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.

Screening by Q Exactive liquid chromatography/tandem mass spectrometry identified Choline, 25-hydroxyvitamin D2, and SM(d18:0/16:1(9Z) (OH)) as biomarkers for high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC-MS/MS, QE) to compare the differentiation between plasma samples (22 HGSOC samples and 22 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC)  ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery SIGNIFICANCE: High-grade serous ovarian cancer (HGSOC) has a high death rate and poor prognosis. The main causes of poor prognosis are asymptomatic early disease, no effective screening method at present, and advanced disease. Changes in cellular metabolism are characteristic of cancer, and plasma metabolome analysis can be used to identify biomarkers. In this study, we used Q Exactive liquid chromatography tandem mass spectrometry (LC-MS/MS, QE) to compare the differentiation between plasma samples (20 HGSOC samples and 20 normal samples). In total, we detected 124 metabolites, and an orthogonal partial least-squares-discriminant analysis (OPLS-DA) model was useful to distinguish HGSOC patients from healthy controls. Choline, 25-hydroxyvitamin D2, and sphingomyelin (d18:0/16:1(9Z) (OH))/SM(d18:0/16:1(9Z) (OH)) showed significantly differential plasma levels in HGSOC patients under the conditions of variable importance in projection (VIP) > 1, p < 0.05 using Student's t-test, and fold change (FC) ≥ 1.5 or ≤ 0.667. Metabolic pathway analysis can provide valuable information to enhance the understanding of the underlying pathophysiology of HGSOC. In conclusion, the Q Exactive LC/MS/MS method validation-based plasma metabolomics approach may have potential as a convenient screening method for HGSOC and may be a method to monitor tumor recurrence in patients with HGSOC after surgery.

NB compounds are potent and efficacious FOXM1 inhibitors in high-grade serous ovarian cancer cells

BACKGROUND

Genetic studies implicate the oncogenic transcription factor Forkhead Box M1 (FOXM1) as a potential therapeutic target in high-grade serous ovarian cancer (HGSOC). We evaluated the activity of different FOXM1 inhibitors in HGSOC cell models.

RESULTS

We treated HGSOC and fallopian tube epithelial (FTE) cells with a panel of previously reported FOXM1 inhibitors. Based on drug potency, efficacy, and selectivity, determined through cell viability assays, we focused on two compounds, NB-73 and NB-115 (NB compounds), for further investigation. NB compounds potently and selectively inhibited FOXM1 with lesser effects on other FOX family members. NB compounds decreased FOXM1 expression via targeting the FOXM1 protein by promoting its proteasome-mediated degradation, and effectively suppressed FOXM1 gene targets at both the protein and mRNA level. At the cellular level, NB compounds promoted apoptotic cell death. Importantly, while inhibition of apoptosis using a pan-caspase inhibitor rescued HGSOC cells from NB compound-induced cell death, it did not rescue FOXM1 protein degradation, supporting that FOXM1 protein loss from NB compound treatment is specific and not a general consequence of cytotoxicity. Drug washout studies indicated that FOXM1 reduction was retained for at least 72 h post-treatment, suggesting that NB compounds exhibit long-lasting effects in HGSOC cells. NB compounds effectively suppressed both two-dimensional and three-dimensional HGSOC cell colony formation at sub-micromolar concentrations. Finally, NB compounds exhibited synergistic activity with carboplatin in HGSOC cells.

CONCLUSIONS

NB compounds are potent, selective, and efficacious inhibitors of FOXM1 in HGSOC cells and are worthy of further investigation as HGSOC therapeutics.

PIK3R1 fusion drives chemoresistance in ovarian cancer by activating ERK1/2 and inducing rod and ring-like structures

Gene fusions are common in high-grade serous ovarian cancer (HGSC). Such genetic lesions may promote tumorigenesis, but the pathogenic mechanisms are currently poorly understood. Here, we investigated the role of a PIK3R1-CCDC178 fusion identified from a patient with advanced HGSC. We show that the fusion induces HGSC cell migration by regulating ERK1/2 and increases resistance to platinum treatment. Platinum resistance was associated with rod and ring-like cellular structure formation. These structures contained, in addition to the fusion protein, CIN85, a key regulator of PI3K-AKT-mTOR signaling. Our data suggest that the fusion-driven structure formation induces a previously unrecognized cell survival and resistance mechanism, which depends on ERK1/2-activation.

Survival time prediction in patients with high-grade serous ovarian cancer based on 18F-FDG PET/CT- derived inter-tumor heterogeneity metrics

BACKGROUND

The presence of heterogeneity is a significant attribute within the context of ovarian cancer. This study aimed to assess the predictive accuracy of models utilizing quantitative 18F-FDG PET/CT derived inter-tumor heterogeneity metrics in determining progression-free survival (PFS) and overall survival (OS) in patients diagnosed with high-grade serous ovarian cancer (HGSOC). Additionally, the study investigated the potential correlation between model risk scores and the expression levels of p53 and Ki-67.

METHODS

A total of 292 patients diagnosed with HGSOC were retrospectively enrolled at Shengjing Hospital of China Medical University (median age: 54 ± 9.4 years). Quantitative inter-tumor heterogeneity metrics were calculated based on conventional measurements and texture features of primary and metastatic lesions in 18F-FDG PET/CT. Conventional models, heterogeneity models, and integrated models were then constructed to predict PFS and OS. Spearman's correlation coefficient (ρ) was used to evaluate the correlation between immunohistochemical scores of p53 and Ki-67 and model risk scores.

RESULTS

The C-indices of the integrated models were the highest for both PFS and OS models. The C-indices of the training set and testing set of the integrated PFS model were 0.898 (95% confidence interval [CI]: 0.881-0.914) and 0.891 (95% CI: 0.860-0.921), respectively. For the integrated OS model, the C-indices of the training set and testing set were 0.894 (95% CI: 0.871-0.917) and 0.905 (95% CI: 0.873-0.936), respectively. The integrated PFS model showed the strongest correlation with the expression levels of p53 (ρ = 0.859, p < 0.001) and Ki-67 (ρ = 0.829, p < 0.001).

CONCLUSIONS

The models based on 18F-FDG PET/CT quantitative inter-tumor heterogeneity metrics exhibited good performance for predicting the PFS and OS of patients with HGSOC. p53 and Ki-67 expression levels were strongly correlated with the risk scores of the integrated predictive models.

Clinical characteristics and treatment modalities in women with newly diagnosed advanced high-grade serous epithelial ovarian cancer in Taiwan

BACKGROUND

This study was designed to investigate the demographics, treatment patterns, and clinical outcomes of patients newly diagnosed with high-grade serous ovarian cancer (HGSOC) in 3 medical centers in Taiwan before the integration of poly (ADP-ribose) polymerase inhibitors in clinical practice.

METHODS

A retrospective analysis was conducted on data from patients diagnosed with HGSOC between January 2014 and December 2018 and followed-up for a minimum of 12 months after diagnosis. Descriptive statistics were used to analyze the data, while survival rates were evaluated using the Kaplan‒Meier method.

RESULTS

There were 251 patients included in the analysis, and 98.8% received platinum plus paclitaxel chemotherapy (PPCT). Primary cytoreductive surgery (PCS) and interval debulking surgery (IDS) were performed in 78.9% and 17.1% of patients, respectively. The percentage of optimal surgery was higher in the IDS cohort than in the PCS cohort (83.8% vs. 53.6%). Bevacizumab was used as initiation therapy in 16.7% of patients, and maintenance therapy was administered in 6.8%. Advanced age, IDS, and suboptimal surgery were independent poor prognostic factors associated with lower overall survival (OS). Patients with optimal surgery had significantly lower OS and progression-free survival in the IDS cohort than in the PCS cohort. The predictive accuracy was good for OS at the 1-year follow-up.

CONCLUSION

Advanced age, IDS, and residual disease are associated with poor OS in patients with HGSOC. Compared to PCS, IDS provides a higher likelihood of optimal surgery but results in a lower probability of survival for patients with HGSOC in Taiwan.

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer

OBJECTIVE

The genome-wide profiling of 5-hydroxymethylcytosines (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for various diseases. The purpose of this study was to investigate 5hmC signals in serum cfDNA and identify novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5hmC profiles in cfDNA reflect the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. Moreover, we sought to identify predictors that would better stratify outcomes for women with intermediate-sensitive HGSOC.

METHODS

Women diagnosed with HGSOC and known platinum sensitivity status were selected for this study. Nano-hmC-Seal was performed on cfDNA isolated from archived serum samples, and differential 5hmC features were identified using DESeq2 to establish a model predictive of chemoresistance.

RESULTS

A multivariate model consisting of three features (preoperative CA-125, largest residual implant after surgery, 5hmC level of OSGEPL), stratified samples from intermediate sensitive, chemo-naive women diagnosed with HGSOC into chemotherapy-resistant- and sensitive-like strata with a significant difference in overall survival (OS). Independent analysis of The Cancer Genome Atlas data further confirmed that high OSGEPL1 expression is a favorable prognostic factor for HGSOC.

CONCLUSIONS

We have developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC modified gene, OSGEPL1, that predicted response to platinum-based chemotherapy in intermediate-sensitive HGSOC. Our multivariate model applies to chemo-naïve samples regardless if the patint was treated with adjuvant or neoadjuvant chemotherapy. These results merit further investigation of the predictive capability of our model in larger cohorts.

Pre-operative levels of angiopoietin protein-like 3 (ANGPTL3) in women diagnosed with high-grade serous carcinoma of the ovary

Cancer cells need constant supplies of lipids to survive and grow. Lipid dependence has been observed in various types of cancer, including high-grade serous ovarian carcinomas (HGSOC), which is a lethal form of gynecological malignancy. ANGPTL3, PCSK9, and Apo CIII are pivotal lipid-modulating factors, and therapeutic antibodies have been developed against each one (Evinacumab, Evolocumab and Volanesorsen, respectively). The roles -if any- of ANGPTL3, PCSK9, and Apo CIII in HGSOC are unclear. Moreover, levels of these lipid-modulating factors have never been reported before in HGSOC. In this study, circulating levels of ANGPTL3, PCSK9, and Apo CIII, along with lipid profiles, are examined to verify whether one or many of these lipid-regulating factors are associated with HGSOC. Methods ELISA kits were used to measure ANGPTL3, PCSK9 and Apo CIII levels in plasma samples from 31 women with HGSOC and 40 women with benign ovarian lesions (BOL) before treatment and surgery. A Roche Modular analytical platform measured lipid panels, Apo B and Lp(a) levels.Results ANGPTL3 levels were higher in women with HGSOC (84 ng/mL, SD: 29 ng/mL, n = 31) than in women with BOL (67 ng/mL, SD: 31 ng/mL, n = 40; HGSOC vs. BOL P = 0.019). Associations between the lipid panel and ANGPTL3, and the inverse relationship between HDL-cholesterol and triglycerides, were present in women with BOL but not with HGSOC. PCSK9 and Apo CIII were not associated with HGSOC.Conclusions In this cohort of 71 women, ANGPTL3 levels were increased in HGSOC patients. The presence of HGSOC disrupted the classic inverse relationship between HDL and triglycerides, as well as the association between the lipid panel and ANGPTL3. These associations were only maintained in cancer-free women. Given the availability of Evinacumab, a therapeutic antibody against ANGPTL3, the current finding prompts an assessment of whether ANGPTL3 inhibition has therapeutic potential in HGSOC.

The CDK4/6 Inhibitor Palbociclib Induces Cell Senescence of High-grade Serous Ovarian Cancer Through Acetylation of p53

Cell senescence is an anti-cancer strategy following DNA repair and apoptosis, which is associated with the initiation, progression, and treatment of ovarian cancer. The CDK4/6 inhibitor alters cell cycle and induces cell senescence dependent on retinoblastoma (RB) family proteins. Objective Herein, we aimed to explore the effects of Palbociclib (a CDK4/6 inhibitor) on cellular senescence of high-grade serous ovarian cancer (HGSOC). Cell viability and cell cycle were evaluated by cell counting kit-8 and flow cytometry. Cell senescence was analyzed using the SA-β-gal staining assay. The senescence-associated secretory phenotype was assessed using quantitative PCR (qPCR). Senescence-related markers were tested using western blot. The role of Palbociclib in vivo was clarified using xenograft tumor. Acetylation of p53 was evaluated by qPCR and western blot. The results showed that Palbociclib inhibited cell viability, blocked cell cycle at G0/G1 phase, and induced cell senescence. A rescue study indicated that knockdown of p53 reversed the effects on cell cycle and senescence induced by Palbociclib. Moreover, we found that Palbociclib promotes P300-mediated p53 acetylation, thus increasing p53 stability and transcription activity. Moreover, Palbociclib suppressed tumor growth in vivo with increased p53 and acetylated p53 levels. In conclusion, Palbociclib induced cell senescence of HGSOC through P300-mediated p53 acetylation, suggesting that Palbociclib may have the effect of treating HGSOC.

Development and validation of an ultrasound‑based radiomics nomogram to predict lymph node status in patients with high-grade serous ovarian cancer: a retrospective analysis

BACKGROUND

Despite advances in medical imaging technology, the accurate preoperative prediction of lymph node status remains challenging in ovarian cancer. This retrospective study aimed to investigate the feasibility of using ultrasound-based radiomics combined with preoperative clinical characteristics to predict lymph node metastasis (LNM) in patients with high-grade serous ovarian cancer (HGSOC).

RESULTS

Patients with 401 HGSOC lesions from two institutions were enrolled: institution 1 for the training cohort (n = 322) and institution 2 for the external test cohort (n = 79). Radiomics features were extracted from the three preoperative ultrasound images of each lesion. During feature selection, primary screening was first performed using the sample variance F-value, followed by recursive feature elimination (RFE) to filter out the 12 most significant features for predicting LNM. The radscore derived from these 12 radiomic features and three clinical characteristics were used to construct a combined model and nomogram to predict LNM, and subsequent 10-fold cross-validation was performed. In the test phase, the three models were tested with external test cohort. The radiomics model had an area under the curve (AUC) of 0.899 (95% confidence interval [CI]: 0.864-0.933) in the training cohort and 0.855 (95%CI: 0.774-0.935) in the test cohort. The combined model showed good calibration and discrimination in the training cohort (AUC = 0.930) and test cohort (AUC = 0.881), which were superior to those of the radiomic and clinical models alone.

CONCLUSIONS

The nomogram consisting of the radscore and preoperative clinical characteristics showed good diagnostic performance in predicting LNM in patients with HGSOC. It may be used as a noninvasive method for assessing the lymph node status in these patients.

A spatial proteomic study of platinum refractory HGSOC implicates dual AKT and WNT activity linked to an immunosuppressive tumor microenvironment

OBJECTIVE

Advanced-stage high-grade serous ovarian cancer (HGSOC) remains a deadly gynecologic malignancy with high rates of disease recurrence and limited, effective therapeutic options for patients. There is a significant need to better stratify HGSOC patients into platinum refractory (PRF) vs. sensitive (PS) cohorts at baseline to improve therapeutic responses and survival outcomes for PRF HGSOC.

METHODS

We performed NanoString for GeoMx Digital Spatial Profile (G-DSP) multiplex protein analysis on PRF and PS tissue microarrays (TMAs) to study the bidirectional communication of cancer cells with immune cells in the tumor microenvironment (TME) of HGSOC. We demonstrate robust stratification of PRF and PS tumors at baseline using multiplex spatial proteomic biomarkers with implications for tailoring subsequent therapy.

RESULTS

PS patients had elevated apoptotic and anti-tumor immune profiles, while PRF patients had dual AKT1 and WNT signaling with immunosuppressive profiles. We found that dual activity of AKT1 and WNT signaling supported the exclusion of immune cells, specifically tumor infiltrating lymphocytes (TILs), from the TME in PRF tumors, and this was not observed in PS tumors. The exclusion of immune cells from the TME of PRF tumors corresponded to abnormal endothelial cell structure in tumors with dual AKT1 and WNT signaling activity.

CONCLUSIONS

We believe our findings provide improved understanding of tumor-immune crosstalk in HGSOC TME highlighting the importance of the relationship between AKT and WNT pathways, immune cell function, and platinum response in HGSOC.

Disparities in treatment modalities and survival among older patients with high-grade serous ovarian cancer

BACKGROUND

Undertreatment of ovarian cancer is common among older women. We aimed to evaluate the treatment modalities offered to older patients and their impact on overall survival (OS).

METHODS

The study identified 5,055 patients with high-grade serous ovarian cancer and 3584 patients with advanced stage (IIIC + IV) disease from the Surveillance, Epidemiology, and End Results (SEER) database from January 1, 2010, to December 31, 2017. We performed comparisons of OS and ovarian cancer-specific survival (OCSS) across age groups using a Cox proportional hazards model.

RESULTS

Very elderly patients (≥ 75 years old) received treatment with significantly less surgical complexity, such as no lymphadenectomy (59.7% vs. 48.6%; p < 0.001) and a lower rate of optimal debulking surgery (44.0% vs. 52.7%; p < 0.001), as well as lower rates of chemotherapy (78.2% vs. 89.4%; P<0.001) and standard treatment (70.6% vs. 85%; p < 0.001). High proportions of both very elderly and elderly patients received neoadjuvant chemotherapy (NACT), with no significant difference (38.7% vs. 36.2%; P = 0.212). Patients aged ≥ 75 years had significantly worse OS and OCSS.

CONCLUSION

With increasing age, the survival rate of women with ovarian cancer decreases significantly. Noticeably fewer ovarian cancer patients aged over 75 years receive standard treatments, and more very elderly patients are treated with NACT.

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.

Replication stress and defective checkpoints make fallopian tube epithelial cells putative drivers of high-grade serous ovarian cancer

Clinical and molecular evidence indicates that high-grade serous ovarian cancer (HGSOC) primarily originates from the fallopian tube, not the ovarian surface. However, the reasons for this preference remain unclear. Our study highlights significant differences between fallopian tube epithelial (FTE) and ovarian surface epithelial (OSE) cells, providing the molecular basis for FTEs as site of origin of HGSOC. FTEs, unlike OSEs, exhibit heightened replication stress (RS), impaired repair of stalled forks, ineffective G2/M checkpoint, and increased tumorigenicity. BRCA1 heterozygosity exacerbates these defects, resulting in RS suppression haploinsufficiency and an aggressive tumor phenotype. Examination of human and mouse sections reveals buildup of the RS marker 53BP1 primarily in the fallopian tubes, particularly at the fimbrial ends. Furthermore, menopausal status influences RS levels. Our study provides a mechanistic rationale for FTE as the site of origin for HGSOC, investigates the impact of BRCA1 heterozygosity, and lays the groundwork for targeting early HGSOC drivers.

CT-based radiomics nomogram analysis for assessing BRCA mutation status in patients with high-grade serous ovarian cancer

BACKGROUND

Radiomics nomogram analysis is widely preoperatively used to assess gene mutations in various tumors.

PURPOSE

To explore the value of computed tomography (CT)-based radiomics nomogram analysis for assessing BRCA gene mutation status of patients with high-grade serous ovarian cancer (HGSOC).

MATERIAL AND METHODS

In total, 96 patients with HGSOC were retrospectively screened and randomly divided into primary (n = 68) and validation cohorts (n = 28). The clinical model was constructed based on clinical features and CT morphological features using univariate and multivariate logistic analyses. Maximum-relevance and minimum-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) were performed for feature dimensionality reduction and radiomics score was calculated. The nomogram model combining the clinical model and the radiomics score was constructed using multivariate logistic regression. Receiver operating characteristic (ROC) curves were generated to assess models' performance. The calibration analysis and decision curve analysis (DCA) were also performed.

RESULTS

The clinical model consisted of CA125 level and supradiaphragmatic lymphadenopathy and yielded an area under the curve (AUC) of 0.69 (primary cohort) and 0.81 (validation cohort). The radiomics model was built with seven selected features and showed an AUC of 0.87 (primary cohort) and 0.81 (validation cohort). The nomogram finally showed the highest AUC of 0.89 (primary cohort) and 0.87 (validation cohort). The nomogram presented favorable calibrations in both the primary and validation cohorts. DCA further confirmed the clinical benefits of the constructed nomogram.

CONCLUSION

CT-based radiomics nomogram provides a non-invasive method to discriminate BRCA gene mutation status of HGSOC and potentially helps develop precise medical strategies.

C5aR1 blockade reshapes immunosuppressive tumor microenvironment and synergizes with immune checkpoint blockade therapy in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC), with a modest response to immune checkpoint blockade (ICB) targeting PD-1/PD-L1 monotherapy, is densely infiltrated by M2-polarized tumor-associated macrophages (TAMs) and regulatory T (Treg) cells. The complement C5a/C5aR1 axis contributes to the programming of the immunosuppressive phenotype of TAMs in solid tumors and represents a promising immunomodulatory target for treating HGSCs. Here, we aimed to identify the relevance of C5aR1 in prognosis, immune microenvironment, and immunotherapy response in HGSCs. The expression and relationship of C5aR1 with tumor-infiltrating immune cells were assessed by immunohistochemistry and flow cytometry in the training cohort (n = 120) and fresh HGSC tissues (n = 36). Transcriptomic analyses of the xenografts delineated the mechanisms driving the immunomodulatory activity of PMX53, an orally bioavailable C5aR1 inhibitor. Therapeutic relevance was confirmed in ex vivo tumor cultures and The Cancer Genome Atlas (TCGA) datasets. C5aR1 expression independently predicted dismal prognosis and was linked to the immunoevasive subtype of HGSC, characterized by increased infiltration of pro-tumor cells (Treg cells, M2-polarized macrophages, and neutrophils) and impaired CD8+T functions. PMX53 antagonized subcutaneous tumor growth, modulated immunosuppressive mechanisms and synergized with aPD-1 in several tumor types. Single-cell RNA-seq analysis revealed predominant C5aR1 expression in TAMs, with an immunosuppressive-related expression signature in C5aR1+TAMs. Furthermore, the combination of C5aR1 and PD-L1 was associated with specific molecular characteristics and matched clinical response annotations. Therefore, the abundance of C5aR1 could predict an inferior prognosis in HGSCs, and incorporating PD-L1 may serve as a novel predictive biomarker to guide therapeutic options.

Genomic analyses of germline and somatic variation in high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 557 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations (SCNA).

RESULTS

Approximately one-third of tumors had loss-of-function (LOF) germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM, and PALB2. LOF germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP, and NF1. In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of LOF variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536, and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival.

CONCLUSIONS

From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 557 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.

MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder

High-grade serous ovarian cancer (HGSOC) is a type of ovarian cancer developed from serous tubal intraepithelial carcinoma. The intrinsic differences among molecular subtypes are closely associated with prognosis and pathological characteristics. At present, multi-omics data integration methods include early integration and late integration. Most existing HGSOC molecular subtypes classification methods are based on the early integration of multi-omics data. The mutual interference among multi-omics data is ignored, which affects the effectiveness of feature learning. High-dimensional multi-omics data contains genes unassociated with HGSOC molecular subtypes, resulting in redundant information, which is not conducive to model training. In this paper, we propose a multi-modal deep autoencoder learning method, MMDAE-HGSOC. MiRNA expression, DNA methylation, and copy number variation (CNV) are integrated with mRNA expression data to construct a multi-omics feature space. The multi-modal deep autoencoder network is used to learn the high-level feature representation of multi-omics data. The superposition LASSO (S-LASSO) regression algorithm is proposed to fully obtain the associated genes of HGSOC molecular subtypes. The experimental results show that MMDAE-HGSOC is superior to the existing classification methods. Finally, we analyze the enrichment gene ontology (GO) terms and biological pathways of these significant genes, which are discovered during the gene selection process.

Molecular cluster mining of high-grade serous ovarian cancer via multi-omics data analysis aids precise medicine

PURPOSE

HGSOC is a kind of gynecological cancer with high mortality and strong heterogeneity. The study used multi-omics and multiple algorithms to identify novel molecular subtypes, which can help patients obtain more personalized treatments.

METHODS

Firstly, the consensus clustering result was obtained using a consensus ensemble of ten classical clustering algorithms, based on mRNA, lncRNA, DNA methylation, and mutation data. The difference in signaling pathways was evaluated using the single-sample gene set enrichment analysis (ssGSEA). Meanwhile, the relationship between genetic alteration, response to immunotherapy, drug sensitivity, prognosis, and subtypes was further analyzed. Finally, the reliability of the new subtype was verified in three external datasets.

RESULTS

Three molecular subtypes were identified. Immune desert subtype (CS1) had little enrichment in the immune microenvironment and metabolic pathways. Immune/non-stromal subtype (CS2) was enriched in the immune microenvironment and metabolism of polyamines. Immune/stromal subtype (CS3) not only enriched anti-tumor immune microenvironment characteristics but also enriched pro-tumor stroma characteristics, glycosaminoglycan metabolism, and sphingolipid metabolism. The CS2 had the best overall survival and the highest response rate to immunotherapy. The CS3 had the worst prognosis and the lowest response rate to immunotherapy but was more sensitive to PARP and VEGFR molecular-targeted therapy. The similar differences among three subtypes were successfully validated in three external cohorts.

CONCLUSION

We used ten clustering algorithms to comprehensively analyze four types of omics data, identified three biologically significant subtypes of HGSOC patients, and provided personalized treatment recommendations for each subtype. Our findings provided novel views into the HGSOC subtypes and could provide potential clinical treatment strategies.

Insights into high-grade serous carcinoma pathobiology using three-dimensional culture model systems

Epithelial ovarian cancer (EOC) research has become more complex as researchers try to fully understand the metastatic process. Especially as we delve into the concept of tumour dormancy, where cells transition between proliferative and dormant states to survive during disease progression. Thus, the in vitro models used to conduct this research need to reflect this vast biological complexity. The innovation behind the many three-dimensional (3D) spheroid models has been refined to easily generate reproducible spheroids so that we may understand the various molecular signaling changes of cells during metastasis and determine therapeutic efficacy of treatments. This ingenuity was then used to develop the 3D ex vivo patient-derived organoid model, as well as multiple co-culture model systems for EOC research. Although, researchers need to continue to push the boundaries of these current models for in vitro and even in vivo work in the future. In this review, we describe the 3D models already in use, where these models can be developed further and how we can use these models to gain the most knowledge on EOC pathogenesis and discover new targeted therapies.

Overexpression of CLDN16 in ovarian cancer is modulated by PI3K and PKC pathways

Epithelial ovarian cancer (EOC) is the gynecological malignant tumor of poorest prognosis and higher mortality rate. Chemotherapy is the base of high-grade serous ovarian cancer (HGSOC) treatment; however, it favors the emergence of chemoresistance and metastasis. Thus, there is an urge to search for new therapeutic targets, such as proteins related to cellular proliferation and invasion. Herein, we investigated the expression profile of claudin-16 (CLDN16 protein and CLDN16 transcript) and its possible functions in EOC. In silico analysis of CLDN16 expression profile was performed using data extracted from GENT2 and GEPIA2 platforms. A retrospective study was carried out with 55 patients to evaluate the expression of CLDN16. The samples were evaluated by immunohistochemistry, immunofluorescence, qRT-PCR, molecular docking, sequencing, and immunoblotting assays. Statistical analyzes were performed using Kaplan-Meier curves, one-way ANOVA, Turkey posttest. Data were analyzed using GraphPad Prism 8.0. In silico experiments showed that CLDN16 is overexpressed in EOC. 80.0% of all EOC types overexpressed CLDN16, of which in 87% of the cases the protein is restricted to cellular cytoplasm. CLDN16 expression was not related to tumor stage, tumor cells differentiation status, tumor responsiveness to cisplatin, or patients' survival rate. When compared to data obtained from in silico analysis regarding EOC stage and degree of differentiation, differences were found in the former but not in the later, neither in survival curves. CLDN16 expression in HGSOC OVCAR-3 cells increased by 1.95-fold (p < 0.001), 2.32-fold (p < 0.001), and 6.57-fold (p < 0.001) via PKC, PI3K, and estrogen pathways, respectively. Altogether, our results suggest that despite the low number of samples included in our in vitro studies, adding to the expression profile findings, we provided a comprehensive study of CLDN16 expression in EOC. Therefore, we hypothesize that CLDN16 is a potential target in the diagnosis and treatment of the disease.

Preoperative prediction of miliary changes in the small bowel mesentery in advanced high-grade serous ovarian cancer using MRI radiomics nomogram

PURPOSE

To develop and validate an MRI-based radiomics nomogram for the preoperative prediction of miliary changes in the small bowel mesentery (MCSBM) in advanced high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

One hundred and twenty-eight patients with pathologically proved  advanced HGSOC (training cohort: n = 91; validation cohort: n = 37) were retrospectively included. All patients were initially evaluated as MCSBM-negative by preoperative imaging modalities but were finally confirmed by surgery and histopathology (MCSBM-positive: n = 53; MCSBM-negative: n = 75). Five radiomics signatures were built based on the features from multisequence magnetic resonance images. Independent clinicoradiological factors and radiomics-fusion signature were further integrated to construct a radiomics nomogram. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves and clinical utility.

RESULTS

Radiomics signatures, ascites, and tumor size were independent predictors of MCSBM. A nomogram integrating radiomics features and clinicoradiological factors demonstrated satisfactory predictive performance with areas under the curves (AUCs) of 0.871 (95% CI 0.801-0.941) and 0.858 (95% CI 0.739-0.976) in the training and validation cohorts, respectively. The net reclassification index (NRI) and integrated discrimination improvement (IDI) revealed that the nomogram had a significantly improved ability compared with the clinical model in the training cohort (NRI = 0.343, p = 0.002; IDI = 0.299, p < 0.001) and validation cohort (NRI = 0.409, p = 0.015; IDI = 0.283, p = 0.001).

CONCLUSION

Our proposed nomogram has the potential to serve as a noninvasive tool for the prediction of MCSBM, which is helpful for the individualized assessment of advanced HGSOC patients.

[Homologous recombination deficiency in epithelial ovarian cancers: from molecular characterization to patient journey]

High-grade serous ovarian carcinoma (HGSOC), the most frequent and aggressive form of epithelial ovarian cancer is characterized in half of cases by homologous recombination deficiency (HRD). This molecular alteration is defined by distinct causes and consequences. The main and most characterized cause is the presence of an alteration affecting BRCA1 and BRCA2 genes. Regarding consequences, a specific genomic instability leads to increased sensitivity to platinum salts and poly (ADP-ribose) polymerase (PARPi) inhibitors. This latter point enabled the advent of PARPi in first and second line maintenance. As such, the initial and rapid evaluation of HRD status with molecular tests is a key step in the management of HGSOC. Until recently, the range of tests offered proved to be very limited and suffered from technical and medical limitations. This has recently led to the development and validation of alternatives, including academic ones. This "state of the art" review will bring a synthesis concerning the assessment of HRD status in HGSOCs. After a brief introduction of HRD (including main causes and consequences) and of its predictive value regarding PARPi, we will discuss the limitations of current molecular tests and the existing alternatives. Finally, we will contextualize this to the situation in France, with special consideration concerning the positioning and the financial coverage of these tests, with the perspective of optimizing patient management .

A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management

BACKGROUND

High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR).

METHODS

A total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves.

RESULTS

Using the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients' age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72-0.92).

CONCLUSIONS

We have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients' care.

DNA methylation of the immediate upstream region of BRCA1 major transcription start sites is an independent favorable prognostic factor in patients with high-grade serous ovarian cancer

OBJECTIVE

To establish a quantitative method to evaluate the DNA methylation level of an immediate upstream region of major BRCA1 transcriptional start sites (TSSs), and to investigate whether methylation of the region is a prognostic factor in high-grade serous ovarian cancer patients after neoadjuvant chemotherapy.

METHODS

Ninety-two FFPE samples of advanced high-grade serous ovarian cancers after neoadjuvant chemotherapy between 2011 and 2018 were used for mutation and methylation analysis. DNA methylation levels were assessed by pyrosequencing and DNA methylation microarray. An association between methylation level (or a mutation) and progression-free survival was assessed by Kaplan-Meier analysis.

RESULT

Major BRCA1 transcripts and CpG sites immediately upstream of their TSSs were identified, and a pyrosequencing method was developed. BRCA1 methylation, BRCA1/2 mutations, and a RAD51C mutation were detected in 17/79 (21.5%), 17/92 (18.5%), and 1/92 (1.1%) high-grade serious ovarian cancer samples. In univariate analysis, BRCA1 methylation and no residual tumor were associated with progression-free survival (BRCA1 methylation: P = 0.025, no residual tumor: P = 0.0026). Multivariate analysis showed that both BRCA1 methylation (P = 0.038, HR = 0.47, 95% CI: 0.21-0.96) and no residual tumor (P = 0.012, HR = 0.49, 95% CI: 0.28-0.85) were significant favorable prognostic factors.

CONCLUSION

A quantitative method to estimate the methylation level of the immediate upstream region of major BRCA1 TSSs was established. Methylation of the region of was an independent favorable prognostic factor in high-grade serous ovarian cancer patients.

Differences between complex epithelial neoplasms of the ovary and high-grade serous ovarian cancer: a retrospective observational cohort study

BACKGROUND

Complex epithelial neoplasms of the ovary (CENO), an uncommon pathological histotype in ovarian cancer, comprises adenosquamous carcinoma and adenocarcinoma with metaplasia. Owing to the rarity of relevant reports, there are currently no statistics on outcomes based on large samples. Meanwhile high-grade serous ovarian cancer (HGSOC) is the most common histotype in ovarian cancer which has a recognized first-line treatment regimen and poor prognosis. Thus, we aimed to determine the characteristics, prognosis, and independent predictors of survival for CENO, compare them with those of HGSOC and construct prognostic predictive models and nomograms.

METHODS

We used the Surveillance, Epidemiology, and End Results (SEER) database to determine patients diagnosed with CENO or HGSOC from 2000 to 2017. Clinical, demographic, and treatment characteristics were compared between these groups. Propensity score matching, Cox risk regression analysis, Kaplan-Meier survival curves, and the Least Absolute Shrinkage and Selection Operator regression analysis were employed for analyzing the data.

RESULTS

Here, 31,567 patients with HGSOC and 216 patients with CENO between 2000 and 2017 in the SEER database were enrolled. Age < 57 years, unmarried, and early-stage diseases were more common in patients with CENO than in those with HGSOC. Women with CENO were less likely to receive adjuvant chemotherapy (65.7% vs. 79.4%) but more likely to receive radiotherapy (6.0% vs. 0.8%; both p < 0.001) than those with HGSOC. Year of diagnosis, surgery status, number of primary tumors, grade, and FIGO stage were independent prognostic factors for overall and cancer-specific survival in CENO. Overall survival rates were significantly lower for CENO than for more malignant HGSOC.

CONCLUSIONS

In summary, CENO was rare in ovarian cancer, while the year of diagnosis, surgery status, number of primary tumors, grade, and FIGO stage were independent prognostic factors. Compared with other common malignant ovarian tumors, CENO had a poor prognosis. Prognostic predictive models and nomograms had been determined to predict the individual survival rates of patients with CENO. These methods could improve evaluations of survival and therapeutic decisions for patients.

TRAF4 promotes the malignant progression of high-grade serous ovarian cancer by activating YAP pathway

High-grade serous ovarian cancer (HGSOC) accounts for the majority of deaths caused by epithelial ovarian cancer. The specific molecular changes attributable to the pathogenesis of HGSOC are still largely unknown. TRAF4 has been identified to be up-regulated in certain cancers. However, the role and mechanism of TRAF4 in HGSOC remain unclear. In this study, we aim to explore the prognostic value and function of TRAF4 in HGSOC. Immunohistochemical staining and prognostic analysis were used to estimate the prognosis value of TRAF4 in HGSOC. Cell counting assays, colony formation assays, sphere formation assays and tumorigenic assays were used to explore the function of TRAF4 in ovarian cancer cells. Furthermore, RNA-seq, qPCR and western blotting were performed to investigate the molecular mechanism of TRAF4 in ovarian cancer cells. The results showed that TRAF4 was significantly higher expressed in ovarian cancer than normal ovarian epithelium. Moreover, high expression of TRAF4 was significantly associated with shorter overall survival and recurrence-free survival in HGSOC. Knockdown of TRAF4 significantly inhibited the proliferation and tumorigenicity of ovarian cancer cells, whereas overexpression of TRAF4 promoted the proliferation and tumorigenicity of ovarian cancer cells both in vitro and in vivo. Mechanistically, our study demonstrated that TRAF4 expression was positively correlated with the YAP pathway gene signatures, and the malignant progression induced by TRAF4 was inhibited after silencing YAP signaling by its selective inhibitor. In conclusion, our findings suggested that TRAF4 promoted the malignant progression of ovarian cancer cells by activating YAP pathway and might serve as a prognostic biomarker for HGSOC.

Are we there yet? An analysis of the prospective biobank for ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the most common subtype of ovarian cancer and is associated with high mortality rates. Surgical outcome is one of the most important prognostic factors. There are no valid biomarkers to identify which patients may benefit from a primary debulking approach.

OBJECTIVE

Our study aimed to discover and validate a predictive panel for surgical outcome of residual tumor mass after first-line debulking surgery.

STUDY DESIGN

Firstly, "In silico" analysis of publicly available datasets identified 200 genes as predictors for surgical outcome. The top selected genes were then validated using the novel Nanostring method, which was applied for the first time for this particular research objective. 225 primary ovarian cancer patients with well annotated clinical data and a complete debulking rate of 60% were compiled for a clinical cohort. The 14 best rated genes were then validated through the cohort, using immunohistochemistry testing. Lastly, we used our biomarker expression data to predict the presence of miliary carcinomatosis patterns.

RESULTS

The Nanostring analysis identified 37 genes differentially expressed between optimal and suboptimal debulked patients (p < 0.05). The immunohistochemistry validated the top 14 genes, reaching an AUC Ø0.650. The analysis for the prediction of miliary carcinomatosis patterns reached an AUC of Ø0.797.

CONCLUSION

The tissue-based biomarkers in our analysis could not reliably predict post-operative residual tumor. Patient and non-patient-associated co-factors, surgical skills, and center experience remain the main determining factors when considering the surgical outcome at primary debulking in high-grade serous ovarian cancer patients.

Impact of neoadjuvant chemotherapy on somatic mutation status in high-grade serous ovarian carcinoma

BACKGROUND

Patients treated with neoadjuvant chemotherapy (NACT) for advanced high-grade serous ovarian carcinoma (HGSC) have a higher rate and shorter time to platinum-resistant recurrence compared to patients treated with primary cytoreductive surgery (PCS) and adjuvant chemotherapy. The purpose of this study is to determine the impact of NACT on somatic mutation status in platinum-sensitive and resistant HGSC. Patients with advanced HGSC who had a documented response to platinum-based NACT, a banked blood sample, and a banked tumor sample before and after NACT were identified. Whole exome and/or targeted deep sequencing was performed in matched normal and pre/post-NACT tumor samples from 3 platinum-resistant and 2 platinum-sensitive patients to identify somatic non-synonymous mutations at each time point.

RESULTS

When comparing exonic non-synonymous mutations in pre-NACT and post-NACT samples from the same patient, an average of 41% (1-68%) of genes were mutated at both time points. There were no trends detected in the mutational burden following exposure to NACT in platinum-resistant vs. platinum-sensitive cases. The majority of mutated genes were unique to each case. We identified several genes that were commonly mutated in pre-NACT samples specific to platinum-resistant (CSPG4, SLC35G5, TUBA3D) or sensitive (CYP2D6, NUTM1, DNAH5) cases. Four mutated genes emerged exclusively in the platinum-resistant cases (ADGRV1, MUC17, MUC20, PAK2) following NACT.

CONCLUSIONS

Patients with advanced HGSC present with significant intra-tumor heterogeneity. NACT significantly impacts the somatic mutation status irrespective of the time to recurrence. The mutated genes detected in chemo-naive pre-NACT tumor samples from either resistant or sensitive cases could potentially have a role in the prediction of chemotherapy response in patients scheduled to receive NACT; larger studies are required to further validate these genes.

Principles of dormancy evident in high-grade serous ovarian cancer

In cancer, dormancy refers to a clinical state in which microscopic residual disease becomes non-proliferative and is largely refractory to chemotherapy. Dormancy was first described in breast cancer where disease can remain undetected for decades, ultimately leading to relapse and clinical presentation of the original malignancy. A long latency period can be explained by withdrawal from cell proliferation (cellular dormancy), or a balance between proliferation and cell death that retains low levels of residual disease (tumor mass dormancy). Research into cellular dormancy has revealed features that define this state. They include arrest of cell proliferation, altered cellular metabolism, and unique cell dependencies and interactions with the microenvironment. These characteristics can be shared by dormant cells derived from disparate primary disease sites, suggesting common features exist between them.

High-grade serous ovarian cancer (HGSOC) disseminates to locations throughout the abdominal cavity by means of cellular aggregates called spheroids. These growth-arrested and therapy-resistant cells are a strong contributor to disease relapse. In this review, we discuss the similarities and differences between ovarian cancer cells in spheroids and dormant properties reported for other cancer disease sites. This reveals that elements of dormancy, such as cell cycle control mechanisms and changes to metabolism, may be similar across most forms of cellular dormancy. However, HGSOC-specific aspects of spheroid biology, including the extracellular matrix organization and microenvironment, are obligatorily disease site specific. Collectively, our critical review of current literature highlights places where HGSOC cell dormancy may offer a more tractable experimental approach to understand broad principles of cellular dormancy in cancer.

Confocal Imaging of Single-Cell Signaling in Orthotopic Models of Ovarian Cancer

Ovarian cancer (OVCA) is frequently detected at late stages of disease, often with dissemination throughout the peritoneal cavity surface, abdomen, and ascites fluid. Tumor signaling via mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) pathways can promote OVCA progression and depend on local microenvironmental cues. To better study OVCA in situ within native tissue contexts, here we describe confocal microscopy techniques to image mouse models of intraperitoneal disease at a single-cell resolution. As a proof of principle demonstration, examples are highlighted for simultaneously imaging tumor vascularization, infiltrating and often immunosuppressive immune cells (tumor-associated macrophages), and OVCA kinase activity.

Mass Cytometry for the Characterization of Individual Cell Types in Ovarian Solid Tumors

Mass cytometry aka Cytometry by Time-Of-Flight (CyTOF) is one of several recently developed multiparametric single-cell technologies designed to address cellular heterogeneity within healthy and diseased tissue. Mass cytometry is an adaptation of flow cytometry in which antibodies are labeled with stable heavy metal isotopes and the readout is by time-of-flight mass spectrometry. With minimal spillover between channels, mass cytometry enables readouts of up to 60 parameters per single cell. Critically, mass cytometry can identify minority cell populations that are lost in bulk tissue analysis. Mass cytometry has been used to great effect for the study of immune cells. We have extended its use to examine single cells within disaggregated solid tissues, specifically freshly resected tubo-ovarian high-grade serous tumors. Here we detail our protocols designed to ensure the production of high-quality single-cell datasets. The methodology can be modified to accommodate the study of other solid tissues.

The prognostic factor for recurrence in advanced-stage high-grade serous ovarian cancer after complete clinical remission: a nested case-control study

BACKGROUND

Women with advanced-stage high-grade serous ovarian cancer (HGSOC) are likely to have a bad prognosis. Relapses are common in patients even with no evidence of disease after primary treatment. We aimed to identify the prognostic factors for disease recurrence in these patients.

METHODS

A nested case-control study was conducted in a large medical center in Southwest China. The primary outcome was recurrence of disease within 3 years after clinical remission (CR). Cox regression was used to calculate the time to event analysis in different groups.

RESULTS

Ninety-seven patients were finally included. Fifty-seven patients (58.8%) relapsed within 3 years after CR. Among all the variables, the difference in posttreatment CA-125 level was statistically significant (P <0.05) between the recurrent group and the progression-free group in both univariate and multivariable analysis. A cutoff value was set at the median level in the recurrent group (10 U/ml) to categorize patients into two arms. In Cox regression, the posttreatment CA-125 level was identified as a prognostic factor for recurrence with an OR of 1.05 (95% CI: 1.02-1.10, P = 0.033). The median time (from initiation of treatment) until relapse was 25 months for patients whose posttreatment CA-125 levels were higher than 10 U/ml, while it was undefined for patients whose posttreatment CA-125 level were ≤ 10 U/ml. Patients with a higher posttreatment CA-125 level showed an increased risk for OC relapse compared to those with a lower posttreatment CA-125 level. Furthermore, as shown in line graphs recording serum CA-125 levels during follow-up in each recurrent case, the increments of serum CA-125 levels were delayed in recurrent OC patients who had a posttreatment CA125 level ≤ 10 U/ml compared with those with a higher CA-125 level.

CONCLUSION

A low serum CA-125 level after primary treatment was a potential prognostic factor in women with advanced HGSOC.

TP53 loss initiates chromosomal instability in fallopian tube epithelial cells

High-grade serous ovarian cancer (HGSOC) originates in the fallopian tube epithelium and is characterized by ubiquitous TP53 mutation and extensive chromosomal instability (CIN). However, direct causes of CIN, such as mutations in DNA replication and mitosis genes, are rare in HGSOC. We therefore asked whether oncogenic mutations that are common in HGSOC can indirectly drive CIN in non-transformed human fallopian tube epithelial cells. To model homologous recombination deficient HGSOC, we sequentially mutated TP53 and BRCA1 then overexpressed MYC. Loss of p53 function alone was sufficient to drive the emergence of subclonal karyotype alterations. TP53 mutation also led to global gene expression changes, influencing modules involved in cell cycle commitment, DNA replication, G2/M checkpoint control and mitotic spindle function. Both transcriptional deregulation and karyotype diversity were exacerbated by loss of BRCA1 function, with whole-genome doubling events observed in independent p53/BRCA1-deficient lineages. Thus, our observations indicate that loss of the key tumour suppressor TP53 is sufficient to deregulate multiple cell cycle control networks and thereby initiate CIN in pre-malignant fallopian tube epithelial cells. This article has an associated First Person interview with the first author of the paper.

Role of integrins in the metastatic spread of high-grade serous ovarian cancer

PURPOSE

Integrins may be involved in the metastatic spread of high-grade serous ovarian cancer (HGSOC) which determines the therapeutical approach and prognosis. We investigated the integrin expression in primary tumor and metastases of advanced HGSOC.

METHODS

The expression of integrin α2, α4, α5, α6, and β1 was assessed by immunostaining in tumor samples of the ovary, omentum, and peritoneum of each patient. Differences in integrin expression among tumor localizations and their association with clinicopathological parameters were examined by Fisher's exact test. The impact of integrin expression on progression-free survival (PFS) and overall survival (OS) was examined by Cox regression and Kaplan-Meier analyses.

RESULTS

Hundred and thirteen tumor samples of 40 HGSOC patients were examined. The expression of the integrins did not differ between the three tumor localizations (all p values > 0.05) with the exception of high expression of integrin α4 in primary tumor and omentum (52.5% versus 47.5%, p = 0.008) and primary tumor and peritoneum (52.5% versus 47.5%, p = 0.050). High expression of integrin α4 in peritoneum was associated with poorer PFS (HR 2.02 95% CI 1.01-4.05, p = 0.047), younger age (p = 0.047), and death (p = 0.046). Median PFS in patients with high expression of integrin α4 was 13.00 months, whereas median PFS in patients without high expression of integrin α4 was 21.00 months (p = 0.040). Expression of other integrins did not correlate with PFS or OS.

CONCLUSION

Expression of integrin α4 may be altered during the metastatic spread of HGSOC and affect prognosis, whereas expression of integrin α2, α5, α6, and β1 did not reveal any prognostic value.

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

BACKGROUND

Poly (ADP)-ribose polymerase (PARP) inhibitors have entered routine clinical practice for the treatment of high-grade serous ovarian cancer (HGSOC), yet the molecular mechanisms underlying treatment response to PARP1 inhibition (PARP1i) are not fully understood.

METHODS

Here, we used unbiased mass spectrometry based proteomics with data-driven protein network analysis to systematically characterize how HGSOC cells respond to PARP1i treatment.

RESULTS

We found that PARP1i leads to pronounced proteomic changes in a diverse set of cellular processes in HGSOC cancer cells, consistent with transcript changes in an independent perturbation dataset. We interpret decreases in the levels of the pro-proliferative transcription factors SP1 and β-catenin and in growth factor signaling as reflecting the anti-proliferative effect of PARP1i; and the strong activation of pro-survival processes NF-κB signaling and lipid metabolism as PARPi-induced adaptive resistance mechanisms. Based on these observations, we nominate several protein targets for therapeutic inhibition in combination with PARP1i. When tested experimentally, the combination of PARPi with an inhibitor of fatty acid synthase (TVB-2640) has a 3-fold synergistic effect and is therefore of particular pre-clinical interest.

CONCLUSION

Our study improves the current understanding of PARP1 function, highlights the potential that the anti-tumor efficacy of PARP1i may not only rely on DNA damage repair mechanisms and informs on the rational design of PARP1i combination therapies in ovarian cancer.

Replication catastrophe is responsible for intrinsic PAR glycohydrolase inhibitor-sensitivity in patient-derived ovarian cancer models

BACKGROUND

Patients with ovarian cancer often present at advanced stage and, following initial treatment success, develop recurrent drug-resistant disease. PARP inhibitors (PARPi) are yielding unprecedented survival benefits for women with BRCA-deficient disease. However, options remain limited for disease that is platinum-resistant and/or has inherent or acquired PARPi-resistance. PARG, the PAR glycohydrolase that counterbalances PARP activity, is an emerging target with potential to selectively kill tumour cells harbouring oncogene-induced DNA replication and metabolic vulnerabilities. Clinical development of PARG inhibitors (PARGi) will however require predictive biomarkers, in turn requiring an understanding of their mode of action. Furthermore, differential sensitivity to PARPi is key for expanding treatment options available for patients.

METHODS

A panel of 10 ovarian cancer cell lines and a living biobank of patient-derived ovarian cancer models (OCMs) were screened for PARGi-sensitivity using short- and long-term growth assays. PARGi-sensitivity was characterized using established markers for DNA replication stress, namely replication fibre asymmetry, RPA foci, KAP1 and Chk1 phosphorylation, and pan-nuclear γH2AX, indicating DNA replication catastrophe. Finally, gene expression in sensitive and resistant cells was also examined using NanoString or RNAseq.

RESULTS

PARGi sensitivity was identified in both ovarian cancer cell lines and patient-derived OCMs, with sensitivity accompanied by markers of persistent replication stress, and a pre-mitotic cell cycle block. Moreover, DNA replication genes are down-regulated in PARGi-sensitive cell lines consistent with an inherent DNA replication vulnerability. However, DNA replication gene expression did not predict PARGi-sensitivity in OCMs. The subset of patient-derived OCMs that are sensitive to single-agent PARG inhibition, includes models that are PARPi- and/or platinum-resistant, indicating that PARG inhibitors may represent an alternative treatment strategy for women with otherwise limited therapeutic options.

CONCLUSIONS

We discover that a subset of ovarian cancers are intrinsically sensitive to pharmacological PARG blockade, including drug-resistant disease, underpinned by a common mechanism of replication catastrophe. We explore the use of a transcript-based biomarker, and provide insight into the design of future clinical trials of PARGi in patients with ovarian cancer. However, our results highlight the complexity of developing a predictive biomarker for PARGi sensitivity.

DNA methylation-based profiling reveals distinct clusters with survival heterogeneity in high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) is the most common type of epigenetically heterogeneous ovarian cancer. Methylation typing has previously been used in many tumour types but not in HGSOC. Methylation typing in HGSOC may promote the development of personalized care. The present study used DNA methylation data from The Cancer Genome Atlas database and identified four unique methylation subtypes of HGSOC. With the poorest prognosis and high frequency of residual tumours, cluster 4 featured hypermethylation of a panel of genes, which indicates that demethylation agents may be tested in this group and that neoadjuvant chemotherapy may be used to reduce the possibility of residual lesions. Cluster 1 and cluster 2 were significantly associated with metastasis genes and metabolic disorders, respectively. Two feature CpG sites, cg24673765 and cg25574024, were obtained through Cox proportional hazards model analysis of the CpG sites. Based on the methylation level of the two CpG sites, the samples were classified into high- and low-risk groups to identify the prognostic information. Similar results were obtained in the validation set. Taken together, these results explain the epigenetic heterogeneity of HGSOC and provide guidance to clinicians for the prognosis of HGSOC based on DNA methylation sites.

Stromal infiltrating mast cells identify immunoevasive subtype high-grade serous ovarian cancer with poor prognosis and inferior immunotherapeutic response

Tumor infiltrating mast cells (TIMs), with pro- or anti-tumorigenic role in different types of malignancies, have been implicated in resistance to anti-PD1 therapy. Here, we aimed to identify the relevance of TIMs with the prognosis, immune contexture, and immunotherapy in high-grade serous ovarian cancer (HGSOC). Tissue microarrays containing 197 HGSOC patients were assessed by immunohistochemistry (IHC) for detecting the expression of mast cell tryptase and other immune markers. Kaplan-Meier curve, log-rank test, and Cox regression model were applied to perform survival analysis. Single-cell RNA-seq analysis and flow cytometric analysis were selected to characterize TIMs. Furthermore, short-term HGSOC organoids were employed to validate the effect of TIMs on anti-PD1 therapy. Abundance of stromal TIMs (sTIMs) predicted dismal prognosis and linked to immunoevasive subtype of HGSOC, characterized by increased infiltration of pro-tumor cells (Treg cells, M2-polarized macrophages, and neutrophils) and impaired anti-tumor immune functions. Intensive inter-cell interactions between TIMs and other immune cells were identified, suggesting potential cross-talks to foster an immunosuppressive microenvironment. Organoids derived from sTIMs-low patients were associated with increased response to anti-PD-1 treatment other than the presence of high sTIMs infiltration. A nomogram, constructed by combining FIGO stage, sTIMs, and PD-L1, with an area under the curve (AUC) for predicting 5-year overall survival of 0.771 was better than that of FIGO staging system of 0.619. sTIMs/PD-L1-based classifier has potential clinical application in predicting prognosis of patients with HGSOC. sTIMs-high tumors correlate with immunosuppressive tumor microenvironment (TME) and possess potential insensitivity to immunotherapy.

Differential gene expression identifies a transcriptional regulatory network involving ER-alpha and PITX1 in invasive epithelial ovarian cancer

Background

The heterogeneous subtypes and stages of epithelial ovarian cancer (EOC) differ in their biological features, invasiveness, and response to chemotherapy, but the transcriptional regulators causing their differences remain nebulous.

Methods

In this study, we compared high-grade serous ovarian cancers (HGSOCs) to low malignant potential or serous borderline tumors (SBTs). Our aim was to discover new regulatory factors causing distinct biological properties of HGSOCs and SBTs.

Results

In a discovery dataset, we identified 11 differentially expressed genes (DEGs) between SBTs and HGSOCs. Their expression correctly classified 95% of 267 validation samples. Two of the DEGs, TMEM30B and TSPAN1, were significantly associated with worse overall survival in patients with HGSOC. We also identified 17 DEGs that distinguished stage II vs. III HGSOC. In these two DEG promoter sets, we identified significant enrichment of predicted transcription factor binding sites, including those of RARA, FOXF1, BHLHE41, and PITX1. Using published ChIP-seq data acquired from multiple non-ovarian cell types, we showed additional regulatory factors, including AP2-gamma/TFAP2C, FOXA1, and BHLHE40, bound at the majority of DEG promoters. Several of the factors are known to cooperate with and predict the presence of nuclear hormone receptor estrogen receptor alpha (ER-alpha). We experimentally confirmed ER-alpha and PITX1 presence at the DEGs by performing ChIP-seq analysis using the ovarian cancer cell line PEO4. Finally, RNA-seq analysis identified recurrent gene fusion events in our EOC tumor set. Some of these fusions were significantly associated with survival in HGSOC patients; however, the fusion genes are not regulated by the transcription factors identified for the DEGs.

Conclusions

These data implicate an estrogen-responsive regulatory network in the differential gene expression between ovarian cancer subtypes and stages, which includes PITX1. Importantly, the transcription factors associated with our DEG promoters are known to form the MegaTrans complex in breast cancer. This is the first study to implicate the MegaTrans complex in contributing to the distinct biological trajectories of malignant and indolent ovarian cancer subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08276-8.

Current update on malignant epithelial ovarian tumors

Epithelial ovarian cancer (EOC) represents the most frequently occurring gynecological malignancy, accounting for more than 70% of ovarian cancer deaths. Preoperative imaging plays an important role in assessing the extent of disease and guides the next step in surgical decision-making and operative planning. In this article, we will review the multimodality imaging features of various subtypes of EOC. We will also discuss the role of imaging in the staging, management, and surveillance of EOC.

The Prevent Ovarian Cancer Program (POCP): Identification of women at risk for ovarian cancer using complementary recruitment approaches

BACKGROUND

Up to 20% of high-grade serous ovarian carcinomas (HGSOC) are hereditary; however, historical uptake of genetic testing is low. We used a unique combination of approaches to identify women in Ontario, Canada, with a first-degree relative (FDR) who died from HGSOC without prior genetic testing, and offer them multi-gene panel testing.

METHODS

From May 2015-Sept 2019, genetic counseling and testing was provided to eligible participants. Two recruitment strategies were employed, including self-identification in response to an outreach campaign and direct targeting of FDRs of deceased HGSOC patients treated at our institution. The rate of pathogenic variants (PV) in established/potential ovarian cancer risk genes and the benefits/challenges of each approach were assessed.

RESULTS

A total of 564 women enrolled in response to our outreach campaign (n = 473) or direct recruitment (n = 91). Mean age at consent was 52 years and 96% did not meet provincial testing criteria. Genetic results were provided to 528 individuals from 458 families. The rate of PVs in ovarian cancer risk genes was highest when FDRs were diagnosed with HGSOC <60 years (9.4% vs. 3.9% ≥ 60y, p = 0.0160). Participants in the outreach vs. direct recruitment cohort had a similar rate of PVs; however, uptake of genetic testing (97% vs. 89%; p = 0.0036) and study completion (95% vs. 87%; p = 0.0062) rates were higher in the former. Eleven participants with pathogenic variants have completed risk-reducing gynecologic surgery, with one stage I HGSOC and two breast cancers identified.

CONCLUSION

Overall PV rates in this large cohort were lower than expected; however, we provide evidence that genetic testing criteria in Ontario should include individuals with a deceased FDR diagnosed with HGSOC <60 years of age.

Chromosome instability is prevalent and dynamic in high-grade serous ovarian cancer patient samples

OBJECTIVE

High-grade serous ovarian cancer (HGSOC) is the most lethal gynaecological malignancy in women with a high level of mortality, metastatic disease, disease recurrence and multi-drug resistance. Many previous studies have focused on characterising genome instability in recurrent resistant HGSOC and while this has advanced our understanding of HGSOC, our fundamental knowledge of the mechanisms driving genome instability remains limited. Chromosome instability (CIN; an increased rate of chromosome gains and losses) is a form of genome instability that is commonly associated with recurrence and multi-drug resistance in many cancer types but has just begun to be characterised in HGSOC.

METHOD

To examine the relationship between CIN and HGSOC, we employed single-cell quantitative imaging microscopy approaches capable of capturing the cell-to-cell heterogeneity associated with CIN, to assess the prevalence and dynamics of CIN within individual and patient-matched HGSOC ascites and solid tumour samples.

RESULTS

CIN occurs in 90.9% of ascites samples and 100% of solid tumours, while in-depth analyses identified statistically significant temporal dynamics within the serial ascites samples. In general, aneuploidy and CIN increase with disease progression and frequently decrease following chemotherapy treatments in responsive disease. Finally, our work identified higher levels of CIN in solid tumours relative to ascites samples isolated from the same individual, which identifies a novel difference existing between solid tumours and ascites samples.

CONCLUSIONS

Our findings provide novel insight into the relationship between CIN and HGSOC, and uncover a previously unknown relationship existing between CIN in solid tumours and metastatic disease (ascites).

Prediction of Platinum-based Chemotherapy Response in Advanced High-grade Serous Ovarian Cancer: ADC Histogram Analysis of Primary Tumors

RATIONALE AND OBJECTIVES

To investigate the feasibility of apparent diffusion coefficient (ADC) histogram analysis of primary advanced high-grade serous ovarian cancer (HGSOC) to predict patient response to platinum-based chemotherapy.

MATERIALS AND METHODS

A total of 70 patients with 102 advanced stage HGSOCs (International Federation of Gynecology and Obstetrics (FIGO) stages III-IV) who received standard treatment of primary debulking surgery followed by the first line of platinum-based chemotherapy were retrospectively enrolled. Patients were grouped as platinum-resistant and platinum-sensitive according to whether relapse occurred within 6 months. Clinical characteristics, including age, pretherapy CA125 level, International Federation of Gynecology and Obstetrics stage, residual tumor, and histogram parameters derived from whole tumor and solid component such as ADC_mean; 10th, 20th, 25th, 30th, 40th, 50th, 60th, 70th, 75th, 80th, 90th percentiles; skewness and kurtosis, were compared between platinum-resistant and platinum-sensitive groups.

RESULTS

No significantly different clinical characteristics were observed between platinum-sensitive and platinum-resistant patients. There were no significant differences in any whole-tumor histogram-derived parameters between the two groups. Significantly higher ADC_mean and percentiles and significantly lower skewness and kurtosis from the solid-component histogram parameters were observed in the platinum-sensitive group when compared with the platinum-resistant group. ADC_mean, skewness and kurtosis showed moderate prediction performances, with areas under the curve of 0.667, 0.733 and 0.616, respectively. Skewness was an independent risk factor for platinum resistance.

CONCLUSION

Pretreatment ADC histogram analysis of primary tumors has the potential to allow prediction of response to platinum-based chemotherapy in patients with advanced HGSOC.

Reduced RBX1 expression induces chromosome instability and promotes cellular transformation in high-grade serous ovarian cancer precursor cells

Despite high-grade serous ovarian cancer (HGSOC) being the most common and lethal gynecological cancer in women, the early etiological events driving disease development remain largely unknown. Emerging evidence now suggests that chromosome instability (CIN; ongoing changes in chromosome numbers) may play a central role in the development and progression of HGSOC. Importantly, genomic amplification of the Cyclin E1 gene (CCNE1) contributes to HGSOC pathogenesis in ~20% of patients, while Cyclin E1 overexpression induces CIN in model systems. Cyclin E1 levels are normally regulated by the SCF (SKP1-CUL1-FBOX) complex, an E3 ubiquitin ligase that includes RBX1 as a core component. Interestingly, RBX1 is heterozygously lost in ~80% of HGSOC cases and reduced expression corresponds with worse outcomes, suggesting it may be a pathogenic event. Using both short (siRNA) and long (CRISPR/Cas9) term approaches, we show that reduced RBX1 expression corresponds with significant increases in CIN phenotypes in fallopian tube secretory epithelial cells, a cellular precursor of HGSOC. Moreover, reduced RBX1 expression corresponds with increased Cyclin E1 levels and anchorage-independent growth. Collectively, these data identify RBX1 as a novel CIN gene with pathogenic implications for HGSOC.

Development of a 3D functional assay and identification of biomarkers, predictive for response of high-grade serous ovarian cancer (HGSOC) patients to poly-ADP ribose polymerase inhibitors (PARPis): targeted therapy

Background

Poly(ADP-ribose) polymerase inhibitors (PARPis) specifically target homologous recombination deficiency (HRD) cells and display good therapeutic effect in women with advanced-stage BRCA1/2-mutated breast and epithelial ovarian cancer (EOC). However, about 50% of high grade serous ovarian cancers (HGSOC) present with HRD due to epigenetic BRCA1 inactivation, as well as genetic/epigenetic inactivation(s) of other HR genes, a feature known as “BRCAness”. Therefore, there is a potential for extending the use of PARPis to these patients if HR status can be identified.

Methods

We have developed a 3D (spheroid) functional assay to assess the sensitivity of two PARPis (niraparib and olaparib) in ascites-derived primary cell cultures (AsPCs) from HGSOC patients. A method for AsPCs preparation was established based on a matrix (agarose), allowing for easy isolation and successive propagation of monolayer and 3D AsPCs. Based on this method, we performed cytotoxicity assays on 42 AsPCs grown both as monolayers and spheroids.

Results

The response to PARPis treatment in monolayer AsPCs, was significantly higher, compared to 3D AsPCs, as 88% and 52% of the monolayer AsPCs displayed sensitivity to niraparib and olaparib respectively, while 66% of the 3D AsPCs were sensitive to niraparib and 38% to olaparib, the latter being more consistent with previous estimates of HRD (40%–60%) in EOC. Moreover, niraparib displayed a significantly stronger cytotoxic effect in both in 3D and monolayer AsPCs, which was confirmed by consecutive analyses of the HR pathway activity (γH2AX foci formation) in PARPis-sensitive and resistant AsPCs. Global gene expression comparison of 6 PARPi-resistant and 6 PARPi-sensitive 3D AsPCs was indicative for the predominant downregulation of numerous genes and networks with previously demonstrated roles in EOC chemoresistance, suggesting that the PARPis-sensitive AsPCs could display enhanced sensitivity to other chemotherapeutic drugs, commonly applied in cancer management. Microarray data validation identified 24 potential gene biomarkers associated with PARPis sensitivity. The differential expression of 7 selected biomarkers was consecutively confirmed by immunohistochemistry in matched EOC tumor samples.

Conclusion

The application of this assay and the potential biomarkers with possible predictive significance to PARPis therapy of EOC patients now need testing in the setting of a clinical trial.

Early-stage clear cell ovarian cancer compared to high-grade histological subtypes: An outcome exploratory analysis in two oncology centers

OBJECTIVE

advanced stage clear cell ovarian cancer (CCOC) carries a higher risk of relapse and death compared to other histological subtypes. The prognosis of early-stage CCOC is controversial.

METHODS

Early-stage high-grade OC patients from two Italian oncologic centers were included. Patients with early-stage CCOC were compared with those with high-grade endometrioid (HGE) and serous (HGS) OC in terms of relapse-free interval (RFI), cancer-specific survival (CSS) and post relapse cancer-specific survival (prCSS). The Cox proportional hazard model and the restricted mean survival time were used.

RESULTS

Between 1981 and 2012, 134 patients with CC, 152 with HGE and 160 with HGS were treated at two referral centers. Median follow-up was 11.5 years. Ten years RFI rates were 80.6%, 72.1%, 60.6%, and CSS rates were 84.3%, 82.6%, 81.7% respectively. Adjuvant chemotherapy significantly improved RFI (aHR 0.61, 95%CI 0.40 to 0.91, P = 0.015). In the multivariable analysis HGS histotype was associated with a shorter RFI compared to CC, (Hazard Ratio [HR]: 1.81; 95%CI: 1.12-2.93; P = 0.016), whereas CSS was not statistically different. prCSS was longer in HGS compared to CCOC (HR, 0.36; 95% CI, 0.17-0.74; P = 0.006). According to the stage, IA/IB/IC1 HGSOC had a shorter RFI (HR, 2.13; 95% CI, 1.14-3.99; P = 0.018) compared to IA/IB/IC1 CCOC, but similar CSS. For prCSS, CC compared to HGS conferred a worse prognosis regardless of the initial stage.

CONCLUSIONS

Early-stage CCOC is associated with a longer RFI, similar CSS and a shorter prCSS compared to HGSOC. No prognostic differences were observed between CC and HGE OC. The relapse risk was the lowest in IA/IB/IC1 CC compared to HGS, whereas CC displayed poor sensitivity to chemotherapy after relapse.

High density of stroma-localized CD11c-positive macrophages is associated with longer overall survival in high-grade serous ovarian cancer

OBJECTIVE

Pre-clinical studies have identified marker- and tumor compartment-defined functionally distinct macrophage subsets. Our study analyzes marker-defined macrophage subsets in different tumor compartments of high-grade serous ovarian cancer (HGSC).

METHODS

A discovery cohort (N = 113) was subjected to immunohistochemistry (IHC) analyses. CD68-positivity was confirmed for CD11c-, CD80- and CD163-positive cells. Subset-marker-positive cells were scored in the total tumor and in four tumor compartments. Correlation analyses investigated co-expression of subsets, relationship to CD8⁺ cells and survival associations. A validation cohort (N = 121) was used to confirm selected findings from the discovery cohort.

RESULTS

CD163-positve cells was the most abundant subtype in all compartments. CD11c and CD163 subsets were strongly correlated with each other in stroma and epithelial areas, whereas CD80 and CD163 were correlated in epithelial areas. CD80 and CD11c in perivascular areas showed low correlations. Strong associations were detected between CD8 and CD80 in the tumor epithelium-dominated areas, and between CD8 and CD11c in stroma areas. High stromal CD11c density was associated with a longer median overall survival in the discovery cohort (HR 0.39; CI 95%, 0.23-0.68; p = 0.001) and in the validation cohort (HR 0.46; CI 95%, 0.22-0.93; p = 0.03).

CONCLUSIONS

Our study supports the existence of clinically relevant marker- and localization defined macrophage subsets in HGSC, which are independently regulated. Moreover, it suggests stromal CD11c as a novel prognostic marker in HGSC.

Ceramide synthase 6 predicts poor prognosis and activates the AKT/mTOR/4EBP1 pathway in high-grade serous ovarian cancer

Objective: Ovarian cancer is one of the most common gynecological malignancies worldwide, and its mortality rate ranks first among gynecologic cancers. Ceramide synthases are closely related to cancer development. In this study, we investigated the role of ceramide synthase 6 (CerS6) in the development of serous ovarian cancer. Methods: Expression of CerS6 in cancerous and healthy ovarian tissue was assessed by database analysis and immunohistochemistry. The biological role of CerS6 in serous ovarian cancer cells was assessed by CerS6 knockdown followed by cell counting, colony formation, transwell migration, wound healing, and flow cytometry assays and measurement of tumor proliferation in nude mice. Signaling pathway components were analyzed by Western blotting. Gene enrichment was analyzed by GSEA and R, and RNA sequencing was used to compare the transcriptomes of serous ovarian cancer cells with and without CerS6 knockdown. Results: High CerS6 expression in ovarian cancer tissues was closely related to poor prognosis. Knockdown of CerS6 inhibited serous ovarian cancer cell proliferation, invasion, and metastasis and promoted their apoptosis. In addition, CerS6 knockdown increased the proportion of serous ovarian cancer cells in G2/M phase. CerS6 regulates cell cycle through the AKT/mTOR/4EBP1 signaling pathway, which affects cell proliferation and metastasis. The GSEA, R, and RNA sequencing analyses showed that knocking down CerS6 significantly affects cell cycle in serous ovarian cancer cells. Conclusions: CerS6 may have an oncogenic role in ovarian cancer and may represent a new prognostic marker and therapeutic target for serous ovarian cancer.

Development and validation of prognostic gene signature for basal-like breast cancer and high-grade serous ovarian cancer

PURPOSE

Molecular similarities have been reported between basal-like breast cancer (BLBC) and high-grade serous ovarian cancer (HGSOC). To date, there have been no prognostic biomarkers that can provide risk stratification and inform treatment decisions for both BLBC and HGSOC. In this study, we developed a molecular signature for risk stratification in BLBC and further validated this signature in HGSOC.

METHODS

RNA-seq data was downloaded from The Cancer Genome Atlas (TCGA) project for 190 BLBC and 314 HGSOC patients. Analyses of differentially expressed genes between recurrent vs. non-recurrent cases were performed using different bioinformatics methods. Gene Signature was established using weighted linear combination of gene expression levels. Their prognostic performance was evaluated using survival analysis based on progression-free interval (PFI) and disease-free interval (DFI).

RESULTS

63 genes were differentially expressed between 18 recurrent and 40 non-recurrent BLBC patients by two different methods. The recurrence index (RI) calculated from this 63-gene signature significantly stratified BLBC patients into two risk groups with 38 and 152 patients in the low-risk (RI-Low) and high-risk (RI-High) groups, respectively (p = 0.0004 and 0.0023 for PFI and DFI, respectively). Similar performance was obtained in the HGSOC cohort (p = 0.0131 and 0.004 for PFI and DFI, respectively). Multivariate Cox regression adjusting for age, grade, and stage showed that the 63-gene signature remained statistically significant in stratifying HGSOC patients (p = 0.0005).

CONCLUSION

A gene signature was identified to predict recurrence in BLBC and HGSOC patients. With further validation, this signature may provide an additional prognostic tool for clinicians to better manage BLBC, many of which are triple-negative and HGSOC patients who are currently difficult to treat.