Ovarian Cancer Tumor Microenvironment Research Articles

Abstract A103: Improved cell phenotyping of ovarian cancer tumor microenvironment

Abstract Introduction: Multiplexed imaging at single-cell resolution is becoming widely used to decipher the role of the cellular microenvironment in cancer and other complex diseases. To identify spatial patterns of single cells on a tissue, accurate cell-type phenotyping is a crucial step. We present Tribus, an interactive, semi-supervised classifier that avoids thresholds and manual labeling, with user-friendly visualization of the results and automated quality control reports. Materials and Methods: We developed Tribus, an open-source Python 3 software utilizing self-organizing maps for data clustering with an integrated Napari plug-in for fast visualization. It assigns the cell phenotypes based on user-defined label description tables and median marker expressions, following a hierarchical structure to minimize overspill bias. It has a modular architecture and can be run via command line, Jupyter Notebook, or the Napari interface. For exploring the Tribus performance, we used 1) manually expert annotated datasets with different tissue origins 2) dataset with cluster-based annotation 3) previously unpublished dataset. To ensure usability, we utilized datasets generated by using different multiplexed imaging technologies, and of variable size including large tissue microarrays and whole-slide images. Results: Using Tribus we accurately annotated the cell phenotypes in an expert-labeled Co-detection by indexing (CODEX) dataset, consisting of 8 regions of tissue samples from a single donor, including both healthy colon and small bowel sections. Tribus analysis of a high-grade ovarian cancer (HGSC) tumor microarray dataset generated by tCyCIF revealed a subset of lymphoid cells previously mislabelled using a cluster annotation approach. Finally, we utilized Tribus for deep cell phenotyping on a large whole-slide image tCyCIF dataset consisting of over a million cells from five matched HGSC samples collected before and after neoadjuvant chemotherapy (NACT). In the paired samples we successfully identified cell subtypes crucial for immune surveillance. Our analysis accurately differentiated M1 and M2 macrophage subpopulations. In addition, the analyzed post-NACT samples showed a higher proportion of tumor-infiltrating CD8+ T-cells, interestingly displaying occasional spatial clusters by the tumor borders. Therefore, Tribus has shown a great potential to study the spatial patterns and cell-cell interactions of relevant immune cells in response to neoadjuvant chemotherapy treatment. Conclusion: Overall, Tribus is an accurate, fast and efficient way to analyze different sizes of datasets across different technologies, resulting in accelerated analysis of the spatial tumor microenvironment (TME). The accurate cell-type phenotyping with Tribus uncovered high-resolution cellular phenotypes and their spatial patterns in the TME in ovarian cancer after neoadjuvant chemotherapy. Citation Format: Ziqi Kang, Teodora Farago, Angela Szabo, Inga-Maria Launonen, Fernando Perez, Ella Anttila, Kevin Elias, Julia Casado, Peter Sorger, Anniina Färkkilä. Improved cell phenotyping of ovarian cancer tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A103.

Abstract A080: CD8+T-cell interplay with myeloid cells as spatial determinant of chemotherapy response in the tumor microenvironment of metastatic high-grade serous ovarian cancer

Abstract Our goal was to characterize the effects of chemotherapy on the tumor microenvironment of high-grade serous ovarian cancer (HGSC) and suggest effective combination treatment strategies. We employed comprehensive multiomic spatial and single-cell profiling techniques, including tissue cyclic immunofluorescence t-CycIF, scRNA sequencing, and spatial transcriptomics (GeoMx) to characterize the tumor microenvironment of a total of 70 HGSC samples obtained from 41 patients from our prospective, observational trials (DECIDER, ONCOSYS-OVA). The longitudinal samples were collected before and after neoadjuvant chemotherapy (NACT), and they predominantly originated from intra-abdominal metastases. Utilizing cell type calls from whole slide t-CycIF high-dimensional marker expression data, we observed a significant increase in antigen presentation in IBA1+CD11c+ macrophages and CD11c+ myeloid cells interacting with CD4+ and interferon activated CD8+T-cells following NACT. These interactions formed spatial gradients within the tissues. To further investigate spatial heterogeneity, we identified recurring cellular neighborhoods using spatial clustering of cell types across all samples. These multicellular structures exhibited varying proportions of the 18 different cell types. Four out of five immune hotspot neighborhoods primarily comprised different myeloid cells. Interestingly, while the expression of the terminal exhaustion marker TIM3 did not differ in CD8+T-cells overall between the pre- and post-chemotherapy samples, TIM3 expression was specifically higher in CD8+T-cells in myeloid cell-rich neighborhoods from the post-chemotherapy samples, highlighting spatially restricted exhaustion patterns in HGSC. Notably, the most significant differences in overall cell type composition and cell-cell interaction patterns in samples collected before and after NACT were observed in the neighborhood corresponding to the tumor-stromal interface. CD8+T-cells exhibited higher-than-expected interactions with various myeloid cells, while their interactions with tumor cells were lower-than-expected, suggesting potential immune modulation following chemotherapy. Ligand-receptor analysis using paired site-matched scRNAseq data revealed upregulation of chemokines CXCL5 and CCL7 in macrophages after NACT, potentially induced by TNF from tumor cells. Spatial transcriptomics analysis provided further insights into the gene expression programs occurring between macrophages, CD8+T-cells, and tumor cells localized at the tumor-stromal interface. The prognostic power of the main findings were tested in bulk RNA-seq data from 33 patients treated with NACT. In conclusion, our findings indicate that the tumor microenvironment undergoes alterations following NACT, characterized by increased spatially coordinated interactions between CD8+T-cells and myeloid cells, particularly at the tumor-stromal interface. These insights contribute to a better understanding of the complex dynamics within the tumor microenvironment, facilitating the development of novel treatment strategies for HGSC. Citation Format: Inga-Maria P. Launonen, Erdogan P. Erkan, Iga Niemiec, Ada Junquera Mencía, Angela Szabo, Fernando Perez, Essi Kahelin, Sampsa Hautaniemi, Jaana Oikkonen, Johanna Hynninen, Anni Virtanen, Tuulia Vallius, Ajit J. Nirmal, Peter Sorger, Anna Vähärautio, Anniina Färkkilä. CD8+T-cell interplay with myeloid cells as spatial determinant of chemotherapy response in the tumor microenvironment of metastatic high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A080.

Abstract A072: Altering the ovarian cancer tumor microenvironment using car t cell therapy

Abstract Ovarian cancer accounts for 12,810 deaths per year in the USA, making it the deadliest gynecologic malignancy. Unfortunately, patients who are resistant to standard of care treatments have very limited effective therapeutic options. Immunotherapies are an emerging class of treatments that utilize a patient’s immune system to recognize and destroy tumor cells and have resulted in dramatic responses in many hematologic malignancies. In particular, reprograming patient T cells to recognize specific surface antigen(s) known as chimeric antigen receptor (CAR) T cell therapy, has provided both pediatric and adult patients with relapsed or treatment-unresponsive hematologic malignancies novel and potentially curative treatment options. CAR T cell therapy received FDA approval in 2018 for the treatment of B cell leukemia, however despite significant efforts, has been largely ineffective in solid malignancies. This is due in part to the complex solid tumor immune microenvironment (TME) and how it may change in response to therapies. For example, there is evidence that an FDA approved treatment for ovarian cancer called poly(ADP) ribose polymerase inhibitors (PARP; PARPi) leads to increased immune cell infiltration and cancer sensitivity to immunotherapies. This proposal will delineate the immune composition of the ovarian cancer TME using mouse models that closely recapitulate ovarian cancer progression and examine the impact of CAR T cells on the TME. We will utilize mouse ovarian cancer models that are sensitive and resistant to PARP inhibition. The information derived from these studies will provide a better understanding of the evolution of ovarian cancer TME and provide insight on how CAR T cells may alter the TME. Ultimately, we hope this work will lead to the development of safer and more effective therapeutic options for ovarian cancer patients. Citation Format: Alexandra N. McMellen, Michael S. Leibowitz. Altering the ovarian cancer tumor microenvironment using car t cell therapy [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A072.

INHBA(+) cancer-associated fibroblasts generate an immunosuppressive tumor microenvironment in ovarian cancer

Effective targeting of cancer-associated fibroblasts (CAFs) is hindered by the lack of specific biomarkers and a poor understanding of the mechanisms by which different populations of CAFs contribute to cancer progression. While the role of TGFβ in CAFs is well-studied, less attention has been focused on a structurally and functionally similar protein, Activin A (encoded by INHBA). Here, we identified INHBA(+) CAFs as key players in tumor promotion and immunosuppression. Spatiotemporal analyses of patient-matched primary, metastatic, and recurrent ovarian carcinomas revealed that aggressive metastatic tumors enriched in INHBA(+) CAFs were also enriched in regulatory T cells (Tregs). In ovarian cancer mouse models, intraperitoneal injection of the Activin A neutralizing antibody attenuated tumor progression and infiltration with pro-tumorigenic subsets of myofibroblasts and macrophages. Downregulation of INHBA in human ovarian CAFs inhibited pro-tumorigenic CAF functions. Co-culture of human ovarian CAFs and T cells revealed the dependence of Treg differentiation on direct contact with INHBA(+) CAFs. Mechanistically, INHBA/recombinant Activin A in CAFs induced the autocrine expression of PD-L1 through SMAD2-dependent signaling, which promoted Treg differentiation. Collectively, our study identified an INHBA(+) subset of immunomodulatory pro-tumoral CAFs as a potential therapeutic target in advanced ovarian cancers which typically show a poor response to immunotherapy.

NLRC5 overexpression in ovarian tumors remodels the tumor microenvironment and increases T-cell reactivity toward autologous tumor-associated antigens.

Epithelial ovarian cancer (OC) stands as one of the deadliest gynecologic malignancies, urgently necessitating novel therapeutic strategies. Approximately 60% of ovarian tumors exhibit reduced expression of major histocompatibility complex class I (MHC I), intensifying immune evasion mechanisms and rendering immunotherapies ineffective. NOD-like receptor CARD domain containing 5 (NLRC5) transcriptionally regulates MHC I genes and many antigen presentation machinery components. We therefore explored the therapeutic potential of NLRC5 in OC. We generated OC cells overexpressing NLRC5 to rescue MHC I expression and antigen presentation and then assessed their capability to respond to PD-L1 blockade and an infected cell vaccine. Analysis of microarray datasets revealed a correlation between elevated NLRC5 expression and extended survival in OC patients; however, NLRC5 was scarcely detected in the OC tumor microenvironment. OC cells overexpressing NLRC5 exhibited slower tumor growth and resulted in higher recruitment of leukocytes in the TME with lower CD4/CD8 T-cell ratios and increased activation of T cells. Immune cells from peripheral blood, spleen, and ascites from these mice displayed heightened activation and interferon-gamma production when exposed to autologous tumor-associated antigens. Finally, as a proof of concept, NLRC5 overexpression within an infected cell vaccine platform enhanced responses and prolonged survival in comparison with control groups when challenged with parental tumors. These findings provide a compelling rationale for utilizing NLRC5 overexpression in "cold" tumor models to enhance tumor susceptibility to T-cell recognition and elimination by boosting the presentation of endogenous tumor antigens. This approach holds promise for improving antitumoral immune responses in OC.

Single-cell RNA sequencing in ovarian cancer: revealing new perspectives in the tumor microenvironment.

Single-cell sequencing technology has emerged as a pivotal tool for unraveling the complexities of the ovarian tumor microenvironment (TME), which is characterized by its cellular heterogeneity and intricate cell-to-cell interactions. Ovarian cancer (OC), known for its high lethality among gynecologic malignancies, presents significant challenges in treatment and diagnosis, partly due to the complexity of its TME. The application of single-cell sequencing in ovarian cancer research has enabled the detailed characterization of gene expression profiles at the single-cell level, shedding light on the diverse cell populations within the TME, including cancer cells, stromal cells, and immune cells. This high-resolution mapping has been instrumental in understanding the roles of these cells in tumor progression, invasion, metastasis, and drug resistance. By providing insight into the signaling pathways and cell-to-cell communication mechanisms, single-cell sequencing facilitates the identification of novel therapeutic targets and the development of personalized medicine approaches. This review summarizes the advancement and application of single-cell sequencing in studying the stromal components and the broader TME in OC, highlighting its implications for improving diagnosis, treatment strategies, and understanding of the disease's underlying biology.

Targeting the immune microenvironment for ovarian cancer therapy.

Ovarian cancer (OC) is an aggressive malignancy characterized by a complex immunosuppressive tumor microenvironment (TME). Immune checkpoint inhibitors have emerged as a breakthrough in cancer therapy by reactivating the antitumor immune response suppressed by tumor cells. However, in the case of OC, these inhibitors have failed to demonstrate significant improvements in patient outcomes, and existing biomarkers have not yet identified promising subgroups. Consequently, there remains a pressing need to understand the interplay between OC tumor cells and their surrounding microenvironment to develop effective immunotherapeutic approaches. This review aims to provide an overview of the OC TME and explore its potential as a therapeutic strategy. Tumor-infiltrating lymphocytes (TILs) are major actors in OC TME. Evidence has been accumulating regarding the spontaneous TILS response against OC antigens. Activated T-helpers secrete a wide range of inflammatory cytokines with a supportive action on cytotoxic T-cells. Simultaneously, mature B-cells are recruited and play a significant antitumor role through opsonization of target antigens and T-cell recruitment. Macrophages also form an important subset of innate immunity (M1-macrophages) while participating in the immune-stimulation context. Finally, OC has shown to engage a significant natural-killer-cells immune response, exerting direct cytotoxicity without prior sensitization. Despite this initial cytotoxicity, OC cells develop various strategies to induce an immune-tolerant state. To this end, multiple immunosuppressive molecules are secreted to impair cytotoxic cells, recruit regulatory cells, alter antigen presentation, and effectively evade immune response. Consequently, OC TME is predominantly infiltrated by immunosuppressive cells such as FOXP3+ regulatory T-cells, M2-polarized macrophages and myeloid-derived suppressor cells. Despite this strong immunosuppressive state, PD-1/PD-L1 inhibitors have failed to improve outcomes. Beyond PD-1/PD-L1, OC expresses multiple other immune checkpoints that contribute to immune evasion, and each representing potential immune targets. Novel immunotherapies are attempting to overcome the immunosuppressive state and induce specific immune responses using antibodies adoptive cell therapy or vaccines. Overall, the OC TME presents both opportunities and obstacles. Immunotherapeutic approaches continue to show promise, and next-generation inhibitors offer exciting opportunities. However, tailoring therapies to individual immune characteristics will be critical for the success of these treatments.

Mitophagy genes in ovarian cancer: a comprehensive analysis for improved immunotherapy

BackgroundMitophagy is a process of selectively degrading damaged mitochondria, which has been found to be related to immunity, tumorigenesis, tumor progression, and metastasis. However, the role of mitophagy-related genes (MRGs) in the tumor microenvironment (TME) of ovarian cancer (OV) remains largely unexplored.MethodsWe analyzed the expression, prognosis, and genetic alterations of 29 MRGs in 480 OV samples. Unsupervised clustering was used to classify OV into two subtypes (clusters A and B) based on MRG changes. We compared the clinical features, differential expressed genes (DEGs), pathways, and immune cell infiltration between the two clusters. We constructed a mitophagy scoring system (MRG_score) based on the DEGs and validated its ability to predict overall survival of OV patients.ResultsWe found that patients with high MRG_scores had better survival status and increased infiltration by immune cells. Further analysis showed that these patients may be more sensitive to immune checkpoint inhibitor (ICI) treatment. Additionally, the MRG_score significantly correlated with the sensitivity of chemotherapeutic drugs and targeted inhibitors.ConclusionOur comprehensive analysis of MRGs in the TME, clinical features, and patient prognosis revealed that the MRG_score is a potentially effective prognostic biomarker and predictor of treatment. This study provides new insights into the role of MRGs in OV and identifies patients who may benefit from ICI treatment, chemotherapy, or targeted treatment.

Deciphering tumor immune microenvironment differences between high-grade serous and endometrioid ovarian cancer to investigate their potential in indicating immunotherapy response

BackgroundOvarian cancer is a significant public health concern with a poor prognosis for epithelial ovarian cancer. To explore the potential of immunotherapy in treating epithelial ovarian cancer, we investigated the immune microenvironments of 52 patients with epithelial ovarian cancer, including 43 with high-grade serous ovarian cancer and 9 with endometrioid ovarian cancer.ResultsFresh tumor tissue was analyzed for genetic mutations and various parameters related to immune evasion and infiltration. The mean stromal score (stromal cell infiltration) in high-grade serous ovarian cancer was higher than in endometrioid ovarian cancer. The infiltration of CD8 T cells and exhausted CD8 T cells were found to be more extensive in high-grade serous ovarian cancer. Tumor Immune Dysfunction and Exclusion scores, T cell exclusion scores, and cancer-associated fibroblasts (CAF) scores were also higher in the high-grade serous ovarian cancer group, suggesting that the number of cytotoxic lymphocytes in the tumor microenvironment of high-grade serous ovarian cancer is likely lower compared to endometrioid ovarian cancer.ConclusionsThe high mean stromal score and more extensive infiltration and exhaustion of CD8 T cells in high-grade serous ovarian cancer indicate that high-grade serous ovarian cancer exhibits a higher level of cytotoxic T cell infiltration, yet these T cells tend to be in a dysfunctional state. Higher Tumor Immune Dysfunction and Exclusion scores, T cell exclusion scores, and CAF scores in high-grade serous ovarian cancers suggest that immune escape is more likely to occur in high-grade serous ovarian cancer, thus endometrioid ovarian cancer may be more conducive to immunotherapy. Therefore, it is crucial to design immunotherapy clinical trials for ovarian cancer to distinguish between high-grade serous and endometrioid ovarian cancer from the outset. This distinction will help optimize treatment strategies and improve outcomes for patients with different subtypes.

Methodical Manipulation of the TME in Ovarian Cancer.

The complex interplay between ovarian cancer cells and the tumor microenvironment (TME) modulates progression, with dynamic cellular interactions influenced by external modulators, including neoadjuvant chemotherapy (NACT). A recent article described the alterations within the TME following NACT, either with or without bevacizumab, in ovarian cancer. See related article by Tavira et al., p. 176.

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients’ tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

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

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

The MYBL2–CCL2 axis promotes tumor progression and resistance to anti-PD-1 therapy in ovarian cancer by inducing immunosuppressive macrophages

BackgroundAn immunosuppressive tumor microenvironment in ovarian cancer facilitates tumor progression and resistance to immunotherapy. The function of MYB Proto-Oncogene Like 2 (MYBL2) in the tumor microenvironment remains largely unexplored.MethodsA syngeneic intraovarian mouse model, flow cytometry analysis, and immunohistochemistry were used to explore the biological function of MYBL2 in tumor progression and immune escape. Molecular and biochemical strategies—namely RNA-sequencing, western blotting, quantitative reverse transcription–polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay, multiplex immunofluorescence, chromatic immunoprecipitation assay (CHIP) and luciferase assay—were used to reveal the mechanisms of MYBL2 in the OVC microenvironment.ResultsWe found tumor derived MYBL2 indicated poor prognosis and selectively correlated with tumor associated macrophages (TAMs) in ovarian cancer. Mechanically, C-C motif chemokine ligand 2 (CCL2) transcriptionally activated by MYBL2 induced TAMs recruitment and M2-like polarization in vitro. Using a syngeneic intraovarian mouse model, we identified MYBL2 promoted tumor malignancyand increased tumor-infiltrating immunosuppressive macrophages. Cyclin-dependent kinase 2 (CDK2) was a known upstream kinase to phosphorylate MYBL2 and promote its transcriptional function. The upstream inhibitor of CDK2, CVT-313, reprogrammed the tumor microenvironment and reduced anti-PD-1 resistance.ConclusionsThe MYBL2/CCL2 axis contributing to TAMs recruitment and M2-like polarization is crucial to immune evasion and anti-PD-1 resistance in ovarian cancer, which is a potential target to enhance the efficacy of immunotherapy.

UGDH promotes tumor-initiating cells and a fibroinflammatory tumor microenvironment in ovarian cancer

BackgroundEpithelial ovarian cancer (EOC) is a global health burden, with the poorest five-year survival rate of the gynecological malignancies due to diagnosis at advanced stage and high recurrence rate. Recurrence in EOC is driven by the survival of chemoresistant, stem-like tumor-initiating cells (TICs) that are supported by a complex extracellular matrix and immunosuppressive microenvironment. To target TICs to prevent recurrence, we identified genes critical for TIC viability from a whole genome siRNA screen. A top hit was the cancer-associated, proteoglycan subunit synthesis enzyme UDP-glucose dehydrogenase (UGDH).MethodsImmunohistochemistry was used to characterize UGDH expression in histological and molecular subtypes of EOC. EOC cell lines were subtyped according to the molecular subtypes and the functional effects of modulating UGDH expression in vitro and in vivo in C1/Mesenchymal and C4/Differentiated subtype cell lines was examined.ResultsHigh UGDH expression was observed in high-grade serous ovarian cancers and a distinctive survival prognostic for UGDH expression was revealed when serous cancers were stratified by molecular subtype. High UGDH was associated with a poor prognosis in the C1/Mesenchymal subtype and low UGDH was associated with poor prognosis in the C4/Differentiated subtype. Knockdown of UGDH in the C1/mesenchymal molecular subtype reduced spheroid formation and viability and reduced the CD133 + /ALDH high TIC population. Conversely, overexpression of UGDH in the C4/Differentiated subtype reduced the TIC population. In co-culture models, UGDH expression in spheroids affected the gene expression of mesothelial cells causing changes to matrix remodeling proteins, and fibroblast collagen production. Inflammatory cytokine expression of spheroids was altered by UGDH expression. The effect of UGDH knockdown or overexpression in the C1/ Mesenchymal and C4/Differentiated subtypes respectively was tested on mouse intrabursal xenografts and showed dynamic changes to the tumor stroma. Knockdown of UGDH improved survival and reduced tumor burden in C1/Mesenchymal compared to controls.ConclusionsThese data show that modulation of UGDH expression in ovarian cancer reveals distinct roles for UGDH in the C1/Mesenchymal and C4/Differentiated molecular subtypes of EOC, influencing the tumor microenvironmental composition. UGDH is a strong potential therapeutic target in TICs, for the treatment of EOC, particularly in patients with the mesenchymal molecular subtype.

Correlation Analysis of Prognostic Gene Expression, Tumor Microenvironment, and Tumor-Infiltrating Immune Cells in Ovarian Cancer.

Tumor microenvironment (TME) research can provide a crucial direction for the innovation and continuous improvement of novel biologic therapies for cancer. This study examined the relationship between the TME, expression profiles of the tumor-infiltrating immune cell, and prognostic gene expression in ovarian cancer (OC). Screening of CD3E, CD3G, CD2, CD3D, CCL19, and IL2RG was performed using the bioinformatics methods. All six genes were found to participate in immune-related molecular mechanisms and could regulate the expression of tumor-infiltrating cells. A Kaplan-Meier survival analysis results demonstrated a strong association between overall survival and all gene expressions in patients with OC. CIBERSORT analysis results showed that the expression level of all genes was positively correlated with γδ T cell proportions. Therefore, in the OC microenvironment, CD3E, CD3G, CD2, CD3D, CCL19, and IL2RG can be potential immunotherapy targets and prognostic markers.

Progress and Prospects of Tumor Microenvironment in Ovarian Cancer

Progress and Prospects of Tumor Microenvironment in Ovarian Cancer

Estrogens, Estrogen Receptors and Tumor Microenvironment in Ovarian Cancer.

Ovarian cancer is one of the most common cancers in women and the most concerning issues in gynecological oncology in recent years. It is postulated that many factors may contribute to the development of ovarian cancer, including hormonal imbalance. Estrogens are a group of hormones that have an important role both in physiological and pathological processes. In ovarian cancer, they may regulate proliferation, invasiveness and epithelial to mesenchymal transition. Estrogen signaling also takes part in the regulation of the biology of the tumor microenvironment. This review summarizes the information connected with estrogen receptors, estrogens and their association with a tumor microenvironment. Moreover, this review also includes information about the changes in estrogen receptor expression upon exposition to various environmental chemicals.

Extracellular vesicles targeting tumor microenvironment in ovarian cancer

Ovarian cancer (OC) is a prevalent neoplastic condition affecting women. Extracellular vesicles (EVs), nano-sized membrane vesicles, are secreted by various cells in both physiological and pathological states. The profound interplay between EVs and the tumor microenvironment (TME) in ovarian cancer is crucial. In this review, we explores the pivotal role of EVs in facilitating intercellular communication between cancer cells and the TME, emphasizing the potential of EVs as promising diagnostic markers and innovative therapeutic targets for ovarian cancer. The comprehensive analysis outlines the specific mechanisms by which EVs engage in communication with the constituents of the TME, including the modulation of tumor growth through EVs carrying matrix metalloproteinases (MMPs) and EV-mediated inhibition of angiogenesis, among other factors. Additionally, the we discuss the potential clinical applications of EVs that target the TME in ovarian cancer, encompassing the establishment of novel treatment strategies and the identification of novel biomarkers for early detection and prognosis. Finally, this review identifies novel strategies for therapeutic interventions, such as utilizing EVs as carriers for drug delivery and targeting specific EV-mediated signaling pathways. In summary, this manuscript offers valuable insights into the role of EVs in ovarian cancer and highlights the significance of comprehending intercellular communication in the realm of cancer biology.

The Emerging Role of the Single-Cell and Spatial Tumor Microenvironment in High-Grade Serous Ovarian Cancer.

The development of single-cell and spatial technologies has enabled a more detailed understanding of the tumor microenvironment and its role in therapy response and clinical outcome of high-grade serous ovarian cancer (HGSC). Interestingly, emerging evidence suggests that HGSCs with different genetic drivers harbor distinct tumor-immune microenvironments. Further, spatial cell-cell interactions have been shown to shape the CD8+ T-cell phenotypes and responses to immune checkpoint blockade therapies. The heterogeneous stroma consisting of cancer-associated fibroblast (CAF) subtypes, endothelia, and site-specific stromal types such as mesothelium modulates treatment responses via increasing stiffness and by producing ligands that promote drug resistance, angiogenesis, or immune escape. Chemotherapy itself shifts CAFs toward an inflammatory phenotype that associates with poor survival and immune-suppressive signaling. New emerging immunotherapies include combinational approaches and agents targeting, for example, the tumor-intrinsic endoplasmic reticulum pathway. A more detailed understanding of the spatial interplay of tumor, immune, and stromal cells in the tumor microenvironment is needed to develop more efficient immunotherapeutic strategies for HGSC.

Insights into the tumor-stromal-immune cell metabolism cross talk in ovarian cancer.

The ovarian cancer tumor microenvironment (TME) consists of a constellation of abundant cellular components, extracellular matrix, and soluble factors. Soluble factors, such as cytokines, chemokines, structural proteins, extracellular vesicles, and metabolites, are critical means of noncontact cellular communication acting as messengers to convey pro- or antitumorigenic signals. Vast advancements have been made in our understanding of how cancer cells adapt their metabolism to meet environmental demands and utilize these adaptations to promote survival, metastasis, and therapeutic resistance. The stromal TME contribution to this metabolic rewiring has been relatively underexplored, particularly in ovarian cancer. Thus, metabolic activity alterations in the TME hold promise for further study and potential therapeutic exploitation. In this review, we focus on the cellular components of the TME with emphasis on 1) metabolic signatures of ovarian cancer; 2) understanding the stromal cell network and their metabolic cross talk with tumor cells; and 3) how stromal and tumor cell metabolites alter intratumoral immune cell metabolism and function. Together, these elements provide insight into the metabolic influence of the TME and emphasize the importance of understanding how metabolic performance drives cancer progression.