Ovarian Cancer Gene Research Articles

RAD51C-XRCC3 structure and cancer patient mutations define DNA replication roles

RAD51C is an enigmatic predisposition gene for breast, ovarian, and prostate cancer. Currently, missing structural and related functional understanding limits patient mutation interpretation to homology-directed repair (HDR) function analysis. Here we report the RAD51C-XRCC3 (CX3) X-ray co-crystal structure with bound ATP analog and define separable RAD51C replication stability roles informed by its three-dimensional structure, assembly, and unappreciated polymerization motif. Mapping of cancer patient mutations as a functional guide confirms ATP-binding matching RAD51 recombinase, yet highlights distinct CX3 interfaces. Analyses of CRISPR/Cas9-edited human cells with RAD51C mutations combined with single-molecule, single-cell and biophysics measurements uncover discrete CX3 regions for DNA replication fork protection, restart and reversal, accomplished by separable functions in DNA binding and implied 5’ RAD51 filament capping. Collective findings establish CX3 as a cancer-relevant replication stress response complex, show how HDR-proficient variants could contribute to tumor development, and identify regions to aid functional testing and classification of cancer mutations.

Metabolism-related gene vaccines and immune infiltration in ovarian cancer: A novel risk score model of machine learning.

The present study aims to develop a metabolic gene signature to evaluate the survival rate of ovarian cancer (OC) patients and analyze the potential mechanisms of metabolic genes in OC because the difficulty in early detection of OC often leads to poor treatment outcomes. A non-negative matrix factorization algorithm was applied to determine molecular subtypes according to metabolism genes. To build a risk prognosis model, least absolute shrinkage and selection operator multivariate Cox analysis was carried out with weighted correlation network analysis (WCGNA). Glycolytic flux and mitochondrial function were evaluated by conducting seahorse analysis. On the basis of metabolism-related genes, the two subtypes of OC samples present in The Cancer Genome Atlas database were distinguished. An analysis of WGCNA identified 1056 genes. Lastly, a 10-gene signature (CMAS, ADH1B, PLA2G2D, BHMT, CACNA1C, AADAC, ALOX12, CYP2R1, SCN1B and ME1) was constructed that demonstrated promising performance in predicting outcome in patients with OC. The RiskScore of the gene signature was linked to microenvironment cell infiltration and immune checkpoint. Higher RiskScores were associated with poorer results for OC patients. Seahorse analysis shows the influence of CMAS in cell energy metabolism. In the present study, a novel marker for evaluating the survival of OC patients was developed through the creation of a gene signature incorporating metabolism-related genes. Our knowledge of immunotherapy and microenvironment cell infiltration may be enriched by evaluating metabolism-related gene modification patterns.

Ginsenoside 20(S)-Rg3 reduces KIF20A expression and promotes CDC25A proteasomal degradation in epithelial ovarian cancer

BackgroundGinsenoside 20(S)-Rg3 shows promising tumor-suppressive effects in ovarian cancer via inhibiting NF-κB signaling. This study aimed to explore the downstream tumor suppressive mechanisms of ginsenoside Rg3 via this signaling pathway. Materials and methodsA systematical screening was applied to examine the expression profile of 41 kinesin family member genes in ovarian cancer. The regulatory effect of ginsenoside Rg3 on KIF20A expression was studied. In addition, we explored interacting proteins of KIF20A and their molecular regulations in ovarian cancer. RNA-seq data from The Cancer Genome Atlas (TCGA) was used for bioinformatic analysis. Epithelial ovarian cancer cell lines SKOV3 and A2780 were used as in vitro and in vivo cell models. Commercial human ovarian cancer tissue arrays were used for immunohistochemistry staining. ResultsKIF20A is a biomarker of poor prognosis among the kinesin genes. It promotes ovarian cancer cell growth in vitro and in vivo. Ginsenoside Rg3 can suppress the transcription of KIF20A. GST pull-down and co-immunoprecipitation (IP) assays confirmed that KIF20A physically interacts with BTRC (β-TrCP1), a substrate recognition subunit for SCFβ−TrCP E3 ubiquitin ligase. In vitro ubiquitination and cycloheximide (CHX) chase assays showed that via interacting with BTRC, KIF20A reduces BTRC-mediated CDC25A poly-ubiquitination and enhances its stability. Ginsenoside Rg3 treatment partly abrogates KIF20A overexpression-induced CDC25A upregulation. ConclusionThis study revealed a novel anti-tumor mechanism of ginsenoside Rg3. It can inhibit KIF20A transcription and promote CDC25A proteasomal degradation in epithelial ovarian cancer.

Pathogenic germline variants in SMARCA4 and further cancer predisposition genes in early onset ovarian cancer.

To assess the role of germline pathogenic variants (PVs) in SMARCA4 and further established ovarian cancer (OC) predisposition genes in early onset OC, we investigated a clinical cohort of 206 unrelated OC index patients with an age at diagnosis of OC ≤40 years using an extended panel of 24 (candidate) cancer predisposition genes. PVs in established OC predisposition genes were most frequent in patients with high grade serous OC (21/62, 33.9%), comparatively rare in patients with epithelial OC other than high grade serous (5/74, 6.8%) or borderline ovarian tumours (2/39, 5.1%) and absent in mucinous OC (0/27). We demonstrate that germline PVs in SMARCA4 unlikely predispose for early onset OC other than SCCOHT.

Unrestricted Ketogenic Diet Feeding Enhances Epithelial Ovarian Cancer Growth In Vivo.

The ketogenic diet (KD) is hypothesized to impact tumor progression by altering tumor metabolism. In this study, we assessed the impact of an unrestricted KD on epithelial ovarian cancer (EOC) tumor growth, gene expression, and metabolite concentration in a mouse model. ID8 EOC cells, which were syngeneic with C57Bl/6J mouse strain and transfected with luciferase (ID8-luc), were injectedand monitored for tumor development. Female mice were fed either a strict KD, a high fat/low carbohydrate (HF/LC) diet, or a low fat/high carbohydrate (LF/HC) diet (n = 10 mice per group) ad libitum. EOC tumor growth was monitored weekly, and tumor burden was determined based on luciferase fluorescence (photons/second). At the endpoint (42 days), tumors were collected and processed for RNA sequencing. Plasma and tumor metabolites were evaluated using LC-MS. The KD-fed mice exhibited a statistically significant increase in tumor progression in comparison to the HF/LC- and LF/HC-fed groups (9.1 vs. 2.0 vs. 3.1-fold, respectively, p < 0.001). The EOC tumors of the KD-fed mice exhibited significant enrichment of the peroxisome proliferator-activated receptor (PPAR) signaling and fatty acid metabolism pathways based on the RNA sequencing analysis when compared to the LF/HC- and HF/LC-fed mice. Thus, unrestricted KD diet enhanced tumor progression in our mouse EOC model. KD was associated with the upregulation of fatty acid metabolism and regulation pathways, as well as enrichment of fatty acid and glutamine metabolites.

A comprehensively prognostic and immunological analysis of chloride intracellular channel protein 5 (CLIC5) in pan-cancer and identification in ovarian cancer.

CLIC5 encoded protein associates with actin-based cytoskeletal and is increasingly thought to play significant roles in human cancers. We use TCGA and GEO to explore CLIC5 expression differences, mutation and DNA methylation, TMB, MSI, and immune cell infiltration. We verified the mRNA expression of CLIC5 in human ovarian cancer cells by real-time PCR and detected the expression of CLIC5 as well as immune marker genes in ovarian cancer by immunohistochemistry. The pan-cancer analysis showed that CLIC5 is highly expressed in several malignant tumors. In some cancers, CLIC5 expression in tumor samples is associated with poorer overall survival. For example, patients with ovarian cancer with high expression of CLIC5 have a poor prognosis. CLIC5 mutation frequency increased in all tumor types. The CLIC5 promoter is hypomethylated in most tumors. CLIC5 was associated with tumor immunity and different immune cells of different tumor types, such as CD8 + T cells, tumor-associated fibroblasts, macrophages, etc. CLIC5 was positively correlated with various immune checkpoints, and TMB and MSI were correlated with dysregulation of CLIC5 in tumors. The expression of CLIC5 in ovarian cancer was detected by qPCR and IHC, and the results were consistent with the bioinformatics results. There were a strong positive correlation between CLIC5 expression and M2 macrophage (CD163) infiltration and a negative correlation with CD8 + T-cell infiltration. In conclusions, our first pan-cancer analysis offered a detailed grasp of the cancerogenic functions of CLIC5 in a variety of malignancies. CLIC5 participated in immunomodulation and performed a crucial function in the tumor microenvironment.

Small-scale variants and large deletions in BRCA1/2 genes in Slovak high-grade serous ovarian cancer.

The role of PARP inhibitors is to prevent the polymerase from repairing the single-strand break that occurred due to tumor growth and thus induce cell apoptosis when the homologous recombination deficiency (HRD) system is disabled. The eliminated system can be monitored especially in patients with serous ovarian epithelial tumors. Current studies still show the highest progression-free survival (PFS) in the examined groups with BRCA mutant status, even though they are also effective in the case of a disrupted HRD system, apart from BRCA genes. The study cohort consists of women diagnosed with high-grade serous ovarian cancer (HGSOC), after at least two lines of chemotherapy and after relapse of the disease, as determined by ESMO standards and guidelines. The commercially available tool SOPHIA DDM™ (SophiaGenetics, Switzerland) was used to classify the variants after sequencing. The most common variants (pathogenic or likely pathogenic) were in BRCA1 c.1067A>G (rs1799950) and c.5266dupC (rs80357906) and in BRCA2 c.9976A>T (rs11571833). Large deletions were detected in one and three cases in the BRCA1 and BRCA2 genes, respectively. A mutation in the BRCA1/2 genes was confirmed in 50% of the examined patients. In the study, we focused on the identification of mutated BRCA genes by a commercially available Sophia DDM™ system to identify a pathogenic or probable pathogenic variant in a cohort of patients with HGSOC in the Slovak population, which could result in better management and stratification of the individual.

Clinicopathological and Survival Characteristics of Mismatch Repair Status and PD-1 Expression in Serous Ovarian Cancer.

To evaluate the clinicopathological characteristics of mismatch repair (MMR) deficiency and its clinical outcomes by performing immunohistochemistry (IHC) for MMR genes in the serous ovarian cancer (SOC) tumour sections. A retrospective case-control study. Place and Duration of the Study: Gynecology Department of Kanuni Sultan Süleyman Training and Research Hospital, and Department of Medical Oncology of Medipol University, between March 2001 and January 2020. IHC was carried out for MLH1, MSH2, MSH6, and PMS2 on full-section slides from 127 SOCs to evaluate the MMR status. MMR-negative and MMR-low groups together were defined as MMR deficient and called microsatellite instability-high (MSI-H). The MSI status and expression of programmed cell death-1 (PD-1) were compared in SOCs with different MMR statuses. A significantly higher frequency of MMR-deficient SOCs was diagnosed at early stages compared with the patients in the MSS group (38.6% and 20.6%, respectively, p=0.022). The frequency of cases with PD-1 expression was significantly higher in the MSI-H group (76.2%) than in the MSS counterparts (58.8%, p=0.028). Patients in the MSI-H group had significantly longer DFS (25.6 months) and OS (not reached) than those in the MSS group (16 months and 48.9 months, p=0.039 and p=0.026, respectively). MSI-H SOCs were diagnosed at an earlier stage as compared to MMR proficient cases. The presence of PD-1 expression was significantly higher in cases presenting MMR deficiency compared with MMR-proficient cases. MSI status was significantly associated with DFS and OS. Serous ovarian cancer, Microsatellite instability, Mismatch repair deficiency.

Comprehensive Analysis Identifies the PPAR-Targeted Genes Associated with Ovarian Cancer Prognosis and Tumor Microenvironment.

There is a significant role for peroxisome proliferator-activated receptors (PPARs) in the development of cancer. Nevertheless, the role of PPARs-related genes in ovarian cancer (OC) remains unclear. The open-accessed data used for analysis were downloaded from The Cancer Genome Atlas database, which was analyzed using the R software. In our study, we comprehensively investigated the PPAR target genes in OC, including their biological role. Meanwhile, a prognosis signature consisting of eight PPAR target genes was established, including apolipoprotein A-V, UDP glucuronosyltransferase 2 family, polypeptide B4, TSC22 domain family, member 1, growth hormone inducible transmembrane protein, renin, dedicator of cytokinesis 4, enoyl CoA hydratase 1, peroxisomal (ECH1), and angiopoietin-like 4, which showed a good prediction efficiency. A nomogram was constructed by combining the clinical feature and risk score. Immune infiltration and biological enrichment analysis were applied to investigate the difference between high- and low-risk patients. Immunotherapy analysis indicated that low-risk patients might respond better to immunotherapy. Drug sensitivity analysis indicated that high-risk patients might respond better to bleomycin, nilotinib, pazopanib, pyrimethamine, and vinorelbine, yet worse to cisplatin and gefitinib. Furthermore, the gene ECH1 was selected for further analysis. Our study identified a prognosis signature that could effectively indicates patients survival. Meanwhile, our study can provide the direction for future studies focused on the PPARs in OC.

Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm.

As an innate immune system effector, natural killer cells (NK cells) play a significant role in tumor immunotherapy response and clinical outcomes. In our investigation, we collected ovarian cancer samples from TCGA and GEO cohorts, and a total of 1793 samples were included. In addition, four high-grade serous ovarian cancer scRNA-seq data were included for screening NK cell marker genes. Weighted gene coexpression network analysis (WGCNA) identified core modules and central genes associated with NK cells. The "TIMER," "CIBERSORT," "MCPcounter," "xCell," and "EPIC" algorithms were performed to predict the infiltration characteristics of different immune cell types in each sample. The LASSO-COX algorithm was employed to build risk models to predict prognosis. Finally, drug sensitivity screening was performed. We first scored the NK cell infiltration of each sample and found that the level of NK cell infiltration affected the clinical outcome of ovarian cancer patients. Therefore, we analyzed four high-grade serous ovarian cancer scRNA-seq data, screening NK cell marker genes at the single-cell level. The WGCNA algorithm screens NK cell marker genes based on bulk RNA transcriptome patterns. Finally, a total of 42 NK cell marker genes were included in our investigation. Among which, 14 NK cell marker genes were then used to develop a 14-gene prognostic model for the meta-GPL570 cohort, dividing patients into high-risk and low-risk subgroups. The predictive performance of this model has been well-verified in different external cohorts. Tumor immune microenvironment analysis showed that the high-risk score of the prognostic model was positively correlated with M2 macrophages, cancer-associated fibroblast, hematopoietic stem cell, stromal score, and negatively correlated with NK cell, cytotoxicity score, B cell, and T cell CD4+Th1. In addition, we found that bleomycin, cisplatin, docetaxel, doxorubicin, gemcitabine, and etoposide were more effective in the high-risk group, while paclitaxel had a better therapeutic effect on patients in the low-risk group. By utilizing NK cell marker genes in our investigation, we developed a new feature that is capable of predicting patients' clinical outcomes and treatment strategies.

SPTBN2 regulates endometroid ovarian cancer cell proliferation, invasion and migration via ITGB4‑mediated focal adhesion and ECM receptor signalling pathway.

Ovarian cancer is as a major contributor to gynaecologic death globally. The present study aimed to investigate the regulatory role of spectrin β non-erythrocytic 2 gene (SPTBN2) in endometroid ovarian cancer and its mechanism of action. According to the Gene Expression Profiling Interactive Analysis (GEPIA) database, SPTBN2 expression is elevated in ovarian cancer tissues and higher SPTBN2 expression indicated a worse prognosis. The present study assessed SPTBN2 mRNA and protein expression levels by reverse transcription-quantitative PCR and western blotting, respectively. Cell viability, proliferation, migration and invasion were assessed with Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine incorporation, wound healing and Transwell assays, respectively. SPTBN2 expression was notably enhanced in ovarian cancer cell lines, especially in A2780 cells compared with HOSEPiC cells (P<0.001). Following transfection with small interfering (si)RNA targeting SPTBN2, the viability, proliferation, migration and invasion of A2780 cells were decreased compared with those of A2780 cells transfected with siRNA-NC (P<0.001). Gene Set Enrichment Analysis database revealed that SPTBN2 was primarily enriched in 'focal adhesion' and 'extracellular matrix (ECM)-receptor interaction', whereas SPTBN2 was significantly associated with integrin β4 (ITGB4) in the GEPIA database. In addition, rescue experiments were performed to determine the mechanism of SPTBN2 in endometroid ovarian cancer. ITGB4 overexpression reversed the inhibitory effects of the SPTBN2 knockdown on viability, proliferation, migration and invasion of A2780 cells (P<0.05). The impacts of SPTBN2 on the expression of focal adhesion and downstream ECM receptor signalling-related proteins, including Src and p-FAK/FAK, were significantly reversed by ITGB4 overexpression (P<0.01). Collectively, SPTBN2 may regulate endometroid ovarian cancer cell proliferation, invasion and migration through the ITGB4-mediated focal adhesion and ECM receptor signalling pathway.

Screening and Identification of a Prognostic Model of Ovarian Cancer by Combination of Transcriptomic and Proteomic Data.

The integration of transcriptome and proteome analysis can lead to the discovery of a myriad of biological insights into ovarian cancer. Proteome, clinical, and transcriptome data about ovarian cancer were downloaded from TCGA's database. A LASSO-Cox regression was used to uncover prognostic-related proteins and develop a new protein prognostic signature for patients with ovarian cancer to predict their prognosis. Patients were brought together in subgroups using a consensus clustering analysis of prognostic-related proteins. To further investigate the role of proteins and protein-coding genes in ovarian cancer, additional analyses were performed using multiple online databases (HPA, Sangerbox, TIMER, cBioPortal, TISCH, and CancerSEA). The final resulting prognosis factors consisted of seven protective factors (P38MAPK, RAB11, FOXO3A, AR, BETACATENIN, Sox2, and IGFRb) and two risk factors (AKT_pS473 and ERCC5), which can be used to construct a prognosis-related protein model. A significant difference in overall survival (OS), disease-free interval (DFI), disease-specific survival (DSS), and progression-free interval (PFI) curves were found in the training, testing, and whole sets when analyzing the protein-based risk score (p < 0.05). We also illustrated a wide range of functions, immune checkpoints, and tumor-infiltrating immune cells in prognosis-related protein signatures. Additionally, the protein-coding genes were significantly correlated with each other. EMTAB8107 and GSE154600 single-cell data revealed that the genes were highly expressed. Furthermore, the genes were related to tumor functional states (angiogenesis, invasion, and quiescence). We reported and validated a survivability prediction model for ovarian cancer based on prognostic-related protein signatures. A strong correlation was found between the signatures, tumor-infiltrating immune cells, and immune checkpoints. The protein-coding genes were highly expressed in single-cell RNA and bulk RNA sequencing, correlating with both each other and tumor functional states.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer.

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

Homologous recombination inquiry through ovarian malignancy investigations: JGOG3025 Study.

The Cancer Genome Atlas (TCGA) network has clarified that ~50% of high-grade serous ovarian cancers show homologous recombination deficiency (HRD). However, the frequency of HRD in Japanese patients with ovarian cancer remains unclear. We aimed to identify the frequency of HR-associated gene mutations in Japanese patients with ovarian cancer. The JGOG3025 study is a multicenter collaborative prospective observational study involving 65 study sites throughout Japan. We recruited 996 patients who were clinically diagnosed with ovarian cancer before surgery from March 2017 to March 2019, and 701 patients were eligible according to the criteria. We used frozen tumor tissues to extract DNA and performed next-generation sequencing for 51 targeted genes (including 29 HR-associated genes) in 701 ovarian cancers (298 high-grade serous cases, 189 clear cell cases, 135 endometrioid cases, 12 mucinous cases, 3 low-grade serous cases, and 64 others). HRD was defined as positive when at least one HR-associated gene was mutated. The frequencies of HRD and tumor BRCA1/2 mutations were 45.2% (317/701) and 18.5% (130/701), respectively, in the full analysis set. Next, we performed multivariate Cox proportional hazards regression analysis for progression-free survival (PFS) and overall survival (OS). Advanced-stage ovarian cancer patients with HRD had adjusted hazard ratios of 0.72 (95% CI, 0.55-0.94) and 0.57 (95% CI, 0.38-0.86) for PFS and OS, respectively, compared with those without HRD (p=0.016 and 0.007). Our study demonstrated that mutations in HR-associated genes were associated with prognosis. Further studies are needed to investigate the prognostic impact of each HR-associated gene in ovarian cancer.

Abstract 4258: Racial and ethnic differences in the mutational landscape of low-grade serous ovarian cancer

Abstract Objective To characterize the mutational landscape of low grade serous ovarian cancer (LGSOC) with racial/ethnic stratification. Methods The AACR Project GENIE database version 12.0 was queried via cBioPortal (http://genie.cbioportal.org) for low-grade serous ovarian cancer (LGSOC) samples. This is a publicly available, de-identified, multi-institutional database of next-generation sequencing genomic profiling results for tumor samples. Mutation frequencies for 9 homologous recombination deficiency (HRD) genes, 4 MAP-Kinase (MAP-K) pathway genes and 6 mismatch-repair (MMR) deficiency genes were reported and compared between racial/ethnic groups using chi-squared or Fischer’s exact tests. The threshold used for statistical significance was a two-sided alpha of 0.05. Results Among 317 tumor samples of LGSOC, there were high rates of MAP-K pathway gene mutations but low rates of HRD, MMR and TP53 gene mutations (Table 1). Non-Hispanic Black patients had significantly higher rates of KRAS mutations compared to non-Hispanic White patients (6/7, 86% vs 48/178, 27%, p&amp;lt;0.01). There was no difference in KRAS mutation frequency among Asian (6/17, 35%), Hispanic (7/24, 29%) and Native American (2/2, 100%) patients when compared to non-Hispanic White patients. BRAF mutations were less common compared to KRAS mutations (32/317, 10%), with no racial/ethnic differences in mutation frequency. Conclusion High rates of MAP-K pathway mutations in LGSOC support development and trials of drugs targeting this pathway, such as MEK protein inhibitors. Furthermore, prior literature has demonstrated the prognostic advantage of KRAS and BRAF mutations in LGSOC as well as the association of KRAS mutations with progression of serous borderline tumors to LGSOC. These racial/ethnic differences in frequencies of these mutations are thus hypothesis generating for clinical research to evaluate the impact of race/ethnicity on the development and prognosis of this rare ovarian cancer. Mutation frequencies of HR, MAP-kinase, MMR and TP53 genes in low-grade serous ovarian cancer Gene No. of samples with ≥1 mutation No. of samples profiled for mutation Mutation frequency BRCA1 3 287 1.05 BRCA2 7 287 2.44 BRIP1 5 271 1.85 CHEK2 2 278 0.72 BARD1 2 239 0.84 RAD51B - - - RAD51C - - - RAD51D 2 246 0.81 PALB2 2 279 0.72 KRAS 93 317 29.34 NRAS 29 317 9.15 BRAF 32 317 10.09 EIF1AX 14 144 9.72 MSH2 3 275 1.09 MSH3 1 113 0.88 MSH6 6 286 2.10 MLH1 1 317 0.32 MLH3 3 96 3.13 PMS2 1 270 0.37 TP53 12 317 3.79 Citation Format: Muhammad Danyal Ahsan, Emily M. Webster, Sarah R. Levi, Natalie T. Nguyen, Juan R. Cubillos-Ruiz, Evelyn Cantillo, Eloise Chapman-Davis, Melissa K. Frey, Kevin Holcomb. Racial and ethnic differences in the mutational landscape of low-grade serous ovarian cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4258.

Universal genetic testing for women with newly diagnosed breast cancer in the context of multidisciplinary team care.

To determine the feasibility of universal genetic testing of women with newly diagnosed breast cancer, to estimate the incidence of pathogenic gene variants and their impact on patient management, and to evaluate patient and clinician acceptance of universal testing. Prospective study of women with invasive or high grade in situ breast cancer and unknown germline status discussed at the Parkville Breast Service (Melbourne) multidisciplinary team meeting. Women were recruited to the pilot (12 June 2020 - 22 March 2021) and expansion phases (17 October 2021 - 8 November 2022) of the Mutational Assessment of newly diagnosed breast cancer using Germline and tumour genomICs (MAGIC) study. Germline testing by DNA sequencing, filtered for nineteen hereditary breast and ovarian cancer genes that could be classified as actionable; only pathogenic variants were reported. Surveys before and after genetic testing assessed pilot phase participants' perceptions of genetic testing, and psychological distress and cancer-specific worry. A separate survey assessed clinicians' views on universal testing. Pathogenic germline variants were identified in 31 of 474 expanded study phase participants (6.5%), including 28 of 429 women with invasive breast cancer (6.5%). Eighteen of the 31 did not meet current genetic testing eligibility guidelines (probability of a germline pathogenic variant ≥ 10%, based on CanRisk, or Manchester score ≥ 15). Clinical management was changed for 24 of 31 women after identification of a pathogenic variant. Including 68 further women who underwent genetic testing outside the study, 44 of 542 women carried pathogenic variants (8.1%). Acceptance of universal testing was high among both patients (90 of 103, 87%) and clinicians; no decision regret or adverse impact on psychological distress or cancer-specific worry were reported. Universal genetic testing following the diagnosis of breast cancer detects clinically significant germline pathogenic variants that might otherwise be missed because of testing guidelines. Routine testing and reporting of pathogenic variants is feasible and acceptable for both patients and clinicians.

SpiderLearner: An ensemble approach to Gaussian graphical model estimation.

Gaussian graphical models (GGMs) are a popular form of network model in which nodes represent features in multivariate normal data and edges reflect conditional dependencies between these features. GGM estimation is an active area of research. Currently available tools for GGM estimation require investigators to make several choices regarding algorithms, scoring criteria, and tuning parameters. An estimated GGM may be highly sensitive to these choices, and the accuracy of each method can vary based on structural characteristics of the network such as topology, degree distribution, and density. Because these characteristics are a priori unknown, it is not straightforward to establish universal guidelines for choosing a GGM estimation method. We address this problem by introducing SpiderLearner, an ensemble method that constructs a consensus network from multiple estimated GGMs. Given a set of candidate methods, SpiderLearner estimates the optimal convex combination of results from each method using a likelihood-based loss function. -fold cross-validation is applied in this process, reducing the risk of overfitting. In simulations, SpiderLearner performs better than or comparably to the best candidate methods according to a variety of metrics, including relative Frobenius norm and out-of-sample likelihood. We apply SpiderLearner to publicly available ovarian cancer gene expression data including 2013 participants from 13 diverse studies, demonstrating our tool's potential to identify biomarkers of complex disease. SpiderLearner is implemented as flexible, extensible, open-source code in the R package ensembleGGM at https://github.com/katehoffshutta/ensembleGGM.

Assessment of pathogenic variation in gynecologic cancer genes in a national cohort

Population-based estimates of pathogenic variation burden in gynecologic cancer predisposition genes are a prerequisite for the development of effective precision public health strategies. This study aims to reveal the burden of pathogenic variants in a comprehensive set of clinically relevant breast, ovarian, and endometrial cancer genes in a large population-based study. We performed a rigorous manual classification procedure to identify pathogenic variants in a panel of 17 gynecologic cancer predisposition genes in a cohort of 7091 individuals, representing 0.35% of the general population. The population burden of pathogenic variants in hereditary gynecologic cancer-related genes in our study was 2.14%. Pathogenic variants in genes ATM, BRCA1, and CDH1 are significantly enriched and the burden of pathogenic variants in CHEK2 is decreased in our population compared to the control population. We have identified a high burden of pathogenic variants in several gynecologic cancer-related genes in the Slovenian population, most importantly in the BRCA1 gene.

Epigenetic reactivation of PEG3 by EZH2 inhibitors suppresses renal clear cell carcinoma progress

PEG3 is a paternally imprinted gene located on chromosome 19q13.4 and one of the most common low-expression genes in human ovarian cancer. PEG3 plays an important role in p53-related cell death. However, whether PEG3 plays a role in renal clear cell carcinoma (ccRCC) remains unclear. Here, we found that PEG3 was epigenetic inactivated and played a tumor suppressor role in ccRCC. Overexpression of PEG3 inhibited ccRCC cell proliferation and colony formation, while removal of PEG3 significantly promoted cell proliferation in vitro and tumor formation in nude mice in vivo. EZH2-mediated H3K27me3 at the PEG3 promoter suppressed PEG3 expression. EZH2 specific inhibitors promote PEG3 transcriptional expression through the transition from H3K27me3 to H3K27ac at the PEG3 promoter region. Depletion of PEG3 inhibited the activation of the p53 signaling pathway, resulting in the resistance of ccRCC to EZH2 inhibitors treatment. Thus, our data show that EZH2-mediated epigenetic inactivation of PEG3 promotes the progress of ccRCC, and reactivation of PEG3 may be a promising strategy for ccRCC.

Analysis of BRCA1 and BRCA2 alternative splicing in predisposition to ovarian cancer

BackgroundThe mRNA splicing is regulated on multiple levels, resulting in the proper distribution of genes' transcripts in each cell and maintaining cell homeostasis. At the same time, the expression of alternative transcripts can change in response to underlying genetic variants, often missed during routine diagnostics. AimThe main aim of this study was to define the frequency of aberrant splicing in BRCA1 and BRCA2 genes in blood RNA extracted from ovarian cancer patients who were previously found negative for the presence of pathogenic alterations in the 25 most commonly analysed ovarian cancer genes, including BRCA1 and BRCA2. Material and methodsFrequency and spectrum of splicing alterations in BRCA1 and BRCA2 genes were analysed in blood RNA from 101 ovarian cancer patients and healthy controls (80 healthy women) using PCR followed by gel electrophoresis and Sanger sequencing. The expression of splicing events was examined using RT-qPCR. ResultsWe did not identify any novel, potentially pathogenic splicing alterations. Nevertheless, we detected six naturally occurring transcripts, named BRCA1ΔE9-10, BRCA1ΔE11, BRCA1ΔE11q, and BRCA2ΔE3, BRCA2ΔE12 and BRCA2ΔE17-18 of which three (BRCA1ΔE11q, BRCA1ΔE11 and BRCA2ΔE3) were significantly higher expressed in the ovarian cancer cohort than in healthy controls (p ≤ 0.0001). ConclusionsThis observation indicates that the upregulation of selected naturally occurring transcripts can be stimulated by non-genetic mechanisms and be a potential systemic response to disease progression and/or treatment. However, this hypothesis requires further examination.