Spatial cytotoxic and memory T cells in tumor predict superior survival outcomes in patients with high-grade serous ovarian cancer.
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SUBMITTER: Zhang G
PROVIDER: S-EPMC8209602 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundStudies have shown that tumor infiltrating lymphocyte (TILs) abundance is associated with overall survival in patients with high-grade serous ovarian cancer (HGSOC); however, the role of the spatial contexture and organization of TILs is less clear.MethodsWe evaluated the association between spatial architecture of T cells and survival in women with HGSOC from three large epidemiological studies in which tumors were analyzed by multiplex immunofluorescence (N = 433). A Ripley's K measure was used to determine the spatial clustering. Cox proportional hazards models assessed the association of spatial clustering with overall survival.ResultsWe found having high abundance and low spatial clustering of CD3+ TILs and CD3+CD8+ cytotoxic T lymphocytes (CTLs) was associated with improved overall survival (TILs HR=0.61, 95% CI 0.46-0.81, P=0.0005; CTLs HR=0.59, 95% CI 0.44-0.80, P=0.0007). Models with abundance and spatial information outperformed models with only the abundance levels (TILs P=0.002, CTLs P=0.00007).ConclusionHigh abundance of TILs and CTLs that are spatially distributed across the tumor was associated with better survival, replicating our work in non-Hispanic Black women, and supporting that the spatial architecture of the tumor microenvironment is an important predictor of survival in HGSOC.
| S-EPMC10827255 | biostudies-literature
Project description:ObjectiveTo examine clinicopathologic variables associated with survival among women with low-grade (grade 1) serous ovarian carcinoma enrolled in a phase III study.MethodsThis was an ancillary data analysis of Gynecologic Oncology Group protocol 182, a phase III study of women with stage III-IV epithelial ovarian carcinoma treated with carboplatin and paclitaxel compared with triplet or sequential doublet regimens. Women with grade 1 serous carcinoma (a surrogate for low-grade serous disease) were included in the analysis.ResultsAmong the 3,686 enrolled participants, 189 had grade 1 disease. The median age was 56.5 years and 87.3% had stage III disease. The median follow-up time was 47.1 months. Stratification according to residual disease after primary surgery was microscopic residual in 24.9%, 0.1-1.0 cm of residual in 51.3%, and more than 1.0 cm of residual in 23.8%. On multivariate analysis, only residual disease status (P=.006) was significantly associated with survival. Patients with microscopic residual had a significantly longer median progression-free (33.2 months) and overall survival (96.9 months) compared with those with residual 0.1-1.0 cm (14.7 months and 44.5 months, respectively) and more than 1.0 cm of residual disease (14.1 months and 42.0 months, respectively; progression-free and overall survival, P<.001). After adjustment for other variables, patients with low-grade serous carcinoma with measurable residual disease had a similar adjusted hazard ratio for death (2.12; P=.002) as their high-grade serous carcinoma counterparts with measurable disease (2.31; P<.001).ConclusionsSurgical cytoreduction to microscopic residual was associated with improved progression-free and overall survival in women with advanced-stage low-grade serous ovarian carcinoma.Clinical trial registrationClinicalTrials.gov, www.clinicaltrials.gov, NCT00011986.Level of evidenceII.
| S-EPMC4870595 | biostudies-literature
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:BackgroundThe major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.Methods and findingsEvolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22-46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66-1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy.ConclusionsThis study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.
| S-EPMC4339382 | 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:Initial identification of biomarkers predicting the exact prognosis of high-grade serous ovarian carcinoma (HGSOC) is important in precision cancer medicine. This study aimed to investigate prognostic biomarkers of HGSOC through proteomic analysis. We conducted label-free liquid chromatography-mass spectrometry using chemotherapy-naïve, fresh-frozen primary HGSOC specimens, and compared the results between a favorable prognosis group (progression-free survival (PFS) ≥ 18 months, n = 6) and a poor prognosis group (PFS < 18 months, n = 6). Among 658 differentially expressed proteins, 288 proteins were upregulated in the favorable prognosis group and 370 proteins were upregulated in the poor prognosis group. Using hierarchical clustering, we selected α1-antitrypsin (AAT), nuclear factor-κB (NFKB), phosphomevalonate kinase (PMVK), vascular adhesion protein 1 (VAP1), fatty acid-binding protein 4 (FABP4), platelet factor 4 (PF4), apolipoprotein A1 (APOA1), and α1-acid glycoprotein (AGP) for further validation via immunohistochemical (IHC) staining in an independent set of chemotherapy-naïve primary HGSOC samples (n = 107). Survival analyses revealed that high expression of AAT, NFKB, and PMVK were independent biomarkers for favorable PFS. Conversely, high expression of VAP1, FABP4, and PF4 were identified as independent biomarkers for poor PFS. Furthermore, we constructed models predicting the 18-month PFS by combining clinical variables and IHC results. Through leave-one-out cross-validation, the optimal model was based on initial serum CA-125, germline BRCA1/2 mutations, residual tumors after surgery, International Federation of Gynecology and Obstetrics (FIGO) stage, and expression levels of the six proteins. The present results elucidate the proteomic landscape of HGSOC and six protein biomarkers to predict the prognosis of HGSOC.
| S-EPMC7226362 | biostudies-literature
Project description:BACKGROUND:Relatively little is known about factors associated with long-term survival (LTS) following a diagnosis of ovarian cancer. METHODS:We conducted a retrospective study of high-grade serous ovarian cancer (HGSOC) to explore predictors of LTS (defined as ?7 years of survival) using electronic medical record data from a network of integrated health care systems. Multivariable logistic regression with forward selection was used to compare characteristics of women who survived ?7 years after diagnosis (n = 148) to those who died within 7 years of diagnosis (n = 494). RESULTS:Our final model included study site, age, stage at diagnosis, CA-125, comorbidity score, receipt of chemotherapy, BMI, and four separate comorbid conditions: weight loss, depression, hypothyroidism, and liver disease. Of these, only younger age, lower stage, and depression were statistically significantly associated with LTS. CONCLUSIONS:We did not identify any new characteristics associated with HGSOC survival. IMPACT:Prognosis of ovarian cancer generally remains poor. Large, pooled studies of ovarian cancer are needed to identify characteristics that may improve survival.
| S-EPMC6500478 | 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:IntroductionWidespread intra-peritoneal metastases is a main feature of high grade serous ovarian carcinoma (HGSOC). Recently, the extent of tumour heterogeneity was used to evaluate the cancer genomes among multi-regions in HGSOC. However, there is no consensus on the effect of tumour heterogeneity on the evolution of the tumour metastasis process in HGSOC.ObjectivesWe performed whole-exome sequencing in multiple regions of matched primary and metastatic HGSOC specimens to reveal the genetic mechanisms of ovarian tumourigenesis and malignant progression.Methods63 samples (including ovarian carcinoma, omentum metastasis, and normal tissues) were used. We analyzed the genomic heterogeneity, traced the subclone dissemination and establishment history and compared the different genetic characters of cancer evolutionary models in HGSOC.ResultsWe found that HGSOC had substantial intra-tumour heterogeneity (median 54.2, range 0 ∼ 106.7), high inter-patient heterogeneity (P < 0.001), but relatively limited intra-patient heterogeneity (P = 0.949). Two COSMIC mutational signatures were identified in HGSOCs: signature 3 was related to homologous recombination, and signature 1 was associated with aging. Two scenarios were identified by phylogenetic reconstruction in our study: 3 cases (33.3 %) showed star topology, and the other 6 cases (66.7 %) displayed tree topology. Compared with star topology group, more driver events were identified in tree topology group (P < 0.001), and occurred more frequently in early stage than in late stage of clonal evolution (P < 0.001). Moreover, compared with the star topology group, the tree topology group showed higher rate of intra-tumour heterogeneity (P = 0.045).ConclusionA dualistic classification model was proposed for the classification of HGSOC based on spatial heterogeneity, which may contribute to better managing patients and providing individual treatment for HGSOC patients.
| S-EPMC10248863 | biostudies-literature
Project description:PurposeMolecular cancer subtyping is an important tool in predicting prognosis and developing novel precision medicine approaches. We developed a novel platform-independent gene expression-based classification system for molecular subtyping of patients with high-grade serous ovarian carcinoma (HGSOC).MethodsUnprocessed exon array (569 tumor and nine normal) and RNA sequencing (RNA-seq; 376 tumor) HGSOC data sets, with clinical annotations, were downloaded from the Genomic Data Commons portal. Sample clustering was performed by non-negative matrix factorization by using isoform-level expression estimates. The association between the subtypes and overall survival was evaluated by Cox proportional hazards regression model after adjusting for the covariates. A novel classification system was developed for HGSOC molecular subtyping. Robustness and generalizability of the gene signatures were validated using independent microarray and RNA-seq data sets.ResultsSample clustering recaptured the four known The Cancer Genome Atlas molecular subtypes but switched the subtype for 22% of the cases, which resulted in significant (P = .006) survival differences among the refined subgroups. After adjusting for covariate effects, the mesenchymal subgroup was found to be at an increased hazard for death compared with the immunoreactive subgroup. Both gene- and isoform-level signatures achieved more than 92% prediction accuracy when tested on independent samples profiled on the exon array platform. When the classifier was applied to RNA-seq data, the subtyping calls agreed with the predictions made from exon array data for 95% of the 279 samples profiled by both platforms.ConclusionIsoform-level expression analysis successfully stratifies patients with HGSOC into groups with differing prognosis and has led to the development of robust, platform-independent gene signatures for HGSOC molecular subtyping. The association of the refined The Cancer Genome Atlas HGSOC subtypes with overall survival, independent of covariates, enhances the clinical annotation of the HGSOC cohort.
| S-EPMC6873993 | biostudies-literature