Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer.
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ABSTRACT:
SUBMITTER: Natanzon Y
PROVIDER: S-EPMC5802704 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Genomic Analysis Using Regularized Regression in High-Grade Serous Ovarian Cancer.
Natanzon Yanina Y Earp Madalene M Cunningham Julie M JM Kalli Kimberly R KR Wang Chen C Armasu Sebastian M SM Larson Melissa C MC Bowtell David Dl DD Garsed Dale W DW Fridley Brooke L BL Winham Stacey J SJ Goode Ellen L EL
Cancer informatics 20180201
High-grade serous ovarian cancer (HGSOC) is a complex disease in which initiation and progression have been associated with copy number alterations, epigenetic processes, and, to a lesser extent, germline variation. We hypothesized that, when summarized at the gene level, tumor methylation and germline genetic variation, alone or in combination, influence tumor gene expression in HGSOC. We used Elastic Net (ENET) penalized regression method to evaluate these associations and adjust for somatic c ...[more]
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Project description:Ovarian cancer is one of the most common gynecologic malignancies globally, which is a significant cause of morbidity and mortality, accounting for 207,252 new deaths each year. The 5-year survival rate of this cancer is reported to be 26-42% and is often diagnosed in an advanced stage. Epithelial ovarian cancer (EOC) is a heterogeneous disease that comprises various histological subtypes. Of them, high-grade serous ovarian cancer (HGSOC) is the most common cancer subtype (70-80%), which is highly aggressive and grows rapidly. Despite the initial success observed with cytoreductive surgery and platinum-based chemotherapy, over 75% of HGSOC patients experience relapse following completion of first-line therapy. The challenge of tailoring therapeutic interventions to control progressive disease is compounded by the inherent cellular heterogeneity and genomic instability characteristic of HGSOC. While platinum chemotherapy remains the cornerstone of contemporary treatment, the grim reality persists that a majority of EOC patients develop chemotherapy resistance, resulting in a five-year survival rate of less than 50%. Numerous ovarian cancer studies have underscored the prognostic significance of factors such as age at diagnosis, disease stage, grade, histology, residual disease post-surgery, and disease recurrence. The genetic predisposition towards EOC indicates that high-grade HGSC exhibits significant chromosomal instability and carries mutations in the tumor protein 53 (TP53) gene, as well as mutations in the breast cancer genes BRCA1/2. Molecular markers like BRCA1/2 mutations and homologous repair deficiency in HGSOC have been validated as predictive of response to platinum therapy and poly-ADP polymerase (PARP) inhibitors. Furthermore, recent research has shed light on the prognostic potential of immune cell populations infiltrating ovarian tumor tissue. The Cancer Genome Atlas (TCGA) and other genomic studies of HGSOC have conducted extensive genomic and transcriptomic analyses of HGSOC to delineate its genomic landscape and facilitate the development of targeted therapies for this highly lethal malignancy. Key findings from previous studies include the prevalent mutation of TP53 genes, frequent and widespread DNA copy number alterations, identification of transcriptional signatures associated with clinical outcome and molecular subtype, and diverse mechanisms of BRCA1/2 inactivation. However, most studies have focused on HGSOC of white populations, and there is limited comprehensive molecular characterization of East Asian HGSOC, including those from Korea. In this study, we aimed to discern clinical and molecular factors distinguishing 123 HGSOC patients from the Korean population through an integrated analysis of clinical features, germline variants, somatic genomic alterations, and the tumor immune microenvironment.
2024-06-01 | GSE268514 | GEO
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: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: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:Resistance to chemotherapy in ovarian cancer is poorly understood. Evolutionary models of cancer predict that, following treatment, resistance emerges either because of outgrowth of an intrinsically resistant sub-clone or evolves in residual disease under the selective pressure of treatment. To investigate genetic evolution in high-grade serous (HGS) ovarian cancers, we first analysed cell line series derived from three cases of HGS carcinoma before and after platinum resistance had developed (PEO1, PEO4 and PEO6; PEA1 and PEA2; and PEO14 and PEO23). Analysis with 24-colour fluorescence in situ hybridisation and single nucleotide polymorphism (SNP) array comparative genomic hybridisation (CGH) showed mutually exclusive endoreduplication and loss of heterozygosity events in clones present at different time points in the same individual. This implies that platinum-sensitive and -resistant disease was not linearly related, but shared a common ancestor at an early stage of tumour development. Array CGH analysis of six paired pre- and post-neoadjuvant treatment HGS samples from the CTCR-OV01 clinical study did not show extensive copy number differences, suggesting that one clone was strongly dominant at presentation. These data show that cisplatin resistance in HGS carcinoma develops from pre-existing minor clones but that enrichment for these clones is not apparent during short-term chemotherapy treatment.
| S-EPMC2933510 | biostudies-literature
Project description:The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue. In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform. The prediction model with SNV had an AUC of 1.00 (95% CI 1.00-1.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances. Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage.
| S-EPMC9738935 | biostudies-literature
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: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