Tumor Microenvironment in Ovarian Cancer: Function and Therapeutic Strategy

The emerging role of circular RNAs in cisplatin resistance in ovarian cancer: From molecular mechanism to future potential

Ovarian cancer (OC) is the most common cause of death in female cancers. The prognosis of OC is very poor due to delayed diagnosis and identification of most patients in advanced stages, metastasis, recurrence, and resistance to chemotherapy. As chemotherapy with platinum-based drugs such as cisplatin (DDP) is the main treatment in most OC cases, resistance to DDP is an important obstacle to achieving satisfactory therapeutic efficacy. Consequently, knowing the different molecular mechanisms involved in resistance to DDP is necessary to achieve new therapeutic approaches. According to numerous recent studies, non-coding RNAs (ncRNAs) could regulate proliferation, differentiation, apoptosis, and chemoresistance in many cancers, including OC. Most of these ncRNAs are released by tumor cells into human fluid, allowing them to be used as tools for diagnosis. CircRNAs are ncRNA family members that have a role in the initiation, progression, and chemoresistance regulation of various cancers. In the current study, we investigated the roles of several circRNAs and their signaling pathways on OC progression and also on DDP resistance during chemotherapy.

Proteomics and Bioinformatics Investigations Link Overexpression of FGF8 and Associated Hub Genes to the Progression of Ovarian Cancer and Poor Prognosis

Ovarian cancer's asymptomatic nature, high recurrence rate, and resistance to platinum-based chemotherapy highlight the need to find and characterize new diagnostic and therapeutic targets. While prior studies have linked aberrant expression of fibroblast growth factor 8 (FGF8) to various cancer types, its precise role has remained elusive. Recently, we observed that FGF8 silencing reduces the cancer-promoting properties of ovarian cancer cells, and thus, this study aimed to understand how FGF8 regulates the development of ovarian cancer. LC-MS/MS-based quantitative proteomics analysis identified 418 DEPs, and most of them were downregulated in FGF8-silenced ovarian cancer cells. Many of these DEPs are associated with cancer progression and unfavorable prognosis. To decipher the biological significance of DEPs, bioinformatics analyses encompassing gene ontology, pathway analysis, protein-protein interaction networks, and expression analysis of hub genes were carried out. Hub genes identified in the FGF8 protein network were upregulated in ovarian cancer compared to controls and were linked to poor prognosis. Subsequently, the expression of hub genes was correlated with patient survival and regulation of the tumor microenvironment. Conclusively, FGF8 and associated hub genes help in the progression of ovarian cancer, and their overexpression may lead to higher immune infiltration, poor prognosis, and poor survival.

Platinum-based chemotherapy promotes antigen presenting potential in monocytes of patients with high-grade serous ovarian carcinoma

Ovarian cancer (OC) is the most lethal gynecologic malignancy worldwide. The major clinical challenge includes the asymptomatic state of the disease, making diagnosis possible only at advanced stages. Another OC complication is the high relapse rate and poor prognosis following the standard first-line treatment with platinum-based chemotherapy. At present, numerous clinical trials are being conducted focusing on immunotherapy in OC; nevertheless, there are still no FDA-approved indications. Personalized decision regarding the immunotherapy, including immune checkpoint blockade and immune cell-based immunotherapies, can depend on the effective antigen presentation required for the cytotoxic immune response. The major aim of our study was to uncover tumor-specific transcriptional and epigenetic changes in peripheral blood monocytes in patients with high-grade serous ovarian cancer (HGSOC). Another key point was to elucidate how chemotherapy can reprogram monocytes and how that relates to changes in other immune subpopulations in the blood. To this end, we performed single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) from patients with HGSOC who underwent neoadjuvant chemotherapeutic treatment (NACT) and in treatment-naïve patients. Monocyte cluster was significantly affected by tumor-derived factors as well as by chemotherapeutic treatment. Bioinformatical analysis revealed three distinct monocyte subpopulations within PBMCs based on feature gene expression - CD14.Mn.S100A8.9hi, CD14.Mn.MHC2hi and CD16.Mn subsets. The intriguing result was that NACT induced antigen presentation in monocytes by the transcriptional upregulation of MHC class II molecules, but not by epigenetic changes. Increased MHC class II gene expression was a feature observed across all three monocyte subpopulations after chemotherapy. Our data also demonstrated that chemotherapy inhibited interferon-dependent signaling pathways, but activated some TGFb-related genes. Our results can enable personalized decision regarding the necessity to systemically re-educate immune cells to prime ovarian cancer to respond to anti-cancer therapy or to improve personalized prescription of existing immunotherapy in either combination with chemotherapy or a monotherapy regimen.

Ecological and evolutionary dynamics to design and improve ovarian cancer treatment

Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.

Molecular biology as a driver in therapeutic choices for ovarian cancer

The majority of patients with ovarian cancer relapse within 3 years of first line chemotherapy. Therefore, choosing the most appropriate treatment in the recurrence setting has a fundamental role in defining a patient's prognosis. Treatment options include systemic and intra-peritoneal chemotherapy, secondary cytoreductive surgery, and stereotactic body radiotherapy. The best therapeutic choice depends on multiple factors and not only on treatment-free interval. For systemic therapy, prior lines therapy, residual toxicities, comorbidities, performance status, and patient preferences should be taken into account. Secondary cytoreductive surgery can be proposed in patients in which complete tumor resectability can be predicted and in those with oligometastatic disease. Stereotactic body radiotherapy represents a valid alternative to surgery for oligometastatic disease with high local control and minimal toxicity. Current evidence has demonstrated an emerging role of BRCA mutational status and molecular profiling in the impacting response to systemic and local treatments. Therefore, these could provide guidance in the treatment decision process and help identify patients who respond better to poly(ADP-ribose) polymerase (PARP)-inhibitors or immunotherapy or to a combined approach with surgery rather than to platinum-based chemotherapy. Current knowledge in this field could help widen therapeutic options, especially for platinum-resistant patients. In this review, we offer an overview of the state of the art regarding the role of chemotherapy, radiotherapy, and surgery in this setting and their implications in clinical practice and in the treatment decision process, so as to provide the best tailored therapy in patients with recurrent ovarian cancer.

Tumor-Intrinsic Activity of Chromobox 2 Remodels the Tumor Microenvironment in High-grade Serous Carcinoma

Chromobox 2 (CBX2), an epigenetic reader and component of polycomb repressor complex 1, is highly expressed in >75% of high-grade serous carcinoma. Increased CBX2 expression is associated with poorer survival, whereas CBX2 knockdown leads to improved chemotherapy sensitivity. In a high-grade serous carcinoma immune-competent murine model, knockdown of CBX2 decreased tumor progression. We sought to explore the impact of modulation of CBX2 on the tumor immune microenvironment (TIME), understanding that the TIME plays a critical role in disease progression and development of therapy resistance. Exploration of existing datasets demonstrated that elevated CBX2 expression significantly correlated with specific immune cell types in the TIME. RNA sequencing and pathway analysis of differentially expressed genes demonstrated immune signature enrichment. Confocal microscopy and co-culture experiments found that modulation of CBX2 leads to increased recruitment and infiltration of macrophages. Flow cytometry of macrophages cultured with CBX2-overexpressing cells showed increased M2-like macrophages and decreased phagocytosis activity. Cbx2 knockdown in the Trp53-null, Brca2-null ID8 syngeneic murine model (ID8 Trp53-/-Brca2-/-) led to decreased tumor progression compared with the control. NanoString immuno-oncology panel analysis suggested that knockdown in Cbx2 shifts immune cell composition, with an increase in macrophages. Multispectral immunohistochemistry (mIHC) further confirmed an increase in macrophage infiltration. Increased CBX2 expression leads to recruitment and polarization of protumor macrophages, and targeting CBX2 may serve to modulate the TIME to enhance the efficacy of immune therapies.

SIGNIFICANCE

CBX2 expression correlates with the TIME. CBX2 modulation shifts the macrophage population, potentially leading to an immunosuppressive microenvironment, highlighting CBX2 as a target to improve efficacy of immunotherapy.

Spatial Profiling of Ovarian Carcinoma and Tumor Microenvironment Evolution under Neoadjuvant Chemotherapy

PURPOSE

This study investigates changes in CD8+ cells, CD8+/Foxp3 ratio, HLA I expression, and immune coregulator density at diagnosis and upon neoadjuvant chemotherapy (NACT), correlating changes with clinical outcomes.

EXPERIMENTAL DESIGN

Multiplexed immune profiling and cell clustering analysis were performed on paired matched ovarian cancer samples to characterize the immune tumor microenvironment (iTME) at diagnosis and under NACT in patients enrolled in the CHIVA trial (NCT01583322).

RESULTS

Several immune cell (IC) subsets and immune coregulators were quantified pre/post-NACT. At diagnosis, patients with higher CD8+ T cells and HLA I+-enriched tumors were associated with a better outcome. The CD8+/Foxp3+ ratio increased significantly post-NACT in favor of increased immune surveillance, and the influx of CD8+ T cells predicted better outcomes. Clustering analysis stratified pre-NACT tumors into four subsets: high Binf, enriched in B clusters; high Tinf and low Tinf, according to their CD8+ density; and desert clusters. At baseline, these clusters were not correlated with patient outcomes. Under NACT, tumors were segregated into three clusters: high BinfTinf, low Tinf, and desert. The high BinfTinf, more diverse in IC composition encompassing T, B, and NK cells, correlated with improved survival. PDL1 was rarely expressed, whereas TIM3, LAG3, and IDO1 were more prevalent.

CONCLUSIONS

Several iTMEs exist during tumor evolution, and the NACT impact on iTME is heterogeneous. Clustering analysis of patients unravels several IC subsets within ovarian cancer and can guide future personalized approaches. Targeting different checkpoints such as TIM3, LAG3, and IDO1, more prevalent than PDL1, could more effectively harness antitumor immunity in this anti-PDL1-resistant malignancy.

Nanoliposomes as nonviral vectors in cancer gene therapy

Nonviral vectors, such as liposomes, offer potential for targeted gene delivery in cancer therapy. Liposomes, composed of phospholipid vesicles, have demonstrated efficacy as nanocarriers for genetic tools, addressing the limitations of off-targeting and degradation commonly associated with traditional gene therapy approaches. Due to their biocompatibility, stability, and tunable physicochemical properties, they offer potential in overcoming the challenges associated with gene therapy, such as low transfection efficiency and poor stability in biological fluids. Despite these advancements, there remains a gap in understanding the optimal utilization of nanoliposomes for enhanced gene delivery in cancer treatment. This review delves into the present state of nanoliposomes as carriers for genetic tools in cancer therapy, sheds light on their potential to safeguard genetic payloads and facilitate cell internalization alongside the evolution of smart nanocarriers for targeted delivery. The challenges linked to their biocompatibility and the factors that restrict their effectiveness in gene delivery are also discussed along with exploring the potential of nanoliposomes in cancer gene therapy strategies by analyzing recent advancements and offering future directions.

Preoperative Immune Cell Dysregulation Accompanies Ovarian Cancer Patients into the Postoperative Period

Ovarian cancer (OC) poses a significant global health challenge with high mortality rates, emphasizing the need for improved treatment strategies. The immune system's role in OC progression and treatment response is increasingly recognized, particularly regarding peripheral blood mononuclear cells (PBMCs) and cytokine production. This study aimed to investigate PBMC subpopulations (T and B lymphocytes, natural killer cells, monocytes) and cytokine production, specifically interleukin-1 beta (IL-1β), interleukin-4 (IL-4), interleukin-6 (IL-6), interleukin-10 (IL-10), interleukin-12 (IL-12), and tumor necrosis factor alpha (TNFα), in monocytes of OC patients both preoperatively and during the early postoperative period. Thirteen OC patients and 23 controls were enrolled. Preoperatively, OC patients exhibited changes in PBMC subpopulations, including decreased cytotoxic T cells, increased M2 monocytes, and the disbalance of monocyte cytokine production. These alterations persisted after surgery with subtle additional changes observed in PBMC subpopulations and cytokine expression in monocytes. Considering the pivotal role of these altered cells and cytokines in OC progression, our findings suggest that OC patients experience an enhanced pro-tumorigenic environment, which persists into the early postoperative period. These findings highlight the impact of surgery on the complex interaction between the immune system and OC progression. Further investigation is needed to clarify the underlying mechanisms during this early postoperative period, which may hold potential for interventions aimed at improving OC management.

The biological roles of CD47 in ovarian cancer progression

Ovarian cancer is one of the most lethal malignant tumors, characterized by high incidence and poor prognosis. Patients relapse occurred in 65-80% after initial treatment. To date, no effective treatment has been established for these patients. Recently, CD47 has been considered as a promising immunotherapy target. In this paper, we reviewed the biological roles of CD47 in ovarian cancer and summarized the related mechanisms. For most types of cancers, the CD47/Sirpα immune checkpoint has attracted the most attention in immunotherapy. Notably, CD47 monoclonal antibodies and related molecules are promising in the immunotherapy of ovarian cancer, and further research is needed. In the future, new immunotherapy regimens targeting CD47 can be applied to the clinical treatment of ovarian cancer patients.

Gut microbiota modulation: a narrative review on a novel strategy for prevention and alleviation of ovarian aging

The global rise in life expectancy corresponds with a delay in childbearing age among women. Ovaries, seen as the chronometers of female physiological aging, demonstrate features of sped up aging, evidenced by the steady decline in both the quality and quantity of ovarian follicles from birth. The multifaceted pathogenesis of ovarian aging has kindled intensive research interest from the biomedical and pharmaceutical sectors. Novel studies underscore the integral roles of gut microbiota in follicular development, lipid metabolism, and hormonal regulation, forging a nexus with ovarian aging. In this review, we outline the role of gut microbiota in ovarian function (follicular development, oocyte maturation, and ovulation), compile and present gut microbiota alterations associated with age-related ovarian aging. We also discuss potential strategies for alleviating ovarian aging from the perspective of gut microbiota, such as fecal microbiota transplantation and probiotics.

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

Introduction

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

Methods

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

Results

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

Conclusions

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

Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics

Ovarian cancer, a highly fatal gynecological cancer, warrants the need for understanding its heterogeneity. The disease's prevalence and impact are underscored with statistics on mortality rates. Ovarian cancer is categorized into distinct morphological groups, each with its characteristics and prognosis. Despite standard treatments, survival rates remain low due to relapses and chemoresistance. Immune system involvement is evident in ovarian cancer's progression, although the tumor employs immune evasion mechanisms. Immunotherapy, particularly immune checkpoint blockade therapy, is promising, but ovarian cancer's heterogeneity limits its efficacy. Single-cell sequencing technology could be explored as a solution to dissect the heterogeneity within tumor-associated immune cell populations and tumor microenvironments. This cutting-edge technology has the potential to enhance diagnosis, prognosis, and personalized immunotherapy in ovarian cancer, reflecting its broader application in cancer research. The present review focuses on recent advancements and the challenges in applying single-cell transcriptomics to ovarian cancer.

Comparison of target agent treatment strategies for platinum-resistant recurrent ovarian cancer: A Bayesian network meta-analysis

BACKGROUND

We aimed to compare 7 newer immunotherapies and targeted therapies for platinum-resistant relapsed ovarian cancer.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library electronic databases for phase III trials involving platinum-resistant recurrent ovarian cancer (PRrOC) patients treated with immunotherapy or targeted therapy in combination with chemotherapy. The quality of the included trials was assessed using the GRADE method. The primary outcome of comparison was progression-free survival, and secondary outcomes included overall survival and safety.

RESULTS

This analysis included 7 randomized phase III controlled trials, encompassing 2485 PRrOC patients. Combining bevacizumab plus chemotherapy and lurbinectedin demonstrated statistically significant differences in progression-free survival compared to all other regimens of interest. However, no statistically significant differences were observed in the overall survival. Nivolumab and mirvetuximab exhibited fewer serious adverse events than the other regimens of interest.

CONCLUSIONS

Our findings indicate that bevacizumab combined with chemotherapy and lurbinectedin monotherapy has significant efficacy in patients with PRrOC. For patients with PRrOC who have exhausted treatment options, nivolumab and mirvetuximab may be considered as alternatives because of their better safety profiles.

Validating reference-based algorithms to determine cell-type heterogeneity in ovarian cancer DNA methylation studies

Information about cell composition in tissue samples is crucial for biomarker discovery and prognosis. Specifically, cancer tissue samples present challenges in deconvolution studies due to mutations and genetic rearrangements. Here, we optimized a robust, DNA methylation-based protocol, to be used for deconvolution of ovarian cancer samples. We compared several state-of-the-art methods (HEpiDISH, MethylCIBERSORT and ARIC) and validated the proposed protocol in an in-silico mixture and in an external dataset containing samples from ovarian cancer patients and controls. The deconvolution protocol we eventually implemented is based on MethylCIBERSORT. Comparing deconvolution methods, we paid close attention to the role of a reference panel. We postulate that a possibly high number of samples (in our case: 247) should be used when building a reference panel to ensure robustness and to compensate for biological and technical variation between samples. Subsequently, we tested the performance of the validated protocol in our own study cohort, consisting of 72 patients with malignant and benign ovarian disease as well as in five external cohorts. In conclusion, we refined and validated a reference-based algorithm to determine cell type composition of ovarian cancer tissue samples to be used in cancer biology studies in larger cohorts.

VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology

In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques necessitate the need for labels, providing manual cell annotations is time-consuming. In this paper, we propose a self-supervised framework (enVironment-aware cOntrastive cell represenTation learning: VOLTA) for cell representation learning in histopathology images using a technique that accounts for the cell's mutual relationship with its environment. We subject our model to extensive experiments on data collected from multiple institutions comprising over 800,000 cells and six cancer types. To showcase the potential of our proposed framework, we apply VOLTA to ovarian and endometrial cancers and demonstrate that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised models, we provide a framework that can empower discoveries without any annotation data, even in situations where sample sizes are limited.

The Role of Glutathione Transferase Omega-Class Variant Alleles in Individual Susceptibility to Ovarian Cancer

The tumor microenvironment is affected by reactive oxygen species and has been suggested to have an important role in ovarian cancer (OC) tumorigenesis. The role of glutathione transferases (GSTs) in the maintenance of redox balance is considered as an important contributing factor in cancer, including OC. Furthermore, GSTs are mostly encoded by highly polymorphic genes, which further highlights their potential role in OC, known to originate from accumulated genetic changes. Since the potential relevance of genetic variations in omega-class GSTs (GSTO1 and GSTO2), with somewhat different activities such as thioltransferase and dehydroascorbate reductase activity, has not been clarified as yet in terms of susceptibility to OC, we aimed to investigate whether the presence of different GSTO1 and GSTO2 genetic variants, individually or combined, might represent determinants of risk for OC development. Genotyping was performed in 110 OC patients and 129 matched controls using a PCR-based assay for genotyping single nucleotide polymorphisms. The results of our study show that homozygous carriers of the GSTO2 variant G allele are at an increased risk of OC development in comparison to the carriers of the referent genotype (OR1 = 2.16, 95% CI: 0.88-5.26, p = 0.08; OR2 = 2.49, 95% CI: 0.93-6.61, p = 0.06). Furthermore, individuals with GST omega haplotype H2, meaning the concomitant presence of the GSTO1*A and GSTO2*G alleles, are more susceptible to OC development, while carriers of the H4 (*A*A) haplotype exhibited lower risk of OC when crude and adjusted haplotype analysis was performed (OR1 = 0.29; 95% CI: 0.12-0.70; p = 0.007 and OR2 = 0.27; 95% CI: 0.11-0.67; p = 0.0054). Overall, our results suggest that GSTO locus variants may confer OC risk.

Connective Tissue Growth Factor: Regulation, Diseases, and Drug Discovery

In drug discovery, selecting targeted molecules is crucial as the target could directly affect drug efficacy and the treatment outcomes. As a member of the CCN family, CTGF (also known as CCN2) is an essential regulator in the progression of various diseases, including fibrosis, cancer, neurological disorders, and eye diseases. Understanding the regulatory mechanisms of CTGF in different diseases may contribute to the discovery of novel drug candidates. Summarizing the CTGF-targeting and -inhibitory drugs is also beneficial for the analysis of the efficacy, applications, and limitations of these drugs in different disease models. Therefore, we reviewed the CTGF structure, the regulatory mechanisms in various diseases, and drug development in order to provide more references for future drug discovery.

Deciphering resistance mechanisms and novel strategies to overcome drug resistance in ovarian cancer: a comprehensive review

Ovarian cancer is among the most lethal gynecological cancers, primarily due to the lack of specific symptoms leading to an advanced-stage diagnosis and resistance to chemotherapy. Drug resistance (DR) poses the most significant challenge in treating patients with existing drugs. The Food and Drug Administration (FDA) has recently approved three new therapeutic drugs, including two poly (ADP-ribose) polymerase (PARP) inhibitors (olaparib and niraparib) and one vascular endothelial growth factor (VEGF) inhibitor (bevacizumab) for maintenance therapy. However, resistance to these new drugs has emerged. Therefore, understanding the mechanisms of DR and exploring new approaches to overcome them is crucial for effective management. In this review, we summarize the major molecular mechanisms of DR and discuss novel strategies to combat DR.

Microphysiological systems as models for immunologically 'cold' tumors

The tumor microenvironment (TME) is a diverse milieu of cells including cancerous and non-cancerous cells such as fibroblasts, pericytes, endothelial cells and immune cells. The intricate cellular interactions within the TME hold a central role in shaping the dynamics of cancer progression, influencing pivotal aspects such as tumor initiation, growth, invasion, response to therapeutic interventions, and the emergence of drug resistance. In immunologically 'cold' tumors, the TME is marked by a scarcity of infiltrating immune cells, limited antigen presentation in the absence of potent immune-stimulating signals, and an abundance of immunosuppressive factors. While strategies targeting the TME as a therapeutic avenue in 'cold' tumors have emerged, there is a pressing need for novel approaches that faithfully replicate the complex cellular and non-cellular interactions in order to develop targeted therapies that can effectively stimulate immune responses and improve therapeutic outcomes in patients. Microfluidic devices offer distinct advantages over traditional in vitro 3D co-culture models and in vivo animal models, as they better recapitulate key characteristics of the TME and allow for precise, controlled insights into the dynamic interplay between various immune, stromal and cancerous cell types at any timepoint. This review aims to underscore the pivotal role of microfluidic systems in advancing our understanding of the TME and presents current microfluidic model systems that aim to dissect tumor-stromal, tumor-immune and immune-stromal cellular interactions in various 'cold' tumors. Understanding the intricacies of the TME in 'cold' tumors is crucial for devising effective targeted therapies to reinvigorate immune responses and overcome the challenges of current immunotherapy approaches.

Profiling of Tumour-Infiltrating Lymphocytes and Tumour-Associated Macrophages in Ovarian Epithelial Cancer-Relation to Tumour Characteristics and Impact on Prognosis

Early evidence suggests a strong impact of tumour-infiltrating lymphocytes (TILs) on both the prognosis and clinical behaviour of ovarian cancer. Proven associations, however, have not yet translated to successful immunotherapies and further work in the field is urgently needed. We aimed to analyse the tumour microenvironment of a well-characterised cohort of ovarian cancer samples. Tumour markers were selected owing to their comparative underrepresentation in the current literature. Paraffin-embedded, formalin-fixed tumour tissue blocks of 138 patients representative of the population and including early stage disease were identified, stained for CD3, CD20, CD68 and CD163 and analysed for both the stromal and intertumoral components. Data were statistically analysed in relation to clinical details, histological subtype, borderline vs. malignant status, survival and management received. Mean stromal CD3, total CD3 count, mean stromal CD20 and total CD20 count all correlated negatively with survival. Malignant ovarian tumours consistently demonstrated significantly higher infiltration of all analysed immune cells than borderline tumours. Assessment of the stromal compartment produced a considerably higher proportion of significant results when compared to the intra-tumoural infiltrates. Customary assessment of solely intra-tumoural cells in advanced stage disease patients undergoing primary debulking surgery should be challenged, with recommendations for future scoring systems provided.

Spotlight on New Hallmarks of Drug-Resistance towards Personalized Care for Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Despite the latest advances, a major clinical issue in EOC is the disappointing prognosis related to chemoresistance in almost one-third of cases. Drug resistance relies on heterogeneous cancer stem cells (CSCs), endowed with tumor-initiating potential, leading to relapse. No biomarkers of chemoresistance have been validated yet. Recently, major signaling pathways, micro ribonucleic acids (miRNAs), and circulating tumor cells (CTCs) have been advocated as putative biomarkers and potential therapeutic targets for drug resistance. However, further investigation is mandatory before their routine implementation. In accordance with the increasing rate of therapeutic efforts in EOC, the need for biomarker-driven personalized therapies is growing. This review aims to discuss the emerging hallmarks of drug resistance with an in-depth insight into the underlying molecular mechanisms lacking so far. Finally, a glimpse of novel therapeutic avenues and future challenges will be provided.

Comprehensive single-cell analysis reveals heterogeneity of fibroblast subpopulations in ovarian cancer tissue microenvironment

Background

Ovarian cancer, as a highly malignant tumor, features the critical involvement of tumor-associated fibroblasts in the ovarian cancer tissue microenvironment. However, due to the apparent heterogeneity within fibroblast subpopulations, the specific functions of these subpopulations in the ovarian cancer tissue microenvironment remain insufficiently elucidated.

Methods

In this study, we integrated single-cell sequencing data from 32 ovarian cancer samples derived from four distinct cohorts and 3226 bulk RNA-seq data from GEO and TCGA-OV cohorts. Utilizing computational frameworks such as Seurat, Monocle 2, Cellchat, and others, we analyzed the characteristics of the ovarian cancer tissue microenvironment, focusing particularly on fibroblast subpopulations and their differentiation trajectories. Employing the CIBERSORTX computational framework, we assessed various cellular components within the ovarian cancer tissue microenvironment and evaluated their associations with ovarian cancer prognosis. Additionally, we conducted Mendelian randomization analysis based on cis-eQTL to investigate causal relationships between gene expression and ovarian cancer.

Results

Through integrative analysis, we identified 13 major cell types present in ovarian cancer tissues, including CD8+ T cells, malignant cells, and fibroblasts. Analysis of the tumor microenvironment (TME) cell proportions revealed a significant increase in the proportion of CD8+ T cells and CD4+ T cells in tumor tissues compared to normal tissues, while fibroblasts predominated in normal tissues. Further subgroup analysis of fibroblasts identified seven subgroups, with the MMP11+Fib subgroup showing the highest activity in the TGFβ signaling pathway. Single-cell analysis suggested that oxidative phosphorylation could be a key pathway driving fibroblast differentiation, and the ATRNL1+KCN + Fib subgroup exhibited chromosomal copy number variations. Prognostic analysis using a large sample size indicated that high infiltration of MMP11+ fibroblasts was associated with poor prognosis in ovarian cancer. SMR analysis identified 132 fibroblast differentiation-related genes, which were linked to pathways such as platinum drug resistance.

Conclusions

In the context of ovarian cancer, fibroblasts expressing MMP11 emerge as the primary drivers of the TGF-beta signaling pathway. Their presence correlates with an increased risk of adverse ovarian prognoses. Additionally, the genetic regulation governing the differentiation of fibroblasts associated with ovarian cancer correlates with the emergence of drug resistance.

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

The Potential Influence of Residual or Recurrent Disease on Bevacizumab Treatment Efficacy in Ovarian Cancer: Current Evidence and Future Perspectives

There were high hopes for the new antiangiogenic medicament, bevacizumab, which could inhibit the creation of new blood vessels through binding to isoform A of vascular endothelial growth factor (VEGF). However, it is not only blood vessels that are responsible for tumor cell spread. During the process of tumor growth, lymphangiogenesis is mediated by other members of the VEGF family, specifically VEGF-C and VEGF-D, which act independent to bevacizumab. Therefore, based on the mechanism of bevacizumab action and the processes of angio- and lymphangiogenesis, we formed three hypotheses: (1) if the lymph nodes in primary ovarian cancers are metastatic, the outcome of bevacizumab treatment is worsened; (2) concerning the second-line treatment, bevacizumab will act in a weakened manner if recurrence occurs in lymph nodes as opposed to a local recurrence; (3) patients treated by bevacizumab are more likely to have recurrences in lymph nodes. These hypotheses raise the issue of the existing knowledge gap, which concerns the effect of bevacizumab on metastatic lymph nodes.

Sindbis Virus Vaccine Platform: A Promising Oncolytic Virus-Mediated Approach for Ovarian Cancer Treatment

This review article provides a comprehensive overview of a novel Sindbis virus vaccine platform as potential immunotherapy for ovarian cancer patients. Ovarian cancer is the most lethal of all gynecological malignancies. The majority of high-grade serous ovarian cancer (HGSOC) patients are diagnosed with advanced disease. Current treatment options are very aggressive and limited, resulting in tumor recurrences and 50-60% patient mortality within 5 years. The unique properties of armed oncolytic Sindbis virus vectors (SV) in vivo have garnered significant interest in recent years to potently target and treat ovarian cancer. We discuss the molecular biology of Sindbis virus, its mechanisms of action against ovarian cancer cells, preclinical in vivo studies, and future perspectives. The potential of Sindbis virus-based therapies for ovarian cancer treatment holds great promise and warrants further investigation. Investigations using other oncolytic viruses in preclinical studies and clinical trials are also presented.

CXC chemokines: Potential biomarker and immunotherapeutic target for uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is one of the most common type of gynecological malignancies. Multiple lines of evidence indicated that CXC chemokines exerted an anti-tumor immunological role in the tumor microenvironment which were critical regulators of cancer immunity. However, the relevance of CXC chemokines in the evaluation of prognosis and immune infiltration of UCEC remains to be explored. This study utilized various online databases, including TCGA, UALCAN, Kaplan-Meier Plotter, cBioPortal, TIMER2.0, TISIDB, and MethSurv to perform the analysis. Gene expression data from the TCGA-UCEC dataset indicated decreased expression of CXCL2/12 and increased expression of CXCL14/17. CXCL2/12 expression was negatively whereas CXCL14/17 expression was positively correlated with clinicopathological features of UCEC patients, including cancer stage, patients' age, weight and menopause status. Patients with higher CXCL12/14 expression corresponded with better clinical outcomes, which were not influenced by the genetic alterations. The differential expression of CXCL2/12/14/17 was not only significantly correlated with immune infiltration levels, but also the abundance of immune checkpoint inhibitors. Heatmaps of DNA methylation of CXCL2/12/14/17 were investigated, and 4 CpGs of CXCL2, 16 CpGs of CXCL12, 3 CpGs of CXCL14/17 were identified where altered methylation affected the prognosis of UCEC patients. These findings provided novel insights into the immunologic features of UCEC and might pave the way toward the prognostic evaluation and immunotherapy selection based on CXCL2/12/14/17 expression status.

Scientific and clinical relevance of non-cellular tumor microenvironment components in ovarian cancer chemotherapy resistance

The tumor microenvironment (TME) components play a crucial role in cancer cells' resistance to chemotherapeutic agents. This phenomenon is exceptionally fundamental in patients with ovarian cancer (OvCa), whose outcome depends mainly on their response to chemotherapy. Until now, most reports have focused on the role of cellular components of the TME, while less attention has been paid to the stroma and other non-cellular elements of the TME, which may play an essential role in the therapy resistance. Inhibiting these components could help define new therapeutic targets and potentially restore chemosensitivity. The aim of the present article is both to summarize the knowledge about non-cellular components of the TME in the development of OvCa chemoresistance and to suggest targeting of non-cellular elements of the TME as a valuable strategy to overcome chemoresistance and to develop new therapeutic strategies in OvCA patients.

Deciphering the Therapeutic Applications of Nanomedicine in Ovarian Cancer Therapy: An Overview

The majority of deadly cancers that afflict the female reproductive system occur in the ovary. Around 1,40,000 women worldwide die from ovarian cancer each year, making it the sixth most common cancer-associated deceases among females in the United States. Modern, cutting-edge treatments like chemotherapy and surgery frequently produce full remissions, but the recurrence rate is still very high. When this crippling condition is diagnosed, there are frequently few therapeutic choices available because of how quietly it manifests. Healthcare practitioners must have a fundamental grasp of the warning signs and symptoms of ovarian cancer, as well as the imaging techniques and treatment choices available, to give the patient the best care possible. The discipline of medical nanotechnology has gained a lot of momentum in recent years in resolving issues and enhancing the detection and treatment of different illnesses, including cancer. This article gives a brief summary of types, risk factors and approaches to ovarian cancer treatment. We subsequently discussed the pathophysiology of ovarian cancer with the risk factors. This review also emphasizes the various signalling pathways involved in ovarian cancer. Our comprehensive integration of recent findings in fundamental research in the nano arena reveals the strong interest in these nanomedicines in ovarian cancer treatment. However, these nanomedicines still require more research, as indicated by the comparatively small number of clinical trials ongoing. This article will provide a reference for ovarian cancer treatment.

Dysregulation of Peripheral Blood Mononuclear Cells and Immune-Related Proteins during the Early Post-Operative Immune Response in Ovarian Cancer Patients

Surgical treatment is a cornerstone of ovarian cancer (OC) therapy and exerts a substantial influence on the immune system. Immune responses also play a pivotal and intricate role in OC progression. The aim of this study was to investigate the dynamics of immune-related protein expression and the activity of peripheral blood mononuclear cells (PBMCs) in OC patients, both before surgery and during the early postoperative phase. The study cohort comprised 23 OC patients and 20 non-cancer controls. A comprehensive analysis of PBMCs revealed significant pre-operative downregulation in the mRNA expression of multiple immune-related proteins, including interleukins, PD-1, PD-L1, and HO-1. This was followed by further dysregulation during the first 5 post-operative days. Although most serum interleukin concentrations showed only minor changes, a distinct increase in IL-6 and HO-1 levels was observed post-operatively. Reduced metabolic and phagocytic activity and increased production of reactive oxygen species (ROS) were observed on day 1 post-surgery. These findings suggest a shift towards immune tolerance during the early post-operative phase of OC, potentially creating a window for treatment. Further research into post-operative PBMC activity could lead to the development of new or improved treatment strategies for OC.

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.

Identifying Explainable Machine Learning Models and a Novel SFRP2+ Fibroblast Signature as Predictors for Precision Medicine in Ovarian Cancer

Ovarian cancer (OC) is a type of malignant tumor with a consistently high mortality rate. The diagnosis of early-stage OC and identification of functional subsets in the tumor microenvironment are essential to the development of patient management strategies. However, the development of robust models remains unsatisfactory. We aimed to utilize artificial intelligence and single-cell analysis to address this issue. Two independent datasets were screened from the Gene Expression Omnibus (GEO) database and processed to obtain overlapping differentially expressed genes (DEGs) in stage II-IV vs. stage I diseases. Three explainable machine learning algorithms were integrated to construct models that could determine the tumor stage and extract important characteristic genes as diagnostic biomarkers. Correlations between cancer-associated fibroblast (CAF) infiltration and characteristic gene expression were analyzed using TIMER2.0 and their relationship with survival rates was comprehensively explored via the Kaplan-Meier plotter (KM-plotter) online database. The specific expression of characteristic genes in fibroblast subsets was investigated through single-cell analysis. A novel fibroblast subset signature was explored to predict immune checkpoint inhibitor (ICI) response and oncogene mutation through Tumor Immune Dysfunction and Exclusion (TIDE) and artificial neural network algorithms, respectively. We found that Support Vector Machine-Shapley Additive Explanations (SVM-SHAP), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) successfully diagnosed early-stage OC (stage I). The area under the receiver operating characteristic curves (AUCs) of these models exceeded 0.990. Their overlapping characteristic gene, secreted frizzled-related protein 2 (SFRP2), was a risk factor that affected the overall survival of OC patients with stage II-IV disease (log-rank test: p < 0.01) and was specifically expressed in a fibroblast subset. Finally, the SFRP2+ fibroblast signature served as a novel predictor in evaluating ICI response and exploring pan-cancer tumor protein P53 (TP53) mutation (AUC = 0.853, 95% confidence interval [CI]: 0.829-0.877). In conclusion, the models based on SVM-SHAP, XGBoost, and RF enabled the early detection of OC for clinical decision making, and SFRP2+ fibroblast signature used in diagnostic models can inform OC treatment selection and offer pan-cancer TP53 mutation detection.

IFN-γ in ovarian tumor microenvironment upregulates HLA-E expression and predicts a poor prognosis

BACKGROUND

Inflammation and immunity are two main characteristics of tumor microenvironment (TME). Interferon-gamma (IFN-γ) is generally considered as a pro-inflammatory cytokine which mediates anti-tumor immune response. Recently, IFN-γ was also reported to play a protumorigenic role. However, the mechanisms of tumor-promoting effect induced by IFN-γ remain unclear.

METHODS

The expression of leukocyte antigen-E (HLA-E), IFN-γ, CD3 and CD56 in clinical samples of ovarian cancer was detected by mutiplexed immunohistochemistry. The mechanism to induce HLA-E overexpression by IFN-γ was explored using human ovarian cancer cell lines through western blot and flow cytometry. We further clarify the role of overexpressed-HLA-E on natural killer (NK)-mediated cell lysis.

RESULTS

We found that IFN-γ could upregulate HLA-E protein expression through activating of JAK/STAT1 signaling pathway, and increase cell surface HLA-E level through enhancing proteasome activity. We also observed that only high levels of membrane HLA-E expression contributed to the inhibition of NK-mediated cytotoxicity. We showed that progression-free survival (PFS) of ovarian cancer patients was negatively correlated with IFN-γ expression in their tumor tissues, due to more tumor infiltrating NK cells compared with T lymphocytes.

CONCLUSIONS

Our study revealed the protumorigenic role of IFN-γ by upregulation of HLA-E expression and rendering tumors less susceptible to immune attack. We also provided a novel insight into the relationship between tumor microenvironment and immune evasion.

New Achievements from Molecular Biology and Treatment Options for Refractory/Relapsed Ovarian Cancer-A Systematic Review

Ovarian cancer (OC) has a high rate of mortality and is the fifth most common cause of death in females all over the world. The etiology is still unclear. Numerous factors such as smoking, obesity, and unhealthy diet may affect the risk of OC. Having a family history of breast and OC is one of the main risks for developing OC. Mutations of BRCA1/2 are associated with OC risk as well. The histopathological classification of OC reveals the four most common types: serous, clear cell, endometrioid, and mucinous; these are epithelial OC types, and other types are rare. Furthermore, OC can be subdivided into types I and II. Type I tumors are most probably caused by atypical proliferative tumors. Type II tumors include high-grade carcinoma of the serous type, carcinosarcoma, and carcinoma, which are not differentiated and generally originate from tubal intraepithelial carcinoma of the serous type. Typically, type I tumors are present in early stages, usually with good prognosis. Type II tumors are classified as high-grade tumors and are most often diagnosed at advanced FIGO stages with poor prognosis. High-grade serous OC accounts for 90% of serous OC. Tumor heterogeneity aggravates OC treatment. The standard care for primary epithelial ovarian cancer (EOC) is cytoreductive surgery followed by platinum-based chemotherapy. Neoadjuvant chemotherapy can be used in certain cases followed by cytoreductive surgery. The main prognostic factor is complete tumor resection. However, about 70% of patients relapse. Resistance to chemotherapeutic agents remains a major challenge in EOC treatment, in which many different factors are involved. In recent years, the examination of molecular parameters and their prognostic impact has become increasingly relevant in EOC, and furthermore, the use of immunotherapy has expanded the therapeutic range. As the clinical need is greatest for relapsed patients, this systematic review will focus on recent advances in molecular biology with prognostic and predictive markers and treatment options for recurrent/refractory OC. Inclusion criteria for the review: potential prospective or predictive biomarkers in preclinical or clinical use in relapsed and refractory OC, prognostic impact, clinical and preclinical trials, and immunotherapy. Exclusion criteria for the review: primary OC, no full text or abstract available, not the topic mentioned above, and text not available in English. Risk of bias: the included studies were evaluated descriptively for the topics mentioned above, and data were not compared with each other. The objective is to highlight the molecular mechanisms of the most promising targeted agents under clinical investigation to demonstrate their potential relevance in recurrent/refractory OC.

Tumor cell cytoplasmic metallothionein expression associates with differential tumor immunogenicity and prognostic outcome in high-grade serous ovarian carcinoma

Background

The underlying mechanism of high T-cell presence as a favorable prognostic factor in high-grade serous ovarian carcinoma (HGSOC) is not yet understood. In addition to immune cells, various cofactors are essential for immune processes. One of those are metallothioneins (MTs), metal-binding proteins comprising various isoforms. MTs play a role in tumor development and drug resistance. Moreover, MTs influence inflammatory processes by regulating zinc homeostasis. In particular, T-cell function and polarization are particularly susceptible to changes in zinc status. The aim of the present study was to investigate a possible role of MT-mediated immune response and its association with prognostic outcome in ovarian cancer.

Methods

A retrospective study was conducted on a clinically well-characterized cohort of 24 patients with HGSOC treated at the University Hospital of Essen. Gene expression patterns for anti-cancer immunogenicity-related targets were performed using the NanoString nCounter platform for digital gene expression analysis with the appurtenant PanCancer Immune Profiling panel, consisting of 770 targets and 30 reference genes. Tumor-associated immunohistochemical MT protein expression was evaluated using a semi-quantitative four-tier Immunohistochemistry (IHC) scoring.

Results

MT immunoexpression was detected in 43% (10/23) of all HGSOC samples. MT immunoexpression levels showed a significant association to survival, leading to prolonged progression-free and overall survival in positively stained tumors. Furthermore, T-cell receptor signaling gene signature showed a strong activation in MT-positive tumors. Activated downstream signaling cascades resulting in elevated interferon-gamma expression with a shift in the balance between T helper cells (TH1 and TH2) could be observed in the MT-positive subgroup. In addition, a higher expression pattern of perforin and several granzymes could be detected, overall suggestive of acute, targeted anti-cancer immune response in MT-positive samples.

Conclusion

This is the first study combining broad, digital mRNA screening of anti-tumor immune response-associated genes and their relation to MT-I/II in ovarian cancer. MT overexpression is associated with molecular characteristics of an anti-cancer immune response and is a strong prognostic marker in ovarian HGSOC. The observed immune cell activation associated with tumor MT expression comprises but is not limited to T cells and natural killer cells.

Aptamers as Potential Therapeutic Tools for Ovarian Cancer: Advancements and Challenges

Ovarian cancer (OC) is the most common lethal gynecologic cause of death in women worldwide, with a high mortality rate and increasing incidence. Despite advancements in the treatment, most OC patients still die from their disease due to late-stage diagnosis, the lack of effective diagnostic methods, and relapses. Aptamers, synthetic, short single-stranded oligonucleotides, have emerged as promising anticancer therapeutics. Their ability to selectively bind to target molecules, including cancer-related proteins and receptors, has revolutionized drug discovery and biomarker identification. Aptamers offer unique insights into the molecular pathways involved in cancer development and progression. Moreover, they show immense potential as drug delivery systems, enabling targeted delivery of therapeutic agents to cancer cells while minimizing off-target effects and reducing systemic toxicity. In the context of OC, the integration of aptamers with non-coding RNAs (ncRNAs) presents an opportunity for precise and efficient gene targeting. Additionally, the conjugation of aptamers with nanoparticles allows for accurate and targeted delivery of ncRNAs to specific cells, tissues, or organs. In this review, we will summarize the potential use and challenges associated with the use of aptamers alone or aptamer-ncRNA conjugates, nanoparticles, and multivalent aptamer-based therapeutics for the treatment of OC.

Stromal DDR2 Promotes Ovarian Cancer Metastasis through Regulation of Metabolism and Secretion of Extracellular Matrix Proteins

Ovarian cancer is the leading cause of gynecologic cancer-related deaths. The propensity for metastasis within the peritoneal cavity is a driving factor for the poor outcomes associated with this disease, but there is currently no effective therapy targeting metastasis. In this study, we investigate the contribution of stromal cells to ovarian cancer metastasis and identify normal stromal cell expression of the collagen receptor, discoidin domain receptor 2 (DDR2), that acts to facilitate ovarian cancer metastasis. In vivo, global genetic inactivation of Ddr2 impairs the ability of Ddr2-expressing syngeneic ovarian cancer cells to spread throughout the peritoneal cavity. Specifically, DDR2 expression in mesothelial cells lining the peritoneal cavity facilitates tumor cell attachment and clearance. Subsequently, omentum fibroblast expression of DDR2 promotes tumor cell invasion. Mechanistically, we find DDR2-expressing fibroblasts are more energetically active, such that DDR2 regulates glycolysis through AKT/SNAI1 leading to suppressed fructose-1,6-bisphosphatase and increased hexokinase activity, a key glycolytic enzyme. Upon inhibition of DDR2, we find decreased protein synthesis and secretion. Consequently, when DDR2 is inhibited, there is reduction in secreted extracellular matrix proteins important for metastasis. Specifically, we find that fibroblast DDR2 inhibition leads to decreased secretion of the collagen crosslinker, LOXL2. Adding back LOXL2 to DDR2 deficient fibroblasts rescues the ability of tumor cells to invade. Overall, our results suggest that stromal cell expression of DDR2 is an important mediator of ovarian cancer metastasis.

IMPLICATIONS

DDR2 is highly expressed by stromal cells in ovarian cancer that can mediate metastasis and is a potential therapeutic target in ovarian cancer.

Cancer-Associated Fibroblast-Induced Remodeling of Tumor Microenvironment in Recurrent Bladder Cancer

Bladder carcinoma (BC) recurrence is a major clinical challenge, and targeting the tumor microenvironment (TME) is a promising therapy. However, the relationship between individual TME components, particularly cancer-associated fibroblasts (CAFs), and tumor recurrence is unclear. Here, TME heterogeneity in primary and recurrent BC is investigated using single-cell RNA sequence profiling of 62 460 cells. Two cancer stem cell (CSC) subtypes are identified in recurrent BC. An inflammatory CAF subtype, ICAM1+ iCAFs, specifically associated with BC recurrence is also identified. iCAFs are found to secrete FGF2, which acts on the CD44 receptor of rCSC-M, thereby maintaining tumor stemness and epithelial-mesenchymal transition. Additionally, THBS1+ monocytes, a group of myeloid-derived suppressor cells (MDSCs), are enriched in recurrent BC and interacted with CAFs. ICAM1+ iCAFs are found to secrete CCL2, which binds to CCR2 in MDSCs. Moreover, elevated STAT3, NFKB2, VEGFA, and CTGF levels in iCAFs reshape the TME in recurrent tumors. CCL2 inhibition in an in situ BC mouse model suppressed tumor growth, decreased MDSCs and Tregs, and fostered tumor immune suppression. The study results highlight the role of iCAFs in TME cell-cell crosstalk during recurrent BC. The identification of pivotal signaling factors driving BC relapse is promising for the development of novel therapies.

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.

Profiling ovarian cancer tumor and microenvironment during disease progression for cell-based immunotherapy design

Ovarian cancer (OC) is highly lethal due to late detection and frequent recurrence. Initial treatments, comprising surgery and chemotherapy, lead to disease remission but are invariably associated with subsequent relapse. The identification of novel therapies and an improved understanding of the molecular and cellular characteristics of OC are urgently needed. Here, we conducted a comprehensive analysis of primary tumor cells and their microenvironment from 16 chemonaive and 10 recurrent OC patient samples. Profiling OC tumor biomarkers allowed for the identification of potential molecular targets for developing immunotherapies, while profiling the microenvironment yielded insights into its cellular composition and property changes between chemonaive and recurrent samples. Notably, we identified CD1d as a biomarker of the OC microenvironment and demonstrated its targeting by invariant natural killer T (iNKT) cells. Overall, our study presents a comprehensive immuno-profiling of OC tumor and microenvironment during disease progression, guiding the development of immunotherapies for OC treatment, especially for recurrent disease.

CXCL8 Promotes Endothelial-to-Mesenchymal Transition of Endothelial Cells and Protects Cells from Erastin-Induced Ferroptosis via CXCR2-Mediated Activation of the NF-κB Signaling Pathway

CXCL8-CXCR1/CXCR2 signaling pathways might form complex crosstalk among different cell types within the ovarian tumor microenvironment, thereby modulating the behaviors of different cells. This study aimed to investigate the expression pattern of CXCL8 in the ovarian tumor microenvironment and its impact on both endothelial-to-mesenchymal transition (EndMT) and ferroptosis of endothelial cells. The human monocytic cell line THP-1 and the human umbilical vein endothelial cell line PUMC-HUVEC-T1 were used to conduct in vitro studies. Erastin was used to induce ferroptosis. Results showed that tumor-associated macrophages are the major source of CXCL8 in the tumor microenvironment. CXCL8 treatment promoted the nucleus entrance of NF-κB p65 and p65 phosphorylation via CXCR2 in endothelial cells, suggesting activated NF-κB signaling. Via the NF-κB signaling pathway, CXCL8 enhanced TGF-β1-induced EndMT of PUMC-HUVEC-T1 cells and elevated their expression of SLC7A11 and GPX4. These trends were drastically weakened in groups with CXCR2 knockdown or SB225002 treatment. TPCA-1 reversed CXCL8-induced upregulation of SLC7A11 and GPX4. CXCL8 protected endothelial cells from erastin-induced ferroptosis. However, these protective effects were largely canceled when CXCR2 was knocked down. In summary, CXCL8 can activate the NF-κB signaling pathway in endothelial cells in a CXCR2-dependent manner. The CXCL8-CXCR2/NF-κB axis can enhance EndMT and activate SLC7A11 and GPX4 expression, protecting endothelial cells from ferroptosis.

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

Background

Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC.

Methods

Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR).

Results

By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data.

Conclusions

The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

Exploring the tumor immune microenvironment in ovarian cancer: a way-out to the therapeutic roadmap

INTRODUCTION

Despite cancer treatment strides, mortality due to ovarian cancer remains high globally. While immunotherapy has proven effective in treating cancers with low cure rates, it has limitations. Growing evidence suggests that both tumoral and non-tumoral components of the tumor immune microenvironment (TIME) play a significant role in cancer growth. Therefore, developing novel and focused therapy for ovarian cancer is critical. Studies indicate that TIME is involved in developing ovarian cancer, particularly genome-, transcriptome-, and proteome-wide studies. As a result, TIME may present a prospective therapeutic target for ovarian cancer patients.

AREAS COVERED

We examined several TIME-targeting medicines and the connection between TIME and ovarian cancer. The key protagonists and events in the TIME and therapeutic strategies that explicitly target these events in ovarian cancer are discussed.

EXPERT OPINION

We highlighted various targeted therapies against TIME in ovarian cancer, including anti-angiogenesis therapies and immune checkpoint inhibitors. While these therapies are in their infancy, they have shown promise in controlling ovarian cancer progression. The use of 'omics' technology is helping in better understanding of TIME in ovarian cancer and potentially identifying new therapeutic targets. TIME-targeted strategies could account for an additional treatment strategy when treating ovarian cancer.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer

Introduction

Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy.

Methods

Paired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio's iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples.

Results

There was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature.

Discussion

We report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.

Targeting AXL in Mesothelioma: from functional characterization to clinical implication

Malignant pleural mesothelioma (MM) is a highly aggressive and lethal cancer with a poor survival rate. Current treatment approaches primarily rely on chemotherapy and radiation, but their effectiveness is limited. Consequently, there is an urgent need for alternative treatment strategies, a comprehensive understanding of the molecular mechanisms underlying MM, and the identification of potential therapeutic targets. Extensive studies over the past decade have emphasized the role of Axl in driving tumor development and metastasis, while high levels of Axl expression have been associated with immune evasion, drug resistance, and reduced patient survival in various cancer types. Ongoing clinical trials are investigating the efficacy of Axl inhibitors for different cancers. However, the precise role of Axl in MM progression, development, and metastasis, as well as its regulatory mechanisms within MM, remain inadequately understood. This review aims to comprehensively investigate the involvement of Axl in MM. We discuss Axl role in MM progression, development, and metastasis, along with its specific regulatory mechanisms. Additionally, we examined the Axl associated signaling pathways, the relationship between Axl and immune evasion, and the clinical implications of Axl for MM treatment. Furthermore, we discussed the potential utility of liquid biopsy as a non-invasive diagnostic technique for early detection of Axl in MM. Lastly, we evaluated the potential of a microRNA signature that targets Axl. By consolidating existing knowledge and identifying research gaps, this review contributes to a better understanding of Axl's role in MM and sets the stage for future investigations and the development of effective therapeutic interventions.

Neo-vascularization-based therapeutic perspectives in advanced ovarian cancer

The process of angiogenesis is well described for its potential role in the development of normal ovaries, and physiological functions as well as in the initiation, progression, and metastasis of ovarian cancer (OC). In advanced stages of OC, cancer cells spread outside the ovary to the pelvic, abdomen, lung, or multiple secondary sites. This seriously limits the efficacy of therapeutic options contributing to fatal clinical outcomes. Notably, a variety of angiogenic effectors are produced by the tumor cells to initiate angiogenic processes leading to the development of new blood vessels, which provide essential resources for tumor survival, dissemination, and dormant micro-metastasis of tumor cells. Multiple proangiogenic effectors and their signaling axis have been discovered and functionally characterized for potential clinical utility in OC. In this review, we have provided the current updates on classical and emerging proangiogenic effectors, their signaling axis, and the immune microenvironment contributing to the pathogenesis of OC. Moreover, we have comprehensively reviewed and discussed the significance of the preclinical strategies, drug repurposing, and clinical trials targeting the angiogenic processes that hold promising perspectives for the better management of patients with OC.

Comparative Tumor Microenvironment Analysis of Primary and Recurrent Ovarian Granulosa Cell Tumors

Adult-type granulosa cell tumors (aGCT) are rare ovarian sex cord tumors with few effective treatments for recurrent disease. The objective of this study was to characterize the tumor microenvironment (TME) of primary and recurrent aGCTs and to identify correlates of disease recurrence. Total RNA sequencing (RNA-seq) was performed on 24 pathologically confirmed, cryopreserved aGCT samples, including 8 primary and 16 recurrent tumors. After read alignment and quality-control filtering, DESeq2 was used to identify differentially expressed genes (DEG) between primary and recurrent tumors. Functional enrichment pathway analysis and gene set enrichment analysis was performed using "clusterProfiler" and "GSVA" R packages. TME composition was investigated through the analysis and integration of multiple published RNA-seq deconvolution algorithms. TME analysis results were externally validated using data from independent previously published RNA-seq datasets. A total of 31 DEGs were identified between primary and recurrent aGCTs. These included genes with known function in hormone signaling such as LHCGR and INSL3 (more abundant in primary tumors) and CYP19A1 (more abundant in recurrent tumors). Gene set enrichment analysis revealed that primarily immune-related and hormone-regulated gene sets expression was increased in recurrent tumors. Integrative TME analysis demonstrated statistically significant depletion of cancer-associated fibroblasts in recurrent tumors. This finding was confirmed in multiple independent datasets.

IMPLICATIONS

Recurrent aGCTs exhibit alterations in hormone pathway gene expression as well as decreased infiltration of cancer-associated fibroblasts, suggesting dual roles for hormonal signaling and TME remodeling underpinning disease relapse.

Secreted Soluble Factors from Tumor-Activated Mesenchymal Stromal Cells Confer Platinum Chemoresistance to Ovarian Cancer Cells

Ovarian cancer (OC) ranks as the second most common type of gynecological malignancy, has poor survival rates, and is frequently diagnosed at an advanced stage. Platinum-based chemotherapy, such as carboplatin, represents the standard-of-care for OC. However, toxicity and acquired resistance to therapy have proven challenging for the treatment of patients. Chemoresistance, a principal obstacle to durable response in OC patients, is attributed to alterations within the cancer cells, and it can also be mediated by the tumor microenvironment (TME). In this study, we report that conditioned medium (CM) derived from murine and human stromal cells, MS-5 and HS-5, respectively, and tumor-activated HS-5, was active in conferring platinum chemoresistance to OC cells. Moreover, CM derived from differentiated murine pre-adipocyte (3T3-L1), but not undifferentiated pre-adipocyte cells, confers platinum chemoresistance to OC cells. Interestingly, CM derived from tumor-activated HS-5 was more effective in conferring chemoresistance than was CM derived from HS-5 cells. Various OC cells exhibit variable sensitivity to CM activity. Exploring CM content revealed the enrichment of a number of soluble factors in the tumor-activated HS-5, such as soluble uPAR (SuPAR), IL-6, and hepatocyte growth factor (HGF). FDA-approved JAK inhibitors were mildly effective in restoring platinum sensitivity in two of the three OC cell lines in the presence of CM. Moreover, Crizotinib, an ALK and c-MET inhibitor, in combination with platinum, blocked HGF's ability to promote platinum resistance and to restore platinum sensitivity to OC cells. Finally, exposure to 2-hydroxyestardiol (2HE2) was effective in restoring platinum sensitivity to OC cells exposed to CM. Our results showed the significance of soluble factors found in TME in promoting platinum chemoresistance and the potential of combination therapy to restore chemosensitivity to OC cells.

Identifying ITGB2 as a Potential Prognostic Biomarker in Ovarian Cancer

Epithelial ovarian cancer is by far the most lethal gynecological malignancy. The exploration of promising immunomarkers to predict prognosis in ovarian cancer patients remains challenging. In our research, we carried out an integrated bioinformatic analysis of genome expressions and their immune characteristics in the ovarian cancer microenvironment with validation in different experiments. We filtrated 332 differentially expressed genes with 10 upregulated hub genes from the Gene Expression Omnibus database. These genes were closely related to ovarian tumorigenesis. Subsequently, the survival and immune infiltration analysis demonstrated that the upregulation of five candidate genes, ITGB2, VEGFA, CLDN4, OCLN, and SPP1, were correlated with an unfavorable clinical outcome and increased immune cell infiltration in ovarian cancer. Of these genes, ITGB2 tended to be the gene most correlated with various immune cell infiltrations and had a strong correlation with significant M2 macrophages infiltration (r = 0.707, p = 4.71 × 10^-39), while it had a moderate correlation with CD4+/CD8+ T cells and B cells. This characteristic explains why the high expression of ITGB2 was accompanied by immune activation but did not reverse carcinogenesis. Additionally, we confirmed that ITGB2 was over-expressed in ovarian cancer tissues and was mainly located in cytoplasm, detected by Western blotting and the immunohistochemical method. In summary, ITGB2 may serve as a prognostic immunomarker for ovarian cancer patients.