Personalising Treatment for High-Grade Serous Ovarian Carcinoma

Residual ANTXR1+ myofibroblasts after chemotherapy inhibit anti-tumor immunity via YAP1 signaling pathway

Although cancer-associated fibroblast (CAF) heterogeneity is well-established, the impact of chemotherapy on CAF populations remains poorly understood. Here we address this question in high-grade serous ovarian cancer (HGSOC), in which we previously identified 4 CAF populations. While the global content in stroma increases in HGSOC after chemotherapy, the proportion of FAP+ CAF (also called CAF-S1) decreases. Still, maintenance of high residual CAF-S1 content after chemotherapy is associated with reduced CD8+ T lymphocyte density and poor patient prognosis, emphasizing the importance of CAF-S1 reduction upon treatment. Single cell analysis, spatial transcriptomics and immunohistochemistry reveal that the content in the ECM-producing ANTXR1+ CAF-S1 cluster (ECM-myCAF) is the most affected by chemotherapy. Moreover, functional assays demonstrate that ECM-myCAF isolated from HGSOC reduce CD8+ T-cell cytotoxicity through a Yes Associated Protein 1 (YAP1)-dependent mechanism. Thus, efficient inhibition after treatment of YAP1-signaling pathway in the ECM-myCAF cluster could enhance CD8+ T-cell cytotoxicity. Altogether, these data pave the way for therapy targeting YAP1 in ECM-myCAF in HGSOC.

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.

Anti-Tumoral Effect of Chemerin on Ovarian Cancer Cell Lines Mediated by Activation of Interferon Alpha Response

Simple Summary

Chemerin is a multifunctional protein with an important role in the immune system. Recent evidence showed that chemerin also regulates the development of cancer. Ovarian cancer is a common type of tumor in women. In this study, we observed that chemerin decreases the growth of ovarian cancer cell lines in vitro when cultivated in standard cell culture or in globular multicellular aggregates. When we examined the mechanisms involved in this process, we found that treatment of ovarian cancer cells with chemerin led to the activation of genes that are known to mediate the effects of interferon alpha (IFNα). The main effect of IFNα is to defend body cells against viral infections, but it is also able to defeat cancer cells. We observed that this activation of IFNα response by chemerin resulted from the increased production of IFNα protein in ovarian cancer cells, which then reduced cancer cells numbers. However, it remains to be investigated how exactly chemerin might be able to activate interferon alpha and its anti-tumoral actions.

Abstract

The pleiotropic adipokine chemerin affects tumor growth primarily as anti-tumoral chemoattractant inducing immunocyte recruitment. However, little is known about its effect on ovarian adenocarcinoma. In this study, we examined chemerin actions on ovarian cancer cell lines in vitro and intended to elucidate involved cell signaling mechanisms. Employing three ovarian cancer cell lines, we observed differentially pronounced effects of this adipokine. Treatment with chemerin (huChem-157) significantly reduced OVCAR-3 cell numbers (by 40.8% on day 6) and decreased the colony and spheroid growth of these cells by half. The spheroid size of SK-OV-3 ovarian cancer cells was also significantly reduced upon treatment. Transcriptome analyses of chemerin-treated cells revealed the most notably induced genes to be interferon alpha (IFNα)-response genes like IFI27, OAS1 and IFIT1 and their upstream regulator IRF9 in all cell lines tested. Finally, we found this adipokine to elevate IFNα levels about fourfold in culture medium of the employed cell lines. In conclusion, our data for the first time demonstrate IFNα as a mediator of chemerin action in vitro. The observed anti-tumoral effect of chemerin on ovarian cancer cells in vitro was mediated by the notable activation of IFNα response genes, resulting from the chemerin-triggered increase of secreted levels of this cytokine.

ACSM3 suppresses the pathogenesis of high-grade serous ovarian carcinoma via promoting AMPK activity

PURPOSE

Ovarian carcinoma is the fifth commonest malignancy in females and exhibits a high recurrence rate. High-grade serous ovarian carcinoma (HGSOC) is the main histologic subtype. It displays extensive genetic heterogeneity. Here, we aimed to identify potential therapeutic targets for HGSOC.

METHODS

Both bioinformatic data from TCGA and 73 pairs of tumor and normal samples from patients were analyzed to reveal the expression level of ACSM3 in HGSOC. Next, cellular and animal experiments, including cell proliferation, colony formation and xenograft assays were performed to explore the suppressive function of ACSM3. Finally, biochemical methods, AMP/ATP ratio measurements and Western blotting were used to elucidate the mechanism underlying the ACSM3-AMPK axis in HGSOC.

RESULTS

After analyzing transcriptome data of TCGA HGSOC samples, we found that ACSM3 is down-regulated in patient samples compared with normal controls. This observation was validated using data from primary clinical samples. Proliferation, soft agar colony formation and xenograft assays revealed that ACSM3 is able to suppress HGSOC tumor growth both in vitro and in vivo. Moreover, we found that ACSM3 overexpression increased the AMP/ATP ratio and the phosphorylation level of AMPK at threonine 172. In addition, we found that AMPK silencing in EFO21 and SKOV3 cells completely abolished the anti-oncogenic effect of ACSM3.

CONCLUSION

Our data indicate that the ACSM3-AMPK axis is involved in the pathogenesis of HGSOC and, as such, may act as a therapeutic target for this cancer.

Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology

The reach of personalized medicine in radiation oncology has expanded greatly over the past few decades as technical precision has improved the delivery of radiation to each patient's unique anatomy. Yet, the consideration of biological heterogeneity between patients has largely not been translated to clinical care. There are innumerable promising advancements in the discovery and validation of biomarkers, which could be used to alter radiation therapy directly or indirectly. Directly, biomarker-informed care may alter treatment dose or identify patients who would benefit most from radiation therapy and who could safely avoid more aggressive care. Indirectly, a variety of biomarkers could assist with choosing the best radiosensitizing chemotherapies. The translation of these advancements into clinical practice will bring radiation oncology even further into the era of precision medicine, treating patients according to their unique anatomical and biological differences.

An Immune-Related Gene-Based Signature as Prognostic Tool in Ovarian Serous Cystadenocarcinoma

Background

Ovarian serous cystadenocarcinoma (OSCC) is a life-threatening malignancy with poor prognosis. Therefore, the identification of immune-related genes associated with OSCC prognosis may reveal new targets of immunotherapy for OSCC.

Patients and Methods

The gene expression profiles of overlapped genes were extracted by weighted gene co-expression network analysis (WGCNA) to identify immune-related modules. Significant genes were identified by univariate Cox regression analysis of model genes. Model characteristic genes were obtained by least absolute shrinkage and selection operator (LASSO) analysis and used to calculate a “signature index”. The model’s ability to predict prognosis in OSCC patients was assessed using time-dependent receiver operator characteristic curves. Differences in the biological processes and Kyoto Encyclopedia of Genes and Genomes pathways between groups with high or low signature index were assessed using gene set enrichment analysis (GSEA). The types of immune cells and their abundance in the two index groups were explored by single-sample GSEA.

Results

The expression profiles of 3517 overlapped genes were extracted by WGCNA, and nine modules related to the immune system of OSCC were obtained. The expression profiles of 114 hub genes were then subjected to LASSO analysis. Among them, 10 immune-related genes were significant, of which six were identified as model characteristic genes and were used to calculate the signature index. Moreover, 24 types of immune cells were identified in the tumor microenvironment, and their abundance was explored in high- and low-signature index groups of two datasets.

Conclusion

ARHGEF18, PLEKHA7, MTOR, VPS45, BRCA1, and HINT2 were identified as characteristic genes and used to develop a new immune-related gene-based signature as a promising prognostic biomarker for OSCC.

Immune Modeling Analysis Reveals Immunologic Signatures Associated With Improved Outcomes in High Grade Serous Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy worldwide, as patients are typically diagnosed at a late stage and eventually develop chemoresistant disease following front-line platinum-taxane based therapy. Only modest results have been achieved with PD-1 based immunotherapy in ovarian cancer patients, despite the fact that immunological responses are observed in EOC patients. Therefore, the goal of this present study was to identify novel immune response genes and cell subsets significantly associated with improved high grade serous ovarian cancer (HGSOC) patient prognosis. A transcriptomic-based immune modeling analysis was employed to determine levels of 8 immune cell subsets, 10 immune escape genes, and 22 co-inhibitory/co-stimulatory molecules in 26 HGSOC tumors. Multidimensional immune profiling analysis revealed CTLA-4, LAG-3, and Tregs as predictive for improved progression-free survival (PFS). Furthermore, the co-stimulatory receptor ICOS was also found to be significantly increased in patients with a longer PFS and positively correlated with levels of CTLA-4, PD-1, and infiltration of immune cell subsets. Both ICOS and LAG-3 were found to be significantly associated with improved overall survival in The Cancer Genome Atlas (TCGA) ovarian cancer cohort. Finally, PVRL2 was identified as the most highly expressed transcript in our analysis, with immunohistochemistry results confirming its overexpression in HGSOC samples compared to normal/benign. Results were corroborated by parallel analyses of TCGA data. Overall, this multidimensional immune modeling analysis uncovers important prognostic immune factors that improve our understanding of the unique immune microenvironment of ovarian cancer.

FOXM1 Inhibition in Ovarian Cancer Tissue Cultures Affects Individual Treatment Susceptibility Ex Vivo

Simple Summary

Late diagnosis of ovarian cancer is a major reason for the high mortality rate of this tumor entity. The time to determine tumor susceptibility to treatment is scarce and resistance to therapy occurs very frequently. Here, we aim for a model system that can determine tumor response to (I) study novel drugs and (II) enhance patient stratification. Tissue specimens (n = 10) were acquired from fresh surgical samples. Tissue cultures were cultivated and treated with clinically relevant therapeutics and an FOXM1 inhibitor for 3–6 days. The transcription factor FOXM1 is a key regulator of tumor survival affecting multiple cancerogenic target genes. Gene expression of FOXM1 and its targets BRCA1/2 and RAD51 were investigated together with tumor susceptibility. Tissue cultures successfully demonstrated the individual benefit of FOXM1 inhibition and revealed the potency of the complex model system for oncological research.

Abstract

Diagnosis in an advanced state is a major hallmark of ovarian cancer and recurrence after first line treatment is common. With upcoming novel therapies, tumor markers that support patient stratification are urgently needed to prevent ineffective therapy. Therefore, the transcription factor FOXM1 is a promising target in ovarian cancer as it is frequently overexpressed and associated with poor prognosis. In this study, fresh tissue specimens of 10 ovarian cancers were collected to investigate tissue cultures in their ability to predict individual treatment susceptibility and to identify the benefit of FOXM1 inhibition. FOXM1 inhibition was induced by thiostrepton (3 µM). Carboplatin (0.2, 2 and 20 µM) and olaparib (10 µM) were applied and tumor susceptibility was analyzed by tumor cell proliferation and apoptosis in immunofluorescence microscopy. Resistance mechanisms were investigated by determining the gene expression of FOXM1 and its targets BRCA1/2 and RAD51. Ovarian cancer tissue was successfully maintained for up to 14 days ex vivo, preserving morphological characteristics of the native specimen. Thiostrepton downregulated FOXM1 expression in tissue culture. Individual responses were observed after combined treatment with carboplatin or olaparib. Thus, we successfully implemented a complex tissue culture model to ovarian cancer and showed potential benefit of combined FOXM1 inhibition.

Upfront debulking surgery for high-grade serous ovarian carcinoma: current evidence

High-grade serous ovarian carcinoma (HGSOC) is a leading cause of mortality among women worldwide. Currently, there is no clear consensus over the regime these patients should receive. The main two options are upfront debulking surgery with adjuvant chemotherapy or neoadjuvant chemotherapy followed by interval debulking surgery (IDS). The former approach is proposed to be accompanied by lower chemoresistance rates but could lead to severe surgical comorbidities and lower quality of life (QoL). Optimizing patient’s selection for upfront debulking surgery might offer higher progression-free and overall survival rates. Further studies need to be conducted in order to elucidate the predictive factors, which are favorable for patients undergoing upfront debulking surgery in cases of high-grade serous ovarian cancer.

The Perfect Combination: Enhancing Patient Response to PD-1-Based Therapies in Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy, with an overall 5-year survival of only 47%. As the development of novel targeted therapies is drastically necessary in order to improve patient survival, current EOC clinical trials have heavily focused on immunotherapeutic approaches, centered upon programmed cell death 1 (PD-1) inhibitors. While PD-1 monotherapies have only exhibited modest responses for patients, it has been theorized that in order to enhance EOC patient response to immunotherapy, combinatorial regimens must be investigated. In this review, unique challenges to EOC PD-1 response will be discussed, along with a comprehensive description of both preclinical and clinical studies evaluating PD-1-based combinatorial therapies. Promising aspects of PD-1-based combinatorial approaches are highlighted, while also discussing specific preclinical and clinical areas of research that need to be addressed, in order to optimize EOC patient immunotherapy response.

The biomarker HE4 (WFDC2) promotes a pro-angiogenic and immunosuppressive tumor microenvironment via regulation of STAT3 target genes

Epithelial ovarian cancer (EOC) is a highly lethal gynecologic malignancy arising from the fallopian tubes that has a high rate of chemoresistant recurrence and low five-year survival rate. The ovarian cancer biomarker HE4 is known to promote proliferation, metastasis, chemoresistance, and suppression of cytotoxic lymphocytes. In this study, we sought to examine the effects of HE4 on signaling within diverse cell types that compose the tumor microenvironment. HE4 was found to activate STAT3 signaling and promote upregulation of the pro-angiogenic STAT3 target genes IL8 and HIF1A in immune cells, ovarian cancer cells, and endothelial cells. Moreover, HE4 promoted increases in tube formation in an in vitro model of angiogenesis, which was also dependent upon STAT3 signaling. Clinically, HE4 and IL8 levels positively correlated in ovarian cancer patient tissue. Furthermore, HE4 serum levels correlated with microvascular density in EOC tissue and inversely correlated with cytotoxic T cell infiltration, suggesting that HE4 may cause deregulated blood vessel formation and suppress proper T cell trafficking in tumors. Collectively, this study shows for the first time that HE4 has the ability to affect signaling events and gene expression in multiple cell types of the tumor microenvironment, which could contribute to angiogenesis and altered immunogenic responses in ovarian cancer.

Murine Oviductal High-Grade Serous Carcinomas Mirror the Genomic Alterations, Gene Expression Profiles, and Immune Microenvironment of Their Human Counterparts

Robust preclinical models of ovarian high-grade serous carcinoma (HGSC) are needed to advance our understanding of HGSC pathogenesis and to test novel strategies aimed at improving clinical outcomes for women with the disease. Genetically engineered mouse models of HGSC recapitulating the likely cell of origin (fallopian tube), underlying genetic defects, histology, and biologic behavior of human HGSCs have been developed. However, the degree to which the mouse tumors acquire the somatic genomic changes, gene expression profiles, and immune microenvironment that characterize human HGSCs remains unclear. We used integrated molecular characterization of oviductal HGSCs arising in the context of Brca1, Trp53, Rb1, and Nf1 (BPRN) inactivation to determine whether the mouse tumors recapitulate human HGSCs across multiple domains of molecular features. Targeted DNA sequencing showed the mouse BPRN tumors, but not endometrioid carcinoma-like tumors based on different genetic defects (e.g., Apc and Pten), acquire somatic mutations and widespread copy number alterations similar to those observed in human HGSCs. RNA sequencing showed the mouse HGSCs most closely resemble the so-called immunoreactive and mesenchymal subsets of human HGSCs. A combined immuno-genomic analysis demonstrated the immune microenvironment of BPRN tumors models key aspects of tumor-immune dynamics in the immunoreactive and mesenchymal subtypes of human HGSC, with enrichment of immunosuppressive cell subsets such as myeloid-derived suppressor cells and regulatory T cells. The findings further validate the BPRN model as a robust preclinical experimental platform to address current barriers to improved prevention, diagnosis, and treatment of this often lethal cancer. SIGNIFICANCE: The acquired gene mutations, broad genomic alterations, and gene expression and immune cell-tumor axis changes in a mouse model of oviductal serous carcinoma closely mirror those of human tubo-ovarian high-grade serous carcinoma.

The Metabolic Inhibitor CPI-613 Negates Treatment Enrichment of Ovarian Cancer Stem Cells

One of the most significant therapeutic challenges in the treatment of ovarian cancer is the development of recurrent platinum-resistant disease. Cancer stem cells (CSCs) are postulated to contribute to recurrent and platinum-resistant ovarian cancer (OvCa). Drugs that selectively target CSCs may augment the standard of care cytotoxics and have the potential to prevent and/or delay recurrence. Increased reliance on metabolic pathway modulation in CSCs relative to non-CSCs offers a possible therapeutic opportunity. We demonstrate that treatment with the metabolic inhibitor CPI-613 (devimistat, an inhibitor of tricarboxylic acid (TCA) cycle) in vitro decreases CD133+ and CD117+ cell frequency relative to untreated OvCa cells, with negligible impact on non-CSC cell viability. Additionally, sphere-forming capacity and tumorigenicity in vivo are reduced in the CPI-613 treated cells. Collectively, these results suggest that treatment with CPI-613 negatively impacts the ovarian CSC population. Furthermore, CPI-613 impeded the unintended enrichment of CSC following olaparib or carboplatin/paclitaxel treatment. Collectively, our results suggest that CPI-613 preferentially targets ovarian CSCs and could be a candidate to augment current treatment strategies to extend either progression-free or overall survival of OvCa.