High-grade Serous Ovarian Cancer Research Articles

776P Liquid biopsy for the determination of homologous recombination deficiency in patients with high-grade serous ovarian cancer: Results of the BOVARY-pilot study

776P Liquid biopsy for the determination of homologous recombination deficiency in patients with high-grade serous ovarian cancer: Results of the BOVARY-pilot study

779P Testing unselected women with newly diagnosed high-grade serous ovarian cancer (HGSOC) for germline pathogenic variants (PVs) in mismatch repair (MMR) genes is unnecessary

779P Testing unselected women with newly diagnosed high-grade serous ovarian cancer (HGSOC) for germline pathogenic variants (PVs) in mismatch repair (MMR) genes is unnecessary

Colocalization of Cancer-Associated Biomarkers on Single Extracellular Vesicles for Early Detection of Cancer

Detection of cancer early, when it is most treatable, remains a significant challenge due to the lack of diagnostic methods sufficiently sensitive to detect nascent tumors. Early-stage tumors are small relative to their tissue of origin, heterogeneous, and infrequently manifest in clinical symptoms. Detection of their presence is made more difficult by a lack of abundant tumor-specific indicators (i.e., protein biomarkers, circulating tumor DNA, etc.) that would enable detection using a non-invasive diagnostic assay. To overcome these obstacles, we have developed a liquid biopsy assay that interrogates circulating extracellular vesicles (EVs) to detect tumor-specific biomarkers colocalized on the surface of individual EVs. We demonstrate the technical feasibility of this approach in human cancer cell line-derived EVs where we show strong correlations between assay signal and cell line gene/protein expression for the ovarian cancer-associated biomarkers BST2, FOLR1, and MUC1. Furthermore, we demonstrate that detecting distinct colocalized biomarkers on the surface of EVs significantly improves discrimination performance relative to single biomarker measurements. Using this approach, we observe promising discrimination of high-grade serous ovarian cancer versus benign ovarian masses and healthy women in a proof-of-concept clinical study.

Patient-derived ovarian cancer organoid carries immune microenvironment and blood vessel keeping high response to cisplatin.

Ovarian cancer is high recurrence and mortality malignant tumor. The most common ovarian cancer was High-Grade Serous Ovarian Cancer. However, High-Grade Serous Ovarian Cancer organoid is rare, which organoid with patient immune microenvironment and blood vessels even absence. Here, we report a novel High-Grade Serous Ovarian Cancer organoid system derived from patient ovarian cancer samples. These organoids recapitulate High-Grade Serous Ovarian Cancer organoids' histological and molecular heterogeneity while preserving the critical immune microenvironment and blood vessels, as evidenced by the presence of CD34 + endothelial cells. Whole exome sequencing identifies key mutations (CSMD3, TP53, GABRA6). Organoids show promise in testing cisplatin sensitivity for patients resistant to carboplatin and paclitaxel, with notable responses in cancer proteoglycans and p53 (TP53) signaling, like ACTG/ACTB1/AKT2 genes and BBC3/MDM2/PERP. Integration of immune microenvironment and blood vessels enhances potential for novel therapies like immunotherapies and angiogenesis inhibitors. Our work may provide a new detection system and theoretical basis for ovarian cancer research and individual therapy.

The Impact of Liquid Biopsy in Advanced Ovarian Cancer Care.

Ovarian cancer is the third most common gynaecological cancer and has a very high mortality rate. The cornerstone of treatment is complete debulking surgery plus chemotherapy. Even with treatment, 80% of patients have a recurrence. Circulating tumour DNA (ctDNA) has been shown to be useful in the control and follow-up of some tumours. It could be an option to define complete cytoreduction and for the early diagnosis of recurrence. We aimed to demonstrate the usefulness of ctDNA and cell-free DNA (cfDNA) as a marker of complete cytoreduction and during follow-up in patients with advanced ovarian cancer. We selected 22 women diagnosed with advanced high-grade serous ovarian cancer, of which only 4 had complete records. We detected cfDNA by polymerase chain reaction (PCR), presented as ng/mL, and detected ctDNA with droplet digital PCR (ddPCR). We calculated Pearson correlation coefficients to evaluate correlations among cfDNA, ctDNA, and cancer antigen 125 (CA125), a biomarker. The results obtained in the evaluation of cfDNA and ctDNA and their correlation with tumour markers and the radiology of patients with complete follow-up show disease progression during the disease, stable disease, or signs of recurrence. cfDNA and ctDNA correlated significantly with CA125. Following cfDNA and ctDNA over time indicated a recurrence several months earlier than computed tomography and CA125 changes. An analysis of cfDNA and ctDNA offers a non-invasive clinical tool for monitoring the primary tumour to establish a complete cytoreduction and to diagnose recurrence early.

A lightweight recurrence prediction model for high grade serous ovarian cancer based on hierarchical transformer fusion metadata

High-grade serous ovarian cancer has a high degree of malignancy, and at detection, it is prone to infiltration of surrounding soft tissues, as well as metastasis to the peritoneum and lymph nodes, peritoneal seeding, and distant metastasis. Whether recurrence occurs becomes an important reference for surgical planning and treatment methods for this disease. Current recurrence prediction models do not consider the potential pathological relationships between internal tissues of the entire ovary. They use convolutional neural networks to extract local region features for judgment, but the accuracy is low, and the cost is high. To address this issue, this paper proposes a new lightweight deep learning algorithm model for predicting recurrence of high-grade serous ovarian cancer. The model first uses ghost convolution (Ghost Conv) and coordinate attention (CA) to establish ghost counter residual (SCblock) modules to extract local feature information from images. Then, it captures global information and integrates multi-level information through proposed layered fusion Transformer (STblock) modules to enhance interaction between different layers. The Transformer module unfolds the feature map to compute corresponding region blocks, then folds it back to reduce computational cost. Finally, each STblock module fuses deep and shallow layer depth information and incorporates patient's clinical metadata for recurrence prediction. Experimental results show that compared to the mainstream lightweight mobile visual Transformer (MobileViT) network, the proposed slicer visual Transformer (SlicerViT) network improves accuracy, precision, sensitivity, and F1 score, with only 1/6 of the computational cost and half the parameter count. This research confirms that the proposed algorithm model is more accurate and efficient in predicting recurrence of high-grade serous ovarian cancer. In the future, it can serve as an auxiliary diagnostic technique to improve patient survival rates and facilitate the application of the model in embedded devices.

Constraint-based modelling predicts metabolic signatures of low and high-grade serous ovarian cancer

Ovarian cancer is an aggressive, heterogeneous disease, burdened with late diagnosis and resistance to chemotherapy. Clinical features of ovarian cancer could be explained by investigating its metabolism, and how the regulation of specific pathways links to individual phenotypes. Ovarian cancer is of particular interest for metabolic research due to its heterogeneous nature, with five distinct subtypes having been identified, each of which may display a unique metabolic signature. To elucidate metabolic differences, constraint-based modelling (CBM) represents a powerful technology, inviting the integration of ‘omics’ data, such as transcriptomics. However, many CBM methods have not prioritised accurate growth rate predictions, and there are very few ovarian cancer genome-scale studies. Here, a novel method for CBM has been developed, employing the genome-scale model Human1 and flux balance analysis, enabling the integration of in vitro growth rates, transcriptomics data and media conditions to predict the metabolic behaviour of cells. Using low- and high-grade ovarian cancer, subtype-specific metabolic differences have been predicted, which have been supported by publicly available CRISPR-Cas9 data from the Cancer Cell Line Encyclopaedia and an extensive literature review. Metabolic drivers of aggressive, invasive phenotypes, as well as pathways responsible for increased chemoresistance in low-grade cell lines have been suggested. Experimental gene dependency data has been used to validate areas of the pentose phosphate pathway as essential for low-grade cellular growth, highlighting potential vulnerabilities for this ovarian cancer subtype.

BBOX1 mediates metabolic reprogramming driven by hypoxia and participates in the malignant progress of high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most aggressive type of ovarian cancer that causes great threats to women's health. Therefore, we performed RNA-sequencing technology in clinical samples to explore the molecular mechanisms underlying the progression of HGSOC. We then noticed BBOX1, a kind of 2-oxoglutarate-dependent enzyme that is highly expressed in HGSOC tumor tissues. Functional studies showed that BBOX1 promotes cell survival and growth of HGSOC cells in vitro and in vivo. Overexpression of the wild-type BBOX1 promoted cell proliferation, but the Asn191 and Asn292 mutation (key amino acid for the enzymatic activity of BBOX1) counteracted this effect (P < 0.05), which indicated that the promotion effect of BBOX1 on HGSOC cell proliferation was related to its catalytic activity. Downregulation of BBOX1 reduced the activity of the mTORC1 pathway, and decreased protein expression of IP3R3 and phosphorylation level of S6KThr389. Metabolomics analysis revealed that BBOX1 is implicated in the glucose metabolism, amino acid metabolism, and nucleotide metabolism of HGSOC cells. In addition, inhibition of BBOX1 suppressed HGSOC cell glycolysis and decreased glucose consumption, lactate production, and the expression of key factors in glycolysis. Finally, we found hypoxia induced the expression of BBOX1 in HGSOC cells and confirmed that BBOX1 could be transcriptionally activated by hypoxia-inducible factor-1α, which could directly bind to the BBOX1 promoter. In summary, BBOX1 mediated the metabolic reprogramming driven by hypoxia, and affected cell metabolism through the mTORC1 pathway, thus acting as an oncogene during HGSOC development.

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA.

Drug resistance is the major cause of therapeutic failure in high-grade serous ovarian cancer (HGSOC). Yet, the mechanisms by which tumors evolve to drug resistant states remains largely unknown. To address this, we aimed to exploit clone-specific genomic structural variations by combining scaled single-cell whole genome sequencing with longitudinally collected cell-free DNA (cfDNA), enabling clonal tracking before, during and after treatment. We developed a cfDNA hybrid capture, deep sequencing approach based on leveraging clone-specific structural variants as endogenous barcodes, with orders of magnitude lower error rates than single nucleotide variants in ctDNA (circulating tumor DNA) detection, demonstrated on 19 patients at baseline. We then applied this to monitor and model clonal evolution over several years in ten HGSOC patients treated with systemic therapy from diagnosis through recurrence. We found drug resistance to be polyclonal in most cases, but frequently dominated by a single high-fitness and expanding clone, reducing clonal diversity in the relapsed disease state in most patients. Drug-resistant clones frequently displayed notable genomic features, including high-level amplifications of oncogenes such as CCNE1 , RAB25 , NOTCH3 , and ERBB2 . Using a population genetics Wright-Fisher model, we found evolutionary trajectories of these features were consistent with drug-induced positive selection. In select cases, these alterations impacted selection of secondary lines of therapy with positive patient outcomes. For cases with matched single-cell RNA sequencing data, pre-existing and genomically encoded phenotypic states such as upregulation of EMT and VEGF were linked to drug resistance. Together, our findings indicate that drug resistant states in HGSOC pre-exist at diagnosis and lead to dramatic clonal expansions that alter clonal composition at the time of relapse. We suggest that combining tumor single cell sequencing with cfDNA enables clonal tracking in patients and harbors potential for evolution-informed adaptive treatment decisions.

Palladium(II)-Indenyl Complexes Bearing N-Heterocyclic Carbene (NHC) Ligands as Potent and Selective Metallodrugs toward High-Grade Serous Ovarian Cancer Models.

In this study, we synthesized novel Pd(II)-indenyl complexes using various N-heterocyclic carbene (NHC) ligands, including chelating NHC-picolyl, NHC-thioether, and diNHC ligands, and two monodentate NHCs. Transmetalation reactions between a Pd(II)-indenyl precursor and silver-NHC complexes were generally employed, except for chelating diNHC derivatives, which required direct reaction with bisimidazolium salts and potassium carbonate. Characterization included NMR, HRMS analysis, and single-crystal X-ray diffraction. In vitro on five ovarian cancer cell lines showed notable cytotoxicity, with IC50 values in the micro- and submicromolar range. Some compounds exhibited intriguing selectivity for cancer cells due to higher tumor cell uptake. Mechanistic studies revealed that monodentate NHCs induced mitochondrial damage while chelating ligands caused DNA damage. One chelating NHC-picolyl ligand showed promising cytotoxicity and selectivity in high-grade serous ovarian cancer models, supporting its consideration for preclinical study.

Pathological PCI as a prognostic marker of survival after neoadjuvant chemotherapy in patients undergoing interval cytoreduction with or without HIPEC in FIGO stage IIIC high grade serous ovarian cancer.

To determine the best possible value of pathological PCI (pPCI) as a prognostic marker for survival in high-grade serous epithelial ovarian cancer patients in patients treated with neoadjuvant chemotherapy and interval cytoreductive surgery. All patients with FIGO stage IIIC high-grade serous ovarian carcinoma were included. Receiver operating curves (ROC) were used to determine the best possible score for pPCI in predicting survival. Survival curves were calculated using the Kaplan-Meier test, and factors affecting survival were compared using the log-rank test. From January 2018 to January 2024, 171 patients who underwent interval cytoreductive surgery were included. Complete cytoreduction was achieved in 88% of the patients. ROC curves determined a (pPCI) cut-off value of 8 as the best possible score for predicting survival with a sensitivity of 82% and specificity of 67% (Youden's Index = 0.60). pPCI with a cut-off value of 8 showed improved OS (p = 0.002) and DFS, (p = 0.001) in both univariate and multivariate analyses. Following interval cytoreductive surgery, despite optimal complete cytoreductive surgery, a pathological PCI of 8 is a poor prognostic indicator of survival and may serve as a surrogate clinical marker for guiding clinicians in adjuvant treatment, especially in resource-driven settings in the real world.

Factors associated with an inconclusive result from commercial homologous recombination deficiency testing in ovarian cancer.

Homologous recombination deficiency (HRD) testing is used to determine the appropriateness of poly ADP-ribose polymerase inhibitors for patients with epithelial ovarian cancer and no germline/somatic BRCA1/2 alterations. Myriad MyChoice CDx reports a genomic instability score (GIS) to quantify the level of HRD, with a positive score defined as ≥42. The authors sought to define factors associated with obtaining an inconclusive HRD test result. GIS was retrieved for patients at their institution with epithelial ovarian cancer without germline/somatic BRCA1/2 deleterious alterations who underwent HRD testing from April 2020-August 2023. Clinical data were abstracted from the medical record. Of 477 HRD test results identified, 57 (12%) were inconclusive. High-grade serous ovarian cancers had higher GIS than other histologic types (median 29 vs. 21, p<.001). Most HRD cases were of high-grade serous histology; no cases with clear cell or endometrioid histology were HRD-positive. On univariate analysis, interval versus primary cytoreductive surgery, other specimen sources versus surgical specimens, and chemotherapy exposure were risk factors for inconclusive HRD testing. On multivariable analysis, chemotherapy exposure, and tissue source were associated with an inconclusive test result, with surgical specimens more likely to yield a conclusive result than other sources (biopsy, cytology, other). Age, stage, self-reported race, and histology were not associated with an inconclusive result. Surgical tissue was more likely to yield a conclusive HRD test result versus other sources of epithelial ovarian cancer tissue acquisition. When feasible, laparoscopic biopsy before initiation of neoadjuvant chemotherapy may increase the likelihood of obtaining interpretable HRD test results.

Does an Autoimmune Disorder Following Ovarian Cancer Diagnosis Affect Prognosis?

We investigated whether developing an autoimmune disorder (AID) following a high-grade epithelial ovarian cancer diagnosis improves overall survival. This retrospective study included data from women treated for high-grade serous, endometrioid, or transitional cell ovarian, fallopian tube, or peritoneal cancer FIGO stage III or IV at a Swiss cantonal gynecological cancer center (2008-2023). We used Kaplan-Meier estimates and the Cox proportional hazards model using time-varying covariates for the survival function estimation. In all, 9 of 128 patients developed an AID following a cancer diagnosis. The median time from cancer diagnosis to AID was 2 years (IQR 2-5). These women survived for a median of 3031 days (IQR 1765-3963) versus 972 days (IQR 568-1819) for those who did not develop an AID (p = 0.001). The median overall survival of nine women with a pre-existing AID was 1093 days (IQR 716-1705), similar to those who never had an AID. The multivariate analyses showed older age (p = 0.003, HR 1.04, 95% CI 1.013-1.064) was associated with a poorer prognosis, and developing an AID after a cancer diagnosis was associated with longer survival (p = 0.033, HR 0.113, 95% CI 0.015-0.837). Clinical manifestations of autoimmune disorders following ovarian cancer diagnoses were associated with better overall survival (8 versus 2.7 years), indicating an overactive immune response may improve cancer control.

Frizzled 6 endows high-grade serous ovarian cancer with stem-like properties and chemoresistance.

Stem-like properties contribute to tumor growth, metastasis, and chemoresistance. High-grade serous ovarian cancer (HGSOC) exhibits a very aggressive phenotype characterized by extensive metastasis, rapid progression, and therapy resistance. Frizzled 6 (FZD6) is overexpressed in HGSOC, and higher levels of FZD6 have been associated with shorter survival times in patients with HGSOC. Functionally, FZD6 promotes HGSOC growth and peritoneal metastasis. It endues HGSOC cells with stem-like properties by modulating POU5F1, ALDH1, and EPCAM. It can also desensitize HGSOC cells to certain chemical drugs. As a putative ligand for FZD6, WNT7B is also implicated in cell proliferation, stem-like properties, invasion and migration, and chemoresistance. SMAD7 is a downstream component of FZD6 signaling that is thought to mediate FZD6-associated phenotypes, at least in part. Therefore, FZD6/WNT7B-SMAD7 can be considered a tumor-promoting signaling pathway in HGSOC that may be responsible for tumor growth, peritoneal metastasis, and chemoresistance.

Integrated analysis of spatial transcriptomics and CT phenotypes for unveiling the novel molecular characteristics of recurrent and non-recurrent high-grade serous ovarian cancer

BackgroundHigh-grade serous ovarian cancer (HGSOC), which is known for its heterogeneity, high recurrence rate, and metastasis, is often diagnosed after being dispersed in several sites, with about 80% of patients experiencing recurrence. Despite a better understanding of its metastatic nature, the survival rates of patients with HGSOC remain poor.MethodsOur study utilized spatial transcriptomics (ST) to interpret the tumor microenvironment and computed tomography (CT) to examine spatial characteristics in eight patients with HGSOC divided into recurrent (R) and challenging-to-collect non-recurrent (NR) groups.ResultsBy integrating ST data with public single-cell RNA sequencing data, bulk RNA sequencing data, and CT data, we identified specific cell population enrichments and differentially expressed genes that correlate with CT phenotypes. Importantly, we elucidated that tumor necrosis factor-α signaling via NF-κB, oxidative phosphorylation, G2/M checkpoint, E2F targets, and MYC targets served as an indicator of recurrence (poor prognostic markers), and these pathways were significantly enriched in both the R group and certain CT phenotypes. In addition, we identified numerous prognostic markers indicative of nonrecurrence (good prognostic markers). Downregulated expression of PTGDS was linked to a higher number of seeding sites (≥ 3) in both internal HGSOC samples and public HGSOC TCIA and TCGA samples. Additionally, lower PTGDS expression in the tumor and stromal regions was observed in the R group than in the NR group based on our ST data. Chemotaxis-related markers (CXCL14 and NTN4) and markers associated with immune modulation (DAPL1 and RNASE1) were also found to be good prognostic markers in our ST and radiogenomics analyses.ConclusionsThis study demonstrates the potential of radiogenomics, combining CT and ST, for identifying diagnostic and therapeutic targets for HGSOC, marking a step towards personalized medicine.

MTCH2 promotes the malignant progression of ovarian cancer through the upregulation of AIMP2 expression levels, mitochondrial dysfunction and by mediating energy metabolism.

Ovarian cancer (OC) is a gynecological malignancy that ranks among the most common female cancers worldwide and notably reduces a patient's quality of life. Mitochondrial carrier homology 2 (MTCH2) is a mitochondrial outer membrane protein that serves a regulatory role in mitochondrial metabolism and cell death. The precise contribution and underlying molecular pathways of MTCH2 in the context of OC development is currently unclear. The present study aimed to investigate the roles of MTCH2 in the energy metabolism, cell proliferation and metastatic potential of OC cells and evaluate the regulatory relationship between MTCH2, aminoacyl transfer RNA synthetase-interacting multifunctional protein 2 (AIMP2) and claudin-3. An analysis of 67 patients with high-grade serous OC demonstrated increased expression levels of MTCH2, AIMP2 and claudin-3 in OC tumor tissue samples compared with in corresponding normal tissues adjacent to OC tissue samples. MTCH2 overexpression was significantly associated with the International Federation of Gynecology and Obstetrics stage and tumor differentiation of the OC tumor samples. In vitro experiments using the SK-OV-3 OC cell line demonstrated that MTCH2 exerts a regulatory effect on the cell proliferation, invasion and migratory capabilities of these cells. Knockdown of MTCH2 reduced ATP production, induced mitochondrial dysfunction and promoted cytoskeleton remodeling and apoptosis in SK-OV-3 OC cells. In addition, MTCH2 knockdown downregulated the expression levels of both claudin-3 and AIMP2 proteins. Knockdown of AIMP2 inhibited the regulatory effect of MTCH2. Co-immunoprecipitation experiments demonstrated that MTCH2 interacts with AIMP2 and claudin-3. The present study provides novel insights into the treatment of OC metastasis, as MTCH2 was demonstrated to serve roles in the progression of OC cells through the regulation of claudin-3 via AIMP2, which could provide novel insights into the treatment of ovarian cancer metastasis.

TP53 mutation as predictive factor of platinum response in BRCA-mutated ovarian cancer: A prospective case-series analysis.

128 Background: Platinum sensitivity (PS) is a prerequisite for first-line PARP inhibitors (PARPi) in locally advanced and relapsed high grade serous ovarian cancer (HGS-OC). BRCA mutations are predictive of PS and of response to PARPi. Notably, platinum and PARPi cytotoxic action is mainly related to p53-mediated inducted apoptosis. Therefore, the integrity of p53 machinery is crucial for platinum-related activity whereas the presence of p53 mutation is a fairly frequent event in ovarian cancer, especially in HGS-OC and in BRCA mutated. Methods: We prospectively analyzed 208 women with primary ovarian cancer undergoing surgery at the Department of Gynecologic Oncology, ARNAS G. Brotzu, Cagliari, Italy, between 2019 and 2023. Somatic NGS analysis was performed to detect BRCA and HRD mutations. TP53 mutations were classified according to according to hotspot, structural (missense/nonsense) and functional classification as “gain of function” (GOF) or “loss of function” (LOF), based on IARC TP53 database. Comparative testing with Fisher's exact test was used to examine TP53 mutation distribution and associations with clinicopathologic factors and PS. BRCA mutation status was further used to stratify the analysis. Results: Globally, we included 127 adult HGS-OC patients (pts). 84.2% had stage III-IV disease. TP53 mutation was found in 83.4% of pts. Somatic BRCA mutations were found in 28.3%. HGS-OC with somatic BRCA mutations had higher TP53 mutation frequency (88.8%) than BRCA WT (81.3%, p=0.1510). Employing the structural classification scheme, most harbored a missense TP53 mutation (76.5%). LOF TP53 mutations were found in 59.4% while GOF in 31.2%. No significant disparity was observed in the distribution of specific TP53 mutations within each classification scheme between cases with BRCA mutations and those without. As for BRCA mutated pts, TP53 WT were all PS. Among those p53 mutated, GOF mutations were associated with PS in 7 pts and platinum resistance in 3 pts; LOF mutations were associated with PS in 7 pts and platinum resistance in 12 pts. The difference in distribution of PS between functional categories of p53 mutations was significant (p=0.0291). As for BRCA WT pts, TP53 WT were all PS. Among TP53 mutated, GOF mutations were associated with PS in 14 pts and platinum resistance in 10 pts, whereas LOF mutations were associated with PS in 19 pts and platinum resistance in 25 pts, even if these findings were not statistically significant (p=0.2357). Of relevance, in 5 cases where LOF mutations of p53 was associated with null HIC p53 expression, pts were refractory to platinum-based chemotherapy. Conclusions: Even if preliminary, our data show that HGS-OC harboring TP53 null mutations are the poorest prognostic subgroup, especially in terms of PS. Further studies are needed to confirm our findings and the role of TP53 mutation as a biomarker of inherent or acquired platinum resistance.

High-grade serous ovarian cancer development and anti-PD-1 resistance is driven by IRE1α activity in neutrophils.

High-grade serous ovarian cancer (HGSOC) is an aggressive malignancy that remains refractory to current immunotherapies. While advanced stage disease has been extensively studied, the cellular and molecular mechanisms that promote early immune escape in HGSOC remain largely unexplored. Here we report that primary HGSO tumors program neutrophils to inhibit T cell anti-tumor function by activating the endoplasmic reticulum (ER) stress sensor IRE1α. We found that intratumoral neutrophils exhibited overactivation of ER stress response markers compared with their counterparts at non-tumor sites. Selective deletion of IRE1α in neutrophils delayed primary ovarian tumor growth and extended the survival of mice with HGSOC by enabling early T cell-mediated tumor control. Notably, loss of IRE1α in neutrophils sensitized tumor-bearing mice to PD-1 blockade, inducing HGSOC regression and long-term survival in ∼50% of treated hosts. Hence, neutrophil-intrinsic IRE1α facilitates early adaptive immune escape in HGSOC and targeting this ER stress sensor might be used to unleash endogenous and immunotherapy-elicited immunity that controls metastatic disease.

Amplified Cell Cycle Genes Identified in High-Grade Serous Ovarian Cancer.

The objective of this study was to identify differentially expressed genes and their potential influence on the carcinogenesis of serous-type ovarian cancer tumors. Serous cancer is an epithelial ovarian cancer subtype and is the most common type of ovarian cancer. Transcriptomic profiles of serous cancer and non-cancerous datasets were obtained from the Gene Expression Omnibus (GEO-NCBI). Differentially expressed genes were then derived from those profiles; the identified genes were consistently upregulated in three or more transcriptomic profiles. These genes were considered as the serous ovarian cancer gene set for further study. The serous gene set derived from the transcriptomic profiles was then evaluated for ontological functional analysis using the Molecular Signatures Database. Next, we examined the mutational impact of this serous gene set on the transcriptomic profile of high-grade serous ovarian (HGSO) adenocarcinoma using the cBioPortal database. Results from OncoPrint revealed that 26 genes were amplified in more than 5% of HGSO cancer patients. Interestingly, several of these genes are involved in cell cycle processes, including genes ATPase family AAA domain containing 2 (ATAD2), recQ-like helicase 4 (RECQL4), cyclin E1 (CCNE1), anti-silencing function 1B histone chaperone (ASF1B), ribonuclease H2 subunit A (RNASEH2A), structural maintenance of chromosome 4 (SMC4), cell division cycle associated 20 (CDC20), and cell division cycle associated 8 (CDCA8). The receiver operating characteristic (ROC) curve results also revealed higher specificity and sensitivity for this subtype of tumors. Furthermore, these genes may affect the recurrence of serous ovarian carcinogenesis. Overall, our analytical study identifies cell cycle-related genes that can potentially be targeted as diagnostic and prognostic markers for serous ovarian cancer.

53BP1 loss elicits cGAS-STING-dependent antitumor immunity in ovarian and pancreatic cancer

53BP1 nucleates the anti-end resection machinery at DNA double-strand breaks, thereby countering BRCA1 activity. Loss of 53BP1 leads to DNA end processing and homologous recombination in BRCA1-deficient cells. Consequently, BRCA1-mutant tumors, typically sensitive to PARP inhibitors (PARPi), become resistant in the absence of 53BP1. Here, we demonstrate that the ‘leaky’ DNA end resection in the absence of 53BP1 results in increased micronuclei and cytoplasmic double-stranded DNA, leading to activation of the cGAS-STING pathway and pro-inflammatory signaling. This enhances CD8+ T cell infiltration, activates macrophages and natural killer cells, and impedes tumor growth. Loss of 53BP1 correlates with a response to immune checkpoint blockade (ICB) and improved overall survival. Immunohistochemical assessment of 53BP1 in two malignancies, high grade serous ovarian cancer and pancreatic ductal adenocarcinoma, which are refractory to ICBs, reveals that lower 53BP1 levels correlate with an increased adaptive and innate immune response. Finally, BRCA1-deficient tumors that develop resistance to PARPi due to the loss of 53BP1 are susceptible to ICB. Therefore, we conclude that 53BP1 is critical for tumor immunogenicity and underpins the response to ICB. Our results support including 53BP1 expression as an exploratory biomarker in ICB trials for malignancies typically refractory to immunotherapy.