Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer.
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ABSTRACT:
SUBMITTER: Pan J
PROVIDER: S-EPMC7708455 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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:ObjectiveWe have established 4 histopathologic subtyping of high-grade serous ovarian cancer (HGSOC) and reported that the mesenchymal transition (MT) type has a worse prognosis than the other subtypes. In this study, we modified the histopathologic subtyping algorithm to achieve high interobserver agreement in whole slide imaging (WSI) and to characterize the tumor biology of MT type for treatment individualization.MethodsFour observers performed histopathological subtyping using WSI of HGSOC in The Cancer Genome Atlas data. As a validation set, cases from Kindai and Kyoto Universities were independently evaluated by the 4 observers to determine concordance rates. In addition, genes highly expressed in MT type were examined by gene ontology term analysis. Immunohistochemistry was also performed to validate the pathway analysis.ResultsAfter algorithm modification, the kappa coefficient, which indicates interobserver agreement, was greater than 0.5 (moderate agreement) for the 4 classifications and greater than 0.7 (substantial agreement) for the 2 classifications (MT vs. non-MT). Gene expression analysis showed that gene ontology terms related to angiogenesis and immune response were enriched in the genes highly expressed in the MT type. CD31 positive microvessel density was higher in the MT type compared to the non-MT type, and tumor groups with high infiltration of CD8/CD103 positive immune cells were observed in the MT type.ConclusionWe developed an algorithm for reproducible histopathologic subtyping classification of HGSOC using WSI. The results of this study may be useful for treatment individualization of HGSOC, including angiogenesis inhibitors and immunotherapy.
| S-EPMC10323300 | biostudies-literature
Project description:Because of the high risk of recurrence in high-grade serous ovarian carcinoma (HGS-OvCa), the development of outcome predictors could be valuable for patient stratification. Using the catalog of The Cancer Genome Atlas (TCGA), we developed subtype and survival gene expression signatures, which, when combined, provide a prognostic model of HGS-OvCa classification, named "Classification of Ovarian Cancer" (CLOVAR). We validated CLOVAR on an independent dataset consisting of 879 HGS-OvCa expression profiles. The worst outcome group, accounting for 23% of all cases, was associated with a median survival of 23 months and a platinum resistance rate of 63%, versus a median survival of 46 months and platinum resistance rate of 23% in other cases. Associating the outcome prediction model with BRCA1/BRCA2 mutation status, residual disease after surgery, and disease stage further optimized outcome classification. Ovarian cancer is a disease in urgent need of more effective therapies. The spectrum of outcomes observed here and their association with CLOVAR signatures suggests variations in underlying tumor biology. Prospective validation of the CLOVAR model in the context of additional prognostic variables may provide a rationale for optimal combination of patient and treatment regimens.
| S-EPMC3533304 | biostudies-literature
Project description:Background:To identify clinically relevant genomic rearrangement signatures in high-grade serous ovarian cancer (HGSOC), we conducted a retrospective analysis of sequenced HGSOC whole-tumor genomes. Methods:Clinical data and whole-genome sequencing (WGS) reads were obtained for primary HGSOC tumors sequenced by the Australian Ovarian Cancer Study (AOCS; n?=?80). Genomic rearrangements were identified, and non-negative matrix factorization (NMF) was used to extract rearrangement signatures. The cohort was then dichotomized around the median signature contribution, and overall survival (OS) was analyzed. An independent cohort from The Cancer Genome Atlas (TCGA) ovarian cancer study (n?=?490) was also examined. The TCGA cohort was dichotomized around the median similarity between tumor copy number profile and a prognostic rearrangement signature, and OS was analyzed. Outcomes were assessed using Kaplan-Meier and multivariable Cox regression methods. All statistical tests were two-sided. Results:We identified five genomic rearrangement signatures (Ov.RS1-5) in HGSOC. Ov.RS3 exhibited 10 kilobase to 10 megabase deletions and tandem duplications, and patients whose tumors exhibited a high contribution from Ov.RS3 had poor OS. The median OS was 22.7?months (95% confidence interval [CI] = 20.2 to 39.0?months) in the Ov.RS3-high group vs 38.2?months (95% CI?=?22.7 to 69.1?months) in the Ov.RS3-low group (hazard ratio [HR] = 1.86, 95% CI?=?1.12 to 3.09, P = .02). For the independent TCGA cohort, median OS rates were 38.0?months (95% CI?=?35.3 to 41.4?months) in the Ov.RS3 high-similarity group vs 48.9?months (95% CI?=?44.1 to 57.1?months) in the Ov.RS3 low-similarity group (HR?=?1.54, 95% CI?=?1.21 to 1.97, P < .001). Conclusion:A novel genomic rearrangement signature is associated with poor prognosis in HGSOC.
| S-EPMC6054271 | biostudies-literature
Project description:BackgroundThe underlying mechanism of high T-cell presence as a favorable prognostic factor in high-grade serous ovarian carcinoma (HGSOC) is not yet understood. In addition to immune cells, various cofactors are essential for immune processes. One of those are metallothioneins (MTs), metal-binding proteins comprising various isoforms. MTs play a role in tumor development and drug resistance. Moreover, MTs influence inflammatory processes by regulating zinc homeostasis. In particular, T-cell function and polarization are particularly susceptible to changes in zinc status. The aim of the present study was to investigate a possible role of MT-mediated immune response and its association with prognostic outcome in ovarian cancer.MethodsA retrospective study was conducted on a clinically well-characterized cohort of 24 patients with HGSOC treated at the University Hospital of Essen. Gene expression patterns for anti-cancer immunogenicity-related targets were performed using the NanoString nCounter platform for digital gene expression analysis with the appurtenant PanCancer Immune Profiling panel, consisting of 770 targets and 30 reference genes. Tumor-associated immunohistochemical MT protein expression was evaluated using a semi-quantitative four-tier Immunohistochemistry (IHC) scoring.ResultsMT immunoexpression was detected in 43% (10/23) of all HGSOC samples. MT immunoexpression levels showed a significant association to survival, leading to prolonged progression-free and overall survival in positively stained tumors. Furthermore, T-cell receptor signaling gene signature showed a strong activation in MT-positive tumors. Activated downstream signaling cascades resulting in elevated interferon-gamma expression with a shift in the balance between T helper cells (TH1 and TH2) could be observed in the MT-positive subgroup. In addition, a higher expression pattern of perforin and several granzymes could be detected, overall suggestive of acute, targeted anti-cancer immune response in MT-positive samples.ConclusionThis is the first study combining broad, digital mRNA screening of anti-tumor immune response-associated genes and their relation to MT-I/II in ovarian cancer. MT overexpression is associated with molecular characteristics of an anti-cancer immune response and is a strong prognostic marker in ovarian HGSOC. The observed immune cell activation associated with tumor MT expression comprises but is not limited to T cells and natural killer cells.
| S-EPMC10663300 | biostudies-literature
Project description:ImportanceDespite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics.ObjectiveTo develop and characterize a gross morphologic classification system for HGSOC.Design, setting, and participantsThis cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021.ExposuresGross tumor morphologic characteristics.Main outcomes and measuresClinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared.ResultsOf 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes.Conclusions and relevanceThis study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.
| S-EPMC9568802 | biostudies-literature
Project description:PURPOSE:High-grade serous cancer (HGSC) is the most common cancer of the ovary and is characterized by chromosomal instability. Defects in homologous recombination repair (HRR) are associated with genomic instability in HGSC, and are exploited by therapy targeting DNA repair. Defective HRR causes uniparental deletions and loss of heterozygosity (LOH). Our purpose is to profile LOH in HGSC and correlate our findings to clinical outcome, and compare HGSC and high-grade breast cancers. EXPERIMENTAL DESIGN:We examined LOH and copy number changes using single nucleotide polymorphism array data from three HGSC cohorts and compared results to a cohort of high-grade breast cancers. The LOH profiles in HGSC were matched to chemotherapy resistance and progression-free survival (PFS). RESULTS:LOH-based clustering divided HGSC into two clusters. The major group displayed extensive LOH and was further divided into two subgroups. The second group contained remarkably less LOH. BRCA1 promoter methylation was associated with the major group. LOH clusters were reproducible when validated in two independent HGSC datasets. LOH burden in the major cluster of HGSC was similar to triple-negative, and distinct from other high-grade breast cancers. Our analysis revealed an LOH cluster with lower treatment resistance and a significant correlation between LOH burden and PFS. CONCLUSIONS:Separating HGSC by LOH-based clustering produces remarkably stable subgroups in three different cohorts. Patients in the various LOH clusters differed with respect to chemotherapy resistance, and the extent of LOH correlated with PFS. LOH burden may indicate vulnerability to treatment targeting DNA repair, such as PARP1 inhibitors.
| S-EPMC4205235 | biostudies-literature
Project description:High-grade serous ovarian cancer is one of the deadliest gynecological malignancies and remains a clinical challenge. There is a critical need to effectively define patient stratification in a clinical setting. In this study, we address this question and determine the optimal number of molecular subgroups for ovarian cancer patients. By studying several independent patient cohorts, we observed that classifying high-grade serous ovarian tumors into four molecular subgroups using a transcriptomic-based approach did not reproducibly predict patient survival. In contrast, classifying these tumors into only two molecular subgroups, fibrosis and non-fibrosis, could reliably inform on patient survival. In addition, we found complementarity between transcriptomic data and the genomic signature for homologous recombination deficiency (HRD) that helped in defining prognosis of ovarian cancer patients. We also established that the transcriptomic and genomic signatures underlined independent biological processes and defined four different risk populations. Thus, combining genomic and transcriptomic information appears as the most appropriate stratification method to reliably subgroup high-grade serous ovarian cancer patients. This method can easily be transferred into the clinical setting.
| S-EPMC7089941 | biostudies-literature
Project description: Not available
| S-EPMC11344801 | biostudies-literature
Project description:Genomic studies of ovarian cancer (OC) cell lines frequently used in research revealed that these cells do not fully represent high-grade serous ovarian cancer (HGSOC), the most common OC histologic type. However, OC lines that appear to genomically resemble HGSOC have not been extensively used and their growth characteristics in murine xenografts are essentially unknown.To better understand growth patterns and characteristics of HGSOC cell lines in vivo, CAOV3, COV362, KURAMOCHI, NIH-OVCAR3, OVCAR4, OVCAR5, OVCAR8, OVSAHO, OVKATE, SNU119 and UWB1.289 cells were assessed for tumor formation in nude mice. Cells were injected intraperitoneally (i.p.) or subcutaneously (s.c.) in female athymic nude mice and allowed to grow (maximum of 90 days) and tumor formation was analyzed. All tumors were sectioned and assessed using H&E staining and immunohistochemistry for p53, PAX8 and WT1 expression.Six lines (OVCAR3, OVCAR4, OVCAR5, OVCAR8, CAOV3, and OVSAHO) formed i.p xenografts with HGSOC histology. OVKATE and COV362 formed s.c. tumors only. Rapid tumor formation was observed for OVCAR3, OVCAR5 and OVCAR8, but only OVCAR8 reliably formed ascites. Tumors derived from OVCAR3, OVCAR4, and OVKATE displayed papillary features. Of the 11 lines examined, three (Kuramochi, SNU119 and UWB1.289) were non-tumorigenic.Our findings help further define which HGSOC cell models reliably generate tumors and/or ascites, critical information for preclinical drug development, validating in vitro findings, imaging and prevention studies by the OC research community.
| S-EPMC4528621 | biostudies-literature