High-grade serous ovarian cancer (MDACC) data access committee
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PROVIDER: EGAC00001001288 | EGA |
REPOSITORIES: EGA
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Project description:High-grade serous ovarian cancer (HGSOC) harbours aberrant epigenetic features, including DNA methylation. In this study we delineate pathways and networks altered by DNA methylation and associated with HGSOC initiation and progression to a platinum-resistant state. By including tumours from patients who had been treated with the hypomethylating agent (HMA) guadecitabine, we also addressed the role of HMAs in treatment of HGSOC. Tumours from patients with primary (platinum-naïve) HGSOC (n = 20) were compared to patients with recurrent platinum-resistant HGSOC and enrolled in a recently completed clinical trial (NCT01696032). Human ovarian surface epithelial cells (HOSE; n = 5 samples) served as normal controls. Genome-wide methylation profiles were determined. DNA methyltransferase (DNMT) expression levels were examined by immunohistochemistry and correlated with clinical outcomes. Cancer-related and tumorigenesis networks were enriched among differentially methylated genes (DMGs) in primary OC vs. HOSE. When comparing platinum-resistant and primary tumours, 452 CpG island (CGI)-containing gene promoters acquired DNA methylation; of those loci, decreased (P < 0.01) methylation after HMA treatment was observed in 42% (n = 189 CGI). Stem cell pluripotency and cytokine networks were enriched in recurrent platinum-resistant OC tumours, while drug metabolism and transport-related networks were downregulated in tumours from HMA-treated patients compared to HOSE. Lower DNMT1 and 3B protein levels in pre-treatment tumours were associated with improved progression-free survival. The findings provide important insight into the DNA methylation landscape of HGSOC tumorigenesis, platinum resistance and epigenetic resensitization. Epigenetic reprogramming plays an important role in HGSOC aetiology and contributes to clinical outcomes.
| S-EPMC8813084 | biostudies-literature
Project description:Background: Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer. Methods: The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with the same standard platinum-based chemotherapy. Twelve patient tumors demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumors from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using a Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumors from the resistant group and the sensitive group. Results: Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels, which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NFκB/ERK gene signalling networks. Conclusions: This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. Future studies to validate these markers are necessary to apply this knowledge to biomarker-based clinical trials.
2014-01-01 | GSE51373 | GEO
Project description:Background: Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer. Methods: The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with the same standard platinum-based chemotherapy. Twelve patient tumors demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumors from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using a Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumors from the resistant group and the sensitive group. Results: Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels, which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NFκB/ERK gene signalling networks. Conclusions: This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. Future studies to validate these markers are necessary to apply this knowledge to biomarker-based clinical trials. Total RNA from 12 chemotherapy resistant and 16 sensitive chemotherapy sensitive high-grade serous epithelial ovarian cancer samples was subjected to whole transcriptome profiling using Affymetrix U133 Plus 2.0 arrays
2014-01-01 | E-GEOD-51373 | biostudies-arrayexpress
Project description:High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.
| S-EPMC4892184 | biostudies-literature
Project description:Comprehensive biomedical proteomic datasets are accumulating exponentially, warranting robust analytics to deconvolute them for identifying novel biological insights. Here, we report a strategic machine learning (ML)-based feature extraction workflow that was applied to unveil high-performing protein markers for high-grade serous ovarian carcinoma (HGSOC) from publicly available ovarian cancer tissue and serum proteomics datasets. Diagnosis of HGSOC, an aggressive form of ovarian cancer, currently relies on diagnostic methods based on tissue biopsy and/or non-specific biomarkers such as the cancer antigen 125 (CA125) and human epididymis protein 4 (HE4). Our newly developed ML-based approach enabled the identification of new serum proteomic biomarkers for HGSOC. The performance verification of these marker combinations using two independent cohorts affirmed their outperformance against known biomarkers for ovarian cancer including clinically used serum markers with >97% AUC. Our analysis also added novel biological insights such as enriched cancer-related processes associated with HGSOC.
| S-EPMC11199488 | biostudies-literature
Project description:Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.
| S-EPMC9239907 | biostudies-literature
Project description:To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.
| S-EPMC10414761 | biostudies-literature
Project description:Epithelial ovarian cancer (OC) ranks first in the number of deaths among diseases of the female reproductive organs. Identification of OC at early stages is highly beneficial for the treatment but is highly challenging due to the asymptomatic or low-symptom disease development. In this study, lipid extracts of venous blood samples from 41 female volunteers, including 28 therapy-naive patients with histologically verified high-grade serous ovarian cancer at different stages (5 patients with I-II stages; 23 patients with III-IV stages) and 13 apparently healthy women of reproductive age, were profiled by high-performance liquid chromatography mass spectrometry (HPLC-MS). Based on MS signals of 128 differential lipid species with statistically significant level variation between the OC patients and control group, an OPLS-DA model was developed for the recognition of OC with 100% sensitivity and specificity R 2 = 0.87 and Q2 = 0.80. The second OPLS-DA model was developed for the differentiation between I-II OC stages and control group with R 2 = 0.97 and Q2 = 0.86 based on the signal levels of 108 differential lipid species. The third OPLS-DA model was developed for the differentiation between I-II OC stages and III-IV stages based on the signal levels of 99 differential lipid species. Various lipid classes (diglycerides, triglycerides, phosphatidylchlorines, ethanolamines, sphingomyelins, ceramides, phosphatidylcholines and phosphoinositols) in blood plasma samples display distinctly characteristic profiles in I-II OC, which indicates the possibility of their use as marker oncolipids in diagnostic molecular panels of early OC stages. Our results suggest that lipid profiling by HPLC-MS can improve identification of early-stage OC and thus increase the efficiency of treatment.
| S-EPMC9048792 | biostudies-literature
Project description:Purpose of reviewEpithelial ovarian cancer is a disease that encompasses a number of histologically and molecularly distinct entities; the most prevalent subtype being high-grade serous (HGS) carcinoma. Standard first-line treatment of advanced HGS carcinoma includes cytoreductive surgery plus intravenous paclitaxel/platinum-based chemotherapy. Despite excellent responses to initial treatment, the majority of patients develop recurrent disease within 3 years. The introduction of the vascular endothelial growth factor (VEGF) inhibitor, bevacizumab, and poly(ADP-ribose) polymerase (PARP) inhibitors into first-line management has changed the outlook for this lethal disease. In this review, we summarise the most recent clinical trials that determine current primary therapy of advanced HGS carcinoma and the ongoing trials that aim to change management in the future.Recent findingsRecent phase III clinical trials have shown that delayed primary surgery after completing neo-adjuvant chemotherapy is non-inferior to immediate primary surgery, but could provide a survival benefit in FIGO (International Federation of Gynecology and Obstetrics) stage IV disease. The use of weekly intravenous chemotherapy regimens has not been proven to be more effective than standard 3-weekly regimens in Western patient populations, and the use of intraperitoneal chemotherapy remains controversial in the first-line setting. In contrast, newer systemic anti-cancer therapies targeting angiogenesis and/or HR-deficient tumours have been successfully incorporated into front-line therapeutic regimens to treat HGS carcinoma. Recent results from randomised trials investigating the use of PARP inhibitors as monotherapy and in combination with the anti-angiogenic agent, bevacizumab, have demonstrated highly impressive efficacy when combined with traditional first-line multi-modality therapy. Management of HGS carcinoma is evolving, but further work is still required to optimise and integrate tumour and plasma biomarkers to exploit the potential of these highly efficacious targeted agents.
| S-EPMC7270049 | biostudies-literature
Project description:High-grade serous ovarian cancer (HGSC) disseminates early and extensively throughout the peritoneal space, causing multiple lesions that are a major clinical problem. The aim of this study was to investigate the cellular composition of peritoneal tumour deposits in patient biopsies and their evolution in mouse models using immunohistochemistry, intravital microscopy, confocal microscopy, and 3D modelling. Tumour deposits from the omentum of HGSC patients contained a prominent leukocyte infiltrate of CD3(+) T cells and CD68(+) macrophages, with occasional neutrophils. Alpha-smooth muscle actin(+) (α-SMA(+) ) pericytes and/or fibroblasts surrounded these well-vascularized tumour deposits. Using the murine bowel mesentery as an accessible mouse peritoneal tissue that could be easily imaged, and two different transplantable models, we found multiple microscopic tumour deposits after i.p. injection of malignant cells. Attachment to the peritoneal surface was rapid (6-48 h) with an extensive CD45(+) leukocyte infiltrate visible by 48 h. This infiltrate persisted until end point and in the syngeneic murine ID8 model, it primarily consisted of CD3(+) T lymphocytes and CD68(+) macrophages with α-SMA(+) cells also involved from the earliest stages. A majority of tumour deposits developed above existing mesenteric blood vessels, but in avascular spaces new blood vessels tracked towards the tumour deposits by 2-3 weeks in the IGROV-1 xenografts and 6 weeks in the ID8 syngeneic model; a vigorous convoluted blood supply was established by end point. Inhibition of tumour cell cytokine production by stable expression of shRNA to CXCR4 in IGROV-1 cells did not influence the attachment of cells to the mesentery but delayed neovascularization and reduced tumour deposit size. We conclude that the multiple peritoneal tumour deposits found in HGSC patients can be modelled in the mouse. The techniques described here may be useful for assessing treatments that target the disseminated stage of this disease.
| S-EPMC3609073 | biostudies-literature