High-Grade Serous Ovarian Cancer: Basic Sciences, Clinical and Therapeutic Standpoints

Harmonization of homologous recombination deficiency testing in ovarian cancer: Results from the MITO16A/MaNGO-OV2 trial

BACKGROUND

Homologous Recombination Deficiency (HRD) status predicts response to treatment with poly(ADP-ribose) polymerase inhibitors in Ovarian Cancer (OC) patients. The Myriad myChoiceCDx Assay is approved by Food and Drug Agency for the HRD assessment. Here we compared the HRD status obtained by three commercial panels with the results from Myriad reference test.

METHODS

The HRD analysis was performed on DNA from formalin-fixed and paraffin-embedded tumor samples of 100 untreated OC patients for which Myriad assay results were available, using TruSight Oncology 500 HRD assay (Illumina), Oncomine Comprehensive Assay Plus (Thermo Fisher Scientific) and SOPHiA DDM HRD solution panel (SOPHiA Genetics).

RESULTS

A good overall concordance with the reference method was demonstrated at three different levels: BRCA mutational status (from 94.4 % to 97.7 %), the genomic instability value (from 88.2 % to 95.3 %) and for the HRD status (from 90.4 % to 97.6 %). Moreover, a trend in favour of HRD positive patients for response rate, progression-free survival and overall survival similar to Myriad was observed for all three tests.

DISCUSSION

Our data suggest the feasibility of commercial testing for assessing HRD status, with a good concordance with the reference method and association with clinical outcome.

Interplay between altered metabolism and DNA damage and repair in ovarian cancer

Ovarian cancer is the most lethal gynecological malignancy and is often associated with both DNA repair deficiency and extensive metabolic reprogramming. While still emerging, the interplay between these pathways can affect ovarian cancer phenotypes, including therapeutic resistance to the DNA damaging agents that are standard-of-care for this tumor type. In this review, we will discuss what is currently known about cellular metabolic rewiring in ovarian cancer that may impact DNA damage and repair in addition to highlighting how specific DNA repair proteins also promote metabolic changes. We will also discuss relevant data from other cancers that could be used to inform ovarian cancer therapeutic strategies. Changes in the choice of DNA repair mechanism adopted by ovarian cancer are a major factor in promoting therapeutic resistance. Therefore, the impact of metabolic reprogramming on DNA repair mechanisms in ovarian cancer has major clinical implications for targeted combination therapies for the treatment of this devastating disease.

Nucleolar Localization of the RNA Helicase DDX21 Predicts Survival Outcomes in Gynecologic Cancers

Cancer cells with DNA repair defects (e.g., BRCA1/2 mutant cells) are vulnerable to PARP inhibitors (PARPi) due to induction of synthetic lethality. However, recent clinical evidence has shown that PARPi can prevent the growth of some cancers irrespective of their BRCA1/2 status, suggesting alternative mechanisms of action. We previously discovered one such mechanism in breast cancer involving DDX21, an RNA helicase that localizes to the nucleoli of cells and is a target of PARP1. We have now extended this observation in endometrial and ovarian cancers and provided links to patient outcomes. When PARP1-mediated ADPRylation of DDX21 is inhibited by niraparib, DDX21 is mislocalized to the nucleoplasm resulting in decreased rDNA transcription, which leads to a reduction in ribosome biogenesis, protein translation, and ultimately endometrial and ovarian cancer cell growth. High PARP1 expression was associated with high nucleolar localization of DDX21 in both cancers. High nucleolar DDX21 negatively correlated with calculated IC50s for niraparib. By studying endometrial cancer patient samples, we were able to show that high DDX21 nucleolar localization was significantly associated with decreased survival. Our study suggests that the use of PARPi as a cancer therapeutic can be expanded to further types of cancers and that DDX21 localization can potentially be used as a prognostic factor and as a biomarker for response to PARPi.

SIGNIFICANCE

Currently, there are no reliable biomarkers for response to PARPi outside of homologous recombination deficiency. Herein we present a unique potential biomarker, with clear functional understanding of the molecular mechanism by which DDX21 nucleolar localization can predict response to PARPi.

Comprehensive next-generation sequencing identifies novel putative pathogenic or likely pathogenic germline variants in patients with concurrent tubo-ovarian and endometrial serous and endometrioid carcinomas or precursors

BACKGROUND

Endometrial serous carcinoma (ESC) and tubo-ovarian high-grade serous carcinoma (HGSC) are characterized by late-stage presentation and high mortality. Current guidelines for prevention recommend risk-reducing salpingo-oophorectomy (RRSO) in patients with hereditary mutations in cancer susceptibility genes. However, HGSC displays extensive genetic heterogeneity with alterations in 168 genes identified in TCGA study, but current germline testing panels are often limited to the handful of recurrently mutated genes, leaving families with rare hereditary gene mutations potentially at-risk.

OBJECTIVE

To determine if there are rare germline mutations that may aid in early identification of more patients at-risk for ESC and/or HGSC by evaluating patients with concurrent ESC, HGSC or precursor lesions, and endometrial atypical hyperplasia (CAH) or low-grade endometrial endometrioid adenocarcinoma (LGEEA).

METHODS

We performed targeted next-generation sequencing using TSO 500, a 523 gene panel, on formalin-fixed paraffin-embedded tumor and matched benign non-tumor tissue blocks from 5 patients with concurrent ESC, HGSC or precursor lesions, and CAH or LGEEA.

RESULTS

We identified germline pathogenic, likely pathogenic or uncertain significance variants in cancer susceptibility genes in 4 of 5 patients - affected genes included GLI1, PIK3R1, FOXP1, FANCD2, INPP4B and H3F3C. Notably, none of these genes were included in the commercially available germline testing panels initially used to evaluate the patients at the time of their diagnoses.

CONCLUSION

Comprehensive germline testing of patients with concurrent LGEEA or CAH and ESC, HGSC or precursor lesions may aid in early identification of relatives at-risk for cancer who may be candidates for RRSO with hysterectomy.

Multicompartmentalized microvascularized tumor-on-a-chip to study tumor-stroma interactions and drug resistance in ovarian cancer

Introduction

The majority of ovarian cancer (OC) patients receiving standard of care chemotherapy develop chemoresistance within 5 years. The tumor microenvironment (TME) is a dynamic and influential player in disease progression and therapeutic response. However, there is a lack of models that allow us to elucidate the compartmentalized nature of TME in a controllable, yet physiologically relevant manner and its critical role in modulating drug resistance.

Methods

We developed a 3D microvascularized multiniche tumor-on-a-chip formed by five chambers (central cancer chamber, flanked by two lateral stromal chambers and two external circulation chambers) to recapitulate OC-TME compartmentalization and study its influence on drug resistance. Stromal chambers included endothelial cells alone or cocultured with normal fibroblasts or cancer-associated fibroblasts (CAF).

Results

The tumor-on-a-chip recapitulated spatial TME compartmentalization including vessel-like structure, stromal-mediated extracellular matrix (ECM) remodeling, generation of oxygen gradients, and delayed drug diffusion/penetration from the circulation chamber towards the cancer chamber. The cancer chamber mimicked metastasis-like migration and increased drug resistance to carboplatin/paclitaxel treatment in the presence of CAF when compared to normal fibroblasts. CAF-mediated drug resistance was rescued by ECM targeted therapy. Critically, these results demonstrate that cellular crosstalk recreation and spatial organization through compartmentalization are essential to determining the effect of the compartmentalized OC-TME on drug resistance.

Conclusions

Our results present a functionally characterized microvascularized multiniche tumor-on-a-chip able to recapitulate TME compartmentalization influencing drug resistance. This technology holds the potential to guide the design of more effective and targeted therapeutic strategies to overcome chemoresistance in OC.

Evaluation of serum CA125, HE4 and CA724 and the risk of ovarian malignancy algorithm score in the diagnosis of high-grade serous ovarian cancer

AIM

To develop a new algorithm for the detection of high-grade serous ovarian cancer (HGSOC).

METHODS

Patients diagnosed with HGSOC, borderline ovarian tumours (BOTs) or benign ovarian masses (BOMs) were enrolled between February 2019 and December 2020. Patients with BOTs or BOMs were grouped as non-HGSOC. The cases were divided randomly into a training cohort (two-thirds of cases) and a validation cohort (one-third of cases). Logistic regression was used to find risk factors for HGSOC and to create a new algorithm in the training cohort. Receiver operating characteristic curves were used to compare the diagnostic value of tumour biomarkers. Sensitivity and specificity of tumour markers and the new algorithm were calculated in the training cohort and validation cohort.

RESULTS

This study found significant differences in age; BRCA1/2 mutation status; CA125, CA724 and HE4 levels; and Risk of Ovarian Malignancy Algorithm score between the two groups.Logistic regression analysis showed that CA125 and BRCA1/2 were risk factors for HGSOC. A new algorithm combining CA125 and BRCA1/2 increased the specificity of CA125 for diagnosis of HGSOC. The new algorithm had sensitivity of 81.08% and specificity of 93.10% in the training cohort.

CONCLUSION

The new algorithm using CA125 and BRCA1/2 helped to distinguish between patients with HGSOC and patients with non-HGSOC.

Uncovering miRNA-mRNA Regulatory Networks Related to Olaparib Resistance and Resensitization of BRCA2MUT Ovarian Cancer PEO1-OR Cells with the ATR/CHK1 Pathway Inhibitors

Resistance to olaparib is the major obstacle in targeted therapy for ovarian cancer (OC) with poly(ADP-ribose) polymerase inhibitors (PARPis), prompting studies on novel combination therapies to enhance olaparib efficacy. Despite identifying various mechanisms, understanding how OC cells acquire PARPi resistance remains incomplete. This study investigated microRNA (miRNA) expression in olaparib-sensitive (PEO1, PEO4) and previously established olaparib-resistant OC cell lines (PEO1-OR) using high-throughput RT-qPCR and bioinformatic analyses. The role of miRNAs was explored regarding acquired resistance and resensitization with the ATR/CHK1 pathway inhibitors. Differentially expressed miRNAs were used to construct miRNA-mRNA regulatory networks and perform functional enrichment analyses for target genes with miRNet 2.0. TCGA-OV dataset was analyzed to explore the prognostic value of selected miRNAs and target genes in clinical samples. We identified potential processes associated with olaparib resistance, including cell proliferation, migration, cell cycle, and growth factor signaling. Resensitized PEO1-OR cells were enriched in growth factor signaling via PDGF, EGFR, FGFR1, VEGFR2, and TGFβR, regulation of the cell cycle via the G2/M checkpoint, and caspase-mediated apoptosis. Antibody microarray analysis confirmed dysregulated growth factor expression. The addition of the ATR/CHK1 pathway inhibitors to olaparib downregulated FGF4, FGF6, NT-4, PLGF, and TGFβ1 exclusively in PEO1-OR cells. Survival and differential expression analyses for serous OC patients revealed prognostic miRNAs likely associated with olaparib resistance (miR-99b-5p, miR-424-3p, and miR-505-5p) and resensitization to olaparib (miR-324-5p and miR-424-3p). Essential miRNA-mRNA interactions were reconstructed based on prognostic miRNAs and target genes. In conclusion, our data highlight distinct miRNA profiles in olaparib-sensitive and olaparib-resistant cells, offering molecular insights into overcoming resistance with the ATR/CHK1 inhibitors in OC. Moreover, some miRNAs might serve as potential predictive signature molecules of resistance and therapeutic response.

Glyoxalase System in Breast and Ovarian Cancers: Role of MEK/ERK/SMAD1 Pathway

The glyoxalase system, comprising GLO1 and GLO2 enzymes, is integral in detoxifying methylglyoxal (MGO) generated during glycolysis, with dysregulation implicated in various cancer types. The MEK/ERK/SMAD1 signaling pathway, crucial in cellular processes, influences tumorigenesis, metastasis, and angiogenesis. Altered GLO1 expression in cancer showcases its complex role in cellular adaptation and cancer aggressiveness. GLO2 exhibits context-dependent functions, contributing to both proapoptotic and antiapoptotic effects in different cancer scenarios. Research highlights the interconnected nature of these systems, particularly in ovarian cancer and breast cancer. The glyoxalase system's involvement in drug resistance and its impact on the MEK/ERK/SMAD1 signaling cascade underscore their clinical significance. Furthermore, this review delves into the urgent need for effective biomarkers, exemplified in ovarian cancer, where the RAGE-ligand pathway emerges as a potential diagnostic tool. While therapeutic strategies targeting these pathways hold promise, this review emphasizes the challenges posed by context-dependent effects and intricate crosstalk within the cellular milieu. Insights into the molecular intricacies of these pathways offer a foundation for developing innovative therapeutic approaches, providing hope for enhanced cancer diagnostics and tailored treatment strategies.

PROTACs in Ovarian Cancer: Current Advancements and Future Perspectives

Ovarian cancer is the deadliest gynecologic malignancy. The majority of patients diagnosed with advanced ovarian cancer will relapse, at which point additional therapies can be administered but, for the most part, these are not curative. As such, a need exists for the development of novel therapeutic options for ovarian cancer patients. Research in the field of targeted protein degradation (TPD) through the use of proteolysis-targeting chimeras (PROTACs) has significantly increased in recent years. The ability of PROTACs to target proteins of interest (POI) for degradation, overcoming limitations such as the incomplete inhibition of POI function and the development of resistance seen with other inhibitors, is of particular interest in cancer research, including ovarian cancer research. This review provides a synopsis of PROTACs tested in ovarian cancer models and highlights PROTACs characterized in other types of cancers with potential high utility in ovarian cancer. Finally, we discuss methods that will help to enable the selective delivery of PROTACs to ovarian cancer and improve the pharmacodynamic properties of these agents.

AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication

BACKGROUND

The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers.

METHODS

We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function.

RESULTS

We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2.

CONCLUSIONS

Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

High expression of SLC7A1 in high-grade serous ovarian cancer promotes tumor progression and is involved in MAPK/ERK pathway and EMT

Our previous studies have shown that upregulation of SLC7A1 in epithelial ovarian cancer (EOC) tumor cells significantly increases cancer cell proliferation, migration, and cisplatin resistance; however, the molecular mechanism by which SLC7A1 functions in EOC remains unknown. In later studies, we found that SLC7A1 is also highly expressed in the interstitial portion of high-grade serous ovarian cancer (HGSOC), but the significance of this high expression in the interstitial remains unclear. Here, we showed the Interstitial high expression of SLC7A1 in HGSOC by immunohistochemistry. SLC7A1 enriched in cancer-associated fibroblasts (CAFs) was upregulated by TGF-β1. Transwell assay, scratch assay, cck8 assay and cell adhesion assay showed that SLC7A1 highly expressed in CAFs promoted tumor cells invasion, migration and metastasis in vitro. The effect of SLC7A1 on MAPK and EMT pathway proteins in ovarian cancer (OC) was verified by RNA sequencing and western blotting. Overexpression of SLC7A1 in OC is involved in MAPK/ ERK pathway and EMT. In general, in HGSOC, CAFs overexpressing SLC7A1 supported the migration and invasion of tumor cells; SLC7A1 is highly expressed in ovarian cancer and is involved in ERK phosphorylation and EMT signaling in MAPK signaling pathway. This suggests that SLC7A1 may be a potential therapeutic target for OC metastasis.

Inactivation of VRK1 sensitizes ovarian cancer to PARP inhibition through regulating DNA-PK stability

Ovarian cancer is the leading cause of gynecologic cancer death. Among the most innovative anti-cancer approaches, the genetic concept of synthetic lethality is that mutations in multiple genes work synergistically to effect cell death. Previous studies found that although vaccinia-related kinase-1 (VRK1) associates with DNA damage repair proteins, its underlying mechanisms remain unclear. Here, we found high VRK1 expression in ovarian tumors, and that VRK1 depletion can significantly promote apoptosis and cell cycle arrest. The effect of VRK1 knockdown on apoptosis was manifested by increased DNA damage, genomic instability, and apoptosis, and also blocked non-homologous end joining (NHEJ) by destabilizing DNA-PK. Further, we verified that VRK1 depletion enhanced sensitivity to a PARP inhibitor (PARPi), olaparib, promoting apoptosis through DNA damage, especially in ovarian cancer cell lines with high VRK1 expression. Proteins implicated in DNA damage responses are suitable targets for the development of new anti-cancer therapeutic strategies, and their combination could represent an alternative form of synthetic lethality. Therefore, normal protective DNA damage responses are impaired by combining olaparib with elimination of VRK1 and could be used to reduce drug dose and its associated toxicity. In summary, VRK1 represents both a potential biomarker for PARPi sensitivity, and a new DDR-associated therapeutic target, in ovarian cancer.

The effectiveness of CA125 and HE4 as clinical prognostic markers in epithelial ovarian cancer patients with BRCA mutation

OBJECTIVE

To investigate the efficacy of cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) in predicting survival outcomes based on breast cancer gene (BRCA) mutational status in epithelial ovarian cancer.

METHODS

Medical records of 448 patients diagnosed with epithelial ovarian cancer at a single tertiary institution in Korea were retrospectively analyzed. Area under the curve, sensitivity, specificity, and accuracy were assessed using the CA125 and HE4 values after surgery and 3 cycles of chemotherapy to predict 1-year survival based on the BRCA mutational status. Kaplan-Meier analysis was used to obtain progression-free and overall survival to evaluate CA125 and HE4 effectiveness in predicting survival outcomes.

RESULTS

A total of 423 patients were analyzed, including 180 (42.6%) who underwent interval debulking surgery (IDS) and 243 (57.4%) who underwent primary debulking surgery (PDS). BRCA mutations were observed in 37 (15.2%) and 44 (22.4%) patients in the PDS and IDS groups, respectively. CA125 and HE4 normalization demonstrated the highest specificity in patients with or without BRCA mutations, with specificities of 97.1% and 99.1% in the PDS group and 78.6% and 86.2% in the IDS group, respectively. Normalizing HE4 alone may be an effective prognostic marker, with an area under the curve of 0.774 and specificity of 75.0%, in patients with BRCA mutations.

CONCLUSION

Normalizing both biomarkers emerged as the most effective predictive marker for the 1-year recurrence rate, regardless of BRCA mutational status. A negative HE4 value can be a useful predictor for 1-year recurrence-free survival in patients with BRCA mutations.

From desert flora to cancer therapy: systematic exploration of multi-pathway mechanisms using network pharmacology and molecular modeling approaches

Ovarian cancer, often labeled a "silent killer," remains one of the most compelling and challenging areas of cancer research. In 2019 alone, a staggering 222,240 new cases of ovarian cancer were reported, with nearly 14,170 lives tragically lost to this relentless disease. The absence of effective diagnostic methods, increased resistance to chemotherapy, and the heterogeneous nature of ovarian cancer collectively contribute to the unfavorable prognosis observed in the majority of cases. Thus, there is a pressing need to explore therapeutic interventions that offer superior efficacy and safety, thereby enhancing the survival prospects for ovarian cancer patients. Recognizing this potential, our research synergizes bioinformatics with a network pharmacology approach to investigate the underlying molecular interactions of Saudi Arabian flora (Onopordum heteracanthum, Acacia ehrenbergiana, Osteospermum vaillantii, Cyperus rotundus, Carissa carandas, Carissa spinarum, and Camellia sinensis) in ovarian cancer treatment. At first, phytoconstituents of indigenous flora and their associated gene targets, particularly those pertinent to ovarian cancer, were obtained from open-access databases. Later, the shared targets of plants and diseases were compared to identify common targets. A protein-protein interaction (PPI) network of predicted targets was then constructed for the identification of key genes having the highest degree of connectivity among networks. Following that, a compound-target protein-pathway network was constructed, which uncovered that, namely, hispidulin, stigmasterol, ascorbic acid, octopamine, cyperene, kaempferol, pungenin, citric acid, d-tartaric acid, beta-sitosterol, (-)-epicatechin gallate, and (+)-catechin demonstrably influence cell proliferation and growth by impacting the AKT1 and VEGFA proteins. Molecular docking, complemented by a 20-ns molecular dynamic (MD) simulation, was used, and the binding affinity of the compound was further validated. Molecular docking, complemented by a 20-ns MD simulation, confirmed the binding affinity of these compounds. Specifically, for AKT1, ascorbic acid showed a docking score of -11.1227 kcal/mol, interacting with residues Ser A:240, Leu A:239, Arg A:243, Arg C:2, and Glu A:341. For VEGFA, hispidulin exhibited a docking score of -17.3714 kcal/mol, interacting with Asn A:158, Val A:190, Gln B:160, Ser A:179, and Ser B:176. To sum up, both a theoretical and empirical framework were established by this study, directing more comprehensive research and laying out a roadmap for the potential utilization of active compounds in the formulation of anti-cancer treatments.

ALDH1A3 contributes to tumorigenesis in high-grade serous ovarian cancer by epigenetic modification

High-grade serous ovarian cancer (HGSOC) is the most lethal histotype of ovarian cancer due to its unspecific symptoms in part. ALDH1A3 (aldehyde dehydrogenase 1 family member A3) is a key enzyme for acetyl-CoA production involving aggressive behaviors of cancers. However, ALDH1A3's effects and molecular mechanisms in HGSOC remain to be clarified. Using RNA-seq and publicly available datasets, ALDH1A3 was found to be highly expressed in HGSOC, and associated with poor survival. Knockdown of ALDH1A3 prevented HGSOC tumorigenesis and enhanced cell sensitivity to paclitaxel or cisplatin. ALDH1A3 expression in HGSOC cells was found to be increased by hypoxia, but decreased by HIF-1α inhibitor KC7F2. The dual-luciferase reporter assay showed that the increased transcriptional activity of ALDH1A3 induced by HIF-1α overexpression was reduced by KC7F2. In addition, PITX1 (paired like homeodomain 1) was identified to be inhibited by ALDH1A3 knockdown, and PITX1 depletion inhibited cell proliferation. The mechanistic studies showed that ALDH1A3 knockdown reduced the acetylation of histone 3 lysine 27 (H3K27ac). Treatment of exogenous acetate with NaOAc or inhibition of histone deacetylase with Pracinostat increased H3K27ac and PITX1 levels. CHIP assay demonstrated a significant enrichment of H3K27ac at the PITX1 promoter, and ALDH1A3 knockdown reduced the binding between H3K27ac and PITX1. Taken together, our data suggest that ALDH1A3, transcriptional activated by HIF-1α, promotes tumorigenesis and decreases chemosensitivity by increasing H3K27ac of PITX1 promoter in HGSOC.

Macrophage Checkpoint Nanoimmunotherapy Has the Potential to Reduce Malignant Progression in Bioengineered In Vitro Models of Ovarian Cancer

Most ovarian carcinoma (OvCa) patients present with advanced disease at the time of diagnosis. Malignant, metastatic OvCa is invasive and has poor prognosis, exposing the need for improved therapeutic targeting. High CD47 (OvCa) and SIRPα (macrophage) expression has been linked to decreased survival, making this interaction a significant target for therapeutic discovery. Even so, previous attempts have fallen short, limited by CD47 antibody specificity and efficacy. Macrophages are an important component of the OvCa tumor microenvironment and are manipulated to aid in cancer progression via CD47-SIRPα signaling. Thus, we have leveraged lipid-based nanoparticles (LNPs) to design a therapy uniquely situated to home to phagocytic macrophages expressing the SIRPα protein in metastatic OvCa. CD47-SIRPα presence was evaluated in patient histological sections using immunohistochemistry. 3D tumor spheroids generated on a hanging drop array with OVCAR3 high-grade serous OvCa and THP-1-derived macrophages created a representative model of cellular interactions involved in metastatic OvCa. Microfluidic techniques were employed to generate LNPs encapsulating SIRPα siRNA (siSIRPα) to affect the CD47-SIRPα signaling between the OvCa and macrophages. siSIRPα LNPs were characterized for optimal size, charge, and encapsulation efficiency. Uptake of the siSIRPα LNPs by macrophages was assessed by Incucyte. Following 48 h of 25 nM siSIRPα treatment, OvCa/macrophage heterospheroids were evaluated for SIRPα knockdown, platinum chemoresistance, and invasiveness. OvCa patient tumors and in vitro heterospheroids expressed CD47 and SIRPα. Macrophages in OvCa spheroids increased carboplatin resistance and invasion, indicating a more malignant phenotype. We observed successful LNP uptake by macrophages causing significant reduction in SIRPα gene and protein expressions and subsequent reversal of pro-tumoral alternative activation. Disrupting CD47-SIRPα interactions resulted in sensitizing OvCa/macrophage heterospheroids to platinum chemotherapy and reversal of cellular invasion outside of heterospheroids. Ultimately, our results strongly indicate the potential of using LNP-based nanoimmunotherapy to reduce malignant progression of ovarian cancer.

Identification of estrogen response-associated STRA6+ granulosa cells within high-grade serous ovarian carcinoma by single-cell sequencing

Background

High-grade serous ovarian carcinoma (HGSOC) is a pathologic subtype of ovarian cancer (OC) with a more lethal prognosis. Extensive heterogeneity results in HGSOC being more susceptible to treatment resistance and adverse treatment effects. Revealing the heterogeneity involved is crucial.

Methods

We downloaded the single-cell RNA-seq (scRNA) data from GEO database and performed a scRNA analysis for cell landscape of HGSOC by using the Seurat package. The highly expressed genes were uploaded into the DAVID and KEGG database for enrichment analysis, and the AUCell package was used to calculate cancer-associated hallmark score. The SCENIC analysis was used for key regulons, the estrogen response enrichment scores in TCGA-OV RNA-seq dataset were calculated by using the GSVA package. Besides, the expression of STRA6 and IRF1 and the cell invasion and migration in si-STRA6 OC cells were detected by using the quantitative reverse transcription (qRT)-PCR method and Transwell assay respectively.

Results

We successfully constructed a single-cell atlas of HGSOC and delineated the heterogeneity of epithelial cells therein. There were five epithelial cell subpopulations, GLDC + Epithelial cells, PEG3+ leydig cells, STRA6+ granulosa cells, POLE2+ Epithelial cells, and AURKA + Epithelial cells. STRA6+ granulosa cells have the potential to promote tumor growth as well as the highest estrogen response early activity through the biological pathways analysis of highly expressed genes and estrogen response score of ssGSEA. We found that IRF1 and STRA6 expression was remarkably upregulated in the OC cancer cell line HEY. Silencing of STRA6 markedly decreased the invasion and migration ability of the OC cancer cell line HEY.

Conclusion

There is extreme heterogeneity of epithelial cells in HGSOC, and STRA6+ granulosa cells may be able to promote cancer progression. Our findings are benefit to the heterogeneity identification of HGSOC and develop targeted therapy strategy for HGSOC patients.

Peritumoral MRI Radiomics Features Increase the Evaluation Efficiency for Response to Chemotherapy in Patients With Epithelial Ovarian Cancer

BACKGROUND

It remains unclear whether extracting peritumoral volume (PTV) radiomics features are useful tools for evaluating response to chemotherapy of epithelial ovarian cancer (EOC).

PURPOSE

To evaluate MRI radiomics signatures (RS) capturing subtle changes of PTV and their added evaluation performance to whole tumor volume (WTV) for response to chemotherapy in patients with EOC.

STUDY TYPE

Retrospective.

POPULATION

219 patients aged from 15 to 79 years were enrolled.

FIELD STRENGTH/SEQUENCE

3.0 or 1.5T, axial fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (CE-T1WI).

ASSESSMENT

MRI features were extracted from the four axial sequences and six different volumes of interest (VOIs) (WTV and WTV + PTV (WPTV)) with different peritumor sizes (PS) ranging from 1 to 5 mm. Those features underwent preprocessing, and the most informative features were selected using minimum redundancy maximum relevance and least absolute shrinkage and selection operator to construct the RS. The optimal RS, with the highest area under the curve (AUC) of receiver operating characteristic was then integrated with independent clinical characteristics through multivariable logistic regression to construct the radiomics-clinical model (RCM).

STATISTICAL TESTS

Mann-Whitney U test, chi-squared test, DeLong test, log-rank test. P < 0.05 indicated a significant difference.

RESULTS

All the RSs constructed on WPTV exhibited higher AUCs (0.720-0.756) than WTV (0.671). Of which, RS with PS = 2 mm displayed a significantly better performance (AUC = 0.756). International Federation of Gynecology and Obstetrics (FIGO) stage was identified as the exclusive independent clinical evaluation characteristic, and the RCM demonstrated higher AUC (0.790) than the RS, but without statistical significance (P = 0.261).

DATA CONCLUSION

The radiomics features extracted from PTV could increase the efficiency of WTV radiomics for evaluating the chemotherapy response of EOC. The cut-off of 2 mm PTV was a reasonable value to obtain effective evaluation efficiency.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Fallopian tube single cell analysis reveals myeloid cell alterations in high-grade serous ovarian cancer

Most high-grade serous ovarian cancers (HGSCs) likely initiate from fallopian tube (FT) epithelia. While epithelial subtypes have been characterized using single-cell RNA-sequencing (scRNA-Seq), heterogeneity of other compartments and their involvement in tumor progression are poorly defined. Integrated analysis of human FT scRNA-Seq and HGSC-related tissues, including tumors, revealed greater immune and stromal transcriptional diversity than previously reported. We identified abundant monocytes in FTs across two independent cohorts. The ratio of macrophages to monocytes is similar between benign FTs, ovaries, and adjacent normal tissues but significantly greater in tumors. FT-defined monocyte and macrophage signatures, cell-cell communication, and gene set enrichment analyses identified monocyte- and macrophage-specific interactions and functional pathways in paired tumors and adjacent normal tissues. Further reanalysis of HGSC scRNA-Seq identified monocyte and macrophage subsets associated with neoadjuvant chemotherapy. Taken together, our work provides data that an altered FT myeloid cell composition could inform the discovery of early detection markers for HGSC.

Advances in nanotechnology-enabled drug delivery for combining PARP inhibitors and immunotherapy in advanced ovarian cancer

Advanced ovarian cancer is a malignancy that spreads beyond the ovaries to the pelvis, abdomen, lungs, or lymph nodes. Effective treatment options are available to improve survival rates in patients with advanced ovarian cancer. These include radiation, surgery, chemotherapy, immunotherapy, and targeted therapy. Drug resistance, however, remains a significant challenge in pharmacotherapeutic interventions, leading to reduced efficacy and unfavorable patient outcomes. Combination therapy, which involves using multiple drugs with different mechanisms of action at their optimal dose, is a promising approach to circumvent this challenge and it involves using multiple drugs with different mechanisms of action at their optimal dose. In recent years, nanotechnology has emerged as a valuable alternative for enhancing drug delivery precision and minimize toxicity. Nanoparticles can deliver drugs to specific cancer cells, resulting in higher drug concentrations at the tumor site, and reducing overall drug toxicity. Nanotechnology-based drug delivery systems have the potential to improve the therapeutic effects of anti-cancer drugs, reduce drug resistance, and improve outcomes for patients with advanced ovarian cancer. This literature review aims to examine the current understanding of combining poly (ADP-ribose) polymerase (PARP) inhibitors and immunotherapy in treating advanced ovarian cancer and the potential impact of nanotechnology on drug delivery.

EM-transcriptomic signature predicts drug response in advanced stages of high-grade serous ovarian carcinoma based on ascites-derived primary cultures

Introduction: High-grade serous ovarian carcinoma (HGSOC) remains a medical challenge despite considerable improvements in the treatment. Unfortunately, over 75% of patients have already metastasized at the time of diagnosis. Advances in understanding the mechanisms underlying how ascites cause chemoresistance are urgently needed to derive novel therapeutic strategies. This study aimed to identify the molecular markers involved in drug sensitivity and highlight the use of ascites as a potential model to investigate HGSOC treatment options. Methods: After conducting an in silico analysis, eight epithelial-mesenchymal (EM)-associated genes related to chemoresistance were identified. To evaluate differences in EM-associated genes in HGSOC samples, we analyzed ascites-derived HGSOC primary cell culture (AS), tumor (T), and peritoneal nodule (NP) samples. Moreover, in vitro experiments were employed to measure tumor cell proliferation and cell migration in AS, following treatment with doxorubicin (DOX) and cisplatin (CIS) and expression of these markers. Results: Our results showed that AS exhibits a mesenchymal phenotype compared to tumor and peritoneal nodule samples. Moreover, DOX and CIS treatment leads to an invasive-intermediate epithelial-to-mesenchymal transition (EMT) state of the AS by different EM-associated marker expression. For instance, the treatment of AS showed that CDH1 and GATA6 decreased after CIS exposure and increased after DOX treatment. On the contrary, the expression of KRT18 has an opposite pattern. Conclusion: Taken together, our study reports a comprehensive investigation of the EM-associated genes after drug exposure of AS. Exploring ascites and their associated cellular and soluble components is promising for understanding the HGSOC progression and treatment response at a personalized level.

Loss of mitochondrial pyruvate carrier 1 supports proline-dependent proliferation and collagen biosynthesis in ovarian cancer

The pyruvate transporter MPC1 (mitochondrial pyruvate carrier 1) acts as a tumour-suppressor, loss of which correlates with a pro-tumorigenic phenotype and poor survival in several tumour types. In high-grade serous ovarian cancers (HGSOC), patients display copy number loss of MPC1 in around 78% of cases and reduced MPC1 mRNA expression. To explore the metabolic effect of reduced expression, we demonstrate that depleting MPC1 in HGSOC cell lines drives expression of key proline biosynthetic genes; PYCR1, PYCR2 and PYCR3, and biosynthesis of proline. We show that altered proline metabolism underpins cancer cell proliferation, reactive oxygen species (ROS) production, and type I and type VI collagen formation in ovarian cancer cells. Furthermore, exploring The Cancer Genome Atlas, we discovered the PYCR3 isozyme to be highly expressed in a third of HGSOC patients, which was associated with more aggressive disease and diagnosis at a younger age. Taken together, our study highlights that targeting proline metabolism is a potential therapeutic avenue for the treatment of HGSOC.

Screening ovarian cancer by using risk factors: machine learning assists

BACKGROUND AND AIM

Ovarian cancer (OC) is a prevalent and aggressive malignancy that poses a significant public health challenge. The lack of preventive strategies for OC increases morbidity, mortality, and other negative consequences. Screening OC through risk prediction could be leveraged as a powerful strategy for preventive purposes that have not received much attention. So, this study aimed to leverage machine learning approaches as predictive assistance solutions to screen high-risk groups of OC and achieve practical preventive purposes.

MATERIALS AND METHODS

As this study is data-driven and retrospective in nature, we leveraged 1516 suspicious OC women data from one concentrated database belonging to six clinical settings in Sari City from 2015 to 2019. Six machine learning (ML) algorithms, including XG-Boost, Random Forest (RF), J-48, support vector machine (SVM), K-nearest neighbor (KNN), and artificial neural network (ANN) were leveraged to construct prediction models for OC. To choose the best model for predicting OC, we compared various prediction models built using the area under the receiver characteristic operator curve (AU-ROC).

RESULTS

Current experimental results revealed that the XG-Boost with AU-ROC = 0.93 (0.95 CI = [0.91-0.95]) was recognized as the best-performing model for predicting OC.

CONCLUSIONS

ML approaches possess significant predictive efficiency and interoperability to achieve powerful preventive strategies leveraging OC screening high-risk groups.

Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma

Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level. Our results show that a high CNA is not necessarily reflected at the gene expression level, and our method is capable of detecting genes and pathways whose activity is strongly influenced by CNAs. Furthermore, the CNI analysis enables unbiased categorization of CNA categories, such as deletions and amplifications. We identified six CNI-driven pathways associated with poor treatment response in ovarian high-grade serous carcinoma (HGSC), which we found to be the most CNA-driven cancer across 14 cancer types. The key driver in most of these pathways was amplified wild-type KRAS, which we validated functionally using CRISPR modulation. Our results suggest that wild-type KRAS amplification is a driver of chemotherapy resistance in HGSC and may serve as a potential treatment target.

Population pharmacokinetics of mirvetuximab soravtansine in patients with folate receptor-α positive ovarian cancer: The antibody-drug conjugate, payload and metabolite

AIMS

Mirvetuximab soravtansine is a first-in-class antibody-drug conjugate recently approved for the treatment of folate receptor-α positive ovarian cancer. The aim of this study was to develop a population pharmacokinetic model to describe the concentration-time profiles of mirvetuximab soravtansine, the payload (DM4) and a metabolite (S-methyl-DM4).

METHODS

Mirvetuximab soravtansine was administered intravenously from 0.15 to 7 mg/kg to 543 patients with predominantly platinum-resistant ovarian cancer in 3 clinical studies, and the plasma drug concentrations were analysed using a nonlinear mixed-effects modelling approach. Stepwise covariate modelling was performed to identify covariates.

RESULTS

We developed a semi-mechanistic population pharmacokinetic model that included linear and nonlinear routes for the elimination of mirvetuximab soravtansine and a target compartment for the formation and disposition of the payload and metabolite in tumour cells. The clearance and volume of the central compartment were 0.0153 L/h and 2.63 L for mirvetuximab soravtansine, 8.83 L/h and 3.67 L for DM4, and 2.04 L/h and 6.3 L for S-methyl-DM4, respectively. Body weight, serum albumin and age were identified as statistically significant covariates. Exposures in patients with renal or hepatic impairment and who used concomitant cytochrome P450 (CYP) 3A4 inhibitors were estimated.

CONCLUSION

There is no need for dose adjustment due to covariate effects for mirvetuximab soravtansine administered at the recommended dose of 6 mg/kg based on adjusted ideal body weight. Dose adjustment is not required for patients with mild or moderate renal impairment, mild hepatic impairment, or when concomitant weak and moderate CYP3A4 inhibitors are used.

CASC4/GOLM2 drives high grade serous carcinoma anoikis resistance through the recycling of EGFR

Ovarian cancer is the deadliest gynecological malignancy, and accounts for over 150,000 deaths per year worldwide. The high grade serous ovarian carcinoma (HGSC) subtype accounts for almost 70% of ovarian cancers and is the deadliest. HGSC originates in the fimbria of the fallopian tube and disseminates through the peritoneal cavity. HGSC survival in peritoneal fluid requires cells to resist anoikis (anchorage-independent apoptosis). Most anoikis resistant mechanisms are dependent on microenvironment interactions with cell surface-associated proteins, such as integrins and receptor tyrosine kinases (RTKs). We previously identified the gene CASC4 as a driver of anoikis resistance. CASC4 is predicted to be a Golgi-associated protein that may regulate protein trafficking to the plasma membrane, but CASC4 is largely uncharacterized in literature; thus, we sought to determine how CASC4 confers anoikis resistance to HGSC cells. Mining of publicly available ovarian cancer datasets (TCGA) showed that CASC4 is associated with worse overall survival and increased resistance to platinum-based chemotherapies. For experiments, we cultured three human HGSC cell lines (PEO1, CaOV3, OVCAR3), and a murine HGSC cell line, (ID8) with shRNA-mediated CASC4 knockdowns (CASC4 KD) in suspension, to recapitulate the peritoneal fluid environment in vitro. CASC4 KD significantly inhibited cell proliferation and colony formation ability, and increased apoptosis. A Reverse Phase Protein Assay (RPPA) showed that CASC4 KD resulted in a broad re-programming of membrane-associated proteins. Specifically, CASC4 KD led to decreased protein levels of the RTK Epidermal Growth Factor Receptor (EGFR), an initiator of several oncogenic signaling pathways, leading us to hypothesize that CASC4 drives HGSC survival through mediating recycling and trafficking of EGFR. Indeed, loss of CASC4 led to a decrease in both EGFR membrane localization, reduced turnover of EGFR, and increased EGFR ubiquitination. Moreover, a syngeneic ID8 murine model of ovarian cancer showed that knocking down CASC4 leads to decreased tumor burden and dissemination.

A 19-Gene Signature of Serous Ovarian Cancer Identified by Machine Learning and Systems Biology: Prospects for Diagnostics and Personalized Medicine

Ovarian cancer is a major cause of cancer deaths among women. Early diagnosis and precision/personalized medicine are essential to reduce mortality and morbidity of ovarian cancer, as with new molecular targets to accelerate drug discovery. We report here an integrated systems biology and machine learning (ML) approach based on the differential coexpression analysis to identify candidate systems biomarkers (i.e., gene modules) for serous ovarian cancer. Accordingly, four independent transcriptome datasets were statistically analyzed independently and common differentially expressed genes (DEGs) were identified. Using these DEGs, coexpressed gene pairs were unraveled. Subsequently, differential coexpression networks between the coexpressed gene pairs were reconstructed so as to identify the differentially coexpressed gene modules. Based on the established criteria, "SOV-module" was identified as being significant, consisting of 19 genes. Using independent datasets, the diagnostic capacity of the SOV-module was evaluated using principal component analysis (PCA) and ML techniques. PCA showed a sensitivity and specificity of 96.7% and 100%, respectively, and ML analysis showed an accuracy of up to 100% in distinguishing phenotypes in the present study sample. The prognostic capacity of the SOV-module was evaluated using survival and ML analyses. We found that the SOV-module's performance for prognostics was significant (p-value = 1.36 × 10-4) with an accuracy of 63% in discriminating between survival and death using ML techniques. In summary, the reported genomic systems biomarker candidate offers promise for personalized medicine in diagnosis and prognosis of serous ovarian cancer and warrants further experimental and translational clinical studies.

The spatial structure of the tumor immune microenvironment can explain and predict patient response in high-grade serous carcinoma

Despite ovarian cancer being the deadliest gynecological malignancy, there has been little change to therapeutic options and mortality rates over the last three decades. Recent studies indicate that the composition of the tumor immune microenvironment (TIME) influences patient outcomes but are limited by a lack of spatial understanding. We performed multiplexed ion beam imaging (MIBI) on 83 human high-grade serous carcinoma tumors - one of the largest protein-based, spatially-intact, single-cell resolution tumor datasets assembled - and used statistical and machine learning approaches to connect features of the TIME spatial organization to patient outcomes. Along with traditional clinical/immunohistochemical attributes and indicators of TIME composition, we found that several features of TIME spatial organization had significant univariate correlations and/or high relative importance in high-dimensional predictive models. The top performing predictive model for patient progression-free survival (PFS) used a combination of TIME composition and spatial features. Results demonstrate the importance of spatial structure in understanding how the TIME contributes to treatment outcomes. Furthermore, the present study provides a generalizable roadmap for spatial analyses of the TIME in ovarian cancer research.

Unlocking the 'ova'-coming power: immunotherapy's role in shaping the future of ovarian cancer treatment

Ovarian cancer is a prominent cancer worldwide with a relatively low survival rate for women diagnosed. Many individuals are diagnosed in the late stage of the disease and are prescribed a wide variety of treatment options. Current treatment options are primarily a combination of surgery and chemotherapy as well as a new but promising treatment involving immunotherapy. Nevertheless, contemporary therapeutic modalities exhibit a discernible lag in advancement when compared with the strides achieved in recent years in the context of other malignancies. Moreover, many surgery and chemotherapy options have a high risk for recurrence due to the late-stage diagnosis. Therefore, there is a necessity to further treatment options. There have been many new advancements in the field of immunotherapy. Immunotherapy has been approved for 16 various types of cancers and has shown significant treatment potential in many other cancers as well. Researchers have also found many promising outlooks for immunotherapy as a treatment for ovarian cancer. This review summarizes many of the new advancements in immunotherapy treatment options and could potentially offer valuable insights to gynecologists aimed at enhancing the efficacy of their treatment approaches for patients diagnosed with ovarian cancer.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Applying Multimodal Mass Spectrometry to Image Tumors Undergoing Ferroptosis Following In Vivo Treatment with a Ferroptosis Inducer

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. One region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.

The Dominant Mechanism of Cyclophosphamide-Induced Damage to Ovarian Reserve: Premature Activation or Apoptosis of Primordial Follicles?

Cyclophosphamide (CPM), a part of most cancer treatment regimens, has demonstrated high gonadal toxicity in females. Initially, CPM is believed to damage the ovarian reserve by premature activation of primordial follicles, for the fact that facing CPM damage, primordial oocytes show the activation of PTEN/PI3K/AKT pathways, accompanied by accelerated activation of follicle developmental waves. Meanwhile, primordial follicles are dormant and not considered the target of CPM. However, many researchers have found DNA DSBs and apoptosis within primordial oocytes under CPM-induced ovarian damage instead of premature accelerated activation. A stricter surveillance system of DNA damage is also thought to be in primordial oocytes. So far, the apoptotic death mechanism is considered well-proved, but the premature activation theory is controversial and unacceptable. The connection between the upregulation of PTEN/PI3K/AKT pathways and DNA DSBs and apoptosis within primordial oocytes is also unclear. This review aims to highlight the flaw and/or support of the disputed premature activation theory and the apoptosis mechanism to identify the underlying mechanism of CPM's injury on ovarian reserve, which is crucial to facilitate the discovery and development of effective ovarian protectants. Ultimately, this review finds no good evidence for follicle activation and strong consistent evidence for apoptosis.

The high-grade serous ovarian cancer metastasis and chemoresistance in 3D models

High-grade serous ovarian cancer (HGSOC) is the most frequent and aggressive type of epithelial ovarian cancer, with high recurrence rate and chemoresistance being the main issues in its clinical management. HGSOC is specifically challenging due to the metastatic dissemination via spheroids in the ascitic fluid. The HGSOC spheroids represent the invasive and chemoresistant cellular fraction, which is impossible to investigate in conventional two-dimensional (2D) monolayer cell cultures lacking critical cell-to-cell and cell-extracellular matrix interactions. Three-dimensional (3D) HGSOC cultures, where cells aggregate and exhibit relevant interactions, offer a promising in vitro model of peritoneal metastasis and multicellular drug resistance. This review summarizes recent studies of HGSOC in 3D culture conditions and highlights the role of multicellular HGSOC spheroids and ascitic environment in HGSOC metastasis and chemoresistance.

Construction and Validation of a Nomogram to Predict the Postoperative Venous Thromboembolism Risk in Patients with HGSOC

Venous thromboembolism (VTE) is a common complication in patients with high-grade serous ovarian cancer (HGSOC) after surgery. This study aims to establish a comprehensive risk assessment model to better identify the potential risk of postoperative VTE in HGSOC. Clinical data from 587 HGSOC patients who underwent surgical treatment were retrospectively collected. Univariate and multivariate logistic regression analyses were performed to identify independent factors influencing the occurrence of postoperative VTE in HGSOC. A nomogram model was constructed in the training set and further validated in the verification set. Logistic regression identified age (odds ratio [OR] = 1.063, P = .002), tumor size (OR = 3.815, P < .001), postoperative transfusion (OR = 5.646, P = .001), and postoperative D-dimer (OR = 1.246, P = .003) as independent risk factors for postoperative VTE in HGSOC patients. A nomogram was constructed using these factors. The receiver operating characteristic curve showed an area under the curve (AUC) of 0.840 (95% confidence interval [CI]: 0.782, 0.898) in the training set and 0.793 (95% CI: 0.704, 0.882) in the validation set. The calibration curve demonstrated a good consistency between model predictions and actual results. The decision curve analysis indicated the model benefits at a threshold probability of less than 70%. A nomogram predicting postoperative VTE in HGSOC was established and validated. This model will assist clinicians in the early identification of high-risk patients, enabling the implementation of appropriate preventive measures.

Drug-Resistant Epithelial Ovarian Cancer: Current and Future Perspectives

Epithelial ovarian cancer (EOC) is a complex disease with diverse histological subtypes, which, based on the aggressiveness and course of disease progression, have recently been broadly grouped into type I (low-grade serous, endometrioid, clear cell, and mucinous) and type II (high-grade serous, high-grade endometrioid, and undifferentiated carcinomas) categories. Despite substantial differences in pathogenesis, genetics, prognosis, and treatment response, clinical diagnosis and management of EOC remain similar across the subtypes. Debulking surgery combined with platinum-taxol-based chemotherapy serves as the initial treatment for High Grade Serous Ovarian Carcinoma (HGSOC), the most prevalent one, and for other subtypes, but most patients exhibit intrinsic or acquired resistance and recur in short duration. Targeted therapies, such as anti-angiogenics (e.g., bevacizumab) and PARP inhibitors (for BRCA-mutated cancers), offer some success, but therapy resistance, through various mechanisms, poses a significant challenge. This comprehensive chapter delves into emerging strategies to address these challenges, highlighting factors like aberrant miRNAs, metabolism, apoptosis evasion, cancer stem cells, and autophagy, which play pivotal roles in mediating resistance and disease relapse in EOC. Beyond standard treatments, the focus of this study extends to alternate targeted agents, including immunotherapies like checkpoint inhibitors, CAR T cells, and vaccines, as well as inhibitors targeting key oncogenic pathways in EOC. Additionally, this chapter covers disease classification, diagnosis, resistance pathways, standard treatments, and clinical data on various emerging approaches, and advocates for a nuanced and personalized approach tailored to individual subtypes and resistance mechanisms, aiming to enhance therapeutic outcomes across the spectrum of EOC subtypes.

Ovarian cancer relies on the PDGFRβ-fibronectin axis for tumorsphere formation and metastatic spread

High-grade serous ovarian cancer (HGSOC) is the deadliest gynecological malignancy. The most common form of metastatic spread of HGSOC is transcoelomic dissemination. In this process, detached cells from the primary tumor aggregate as tumorspheres and promote the accumulation of peritoneal ascites. This represents an early event in HGSOC development and is indicative of poor prognosis. In this study, based on tumorspheres isolated from ascitic liquid samples from HGSOC patients, ovarian cancer spheroid 3D cultures, and in vivo models, we describe a key signal for tumorsphere formation in HGSOC. We report that platelet-derived growth factor receptor beta (PDGFRβ) is essential for fibronectin-mediated cell clustering of ovarian cancer cells into tumorspheres. This effect is mediated by the kinase NUAK family SNF1-like kinase 1 (NUAK1) and blocked by PDGFRβ pharmacological or genetic inhibition. In the absence of PDGFRβ, ovarian cancer cells can be provided with fibronectin by cancer-associated fibroblasts to generate chimeric spheroids. This work provides new insights that uncover potential targets to prevent peritoneal dissemination, the main cause of advanced disease in HGSOC patients.

The Role of the Human Microbiome in Epithelial Ovarian Cancer

Ovarian cancer is the fifth-leading cause of cancer deaths among women due to the absence of available screening methods to identify early disease. Thus, prevention and early disease detection investigations are of high priority, surrounding a critical window of opportunity to better understand important pathogenic mechanisms of disease progression. Microorganisms modulate molecular interactions in humans that can influence states of health and disease, including ovarian cancer. While the mechanisms of infectious microbial invasion that trigger the immune-inflammatory axis are well studied in cancer research, the complex interactions that promote the transition of noninfectious healthy microbes to pathobiont expansion are less understood. As traditional research has focused on the influences of infectious pathogens on ovarian cancer development and progression, the impact of noninfectious microbes has gained scientific attention. The objective of this chapter is to summarize current evidence on the role of microbiota in epithelial ovarian cancer throughout disease.

miR-29c-3p acts as a tumor promoter by regulating β-catenin signaling through suppressing DNMT3A, TET1 and HBP1 in ovarian carcinoma

Ovarian Carcinoma (OvCa) is characterized by rapid and sustained growth, activated invasion and metastasis. Studies have shown that microRNAs recruit and alter the expression of key regulators to modulate carcinogenesis. Here, we find that miR-29c-3p is increased in benign OvCa and malignant OvCa compared to normal ovary. Univariate and multivariate analyses report that miR-29c-3p overexpression is associated with poor prognosis in OvCa. Furthermore, we investigate that expression of miR-29c-3p is inversely correlated to DNA methyltransferase (DNMT) 3 A and Ten-Eleven-Translocation enzyme TET1. The high-throughput mRNA sequencing, bioinformatics analysis and pharmacological studies confirm that aberrant miR-29c-3p modulates tumorigenesis in OvCa cells, including epithelial-mesenchymal transition (EMT), proliferation, migration, and invasion. This modulation occurs through the regulation of β-catenin signaling by directly targeting 3'UTR of DNMT3A, TET1 and the HMG box transcription factor HBP1 and suppressing their expression. The further 3D spheres assay clearly shows the regulatory effects of miR-29c-3p on OvCa tumorigenesis. Additionally, the receiver operating characteristic (ROC) curve analysis of miR-29c-3p and the clinical detection/diagnostic biomarker CA125 suggests that miR-29c-3p may be conducive for clinical diagnosis or co-diagnosis of OvCa. These findings support miR-29c-3p functions as a tumor promoter by targeting its functional targets, providing new potential biomarker (s) for precision medicine strategies in OvCa.

Unveiling the Promise: A Comprehensive Review of Salpingectomy as a Vanguard for Ovarian Cancer Prevention

This comprehensive review explores the potential of salpingectomy as a groundbreaking strategy for the prevention of ovarian cancer. The discussion encompasses the biological rationale behind salpingectomy, emphasizing its foundation in the tubal hypothesis, which posits the fallopian tubes as a possible origin site for certain ovarian cancers. Ongoing clinical trials and observational studies provide evolving evidence supporting the safety and efficacy of salpingectomy, particularly in high-risk populations. The procedure's ethical considerations, including its impact on fertility and equitable access, are thoroughly examined. Implications for clinical practice underscore the importance of informed decision-making, risk-benefit assessments, and the integration of emerging evidence into reproductive health discussions. Looking ahead, the future landscape of ovarian cancer prevention involves continued research, technological innovations, and collaborative efforts to ensure a holistic and evidence-based approach. The goal is to forge a future where ovarian cancer is not only treatable but also preventable, with salpingectomy potentially playing a pivotal role in this transformative journey.

Personalized neoantigen-based T cell therapy triggers cytotoxic lymphocytes expressing polyclonal TCR against metastatic ovarian cancer

Neoantigen-reactive cytotoxic T lymphocytes play a vital role in precise cancer cell elimination. In this study, we demonstrate the effectiveness of personalized neoantigen-based T cell therapy in inducing tumor regression in two patients suffering from heavily-burdened metastatic ovarian cancer. Our approach involved the development of a robust pipeline for ex vivo expansion of neoantigen-reactive T lymphocytes. Neoantigen peptides were designed and synthesized based on the somatic mutations of the tumors and their predicted HLA binding affinities. These peptides were then presented to T lymphocytes through co-culture with neoantigen-loaded dendritic cells for ex vivo expansion. Subsequent to cell therapy, both patients exhibited significant reductions in tumor marker levels and experienced substantial tumor regression. One patient achieved repeated cancer regression through infusions of T cell products generated from newly identified neoantigens. Transcriptomic analyses revealed a remarkable increase in neoantigen-reactive cytotoxic lymphocytes in the peripheral blood of the patients following cell therapy. These cytotoxic T lymphocytes expressed polyclonal T cell receptors (TCR) against neoantigens, along with abundant cytotoxic proteins and pro-inflammatory cytokines. The efficacy of neoantigen targeting was significantly associated with the immunogenicity and TCR polyclonality. Notably, the neoantigen-specific TCR clonotypes persisted in the peripheral blood after cell therapy. Our findings indicate that personalized neoantigen-based T cell therapy triggers cytotoxic lymphocytes expressing polyclonal TCR against ovarian cancer, suggesting its promising potential in cancer immunotherapy.

Correlation between gynecological tumors and atherosclerotic diseases

Gynecological cancer is among the leading causes of cancer-related mortality worldwide, with malignancies of the ovary, uterus, fallopian tube, cervix, vagina, and vulva making up 10-18% of all cancers diagnosed in women globally. Gynecological cancer and atherosclerosis are two of the most frequent medical entities that afflict women worldwide; thus the possible correlations between them ought to be explored. Vulvar, cervical, vaginal, endometrial, and ovarian cancers have been found to have common points with atherosclerosis regarding their pathogenesis and predisposing factors. Obesity and metabolic syndrome, HPV infection, vitamin D deficiency, and increased telomere length constitute common ground between these two afflictions, which this article aims to analyze.

A tumor-restricted glycoform of podocalyxin is a highly selective marker of immunologically cold high-grade serous ovarian carcinoma

Introduction

Targeted-immunotherapies such as antibody-drug conjugates (ADC), chimeric antigen receptor (CAR) T cells or bispecific T-cell engagers (eg, BiTE®) all aim to improve cancer treatment by directly targeting cancer cells while sparing healthy tissues. Success of these therapies requires tumor antigens that are abundantly expressed and, ideally, tumor specific. The CD34-related stem cell sialomucin, podocalyxin (PODXL), is a promising target as it is overexpressed on a variety of tumor types and its expression is consistently linked to poor prognosis. However, PODXL is also expressed in healthy tissues including kidney podocytes and endothelia. To circumvent this potential pitfall, we developed an antibody, named PODO447, that selectively targets a tumor-associated glycoform of PODXL. This tumor glycoepitope is expressed by 65% of high-grade serous ovarian carcinoma (HGSOC) tumors.

Methods

In this study we characterize these PODO447-expressing tumors as a distinct subset of HGSOC using four different patient cohorts that include pre-chemotherapy, post-neoadjuvant chemotherapy (NACT) and relapsing tumors as well as tumors from various peritoneal locations.

Results

We find that the PODO447 epitope expression is similar across tumor locations and negligibly impacted by chemotherapy. Invariably, tumors with high levels of the PODO447 epitope lack infiltrating CD8+ T cells and CD20+ B cells/plasma cells, an immune phenotype consistently associated with poor outcome.

Discussion

We conclude that the PODO447 glycoepitope is an excellent biomarker of immune "cold" tumors and a candidate for the development of targeted-therapies for these hard-to-treat cancers.

miR-146a inhibits ovarian tumor growth in vivo via targeting immunosuppressive neutrophils and enhancing CD8+ T cell infiltration

Immunotherapies have emerged as promising strategies for cancer treatment. However, existing immunotherapies have poor activity in high-grade serous ovarian cancer (HGSC) due to the immunosuppressive tumor microenvironment and the associated low tumoral CD8+ T cell (CTL) infiltration. Through multiple lines of evidence, including integrative analyses of human HGSC tumors, we have identified miR-146a as a master regulator of CTL infiltration in HGSC. Tumoral miR-146a expression is positively correlated with anti-cancer immune signatures in human HGSC tumors, and delivery of miR-146a to tumors resulted in significant reduction in tumor growth in both ID8-p53-/- and IG10 murine HGSC models. Increasing miR-146a expression in tumors improved anti-tumor immune responses by decreasing immune suppressive neutrophils and increasing CTL infiltration. Mechanistically, miR-146a targets IL-1 receptor-associated kinase 1 and tumor necrosis factor receptor-associated factor 6 adaptor molecules of the transcription factor nuclear factor κB signaling pathway in ID8-p53-/- cells and decreases production of the downstream neutrophil chemoattractant, C-X-C motif chemokine ligand 1. In addition to HGSC, tumoral miR-146a expression also correlates strongly with CTL infiltration in other cancer types including thyroid, prostate, breast, and adrenocortical cancers. Altogether, our findings highlight the ability of miR-146a to overcome immune suppression and improve CTL infiltration in tumors.

Targeted inhibition of the ATR/CHK1 pathway overcomes resistance to olaparib and dysregulates DNA damage response protein expression in BRCA2MUT ovarian cancer cells

Olaparib is a PARP inhibitor (PARPi) approved for targeted treatment of ovarian cancer (OC). However, its efficacy is impeded by the inevitable occurrence of resistance. Here, we investigated whether the cytotoxic activity of olaparib could be synergistically enhanced in olaparib-resistant OC cells with BRCA2 reversion mutation by the addition of inhibitors of the ATR/CHK1 pathway. Moreover, we provide insights into alterations in the DNA damage response (DDR) pathway induced by combination treatments. Antitumor activity of olaparib alone or combined with an ATR inhibitor (ATRi, ceralasertib) or CHK1 inhibitor (CHK1i, MK-8776) was evaluated in OC cell lines sensitive (PEO1, PEO4) and resistant (PEO1-OR) to olaparib. Antibody microarrays were used to explore changes in expression of 27 DDR-related proteins. Olaparib in combination with ATR/CHK1 inhibitors synergistically induced a decrease in viability and clonogenic survival and an increase in apoptosis mediated by caspase-3/7 in all OC cells. Combination treatments induced cumulative alterations in expression of DDR-related proteins mediating distinct DNA repair pathways and cell cycle control. In the presence of ATRi and CHK1i, olaparib-induced upregulation of proteins determining cell fate after DNA damage (PARP1, CHK1, c-Abl, Ku70, Ku80, MDM2, and p21) was abrogated in PEO1-OR cells. Overall, the addition of ATRi or CHK1i to olaparib effectively overcomes resistance to PARPi exerting anti-proliferative effect in BRCA2MUT olaparib-resistant OC cells and alters expression of DDR-related proteins. These new molecular insights into cellular response to olaparib combined with ATR/CHK1 inhibitors might help improve targeted therapies for olaparib-resistant OC.

Prediction model of adnexal masses with complex ultrasound morphology

Background

Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.

Methods

In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).

Results

Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.

Conclusion

The risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.

Homologous Recombination Deficiency (HRD) Scoring, by Means of Two Different Shallow Whole-Genome Sequencing Pipelines (sWGS), in Ovarian Cancer Patients: A Comparison with Myriad MyChoice Assay

High-grade serous ovarian cancer (HGSOC) patients carrying the BRCA1/2 mutation or deficient in the homologous recombination repair system (HRD) generally benefit from treatment with PARP inhibitors. Some international recommendations suggest that BRCA1/2 genetic testing should be offered for all newly diagnosed epithelial ovarian cancer, along with HRD assessment. Academic tests (ATs) are continuously under development, in order to break down the barriers patients encounter in accessing HRD testing. Two different methods for shallow whole-genome sequencing (sWGS) were compared to the reference assay, Myriad. All these three assays were performed on 20 retrospective HGSOC samples. Moreover, HRD results were correlated with the progression-free survival rate (PFS). Both sWGS chemistries showed good correlation with each other and a complete agreement, even when compared to the Myriad score. Our academic HRD assay categorized patients as HRD-Deficient, HRM-Mild and HRN-Negative. These three groups were matched with PFS, providing interesting findings in terms of HRD scoring and months of survival. Both our sWGS assays and the Myriad test correlated with the patient's response to treatments. Finally, our AT confirms its capability of determining HRD status, with the advantage of being faster, cheaper, and easier to carry out. Our results showed a prognostic value for the HRD score.

BRCA1 expression, its correlation with clinicopathological features, and response to neoadjuvant chemotherapy in high-grade serous ovarian cancer

AIM

In high-grade serous ovarian cancers (HG-SOC), BRCA1 mutation is one of the predominant mutations reported by various studies. However, the non-mutational mechanisms of BRCA pathway inactivation in HG-SOC are unclear. We evaluated BRCA1 inactivation by estimating its expression with its repressor, ID4, in primary and neoadjuvant chemotherapy (NACT)-treated HG-SOC tumors with known therapeutic responses.

METHODS

We evaluated the expression pattern of BRCA1 protein by immunohistochemistry in 119 cases of HG-SOC from a hospital cohort consisting of primary (N = 69) and NACT-treated (N = 50) tumors. Histological patterns (SET), stromal infiltration by lymphocytes (sTILs), and chemotherapy response score (CRS) were estimated by microscopic examination. Gene expression levels of BRCA1, and its repressor ID4, were estimated by qPCR. The association of BRCA1 protein and mRNA with clinicopathological features was studied. The relevance of the BRCA1/ID4 ratio was evaluated in tumors with different CRS.

RESULTS

BRCA1 protein expression was observed in 12% of primary and 19% of NACT-treated HG-SOC tumors. We observed moderate concordance between BRCA1 protein and mRNA expression (AUC = 0.677). High BRCA1 mRNA expression was significantly associated with a more frequent SET pattern (p = 0.024), higher sTILs density (p = 0.042), and increased mitosis (p = 0.028). BRCA1-negative tumors showed higher expression of ID4 though not statistically significant. A higher BRCA1/ID4 ratio was associated with high sTILs density in primary (p = 0.042) and NACT-treated tumors (p = 0.040).

CONCLUSION

Our findings show the utility of the BRCA1/ID4 ratio in predicting neoadjuvant therapy response, which needs further evaluation in larger cohorts with long-term outcomes.

Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment 18F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment 18F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC.