ER-positive high-grade serous ovarian cancer (HGSC) remains undefined. Methods: A retrospective analysis was conducted on clinicopathological data from patients with newly diagnosed ER-positive HGSC following completion of adjuvant chemotherapy. Patients received maintenance therapy either with or without the aromatase inhibitor letrozole, in addition to standard maintenance care. ER expression levels and the administration of letrozole were analyzed, along with outcome measures for the entire cohort, with stratification based on residual disease status. Results: A total of 102 patients with newly diagnosed HGSC were included in the analysis, with 64 (62.7%) receiving letrozole and 38 (37.3%) not receiving letrozole. The median ER expression was 70%, with higher expression observed in the letrozole group compared to the no letrozole group (77.5% vs. 60%). No significant correlation was found between ER expression status and therapy response (p = 0.295 and p = 0.176, respectively). Letrozole therapy was well tolerated with no major adverse effects reported. In the overall cohort, maintenance letrozole therapy did not confer a significant improvement in progression-free survival (median 20.56 months vs. 29.34 months, p = 0.53) or overall survival (OS) (median 79.48 months vs. 46.85 months, p = 0.71) over a median follow-up duration of 23.5 months. However, among patients with no residual disease, maintenance letrozole therapy was associated with a statistically significant improvement in OS compared to those not receiving letrozole (median 114 months vs. 46.9 months, p = 0.006). Conclusions: Maintenance letrozole therapy appears to be a well-tolerated and potentially beneficial intervention in a subset of patients with ER-positive HGSC with no residual disease post-treatment. These findings highlight the need for further validation through prospective randomized trials to comprehensively assess the efficacy of endocrine therapy in this setting and its implications for patient quality of life. Full article

Patient-derived xenograft (PDX) models are powerful tools in cancer research, offering an accurate platform for evaluating cancer treatment efficacy and predicting responsiveness. However, these models necessitate surgical techniques for tumor tissue transplantation and face challenges with non-uniform tumor growth among animals. To address these issues, we attempted to develop a new PDX modeling method using high-grade serous ovarian cancer (HGSC), a fatal disease with a 5-year survival rate of 29%, which requires personalized research due to its morphological, genetic, and molecular heterogeneities. In this study, we developed a new patient-derived cancer cell xenograft (PDCX) model with high engraftment efficiency (64%) that utilizes primary cancer cells instead of patient tissues. Primary cancer cells can be stably cryopreserved for extended periods (up to 485 days), and when transplanted into female NSGA mice, they maintain morphological and molecular characteristics without significant genetic differences compared to their original primary tumors. Furthermore, PDCX models can be easily produced using a syringe, allowing for uniform tumor sizes across multiple animals. Additionally, M2 PDCXs exhibited a significantly faster growth rate compared to M2 PDTXs. Consequently, our PDCX model offers a streamlined approach for evaluating personalized cancer treatments with minimal experimental variability. Full article

In 2025, gynecological cancers are projected to account for approximately 10% of cancer-related deaths in women. High-grade serous ovarian carcinoma (HGSC) and serous endometrial carcinoma (SEC) are the most lethal gynecological cancer subtypes. Both malignancies commonly have TP53 mutations, alterations of the RB1 pathway, and numerous secondary mutations. Both carcinoma types consist of poorly differentiated and highly heterogeneous cell populations at the time of detection. Latent development and rapid progression of HGSC and SEC impede the identification of definitive cells of origin and genetic drivers. Here, we review our current knowledge about cancer-prone cell states and genetic drivers. We also discuss how emerging transcriptomic and genetic tools applied to contemporary model systems may facilitate the identification of novel targets for timely detection and therapeutic intervention. Full article

Women diagnosed with advanced-stage ovarian cancer have a much worse survival rate than women diagnosed with early-stage ovarian cancer, but the early detection of this disease remains a clinical challenge. Some recent reports indicate that genetic variations could be useful for the early detection of several malignancies. In this pilot observational retrospective study, we aimed to assess whether mitochondrial DNA (mtDNA) variations could discriminate the most frequent type of ovarian cancer, high-grade serous carcinoma (HGSC), from normal tissue. We identified mtDNA variations from 20 whole-exome sequenced (WES) HGSC samples and 14 controls (normal tubes) using the best practices of genome sequencing. We built prediction models of cancer with these variants, with good performance measured by the area under the curve (AUC) of 0.88 (CI: 0.74–1.00). The variants included in the best model were correlated with gene expression to assess the potentially affected processes. These analyses were validated with the Cancer Genome Atlas (TCGA) dataset, (including over 420 samples), with a fair performance in AUC terms (0.63–0.71). In summary, we identified a set of mtDNA variations that can discriminate HGSC with good performance. Specifically, variations in the MT-CYB gene increased the risk for HGSC by over 30%, and MT-CYB expression was significantly decreased in HGSC patients. Robust models of ovarian cancer detection with mtDNA variations could be applied to liquid biopsy technology, like those which have been applied to other cancers, with a special focus on the early detection of this lethal disease. Full article

Background/Objectives: All 11 metallothionein protein-coding genes are located on human chromosome 16q13. It is unique among human genetics to have an entire pathway’s genes clustered in a short chromosomal region. Since solid tumors, particularly high-grade serous ovarian cancer (HGSC), exhibit high rates of monoallelic aneuploidy, this region is commonly lost. Studies have not yet been performed to determine what vulnerability may be created in cancer cells with low metallothionein expression. Here, a screen of FDA-approved cancer small molecule drugs for those best targeting low metallothionein ovarian cancer was completed. Methods: Screening methods were tested and compared using vehicle-treated negative controls and cadmium chloride, a positive control for cell loss selective for low metallothionein cells. CAOV3 cells, which are unique in their expression of only two metallothionein isoforms, were used, with or without shRNA knockdown of the predominantly expressed MT2A gene. A library of FDA-approved molecules was then screened. Results: The optimal assay utilized Hoechst 33342 nuclear staining and mechanized fluorescent microscope counting of cell content. Encorafenib, an RAF inhibitor, was identified as the most selective for enhanced cytotoxicity in MT2A knockdown cells compared to scrambled controls. Conclusions: The nuclear stain Hoechst 33342, assessed by fluorescence microscopy, provides a low variance, moderate throughput platform for cancer cell loss screens. Low metallothionein ovarian cancer cells exhibit a vulnerability to the RAF inhibitor encorafenib. Full article

Background: Chemoresistance is a major obstacle in high-grade serous carcinoma (HGSC) treatment. Although many patients initially respond to chemotherapy, the majority of them relapse due to Carboplatin and Paclitaxel resistance. Drug repurposing has surfaced as a potentially effective strategy that works synergically with standard chemotherapy to bypass chemoresistance. In a prior study, using 2D cultures and two HGSC chemoresistant cell lines, it was demonstrated that combining Carboplatin or Paclitaxel with Pitavastatin or Ivermectin resulted in the most notable synergy. Acknowledging that 2D culture systems are limited in reflecting the tumor architecture, 3D cultures were generated to provide insights on treatment efficacy tests in more complex models. Objectives: We aimed to investigate whether combining Carboplatin or Paclitaxel with Pitavastatin or Ivermectin offers therapeutic benefits in a Cultrex-based 3D model. Methods: Here, the cytotoxicity of Carboplatin and Paclitaxel, both alone and in combination with Pitavastatin or Ivermectin, were analyzed on two chemoresistant tumor cell lines, OVCAR8 and OVCAR8 PTX R C, in 3D cultures. Cellular viability was assessed using CellTiter-Glo^® Luminescent assays. Also, it explored synergistic interactions using zero interaction potency, Loewe, Bliss independence, and High-single agent reference models. Results: Our research indicates combining chemotherapeutic drugs with Pitavastatin or Ivermectin yields significantly more cytotoxic effects than chemotherapy alone. For all the combinations tested, at least one model indicated an additive effect; however, only the combination of Paclitaxel and Ivermectin consistently demonstrated an additive effect across all chemoresistant cell lines cultured in 3D models, as well as in all four synergy reference models used to assess drug interactions. Conclusions: Combining Paclitaxel with Ivermectin has the highest cytotoxic and the strongest additive effect for both chemoresistant cell lines compared to Paclitaxel alone. Full article

Background/Objectives: High-grade serous carcinomas (HGSCs) are highly heterogeneous tumors, both among patients and within a single tumor. Differences in molecular mechanisms significantly describe this heterogeneity. Four molecular subtypes have been previously described by the Cancer Genome Atlas Consortium: differentiated, immunoreactive, mesenchymal, and proliferative. These subtypes may have varying degrees of progression, relapse-free survival, and overall survival, as well as response to therapy. The precise determination of these subtypes is certainly necessary both for diagnosis and future development of targeted therapies within personalized medicine. Methods: In this study, we analyzed gene expression data based on bulk RNA-seq, scRNA-seq, and spatial transcriptomic data from six cohorts (totaling 535 samples, including 60 single-cell samples). Differential expression analysis was performed using the edgeR package. The KEGG database and GSVA package were used for pathways enrichment analysis. As a predictive model, a deep neural network was created using the keras and tensorflow libraries. Results: We identified 357 differentially expressed genes among the four subtypes: 96 differentiated, 33 immunoreactive, 91 mesenchymal, and 137 proliferative. Based on these, we created OVsignGenes, a neural network model resistant to the effects of platform (test dataset AUC = 0.969). We then ran data from five more cohorts through our model, including scRNA-seq and spatial transcriptomics. Conclusions: Because the differentiated subtype is located at the intersection of the other three subtypes based on PCA and does not have a unique profile of differentially expressed genes or enriched pathways, it can be considered an initiating subtype of tumor that will develop into one of the three other subtypes. Full article

Background: Serous tubal intraepithelial carcinoma (STIC) is an early-stage cancerous lesion found in the fallopian tubes, often at the fimbrial end. It is strongly associated with high-grade serous carcinoma (HGSC), a highly aggressive type of ovarian cancer. STIC is considered a precursor to many HGSC cases, originating in the fallopian tubes. Its development is frequently linked to mutations in the TP53 gene, leading to the formation of a p53 signature, an early abnormality that may progress to HGSC. This signature is more common in BRCA mutation carriers, explaining the higher incidence of STIC in this group. The aim of this review is to evaluate the literature on the incidence of serous tubal intraepithelial carcinoma in patients (both BRCA-positive and BRCA-negative) undergoing preventive salpingo-oophorectomy, analysing the available data and identifying associations between specific characteristics and the onset of STIC. Methods: A comprehensive review of the literature from 2016 to 2023 was conducted using PubMed, focusing on studies analysing the incidence of STIC in BRCA-positive patients undergoing preventive salpingo-oophorectomy. Data on patient characteristics, interventions, outcomes, and incidence of STIC were extracted and analysed. Results: Nine international studies were included in the review, reporting varying incidences of STIC among patients undergoing salpingo-oophorectomy. The overall incidence of STIC in all the women included in the studies was 7.31%, while that in the BRCA-mutated women was approximately 6.08%. Notably, the presence of the TP53 signature was significantly associated with the occurrence of STIC. Conclusions: The etiopathogenesis of STIC involves complex interactions between genetic, environmental, and molecular factors. Further research is needed to fully understand its mechanisms and identify additional risk factors beyond BRCA mutations. Establishing a national database of STIC cases could facilitate future research and improve patient outcomes. Full article

Background: High-grade serous carcinoma (HGSC) is the most lethal of gynecological cancers in developed countries. It usually presents late with non-specific symptoms and most cases are diagnosed at an advanced stage, with 5-year overall survival being around 40%. Biomarkers for screening and early diagnosis of this aggressive disease are, thus, a research priority. Extracellular vesicles (EVs) that reflect the cell of origin and that can be isolated from local fluid and plasma by minimally invasive liquid biopsy are such promising biomarkers. Besides EV concentration and molecular profile, which have been the main focus of research for many years, recent studies have also called attention to EV size distribution. The aim of our study was to evaluate the potential of EV concentration and size distribution in local fluid and plasma as diagnostic biomarkers for HGSC. Methods: Paired pretreatment ascites and plasma samples from 37 patients with advanced HGSC and paired pretreatment free peritoneal fluid (FPF) and plasma samples from 40 controls with benign ovarian pathology (BOP) were analyzed using nanoparticle tracking analysis (NTA). Results: We observed a significant difference in EV concentration in local fluid, but not in plasma, between HGSC patients and the control group. We also found a significant difference in EV size distribution in both local fluid and plasma between HGSC patients and the control group. The receiver operating characteristics (ROC) curve analysis of EV characteristics showed excellent diagnostic performance for the mode, D10, and D50 in local fluid and acceptable diagnostic performance for EV concentration and mean EV size in local fluid, as well as for the mode and D10 value in plasma. Conclusions: The results of our study show that EV concentration in local fluid and more importantly EV size distribution in both local fluid and plasma are significantly changed in the presence of HGSC. Future research of size-dependent molecular profiling of EVs could help identify novel diagnostic biomarkers for HGSC. Full article

Objective: The goal of this study was to compare the results of CNV detection by three different methods using 13 paired carcinoma samples, as well as to perform a statistical analysis of the agreement. Methods: CNV was studied using NanoString nCounter v2 Cancer CN Assay (Nanostring), Illumina Infinium CoreExome microarrays (CoreExome microarrays) and digital droplet PCR (ddPCR). Results: There was a good level of agreement (PABAK score > 0.6) between the CoreExome microarrays and the ddPCR results for finding CNVs. There was a moderate level of agreement (PABAK values ≈ 0.3–0.6) between the NanoString Assay results and microarrays or ddPCR. For 83 out of 87 target genes studied (95%), the agreement between the CoreExome microarrays and NanoString nCounter was characterized by PABAK values < 0.75, except for MAGI3, PDGFRA, NKX2-1 and KDR genes (>0.75). The MET, HMGA2, KDR, C8orf4, PAX9, CDK6, and CCND2 genes had the highest agreement among all three approaches. Conclusions: Therefore, to get a better idea of how to genotype an unknown CNV spectrum in tumor or normal tissue samples that are very different molecularly, it makes sense to use at least two CNV detection methods. One of them, like ddPCR, should be able to quantitatively confirm the results of the other. Full article