Reprogramming of Ovarian Granulosa Cells by YAP1 Leads to Development of High-Grade Cancer with Mesenchymal Lineage and Serous Features.
Ontology highlight
ABSTRACT:
SUBMITTER: Lv X
PROVIDER: S-EPMC8654108 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:In the early 2000s a two-tier grading system was introduced for serous ovarian cancer. Since then, we have increasingly come to accept that low-grade serous ovarian carcinoma (LGSOC) is a separate entity with a unique mutational landscape and clinical behaviour. As less than 10% of serous carcinomas of the ovary are low-grade, they are present in only a small number of patients in clinical trials for ovarian cancer. Therefore the current treatment of LGSOC is based on smaller trials, retrospective series, and subgroup analysis of large clinical trials on ovarian cancer. Surgery plays a major role in the treatment of patients with LGSOC. In the systemic treatment of LGSOC, hormonal treatment and targeted therapies seem to play an important role.
| S-EPMC6195427 | biostudies-literature
Project description:ObjectiveThe objective of our study was to investigate whether the CT features of serous borderline tumors (SBTs) differ from those of low-grade serous carcinomas (LGSCs) and to evaluate if mutation status is associated with distinct CT phenotypes.Materials and methodsThis retrospective study included 59 women, 37 with SBT and 22 with LGSC, who underwent CT before primary surgical resection. Thirty of 59 patients were genetically profiled. Two radiologists (readers 1 and 2) independently and retrospectively reviewed CT examinations for qualitative features and quantified total tumor volumes (TTVs), solid tumor volumes (STVs), and solid proportion of ovarian masses. Univariate and multivariate associations of the CT features with histopathologic diagnoses and mutations were evaluated, and interreader agreement was determined.ResultsAt multivariate analysis, the presence of bilateral ovarian masses (p = 0.03), the presence of peritoneal disease (PD) (p = 0.002), and higher STV of ovarian masses (p = 0.002) were associated with LGSC. The presence of nodular PD pattern (p < 0.001 each reader) and the presence of PD calcifications (reader 1, p = 0.02; reader 2, p = 0.003) were associated with invasive peritoneal lesions (i.e., LGSC). The presence of bilateral ovarian masses (p = 0.04 each reader), PD (reader 1, p = 0.01; reader 2, p = 0.004), and higher STV (p = 0.03 for each reader) were associated with the absence of BRAF mutation (i.e., wild type [wt]-BRAF).ConclusionThe CT features of LGSCs were distinct from those of SBTs. The CT manifestations of LGSC and the wt-BRAF phenotype were similar.
| S-EPMC6690180 | biostudies-literature
Project description:BackgroundSerous borderline ovarian tumor (SBOT) and high-grade serous ovarian cancer (HGSOC) are two distinct subtypes of epithelial ovarian tumors, with markedly different biologic background, behavior, prognosis, and treatment. However, the histologic diagnosis of serous ovarian tumors can be subjectively variable and labor-intensive as multiple tumor slides/blocks need to be thoroughly examined to search for these features.Materials and methodsWe developed a novel informatics system to facilitate objective and scalable diagnosis screening for SBOT and HGSOC. The system was built upon Groovy scripts and QuPath to enable interactive annotation and data exchange.ResultsThe system was used to successfully detect cellular boundaries and extract an expanded set of cellular features representing cell- and tissue-level characteristics. The performance of cell-level classification for both tumor and stroma cells achieved >90% accuracy. The performance of differentiating HGSOC versus SBOT achieved 91%-95% accuracy for 6485 imaging patches which have sufficient tumor and stroma cells (minimum of ten each) and 97% accuracy for classifying patients when aggregating the results to whole-slide image based on consensus.ConclusionsCellular features digitally extracted from pathological images can be used for cell classification and SBOT v. HGSOC differentiation. Introducing digital pathology into ovarian cancer research could be beneficial to discover potential clinical implications. A larger cohort is required to further evaluate the system.
| S-EPMC8356706 | biostudies-literature
Project description:Neurofibromatosis type 1 (NF1) is caused by mutations in the NF1 gene encoding neurofibromin, which negatively regulates Ras signaling. NF1 patients have an increased risk of developing early onset breast cancer, however, the association between NF1 and high grade serous ovarian cancer (HGSOC) is unclear. Since most NF1-related tumors exhibit early biallelic inactivation of NF1, we evaluated the evolution of genetic alterations in HGSOC in an NF1 patient. Somatic variation analysis of whole exome sequencing of tumor samples from both ovaries and a peritoneal metastasis showed a clonal lineage originating from an ancestral clone within the left adnexa, which exhibited copy number (CN) loss of heterozygosity (LOH) in the region of chromosome 17 containing TP53, NF1, and BRCA1 and mutation of the other TP53 allele. This event led to biallelic inactivation of NF1 and TP53 and LOH for the BRCA1 germline mutation. Subsequent CN alterations were found in the dominant tumor clone in the left ovary and nearly 100% of tumor at other sites. Neurofibromin modeling studies suggested that the germline NF1 mutation could potentially alter protein function. These results demonstrate early, biallelic inactivation of neurofibromin in HGSOC and highlight the potential of targeting RAS signaling in NF1 patients.
| S-EPMC5993517 | biostudies-literature
Project description:Claudin-low cancer (CL) represents a rare and biologically aggressive variant of epithelial tumor. Here, we identified a claudin-low molecular profile of ovarian high-grade serous carcinoma (HGSOC), which exhibits the main characteristics of the homonym breast cancer subtype, including low epithelial differentiation and high mesenchymal signature. Hierarchical clustering and a centroid based algorithm applied to cell line collection expression dataset labeled 6 HGSOC cell lines as CL. These have a high energy metabolism and are enriched in CD44+/CD24- mesenchymal stem-like cells expressing low levels of cell-cell adhesion molecules (claudins and E-Cadherin) and high levels of epithelial-to-mesenchymal transition (EMT) induction transcription factors (Zeb1, Snai2, Twist1 and Twist2). Accordingly, the centroid base algorithm applied to large retrospective collections of primary HGSOC samples reveals a tumor subgroup with transcriptional features consistent with the CL profile, and reaffirms EMT as the dominant biological pathway functioning in CL-HGSOC. HGSOC patients carrying CL profiles have a worse overall survival when compared to others, likely to be attributed to its undifferentiated/stem component. These observations highlight the lack of a molecular diagnostic in the management of HGSOC and suggest a potential prognostic utility of this molecular subtyping.
| S-EPMC7926503 | biostudies-literature
Project description:BackgroundHigh-grade serous ovarian carcinoma (HGSOC) is a pathologic subtype of ovarian cancer (OC) with a more lethal prognosis. Extensive heterogeneity results in HGSOC being more susceptible to treatment resistance and adverse treatment effects. Revealing the heterogeneity involved is crucial.MethodsWe downloaded the single-cell RNA-seq (scRNA) data from GEO database and performed a scRNA analysis for cell landscape of HGSOC by using the Seurat package. The highly expressed genes were uploaded into the DAVID and KEGG database for enrichment analysis, and the AUCell package was used to calculate cancer-associated hallmark score. The SCENIC analysis was used for key regulons, the estrogen response enrichment scores in TCGA-OV RNA-seq dataset were calculated by using the GSVA package. Besides, the expression of STRA6 and IRF1 and the cell invasion and migration in si-STRA6 OC cells were detected by using the quantitative reverse transcription (qRT)-PCR method and Transwell assay respectively.ResultsWe successfully constructed a single-cell atlas of HGSOC and delineated the heterogeneity of epithelial cells therein. There were five epithelial cell subpopulations, GLDC + Epithelial cells, PEG3+ leydig cells, STRA6+ granulosa cells, POLE2+ Epithelial cells, and AURKA + Epithelial cells. STRA6+ granulosa cells have the potential to promote tumor growth as well as the highest estrogen response early activity through the biological pathways analysis of highly expressed genes and estrogen response score of ssGSEA. We found that IRF1 and STRA6 expression was remarkably upregulated in the OC cancer cell line HEY. Silencing of STRA6 markedly decreased the invasion and migration ability of the OC cancer cell line HEY.ConclusionThere is extreme heterogeneity of epithelial cells in HGSOC, and STRA6+ granulosa cells may be able to promote cancer progression. Our findings are benefit to the heterogeneity identification of HGSOC and develop targeted therapy strategy for HGSOC patients.
| S-EPMC10950672 | biostudies-literature
Project description:High-grade serous ovarian cancers (HGSOC) represent the most common subtype of ovarian malignancies. Due to the frequency of late-stage diagnosis and high rates of recurrence following standard of care treatments, novel therapies are needed to promote durable responses. We investigated the anti-tumor activity of CD3 T cell engaging bispecific antibodies (TCBs) directed against the PAX8 lineage-driven HGSOC tumor antigen LYPD1 and demonstrated that anti-LYPD1 TCBs induce T cell activation and promote in vivo tumor growth inhibition in LYPD1-expressing HGSOC. To selectively target LYPD1-expressing tumor cells with high expression while sparing cells with low expression, we coupled bivalent low-affinity anti-LYPD1 antigen-binding fragments (Fabs) with the anti-CD3 scFv. In contrast to the monovalent anti-LYPD1 high-affinity TCB (VHP354), the bivalent low-affinity anti-LYPD1 TCB (QZC131) demonstrated antigen density-dependent selectivity and showed tolerability in cynomolgus monkeys at the maximum dose tested of 3 mg/kg. Collectively, these data demonstrate that bivalent TCBs directed against LYPD1 have compelling efficacy and safety profiles to support its use as a treatment for high-grade serous ovarian cancers.
| S-EPMC8295318 | biostudies-literature
Project description:High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment 18F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment 18F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC.
| S-EPMC10670627 | biostudies-literature
Project description:Women diagnosed with high-grade serous ovarian cancers (HGSOC) are still likely to exhibit a bad prognosis, particularly when suffering from HGSOC of the Mesenchymal molecular subtype (50% cases). These tumors show a desmoplastic reaction with accumulation of extracellular matrix proteins and high content of cancer-associated fibroblasts. Using patient-derived xenograft mouse models of Mesenchymal and Non-Mesenchymal HGSOC, we show here that HGSOC exhibit distinct stiffness depending on their molecular subtype. Indeed, tumor stiffness strongly correlates with tumor growth in Mesenchymal HGSOC, while Non-Mesenchymal tumors remain soft. Moreover, we observe that tumor stiffening is associated with high stromal content, collagen network remodeling, and MAPK/MEK pathway activation. Furthermore, tumor stiffness accompanies a glycolytic metabolic switch in the epithelial compartment, as expected based on Warburg's effect, but also in stromal cells. This effect is restricted to the central part of stiff Mesenchymal tumors. Indeed, stiff Mesenchymal tumors remain softer at the periphery than at the core, with stromal cells secreting high levels of collagens and showing an OXPHOS metabolism. Thus, our study suggests that tumor stiffness could be at the crossroad of three major processes, i.e. matrix remodeling, MEK activation and stromal metabolic switch that might explain at least in part Mesenchymal HGSOC aggressiveness.
| S-EPMC7892556 | biostudies-literature
Project description:High grade serous ovarian carcinoma (HGSOC) accounts for ~ 70% of ovarian cancer cases. Non-invasive, highly specific blood-based tests for pre-symptomatic screening in women are crucial to reducing the mortality associated with this disease. Since most HGSOCs typically arise from the fallopian tubes (FT), our biomarker search focused on proteins found on the surface of extracellular vesicles (EVs) released by both FT and HGSOC tissue explants and representative cell lines. Using mass spectrometry, 985 EV proteins (exo-proteins) were identified that comprised the FT/HGSOC EV core proteome. Transmembrane exo-proteins were prioritized because these could serve as antigens for capture and/or detection. With a nano-engineered microfluidic platform, six newly discovered exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF) plus a known HGSOC associated protein, FOLR1 exhibited classification performance ranging from 85 to 98% in a case-control study using plasma samples representative of early (including stage IA/B) and late stage (stage III) HGSOCs. Furthermore, by a linear combination of IGSF8 and ITGA5 based on logistic regression analysis, we achieved a sensitivity of 80% with 99.8% specificity and a positive predictive value of 13.8%. Importantly, these exo-proteins also can accurately discriminate between ovarian and 12 types of cancers commonly diagnosed in women. Our studies demonstrate that these lineage-associated exo-biomarkers can detect ovarian cancer with high specificity and sensitivity early and potentially while localized to the FT when patient outcomes are more favorable.
| S-EPMC10603107 | biostudies-literature