Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay.

BACKGROUND: Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera. METHODS: To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates. RESULTS: We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions. CONCLUSIONS: A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Human Fallopian Tube-Derived Organoids with TP53 and RAD51D Mutations Recapitulate an Early Stage High-Grade Serous Ovarian Cancer Phenotype In Vitro.

RAD51D mutations have been implicated in the transformation of normal fallopian tube epithelial (FTE) cells into high-grade serous ovarian cancer (HGSOC), one of the most prevalent and aggressive gynecologic malignancies. Currently, no suitable model exists to elucidate the role of RAD51D in disease initiation and progression. Here, we established organoids from primary human FTE and introduced TP53 as well as RAD51D knockdown to enable the exploration of their mutational impact on FTE lesion generation. We observed that TP53 deletion rescued the adverse effects of RAD51D deletion on the proliferation, stemness, senescence, and apoptosis of FTE organoids. RAD51D deletion impaired the homologous recombination (HR) function and induced G2/M phase arrest, whereas concurrent TP53 deletion mitigated G0/G1 phase arrest and boosted DNA replication when combined with RAD51D mutation. The co-deletion of TP53 and RAD51D downregulated cilia assembly, development, and motility, but upregulated multiple HGSOC-associated pathways, including the IL-17 signaling pathway. IL-17A treatment significantly improved cell viability. TP53 and RAD51D co-deleted organoids exhibited heightened sensitivity to platinum, poly-ADP ribose polymerase inhibitors (PARPi), and cell cycle-related medication. In summary, our research highlighted the use of FTE organoids with RAD51D mutations as an invaluable in vitro platform for the early detection of carcinogenesis, mechanistic exploration, and drug screening.

Differential histone deacetylase inhibitor-induced perturbations of the global proteome landscape in the setting of high-grade serous ovarian cancer.

High-grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy in women. Its low survival rate is attributed to late detection, relapse, and drug resistance. The lack of effective second-line therapeutics remains a significant challenge. There is an opportunity to incorporate the use of histone deacetylase inhibitors (HDACi) into HGSOC treatment. However, the mechanism and efficacy of HDACi in the context of BRCA-1/2 mutation status is understudied. Therefore, we set out to elucidate how HDACi perturb the proteomic landscape within HGSOC cells. In this work, we used TMT labeling followed by data-dependent acquisition LC-MS/MS to quantitatively determine differences in the global proteomic landscape across HDACi-treated CAOV3, OVCAR3, and COV318 (BRCA-1/2 wildtype) HGSOC cells. We identified significant differences in the HDACi-induced perturbations of global protein regulation across CAOV3, OVCAR3, and COV318 cells. The HDACi Vorinostat and Romidepsin were identified as being the least and most effective in inhibiting HDAC activity across the three cell lines, respectively. Our results provide a justification for the further investigation of the functional mechanisms associated with the differential efficacy of FDA-approved HDACi within the context of HGSOC. This will enhance the efficacy of targeted HGSOC therapeutic treatment modalities that include HDACi.

Linoleic Acid-Glucosamine Hybrid for Endogenous Iron-Activated Ferroptosis Therapy in High-Grade Serous Ovarian Cancer.

As the most common subtype in ovarian malignancies, high-grade serous ovarian cancer (HGSOC) made less therapeutic progress in past decades due to the lack of effective drug-able targets. Herein, an effective linoleic acid (LA) and glucosamine (GlcN) hybrid (LA-GlcN) was synthesized for the treatment of HGSOC. The GlcN was introduced to recognize the glucose transporter 1 (GLUT 1) overexpressed in tumor cells to enhance the uptake of LA-GlcN, and the unsaturated LA was employed to trigger ferroptosis by iron-dependent lipid peroxidation. Since the iron content of HGSOC was ∼5 and 2 times, respectively, higher than that of the normal ovarian cells and low-grade serous ovarian cancer cells, these excess irons make them a good target to enhance the ferroptosis of LA-GlcN. The in vitro study demonstrated that LA-GlcN could selectively kill HGSOC cells without affecting normal cells; the in vivo study revealed that LA-GlcN at the dose of 50 mg kg-1 achieved a comparable tumor inhibition as doxorubicin hydrochloride (4 mg kg-1) while the overall survival of mice was extended largely due to the low toxicity, and when the dose was increased to 100 mg kg-1, the therapeutic outcomes could be improved further. This dietary hybrid which targets the excess endogenous iron to activate ferroptosis represents a promising drug for HGSOC treatment.

High expression of fibroblast activation protein (FAP) predicts poor outcome in high-grade serous ovarian cancer.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is a fatal form of ovarian cancer. Previous studies indicated some potential biomarkers for clinical evaluation of HGSOC prognosis. However, there is a lack of systematic analysis of different expression genes (DEGs) to screen and detect significant biomarkers of HGSOC. METHODS: TCGA database was conducted to analyze relevant genes expression in HGSOC. Outcomes of candidate genes expression, including overall survival (OS) and progression-free survival (PFS), were calculated by Cox regression analysis for hazard rates (HR). Histopathological investigation of the identified genes was carried out in 151 Chinese HGSOC patients to validate gene expression in different stages of HGSOC. RESULTS: Of all 57,331 genes that were analyzed, FAP was identified as the only novel gene that significantly contributed to both OS and PFS of HGSOC. In addition, FAP had a consistent expression profile between carcinoma-paracarcinoma and early-advanced stages of HGSOC. Immunological tests in paraffin section also confirmed that up-regulation of FAP was present in advanced stage HGSOC patients. Prediction of FAP network association suggested that FN1 could be a potential downstream gene which further influenced HGSOC survival. CONCLUSIONS: High-level expression of FAP was associated with poor prognosis of HGSOC via FN1 pathway.

Cancer-associated stroma significantly contributes to the mesenchymal subtype signature of serous ovarian cancer.

OBJECTIVE: Mesenchymal (MES) subtype of high-grade serous ovarian cancer (HGSOC) is associated with worse outcomes including survival and resectability compared with other molecular subtypes. Molecular subtypes have historically been derived from 'tumor', consisting of both cancer and stromal cells. We sought to determine the origins of multiple MES subtype gene signatures in HGSOC. METHODS: Fifteen patients with MES subtype of HGSOC diagnosed between 2010 and 2013 were identified. Formalin-fixed paraffin-embedded (FFPE) blocks from primary surgery were sectioned for immunohistochemistry (IHC) staining of relevant proteins. Eight genes (ACTA2, COL5A1, COL11A1, FAP, POSTN, VCAN, ZEB1 and p-SMAD2) were selected for IHC staining based on their differential expression in MES vs. non-MES subtypes of HGSOC. Slides were scored for intensity and localization and simple statistics were used to compare expression results in cancer vs. stroma and between primary and metastatic sites. RESULTS: COL5A1, VCAN, FAP, and ZEB1 proteins were almost exclusively expressed by stroma as opposed to cancer cells. In addition, stromal expression was dominant for ACTA2, COL11A1, POSTN and p-SMAD2. In general there were minimal differences in expression of proteins between primary and metastatic sites, exceptions being COL5A1 (reduced in metastases) and COL11A1 (increased in metastases). Nuclear p-SMAD2 expression was more common in metastatic stroma. CONCLUSIONS: The existing molecular classification of HGSOC MES subtype reflects a significant stromal contribution, suggesting an important role in HGSOC behavior and thus stroma may be a relevant therapeutic target. Specific patterns of expression indicate that collagens and TGF-ß signaling are involved in the metastatic process.

Class I-Histone Deacetylase (HDAC) Inhibition is Superior to pan-HDAC Inhibition in Modulating Cisplatin Potency in High Grade Serous Ovarian Cancer Cell Lines.

High grade serous ovarian cancer (HGSOC) is the most common and aggressive ovarian cancer subtype with the worst clinical outcome due to intrinsic or acquired drug resistance. Standard treatment involves platinum compounds. Cancer development and chemoresistance is often associated with an increase in histone deacetylase (HDAC) activity. The purpose of this study was to examine the potential of HDAC inhibitors (HDACi) to increase platinum potency in HGSOC. Four HGSOC cell lines with different cisplatin sensitivity were treated with combinations of cisplatin and entinostat (class I HDACi), panobinostat (pan-HDACi), or nexturastat A (class IIb HDACi), respectively. Inhibition of class I HDACs by entinostat turned out superior in increasing cisplatin potency than pan-HDAC inhibition in cell viability assays (MTT), apoptosis induction (subG1), and caspase 3/7 activation. Entinostat was synergistic with cisplatin in all cell lines in MTT and caspase activation assays. MTT assays gave combination indices (CI values) < 0.9 indicating synergism. The effect of HDAC inhibitors could be attributed to the upregulation of pro-apoptotic genes (CDNK1A, APAF1, PUMA, BAK1) and downregulation of survivin. In conclusion, the combination of entinostat and cisplatin is synergistic in HGSOC and could be an effective strategy for the treatment of aggressive ovarian cancer.

Identification of Novel Somatic TP53 Mutations in Patients with High-Grade Serous Ovarian Cancer (HGSOC) Using Next-Generation Sequencing (NGS).

Somatic mutations in TP53 are a hallmark of high-grade serous ovarian cancer (HGSOC), although their prognostic and predictive value as markers is not well defined. Next-generation sequencing (NGS) can identify novel mutations with high sensitivity, that may be repurposed as potential druggable anti-cancer targets and aid in therapeutic decisions. Here, a commercial NGS cancer panel comprising 26 genes, including TP53, was used to identify new genetic markers of platinum resistance and patient prognosis in a retrospective set of patients diagnosed with epithelial ovarian cancer. Six novel TP53 somatic mutations in untreated tumors from six distinct patients diagnosed with HGSOC were identified: TP53 c.728_739delTGGGCGGCATGA (p.Met243_Met247del, in-frame insertion or deletion (INDEL); TP53 c.795_809delGGGACGGAACAGCTT (p.Gly266_Phe270del, in-frame INDEL); TP53 c.826_827GC>AT (p.Ala276Ile, missense); TP53 c.1022insT (p.Arg342Profs*5, frameshift INDEL); TP53 c.1180delT (p.Ter394Aspfs*28, frameshift INDEL); and TP53 c.573insT (p.Gln192Serfs*17, frameshift INDEL). Novel TP53 variants were validated by classical sequencing methods and their impact on protein expression in tumors explored by immunohistochemistry. Further insights into the potential functional effect of the mutations were obtained by different in silico approaches, bioinformatics tools, and structural modeling. This discovery of previously unreported TP53 somatic mutations provides an opportunity to translate NGS technology into personalized medicine and identify new potential targets for therapeutic applications.

The number of cycles of neoadjuvant chemotherapy is associated with prognosis of stage IIIc-IV high-grade serous ovarian cancer.

OBJECTIVE: No consensus exists on the number of chemotherapy cycles to be administered before and after interval debulking surgery (IDS) in patients with advanced stage epithelial ovarian cancer. The present study aims to explore the optimal number of cycles of neoadjuvant chemotherapy (NAC) and post-operation chemotherapy to treat the International Federation of Gynecology and Obstetrics stage IIIc-IV high-grade serous ovarian cancer (HG-SOC). MATERIALS AND METHODS: A total of 129 IIIc-IV stage HG-SOC cases were retrospectively analyzed. Cases were comprised of patients who underwent NAC followed by IDS and who achieved clinical complete response (CCR) at the end of primary therapy. Patients were recruited from the Jiangsu Institute of Cancer Research between 1993 and 2013. Optimal IDS-associated factors were explored with logistic regression. The association between progression-free survival (PFS), overall survival (OS) duration, and covariates was assessed by Cox proportional hazards model and log-rank test. RESULTS: The median number of NAC cycle was 3 (range 1-8). CA-125 decreasing kinetics (p = 0.01) was independently associated with optimal IDS. CA-125 decreasing kinetics, optimal IDS, and NAC cycles was independently associated with OS (p < 0.01, p < 0.01, p = 0.03, respectively) and PFS (p < 0.01, p < 0.01, p = 0.04, respectively). The PFS of patients who underwent ≥5 NAC cycles was shorter than those of patients who underwent <5 NAC cycles (12.3 versus 17.2 months). The PFS and OS of patients who underwent <5 cycles of adjuvant chemotherapy post-IDS were shorter than those of patients who underwent ≥5 cycles (14.2 and 20.3 versus 21.2 and 28.8 months). CONCLUSION: NAC cycles, CA-125 decreasing kinetics, and optimal debulking are independently associated with the prognosis of patients with advanced stage HG-SOC who underwent NAC/IDS and achieved CCR. The number of administered NAC cycles should not exceed 4.

The molecular prognostic score, a classifier for risk stratification of high-grade serous ovarian cancer.

BACKGROUND: The clinicopathological parameters such as residual tumor, grade, the International Federation of Gynecology and Obstetrics (FIGO) score are often used to predict the survival of ovarian cancer patients, but the 5-year survival of high grade serous ovarian cancer (HGSOC) still remains around 30%. Hence, the relentless pursuit of enhanced prognostic tools for HGSOC, this study introduces an unprecedented gene expression-based molecular prognostic score (mPS). Derived from a novel 20-gene signature through Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression, the mPS stands out for its predictive prowess. RESULTS: Validation across diverse datasets, including training and test sets (n = 491 each) and a large HGSOC patient cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium (n = 7542), consistently shows an area-under-curve (AUC) around 0.7 for predicting 5-year overall survival. The mPS's impact on prognosis resonates profoundly, yielding an adjusted hazard-ratio (HR) of 6.1 (95% CI: 3.65-10.3; p < 0.001), overshadowing conventional parameters-FIGO score, residual disease, and age. Molecular insights gleaned from mPS stratification uncover intriguing pathways, with focal-adhesion, Wnt, and Notch signaling upregulated, and antigen processing and presentation downregulated (p < 0.001) in high-risk HGSOC cohorts. CONCLUSION: Positioned as a robust prognostic marker, the 20-gene signature-derived mPS emerges as a potential game-changer in clinical settings. Beyond its role in predicting overall survival, its implications extend to guiding alternative therapies, especially targeting Wnt/Notch signaling pathways and immune evasion-a promising avenue for improving outcomes in high-risk HGSOC patients.

Immunosuppressive M2 TAMs represent a promising target population to enhance phagocytosis of ovarian cancer cells in vitro.

Introduction: Tumor-associated macrophages (TAMs) represent an important cell population within the tumor microenvironment, but little is known about the phenotype and function of these cells. The present study aims to characterize macrophages in high-grade serous ovarian cancer (HGSOC). Methods: Phenotype and expression of co-regulatory markers were assessed on TAMs derived from malignant ascites (MA) or peripheral blood (PB) by multiparametric flow cytometry. Samples were obtained from HGSOC patients (n=29) and healthy donors (HDs, n=16). Additional expression analysis was performed by RNAseq (n=192). Correlation with clinically relevant parameters was conducted and validated by a second patient cohort (n=517). Finally, the role of TIGIT in repolarization and phagocytosis was investigated in vitro. Results: Expression of the M2-associated receptors CD163, CD204, and CD206, as well as of the co-regulatory receptors TIGIT, CD226, TIM-3, and LAG-3 was significantly more frequent on macrophages in HGSOC than in HDs. CD39 and CD73 were broadly expressed on (mainly M2) macrophages, but without a clear clustering in HGSOC. CD163 mRNA levels were higher in TAMs from patients with residual tumor mass after surgery and associated with a shorter overall survival. In addition, TIGIT expression was associated with a higher tumor grading, indicating a prognostic relevance of M2 infiltration in HGSOC. TIGIT blockade significantly reduced the frequency of M2 macrophages. Moreover, combined blockade of TIGIT and CD47 significantly increased phagocytosis of ovarian cancer cells by TAMs in comparison to a single blockade of CD47. Conclusion: Combined blockade of TIGIT and CD47 represents a promising approach to enhance anti-CD47-facilitated phagocytosis.

Combining Mass Cytometry Data by CyTOFmerge Reveals Additional Cell Phenotypes in the Heterogeneous Ovarian Cancer Tumor Microenvironment: A Pilot Study.

The prognosis of high-grade serous ovarian carcinoma (HGSOC) is poor, and treatment selection is challenging. A heterogeneous tumor microenvironment (TME) characterizes HGSOC and influences tumor growth, progression, and therapy response. Better characterization with multidimensional approaches for simultaneous identification and categorization of the various cell populations is needed to map the TME complexity. While mass cytometry allows the simultaneous detection of around 40 proteins, the CyTOFmerge MATLAB algorithm integrates data sets and extends the phenotyping. This pilot study explored the potential of combining two datasets for improved TME phenotyping by profiling single-cell suspensions from ten chemo-naïve HGSOC tumors by mass cytometry. A 35-marker pan-tumor dataset and a 34-marker pan-immune dataset were analyzed separately and combined with the CyTOFmerge, merging 18 shared markers. While the merged analysis confirmed heterogeneity across patients, it also identified a main tumor cell subset, additionally to the nine identified by the pan-tumor panel. Furthermore, the expression of traditional immune cell markers on tumor and stromal cells was revealed, as were marker combinations that have rarely been examined on individual cells. This study demonstrates the potential of merging mass cytometry data to generate new hypotheses on tumor biology and predictive biomarker research in HGSOC that could improve treatment effectiveness.

A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC.

Background: Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC. Methods: Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR). Results: By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data. Conclusions: The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

Integrated Multi-Omic Analysis Reveals Immunosuppressive Phenotype Associated with Poor Outcomes in High-Grade Serous Ovarian Cancer.

High-grade serous ovarian cancer (HGSOC) is characterized by a complex genomic landscape, with both genetic and epigenetic diversity contributing to its pathogenesis, disease course, and response to treatment. To better understand the association between genomic features and response to treatment among 370 patients with newly diagnosed HGSOC, we utilized multi-omic data and semi-biased clustering of HGSOC specimens profiled by TCGA. A Cox regression model was deployed to select model input features based on the influence on disease recurrence. Among the features most significantly correlated with recurrence were the promotor-associated probes for the NFRKB and DPT genes and the TREML1 gene. Using 1467 transcriptomic and methylomic features as input to consensus clustering, we identified four distinct tumor clusters-three of which had noteworthy differences in treatment response and time to disease recurrence. Each cluster had unique divergence in differential analyses and distinctly enriched pathways therein. Differences in predicted stromal and immune cell-type composition were also observed, with an immune-suppressive phenotype specific to one cluster, which associated with short time to disease recurrence. Our model features were additionally used as a neural network input layer to validate the previously defined clusters with high prediction accuracy (91.3%). Overall, our approach highlights an integrated data utilization workflow from tumor-derived samples, which can be used to uncover novel drivers of clinical outcomes.

Tertiary Lymphoid Structures Are Associated with a Favorable Prognosis in High-Grade Serous Ovarian Cancer Patients.

There was accumulating evidence indicating that tertiary lymphoid structures (TLSs) were strongly associated with improved survival and clinical outcome in several solid tumors. In this study, we intended to assess the presence of TLSs and their potential clinical significance in high-grade serous ovarian cancer (HGSOC). TCGA (The Cancer Genome Atlas) cohort included RNA-seq data of 376 HGSOC patients, of which 74 patients included available hematoxylin-eosin (H&E) sections; GEO (Gene Expression Omnibus) cohort, GSE140082, included microarray data of 212 HGSOC patients. TLSs were counted by pathological sections, and the relative abundance of TLSs was assessed by the unsupervised consensus clustering of 12-chemokine transcriptome signatures. The potential associations between TLSs and clinical prognosis, tumor microenvironment (TME), and immunotherapy response of HGSOC were further performed based on transcriptome data. In the H&E sections of HGSOC, TLSs were predominantly located in the stroma and invasive margin of the tumor. Pathological counting results suggested that the expression of 12 chemokines was significantly higher in samples abundant with TLSs than that in the lack of TLSs. Consensus clustering of both TCGA and GEO cohorts divided HGSOC patients into two clusters with different TLSs abundance: low- and high-TLSs. Based on transcriptome analysis, the high-TLS cluster was characterized by better clinical prognosis, a higher degree of immune infiltration, more biological pathways, higher tumor mutational burden score, and higher expression of immune checkpoints. In conclusion, TLSs strongly correlated with the immune-responsive microenvironment and remained a favorable prognostic factor independent of other clinical characteristics in HGSOC. The presence of TLSs was also associated with a potentially favorable response to immune checkpoint blockade (ICB) therapy in HGSOC.

Evaluation of mitochondrial biogenesis and ROS generation in high-grade serous ovarian cancer.

Introduction: Ovarian cancer is one of the leading causes of death for women with cancer worldwide. Energy requirements for tumor growth in epithelial high-grade serous ovarian cancer (HGSOC) are fulfilled by a combination of aerobic glycolysis and oxidative phosphorylation (OXPHOS). Although reduced OXPHOS activity has emerged as one of the significant contributors to tumor aggressiveness and chemoresistance, up-regulation of mitochondrial antioxidant capacity is required for matrix detachment and colonization into the peritoneal cavity to form malignant ascites in HGSOC patients. However, limited information is available about the mitochondrial biogenesis regulating OXPHOS capacity and generation of mitochondrial reactive oxygen species (mtROS) in HGSOC. Methods: To evaluate the modulation of OXPHOS in HGSOC tumor samples and ovarian cancer cell lines, we performed proteomic analyses of proteins involved in mitochondrial energy metabolism and biogenesis and formation of mtROS by immunoblotting and flow cytometry, respectively. Results and discussion: We determined that the increased steady-state expression levels of mitochondrial- and nuclear-encoded OXPHOS subunits were associated with increased mitochondrial biogenesis in HGSOC tumors and ovarian cancer cell lines. The more prominent increase in MT-COII expression was in agreement with significant increase in mitochondrial translation factors, TUFM and DARS2. On the other hand, the ovarian cancer cell lines with reduced OXPHOS subunit expression and mitochondrial translation generated the highest levels of mtROS and significantly reduced SOD2 expression. Evaluation of mitochondrial biogenesis suggested that therapies directed against mitochondrial targets, such as those involved in transcription and translation machineries, should be considered in addition to the conventional chemotherapies in HGSOC treatment.

Transcriptional Landscape of 3D vs. 2D Ovarian Cancer Cell Models.

Three-dimensional (3D) cancer models are revolutionising research, allowing for the recapitulation of an in vivo-like response through the use of an in vitro system, which is more complex and physiologically relevant than traditional monolayer cultures. Cancers such as ovarian (OvCa) are prone to developing resistance, are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D cultures. However, the current models often fall short of the predicted response, where reproducibility is limited owing to the lack of standardised methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in the genetic profiles presented by a vast array of 3D cultures. An analysis of the literature (Pubmed.gov) spanning 2012-2022 was used to identify studies with paired data of 3D and 2D monolayer counterparts in addition to RNA sequencing and microarray data. From the data, 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e., agarose, collagen, or Matrigel) compared to 2D cell cultures. The top genes differentially expressed in 2D vs. 3D included C3, CXCL1, 2, and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. The top enriched gene sets for 2D vs. 3D included IFN-α and IFN-γ response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial-mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape and identify key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironments.

Establishment of a prognostic model for ovarian cancer based on mitochondrial metabolism-related genes.

Background: Mitochondrial metabolism and mitochondrial structure were found to be altered in high-grade serous ovarian cancer (HGSOC). The intent of this exploration was to systematically depict the relevance between mitochondrial metabolism-related genes (MMRGs) and the prognosis of HGSOC patients by bioinformatics analysis and establish a prognostic model for HGSOC. Methods: First of all, screened differentially expressed genes (DEGs) between TCGA-HGSOC and GTEx-normal by limma, with RNA-seq related HGSOC sourced from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. Subsequently, expressed MMRGs (DE-MMRGs) were acquired by overlapping DEGs with MMRGs, and an enrichment analysis of DE-MMRGs was performed. Kaplan-Meier (K-M) survival analysis and Cox regression analysis were conducted to validate the genes' prognostic value, Gene Set Enrichment Analysis (GSEA) to elucidate the molecular mechanisms of the risk score, and CIBERSORT algorithm to explore the immuno landscape of HGSOC patients. Finally, a drug sensitivity analysis was made via the Drug Sensitivity in Cancer (GDSC) database. Results: 436 HGSOC-related DE-MMRGs (222 up-regulated and 214 down-regulated) were observed to participate in multiple metabolic pathways. The study structured a MMRGs-related prognostic signature on the basis of IDO1, TNFAIP8L3, GPAT4, SLC27A1, ACSM3, ECI2, PPT2, and PMVK. Risk score was the independent prognostic element for HGSOC. Highly dangerous population was characterized by significant association with mitochondria-related biological processes, lower immune cell abundance, lower expression of immune checkpoint and antigenic molecules. Besides, 54 drugs associated with eight prognostic genes were obtained. Furthermore, copy number variation was bound up with the 8 prognostic genes in expression levels. Conclusion: We have preliminarily determined the prognostic value of MMRGs in HGSOC as well as relationship between MMRGs and the tumor immune microenvironment.

Development of a dual energy CT based model to assess response to treatment in patients with high grade serous ovarian cancer: a pilot cohort study.

BACKGROUND: In patients with cancer, the current gold standard for assessing response to treatment involves measuring cancer lesions on computed tomography (CT) imaging. The percentage change in size of specific lesions determines whether patients have had a complete/partial response or progressive disease, according to RECIST criteria. Dual Energy CT (DECT) permits additional measurements of iodine concentration, a surrogate marker of vascularity. Here we explore the role of changes in iodine concentration within cancer tissue on CT scans to assess its suitability for determining treatment response in patients with high grade serous ovarian cancer (HGSOC). METHODS: Suitable RECIST measurable lesions were identified from the CT images of HGSOC patients, taken at 2 different time points (pre and post treatment). Changes in size and iodine concentration were measured for each lesion. PR/SD were classified as responders, PD was classified as non-responder. Radiological responses were correlated with clinical and CA125 outcomes. RESULTS: 62 patients had appropriate imaging for assessment. 22 were excluded as they only had one DECT scan. 32/40 patients assessed (113 lesions) had received treatment for relapsed HGSOC. RECIST and GCIG (Gynaecologic Cancer Inter Group) CA125 criteria / clinical assessment of response for patients was correlated with changes in iodine concentration, before and after treatment. The prediction of median progression free survival was significantly better associated with changes in iodine concentration (p = 0.0001) and GCIG Ca125 / clinical assessment (p = 0.0028) in comparison to RECIST criteria (p = 0.43). CONCLUSION: Changes in iodine concentration from dual energy CT imaging may be more suitable than RECIST in assessing response to treatment in patients with HGSOC. TRIAL REGISTRATION: CICATRIx IRAS number 198179, 14 Dec 2015, https://www.myresearchproject.org.uk/ .

Epithelial ovarian cancer is infiltrated by activated effector T cells co-expressing CD39, PD-1, TIM-3, CD137 and interacting with cancer cells and myeloid cells.

Introduction: Despite predicted efficacy, immunotherapy in epithelial ovarian cancer (EOC) has limited clinical benefit and the prognosis of patients remains poor. There is thus a strong need for better identifying local immune dynamics and immune-suppressive pathways limiting T-cell mediated anti-tumor immunity. Methods: In this observational study we analyzed by immunohistochemistry, gene expression profiling and flow cytometry the antigenic landscape and immune composition of 48 EOC specimens, with a focus on tumor-infiltrating lymphocytes (TILs). Results: Activated T cells showing features of partial exhaustion with a CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ surface profile were exclusively present in EOC specimens but not in corresponding peripheral blood or ascitic fluid, indicating that the tumor microenvironment might sustain this peculiar phenotype. Interestingly, while neoplastic cells expressed several tumor-associated antigens possibly able to stimulate tumor-specific TILs, macrophages provided both co-stimulatory and inhibitory signals and were more abundant in TILs-enriched specimens harboring the CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ signature. Conclusion: These data demonstrate that EOC is enriched in CD137+CD39+PD-1+TIM-3+CD45RA-CD62L-CD95+ T lymphocytes, a phenotype possibly modulated by antigen recognition on neoplastic cells and by a combination of inhibitory and co-stimulatory signals largely provided by infiltrating myeloid cells. Furthermore, we have identified immunosuppressive pathways potentially hampering local immunity which might be targeted by immunotherapeutic approaches.