Ovarian Cancer Gene Research Articles

Diagnostic, prognostic, and immunological roles of CDSN in ovarian cancer

Globally, ovarian cancer (OC) ranks as a principal cause of cancer-related mortality in females. Immunotherapy has revolutionized the treatment of OC, but the efficacy of immunotherapy is often limited by different immune microenvironments. The objective of this research was to pinpoint and validate candidate genes with potential value as diagnostic and prognostic biomarkers and therapeutic targets in OC. Data on genes associated with gene mutation, prognostic survival, and immune infiltration in OC were procured from the Cancer Genome Atlas (TCGA). Gene differential analysis, mutation site analysis, prognosis and survival analysis, and functional and signaling pathway enrichment analysis were conducted to identify and evaluate key genes. The genes were further investigated using immune infiltration analysis, receiver operating characteristic curves, and immunohistochemistry. The impact of CDSN on OC cell proliferation was investigated utilizing CCK-8, colony formation, and apoptosis detection assays. We identified a set of genes (CDSN, WARS, and CD38) that were highly expressed in OC and significantly associated with mutations and prognosis. Immune infiltration analysis and immunohistochemistry results indicated a correlation with immune infiltration in the tumor microenvironment, particularly in antigen-presenting cells. Receiver operating characteristic curve analysis demonstrated the diagnostic potential of these three genes in OC, with all three genes showing the area under the curve (AUC) above 0.8. In vitro studies suggested that knocked down CDSN expression resulted in a marked lower in the proliferative capacity of OC cells. The candidate gene CDSN identified through bioinformatics analysis and in vitro experiments is associated with mutation and immune infiltration, showing promise as a diagnostic and prognostic biomarker, as well as a therapeutic objective in OC.

Mutation spectra of the BRCA1/2 genes in human breast and ovarian cancer and germline.

Annotating genomic sequence alterations is sometimes a difficult decision, particularly in missense variants with uncertain pathogenic significance and also in those presumed as germline pathogenic variants. We here suggest that mutation spectrum may also be useful for judging them. From the public databases, 982 BRCA1/1861 BRCA2 germline missense variants and 294 BRCA1/420 BRCA2 somatic missense variants were obtained. We then compared their mutation spectra, i.e., the frequencies of two transition- and four transversion-type mutations, in each category. Intriguingly, in BRCA1 variants, A:T to C:G transversion, which was relatively frequent in the germline, was extremely rare in somatic, particularly breast cancer, cells (p = .03). Conversely, A:T to T:A transversion was most infrequent in the germline, but not rare in somatic cells. Thus, BRCA1 variants with A:T to T:A transversion may be suspected as somatic, and those with A:T to C:G as being in the germline. These tendencies of mutation spectrum may also suggest the biological and chemical origins of the base alterations. On the other hand, unfortunately, variants of uncertain significance (VUS) were not distinguishable by mutation spectrum. Our findings warrant further and more detailed studies.

An analysis of likely germline events by tumor tissue testing on large somatic panels.

e22524 Background: The increase in large panel testing has facilitated the detection of numerous events, including those in genes associated with inherited cancer. Further, large panel sequencing may uncover variants in these genes in non-inherited cancers. Hence the frequency of pathogenic/likely pathogenic (P/LP) events in some common germline genes was studied across cancers in the Indian population. Methods: A statistical model was used to derive a method to label variants as likely germline. Variants in hereditary breast and ovarian cancer (HBOC) and mismatch repair (MMR) genes from 1553 cases sequenced at our referral laboratory on the TruSight Oncology 500 panel (TSO500) were analyzed for their variant allele frequency (VAF) distribution. A 3 component Gaussian mixture model (intended to separate somatic, germline heterozygous, homozygous variants) was fit to this VAF distribution and a cutoff was determined such that the area under the curve of the somatic component above the cutoff was below 0.01. This gave a threshold value of 40% VAF for determining likely germline variants (LGVs). Data from 1713 TSO500 cases was then analyzed to identify LGVs. Results: The dataset of 1713 cases comprised 20.67% NSCLC, 12.61% breast, 12.49% ovarian and 10.5% colorectal cancer and < 10% of other cancer types including 2.39% pancreatic and 2.04% prostate cancer. 23.8% of ovarian, 17.14% of prostate, 12.5% of breast and 12.2% of pancreatic cancer cases had variants in BRCA1/BRCA2. Among these, 18.69% of ovarian, 17.14% of prostate, 8.33% of breast and 7.32% of pancreatic cancers had LGVs. LGVs in BRCA1/2 were also found in 3.33% of colorectal and 1.13% of NSCLC. The BRCA1/BRCA2 LGV ratio was found to be 3.0 in ovarian, 1.0 in breast and 2.0 in pancreatic but 0.2 in prostate and colorectal and 0.33 in NSCLC cancer. Adding other HBOC genes (ATM, BRCA1/2, BRIP1, CHEK2, PALB2, RAD51C, RAD51D) increased the LGV frequency to 22.43% of ovarian, 22.86% of prostate, 11.11% of breast, 9.76% of pancreatic, 4.44% of colorectal and 2.26% of NSCLC. MMR gene LGVs were seen in 1.23% of all cancers mainly in 10.71% of endometrial and 4.44% of colorectal cancers. Unlike the HBOC genes, MMR gene variants were not observed across multiple cancers and did not show a predominantly germline distribution (somatic/LGV 1:1). In contrast, the background P/LP frequency calculated from gnomAD v4 South Asian data (excluding those with conflicting labels) was 0.74% for BRCA1/2, 1.82% for the extended HBOC list and 0.5% for the MMR genes. Conclusions: Somatic testing was used to identify LGVs and determine the frequencies of HBOC and MMR genes in cancers in the Indian population. Somatic testing also identified LGVs in multiple tissues at frequencies above the background P/LP frequency for this population, suggesting a possible role for these genes in other cancers. This information underscores the need for further study and may be useful to define a clinically relevant subset of patients.

Incidental Serous Tubal Intraepithelial Carcinoma Finding in a Nepalese Patient Undergoing Opportunistic Salpingectomy and the Discovery of a BRCA1 Pathogenic Variant

BACKGROUND: Serous tubal intraepithelial carcinoma lesions are the precursor to high-grade serous ovarian carcinomas, which have the highest mortality rate among gynecologic malignancies. In women diagnosed with high-grade serous ovarian carcinoma, 20% of the carcinomas are found to be secondary to hereditary causes, with the majority being associated with germline pathogenic variants in BRCA1 and BRCA2 genes. Patients with a pathogenic variant are at high risk for developing high-grade serous ovarian carcinoma, so it is recommended that they undergo risk-reducing salpingo-oophorectomy in their 30s–40s. Opportunistic salpingectomy is the only ovarian cancer prevention method available for patients at average risk. Although serous tubal intraepithelial carcinoma lesions are rare in women at average risk, studies quote incidental serous tubal intraepithelial carcinoma lesion findings in 1–7% of patients undergoing opportunistic salpingectomy. CASE: A 38-year-old woman, gravida 2 para 2, of Nepalese ethnicity had an incidental finding of a serous tubal intraepithelial carcinoma lesion at the time of opportunistic salpingectomy for permanent sterilization at cesarean delivery. The serous tubal intraepithelial carcinoma lesion was found with representative sampling of the fallopian tubes because the patient was considered to be at average risk for ovarian cancer. This method is much less sensitive than the Sectioning and Extensively Examining the Fimbriated End (SEE-FIM) protocol, which is used with women known to be at high risk. This ultimately led to discovery of a BRCA1 mutation in the patient. CONCLUSION: The SEE-FIM protocol is used to identify serous tubal intraepithelial carcinoma lesions, but it is not routinely used on fallopian tubes of patients at average risk. Using the SEE-FIM protocol would lead to fewer missed serous tubal intraepithelial carcinoma lesions, but it is unclear how much extra cost and effort would be required to implement this protocol. There are knowledge gaps when it comes to understudied populations and hereditary breast and ovarian cancer gene prevalence. Studies show that current BRCA prediction models underestimate hereditary breast and ovarian cancer gene prevalence in Asian populations. Diagnosing serous tubal intraepithelial carcinoma lesions in understudied populations could lead to the discovery of a hereditary breast and ovarian cancer pathogenic variant that the patient may not have discovered until after a cancer diagnosis. Identification of a serous tubal intraepithelial carcinoma in a patient at average risk should lead to a referral for genetic counseling and screening.

A novel lactylation-related gene signature for effectively distinguishing and predicting the prognosis of ovarian cancer.

Lactylation has been found to regulate several types of biological processes in cancer. However, there is limited research on lactylation-related genes in predicting the prognosis of ovarian cancer (OC). This study aimed to explore the functional roles of lactylation-related genes in OC. Based on TCGA database, we obtained RNA sequencing data and clinical characteristics of patients with OC. Fourteen lactylation-related genes were screened for bioinformatic analysis in OC. Tumor classification of OC was constructed via a consistency cluster analysis. We examined the prognosis, immune-cell infiltration, and immunotherapy in relation to a lactylation-related model for OC. A total of 707 prognostic genes and 14 key lactylation-related genes (SNRPA1, MPHOSPH6, POLDIP3, RB1, AHNAK, MAGOHB, CALM1, EP300, HDAC1, HDAC2, HDAC3, SIRT1, SIRT2, and SIRT3) were identified in TCGA-OC patients. Based on 14 genes involved in lactylation, TCGA-OC patients were split into low-risk (G1) and high-risk (G2) groups. Downregulated differentially expressed genes (DEGs) in the low-risk G1 group were associated with thermogenesis, oxidative phosphorylation, neutrophil extracellular trap formation, and interleukin 17 (IL-17) signaling pathway, whereas upregulated DEGs were associated with proteoglycans in cancer, focal adhesion, Wnt signaling pathway, extracellular matrix (ECM)-receptor interaction, and the adherens junction. The immune activity of the low-risk G1 group was lower than that of the high-risk G2 group. Gemcitabine, bleomycin, and doxorubicin had lower half-maximal inhibitory concentration (IC50) values in the high-risk G2 patients with OC, while cisplatin and paclitaxel had higher IC50 values compared to the low-risk G1 patients. The prognosis of patients with OC was also predicted with the help of an eight-lactylation-related gene prognostic model, comprising SNRPA1, MPHOSPH6, POLDIP3, RB1, HDAC1, CALM1, HDAC2, and SIRT2. The lactylation-related genes are closely related to tumor classification and immunity in patients with OC. There was good prognostic predictive performance for OC based on a lactylation-related signature. Our findings may offer new insights into the diagnosis and treatment of OC.

Analysis of prognostic value of lactate metabolism-related genes in ovarian cancer based on bioinformatics

BackgroundRecent studies have provided evidence supporting the functional role and mechanism of lactate in suppressing anticancer immunity. However, there is no systematic analysis of lactate metabolism-related genes (LMRGs) and ovarian cancer (OV) prognosis.ResultsSix genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) were selected as prognostic genes and a prognostic model was utilized. Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) analyses were further performed and indicated that the prognostic model was effective. Subsequently, the neoplasm_cancer_status and RiskScore were determined as independent prognostic factors, and a nomogram was established with relatively accurate forecasting ability. Additionally, 2 types of immune cells (Central memory CD8 T cell and Immature B cell), 4 types of immune functions (APC co inhibition, DCs, Tfh and Th1 cells), 9 immune checkpoints (BTLA, CTLA4, IDO1, LAG3, VTCN1, CXCL10, CXCL9, IFNG, CD27) and tumor immune dysfunction and exclusion (TIDE) scores were significantly different between risk groups. The expression of 6 genes were verified by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and the expression of 6 genes were higher in the high-grade serous carcinoma (HGSC) samples.ConclusionA prognostic model related to lactate metabolism was established for OV based on six genes (CCL18, CCND1, MXRA5, NRBP2, OLFML2B and THY1) that could provide new insights into therapy.

Mutation characteristics of cancer susceptibility genes in Chinese ovarian cancer patients.

The association between mutations in susceptibility genes and the occurrence of ovarian cancer has been extensively studied. Previous research has primarily concentrated on genes involved in the homologous recombination repair pathway, particularly BRCA1 and BRCA2. However, a wider range of genes related to the DNA damage response pathways has not been fully explored. To investigate the mutation characteristics of cancer susceptibility genes in the Chinese ovarian cancer population and the associations between gene mutations and clinical data, this study initially gathered a total of 1171 Chinese ovarian cancer samples and compiled a dataset of germline mutations in 171 genes. In this study, it was determined that MC1R and PRKDC were high-frequency ovarian cancer susceptibility genes in the Chinese population, exhibiting notable distinctions from those in European and American populations; moreover high-frequency mutation genes, such as MC1R: c.359T>C and PRKDC: c.10681T>A, typically had high-frequency mutation sites. Furthermore, we identified c.8187G>T as a characteristic mutation of BRCA2 in the Chinese population, and the CHEK2 mutation was significantly associated with the early onset of ovarian cancer, while the CDH1 and FAM175A mutations were more prevalent in Northeast China. Additionally, Fanconi anemia pathway-related genes were significantly associated with ovarian carcinogenesis. In summary, this research provided fundamental data support for the optimization of ovarian cancer gene screening policies and the determination of treatment, and contributed to the precise intervention and management of patients.

Promoter Methylation Changes in DNA Damage-Response Genes in Ovarian Cancer and Their Correlation with Prognosis

Promoter Methylation Changes in DNA Damage-Response Genes in Ovarian Cancer and Their Correlation with Prognosis

Expression of Nuclear Division Cycle 80 Complex Genes in Ovarian Cancer and Correlation with the Clinicopathological Features and Survival Outcomes

Expression of Nuclear Division Cycle 80 Complex Genes in Ovarian Cancer and Correlation with the Clinicopathological Features and Survival Outcomes

Exploring the Role of the MUTYH Gene in Breast, Ovarian and Endometrial Cancer.

MUTYH germline monoallelic variants have been detected in a number of patients affected by breast/ovarian cancer or endometrial cancer, suggesting a potential susceptibility role, though their significance remains elusive since the disease mechanism is normally recessive. Hence, the aim of this research was to explore the hypothesis that a second hit could have arisen in the other allele in the tumor tissue. we used Sanger sequencing and immunohistochemistry to search for a second MUTYH variant in the tumoral DNA and to assess protein expression, respectively. we detected one variant of unknown significance, one variant with conflicting interpretation of pathogenicity and three benign/likely benign variants; the MUTYH protein was not detected in the tumor tissue of half of the patients, and in others, its expression was reduced. our results fail to demonstrate that germinal monoallelic MUTYH variants increase cancer risk through a LOH (loss of heterozygosity) mechanism in the somatic tissue; however, the absence or partial loss of the MUTYH protein in many tumors suggests its dysregulation regardless of MUTYH genetic status.

Machine learning developed a fibroblast-related signature for predicting clinical outcome and drug sensitivity in ovarian cancer.

Ovarian cancer (OC) is the leading cause of gynecological cancer death. Cancer-associated fibroblasts (CAF) is involved in wound healing and inflammatory processes, tumor occurrence and progression, and chemotherapy resistance in OC. GSE184880 dataset was used to identify CAF-related genes in OC. CAF-related signature (CRS) was constructed using integrative 10 machine learning methods with the datasets from the Cancer Genome Atlas, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082. The performance of CRS in predicting immunotherapy benefits was verified using 3 immunotherapy datasets (GSE91061, GSE78220, and IMvigor210) and several immune calculating scores. The Lasso + StepCox[forward] method-based predicting model having a highest average C index of 0.69 was referred as the optimal CRS and it had a stable and powerful performance in predicting clinical outcome of OC patients, with the 1-, 3-, and 5-year area under curves were 0.699, 0.708, and 0.767 in the Cancer Genome Atlas cohort. The C index of CRS was higher than that of tumor grade, clinical stage, and many developed signatures. Low CRS score demonstrated lower tumor immune dysfunction and exclusion score, lower immune escape score, higher PD1&CTLA4 immunophenoscore, higher tumor mutation burden score, higher response rate and better prognosis in OC, suggesting a better immunotherapy response. OC patients with low CRS score had a lower half maximal inhibitory concentration value of some drugs (Gemcitabine, Tamoxifen, and Nilotinib, etc) and lower score of some cancer-related hallmarks (Notch signaling, hypoxia, and glycolysis, etc). The current study developed an optimal CRS in OC, which acted as an indicator for the prognosis, stratifying risk and guiding treatment for OC patients.

An Antibody-CRISPR/Cas Conjugate Platform for Target-Specific Delivery and Gene Editing in Cancer.

The CRISPR/Cas system has been introduced as an innovative tool for therapy, however achieving specific delivery to the target has been a major challenge. Here, an antibody-CRISPR/Cas conjugate platform that enables specific delivery and target gene editing in HER2-positive cancer is introduced. The CRISPR/Cas system by replacing specific residues of Cas9 with an unnatural amino acid is engineered, that can be complexed with a nanocarrier and bioorthogonally functionalized with a monoclonal antibody targeting HER2. The resultant antibody-conjugated CRISPR/Cas nanocomplexes can be specifically delivered and induce gene editing in HER2-positive cancer cells in vitro. It is demonstrated that the in vivo delivery of the antibody-CRISPR/Cas nanocomplexes can effectively disrupt the plk1 gene in HER2-positive ovarian cancer, resulting in substantial suppression of tumor growth. The current study presents a useful therapeutic platform for antibody-mediated delivery of CRISPR/Cas for the treatment of various cancers and genetic diseases.

Abstract 6133: Genetic profiling landscape among gynecological and breast cancer patients in the borde city of Tijuana, Mexico: A comprehensive study

Abstract Background: Individuals in Tijuana have been identified as having multicultural and racial diversity. In Baja, California, Mexico, the prevalence and composition of cancer-predisposing germline variants in gynecologic cancers in Tijuana patients have not been evaluated. Aim and Methods: We aimed to evaluate the prevalence of pathogenic variants (PV) using a panel of 84 cancer-predisposing genes in breast, endometrial, and ovarian cancer from the General Hospital of Tijuana during the period of October 2021-October 2023, who were contacted and invited to participate in the evaluation. Pre- and post-test genetic counseling was given, and a questionnaire on personal, gyneco-obstetric, demographic, and lifestyle variables was conducted. Peripheral blood samples were obtained from all patients, and Next-generation sequencing (NGS) was performed on the Illumina commercial platform (Illumina, SD, USA). Variants were classified according to the American College of Medical Genetics and Genomics (ACMG). Data was collected and descriptive statistics was applied to describe the characteristics of the population. Results: A total of 51 patients were included in our cohort; 98.0% (50/51) were females and 2% (1/51) were males. Among study participants (mean age ±standard deviation: 46.1 ± 10.9), 49% reported a personal history of cancer (25/51). Diagnosis of breast cancer was present in 80.3% of the patients (41/51), 9% (5/51) with ovarian cancer, and 3.9% (2/51) with endometrial cancer. Twenty-five percent of participants (13/51) harbor a PV or likely pathogenic (LP) variant distributed among four cancer-risk genes (BRCA1, BRCA2, ATM, and TP53). The distribution by gene in the patients with a PV was: BRCA1 in 61% (8/13), BRCA2 in 23% (3/13), TP53 in 8% (1/13), and ATM in 8% (1/13). Whereas 39.2% (20/51) had variants of uncertain clinical significance in genes with ambiguous or non-well-established risk association for cancer (BARD1, AXIN2, GPC3, NF2, CEBPA, MSH3, ALK, DIS3L2, CDC73, BAP1, RAD51D, NF1, MSH2, BLM, NBN, BRCA2, BARD1, RUNX1, RECQL4, EGFR, PALB2, CASR, and POLD1), and 35.2% (18/51) had negative results for both; PV and VUS. Conclusion: Our findings show a diverse pathogenic variant composition among the recruited individuals of the gynecological cancer population in Tijuana, Mexico, consistent with being a high-risk population for genetic diseases, which warrants further investigation to adequately assess the burden of hereditary cancer and implement appropriate preventative programs. Disparities in access to testing have a significant impact on affected populations, due in part to underrepresentation in surveys of regional cancer etiology and in genomic variant databases. Citation Format: Jorge Alberto Guadarrama-Orozco, Paula Leal-Anaya, Eva Guerrero-Santillan. Genetic profiling landscape among gynecological and breast cancer patients in the borde city of Tijuana, Mexico: A comprehensive study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6133.

Abstract 2003: Chromatin based targeting of a master regulatory complex in estrogen receptor epithelial ovarian cancer

Abstract Ovarian cancer remains a significant contributor to cancer-related mortality in the United States, with low survival rates over the past decades. Hormonal therapies targeting estrogen receptors have shown limited efficacy. To explore mechanism of the inefficacy, our approach involved investigating ESR1 degradation within the higher order chromatin structure formed by Megacomplex. We identified a 1.3MDa Megacomplex containing ESR1, FOXA1 and PITX1, with colocalization at 2,440 genomic positions within the PEO4 cell line. Unlike cytoplasmic ESR1, the nuclear form was degraded minimally by ICI182780 (ICI), moreover, ESR1 incorporated into the Megacomplex macromolecule was least degraded. We hypothesized that this resistance might be due to sequestration within the Megacomplex, thereby preventing ICI from effectively targeting ESR1. Addition of a small molecule inhibitor of active chromatin, JQ1, in combination with ICI effectively enhanced the degradation of ESR1 within Megacomplex. The combination stopped nuclear occupancy of ESR1 and also degraded the cytoplasmic protein, thus breaking the ESR1 signaling circuit responsible for tumor cell proliferation. Pathway enrichment results consistently identified similar gene sets obtained independently for RNA-seq analysis after ESR1 modulation, and ChIP-seq analysis of Megacomplex bound genes. Likewise, proteins enriched within the Megacomplex macromolecule, as revealed from mass-spec analysis, returned similar pathway enrichments, directly implicating Megacomplex in ESR1 ovarian cancer gene regulation. We conclude, ESR1 in Megacomplex is resistant to ICI and sensitized by combining ICI with JQ1. This combined treatment strategy showed inhibition of cell proliferation and viability by uncovering ESR1 within the Megacomplex, thus elucidating a novel drug resistance mechanism. Citation Format: Sushil K. Jaiswal, Kevin Fedkenheuer, Ronak Khamar, Hua Tan, Valer Gotea, Abdel Elkahloun, Christina Annunziata, Laura Elnitski. Chromatin based targeting of a master regulatory complex in estrogen receptor epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2003.

Abstract 5479: Spatially resolved molecular features in the tumor-immune microenvironment of germline BRCA1/2 mutated versus BRCA wild type high grade serous ovarian cancers

Abstract High-grade serous ovarian cancer (HGSC) is the most common and aggressive subtype of epithelial ovarian cancer. Importantly, germline mutations in BRCA1/2 give rise to HGSC. Because most HGSC are diagnosed at stage III/IV, outcomes are poor and more effective therapies are needed. Although immune checkpoint inhibitors show promise for a number of cancer types, efficacy has been variable in HGSC. To help provide new clues to the molecular features of HGSC, we set out to elucidate the tumor microenvironment of HGSC using spatial transcriptomics approaches. Specifically, we applied 10x Genomics Visium Spatial Transcriptomics (ST) technology to 48 samples representing primary HGSC tumors from 24 patients, including 15 BRCA1/2 mutated cases and 9 BRCA non-mutated cases. In addition to individual sample analysis, we normalized data from 64,784 total features across all sections and performed an integrated cluster analysis to get an overall picture of the cellular architecture of HGSC, but to also directly investigate differences in the tumor microenvironment based on BRCA mutation status. The resulting 17 integrated clusters were subjected to molecular annotation using GSEA, ESTIMATE, and CIBERSORTx, which revealed feature clusters representing important cell types defined by marker genes. Analysis of the entire dataset identified a primary tumor cluster defined by the expression of known ovarian cancer genes including WFDC2 and “don’t eat me” marker genes CD24 and CD47. However, the predominant tumor cell population in BRCA mutated cases was marked by the expression of MUC1, EPCAM, CLDN3, and CD24, while BRCA non-mutated tumor cell cluster was marked by EFNA1, ID1, LSR, and CD9. Importantly, both groups revealed the presence of a specialized monocyte derived macrophage cluster defined by the expression of LYZ and genes involved in cholesterol metabolism including APOE and APOC1. These lipid-associated macrophages are M2 polarized and shown to be associated with poor outcome. Additional analyses are underway to determine spatial dependencies of various tumor and immunological cell compartments. These data provide novel insights into the HGSC tumor microenvironment that may influence HGSC’s vulnerability to immunological therapies. Citation Format: Jing Qian, Lynda D. Roman, Rania Bassiouni, Seeta Rajpara, Monica Neuman, Varun Khetan, David W. Craig, Joseph W. Carlson, John D. Carpten. Spatially resolved molecular features in the tumor-immune microenvironment of germline BRCA1/2 mutated versus BRCA wild type high grade serous ovarian cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5479.

Characteristics of germline DNA damage response gene mutations in ovarian cancer in Southwest China

DNA damage response (DDR) pathways are responsible for repairing endogenous or exogenous DNA damage to maintain the stability of the cellular genome, including homologous recombination repair (HRR) pathway, mismatch repair (MMR) pathway, etc. In ovarian cancer, current studies are focused on HRR genes, especially BRCA1/2, and the results show regional and population differences. To characterize germline mutations in DDR genes in ovarian cancer in Southwest China, 432 unselected ovarian cancer patients underwent multi-gene panel testing from October 2016 to October 2020. Overall, deleterious germline mutations in DDR genes were detected in 346 patients (80.1%), and in BRCA1/2 were detected in 126 patients (29.2%). The prevalence of deleterious germline mutations in BRCA2 is higher than in other studies (patients are mainly from Eastern China), and so is the mismatch repair genes. We identified three novel BRCA1/2 mutations, two of which probably deleterious (BRCA1 p.K1622* and BRCA2 p.L2987P). Furthermore, we pointed out that deleterious mutations of FNACD2 and RECQL4 are potential ovarian cancer susceptibility genes and may predispose carriers to ovarian cancer. In conclusion, our study highlights the necessity of comprehensive germline mutation detection of DNA damage response genes in ovarian cancer patients, which is conducive to patient management and genetic counseling.

Machine learning developed a CD8+ exhausted T cells signature for predicting prognosis, immune infiltration and drug sensitivity in ovarian cancer

CD8+ exhausted T cells (CD8+ Tex) played a vital role in the progression and therapeutic response of cancer. However, few studies have fully clarified the characters of CD8+ Tex related genes in ovarian cancer (OC). The CD8+ Tex related prognostic signature (TRPS) was constructed with integrative machine learning procedure including 10 methods using TCGA, GSE14764, GSE26193, GSE26712, GSE63885 and GSE140082 dataset. Several immunotherapy benefits indicators, including Tumor Immune Dysfunction and Exclusion (TIDE) score, immunophenoscore (IPS), TMB score and tumor escape score, were used to explore performance of TRPS in predicting immunotherapy benefits of OC. The TRPS constructed by Enet (alpha = 0.3) method acted as an independent risk factor for OC and showed stable and powerful performance in predicting clinical outcome of patients. The C-index of the TRPS was higher than that of tumor grade, clinical stage, and many developed signatures. Low TRPS score indicated a higher level of CD8+ T cell, B cell, macrophage M1, and NK cells, representing a relative immunoactivated ecosystem in OC. OC patients with low risk score had a higher PD1&CTLA4 immunophenoscore, higher TMB score, lower TIDE score and lower tumor escape score, suggesting a better immunotherapy response. Moreover, higher TRPS score indicated a higher score of cancer-related hallmarks, including angiogenesis, EMT, hypoxia, glycolysis, and notch signaling. Vitro experiment showed that ARL6IP5 was downregulated in OC tissues and inhibited tumor cell proliferation. The current study constructed a novel TRPS for OC, which could serve as an indicator for predicting the prognosis, immune infiltration and immunotherapy benefits for OC patients.

Predictive Value and Therapeutic Significance of Somatic BRCA Mutation in Solid Tumors.

Ten percent of patients with breast cancer, and probably somewhat more in patients with ovarian cancer, have inherited germline DNA mutations in the breast and ovarian cancer genes BRCA1 and BRCA2. In the remaining cases, the disease is caused by acquired somatic genetic and epigenetic alterations. Targeted therapeutic agents, such as poly ADP-ribose polymerases (PARP) inhibitors (PARPi), have emerged in treating cancers associated with germline BRCA mutations since 2014. The first PARPi was FDA-approved initially for ovarian cancer patients with germline BRCA mutations. Deleterious variants in the BRCA1/BRCA2 genes and homologous recombination deficiency status have been strong predictors of response to PARPi in a few solid tumors since then. However, the relevance of somatic BRCA mutations is less clear. Somatic BRCA-mutated tumors might also respond to this new class of therapeutics. Although the related literature is often controversial, recently published case reports and/or randomized studies demonstrated the effectiveness of PARPi in treating patients with somatic BRCA mutations. The aim of this review is to summarize the predictive role of somatic BRCA mutations and to provide further assistance for clinicians with the identification of patients who could potentially benefit from PARPi.

5 signature genes revealed by single-cell profiling identified unique immune subtypes affecting the prognosis of ovarian cancer.

Ovarian cancer (OC) ranks among the most prevalent gynecological malignancies, with surgery, chemotherapy, and immunotherapy constituting primary treatment modalities. However, despite advancements, immunotherapy, particularly immune checkpoint inhibitors, has yielded suboptimal outcomes. The pressing need to identify biomarkers predictive of clinical prognosis underscores our objective. We aim to discern gene signatures and establish prognostic subgroups, specifically in the context of immunotherapy and chemotherapy, guiding clinical decision-making. We used the Tumor Immunotherapy Gene Expression Resource (TIGER) and The Cancer Genome Atlas (TCGA) databases to extract signature genes of prognostic significance. Unsupervised consensus clustering was employed to classify patients based on these signature genes. The Tumor Immune Estimation Resource (TIMER) database, along with the R packages "maftools" and "ESTIMATE" facilitated immune infiltration estimation. Gene set variation analysis (GSVA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were implemented to probe immune-related cell signaling pathways among distinct subtypes. The Tumor Immune Dysfunction and Exclusion (TIDE) database was used to assess immunotherapy effects, while the R package "OncoPredict" evaluated drug sensitivity differences among subtypes. We identified five prognostically influential genes in ovarian cancer: IGFBP7, JCHAIN, CCDC80, VSIG4, and MS4A1. Utilizing these signature genes, we categorized TCGA-OV patients into five clusters, each associated with varying clinical prognoses. Notably, 2 clusters exhibited superior prognoses, accompanied by enhanced immune cell infiltration. KEGG enrichment analysis revealed their heightened enrichment in cellular immunity and immune cell interaction pathways. Given the elevated expression levels of multiple immune checkpoint molecules, these clusters may substantially benefit from immune checkpoint inhibitor therapy. Additionally, chemotherapy sensitivity analysis indicated their favorable responses to first or second-line chemotherapy regimens. We subclustered ovarian cancer patients by 5 signature genes obtained from the Single-cell RNA sequencing (scRNA-seq) dataset, which demonstrated a good typing effect. Patients in the two molecular subtypes showed better survival, higher immune cell infiltration, and higher drug sensitivity. This meticulous typing may help clinicians to quickly assess the prognosis of patients and the response to immunotherapy and chemotherapy.

Anoikis related genes may be novel markers associated with prognosis for ovarian cancer

The aim of this study was to determine the prognostic significance of anoikis related genes (ARGs) in ovarian cancer (OC) and to develop a prognostic signature based on ARG expression. We analyzed cohorts of OC patients and used nonnegative matrix factorization (NMF) for clustering. Single-sample gene-set enrichment analysis (ssGSEA) was employed to quantify immune infiltration. Survival analyses were performed using the Kaplan–Meier method, and differences in survival were determined using the log-rank test. The extent of anoikis modification was quantified using a risk score generated from ARG expression. The analysis of single-cell sequencing data was performed by the Tumor Immune Single Cell Hub (TISCH). Our analyses revealed two distinct patterns of anoikis modification. The risk score was used to evaluate the anoikis modification patterns in individual tumors. Three hub-genes were screened using the LASSO (Least Absolute Shrinkage and Selection Operator) method and patients were classified into different risk groups based on their individual score and the median score. The low-risk subtype was characterized by decreased expression of hub-genes and better overall survival. The risk score, along with patient age and gender, were considered to identify the prognostic signature, which was visualized using a nomogram. Our findings suggest that ARGs may play a novel role in the prognosis of OC. Based on ARG expression, we have developed a prognostic signature for OC that can aid in patient stratification and treatment decision-making. Further studies are needed to validate these results and to explore the underlying mechanisms.