The Ovarian Cancer Tumor Immune Microenvironment (TIME) as Target for Therapy: A Focus on Innate Immunity Cells as Therapeutic Effectors

CST2 promotes cell proliferation and regulates cell cycle by activating Wnt-β-catenin signalling pathway in serous ovarian cancer

BACKGROUND

Cystatin SA (CST2) plays multiple roles in different types of malignant tumours; however, its role in serous ovarian cancer (SOC) remains unclear. Therefore, we aimed to investigate the expression levels, survival outcomes, immune cell infiltration, proliferation, cell cycle, and underlying molecular mechanisms associated with the CST2 signature in SOC.

METHODS

The Cancer Genome Atlas database was used to acquire clinical information and CST2 expression profiles from patients with SOC. Wilcoxon rank-sum tests were used to compare CST2 expression levels between SOC and normal ovarian tissues. A prognostic assessment of CST2 was conducted using Cox regression analysis and the Kaplan-Meier method. Differentially expressed genes were identified using functional enrichment analysis. Immune cell infiltration was examined using a single-sample gene set enrichment analysis. Cell cycle characteristics and proliferation were assessed using a colony formation assay, flow cytometry, and a cell counting kit-8 assay. Western blots and quantitative reverse transcription PCR analyses were employed to examine CST2 expressions and related genes involved in the cell cycle and the Wnt-β-catenin signalling pathway.

RESULTS

Our findings revealed significant upregulation of CST2 in SOC, and elevated CST2 expression was correlated with advanced clinicopathological characteristics and unfavourable prognoses. Pathway enrichment analysis highlighted the association between the cell cycle and the Wnt signalling pathway. Moreover, increased CST2 levels were positively correlated with immune cell infiltration. Functionally, CST2 played vital roles in promoting cell proliferation, orchestrating the G1-to-S phase transition, and driving malignant SOC progression through activating the Wnt-β-catenin signalling pathway.

CONCLUSIONS

The elevated expression of CST2 may be related to the occurrence and progression of SOC by activating the Wnt-β-catenin pathway. Additionally, our findings suggest that CST2 is a promising novel biomarker with potential applications in therapeutic, prognostic, and diagnostic strategies for SOC.

Mitochondrial activity related genes of mast cells identify poor prognosis and metastasis of ovarian cancer

The pro-tumorigenic or anti-tumorigenic role of tumor infiltrating mast cells (TIMs) in tumors depends not only on the type of cancer and the degree of tumor progression, but also on their location in the tumor bulk. In our investigation, we employed immunohistochemistry to reveal that the mast cells (MCs) in the tumor stroma are positively correlated with metastasis of ovarian cancer (OC), but not in the tumor parenchyma. To delve deeper into the influence of different culture matrix stiffness on MCs' biological functions within the tumor parenchymal and stromal regions, we conducted a transcriptome analysis of the mouse MC line (P815) cultured in two-dimensional (2D) or three-dimensional (3D) culture system. Further research has found that the softer 3D extracellular matrix stiffness could improve the mitochondrial activity of MCs to promote proliferation by increasing the expression levels of mitochondrial activity-related genes, namely Pet100, atp5md, and Cox7a2. Furthermore, employing LASSO regression analysis, we identified that Pet100 and Cox7a2 were closely associated with the prognosis of OC patients. These two genes were subsequently employed to construct a risk score model, which revealed that the high-risk group model as one of the prognostic factors for OC patients. Additionally, the XCell algorithm analysis showed that the high-risk group displayed a broader spectrum of immune cell infiltrations. Our research revealed that TIMs in the tumor stroma could promote the metastasis of OC, and mitochondrial activity-related proteins Pet100/Cox7a2 can serve as biomarkers for prognostic evaluation of OC.

Blockade of TGF-β and PD-L1 by bintrafusp alfa promotes survival in preclinical ovarian cancer models by promoting T effector and NK cell responses

BACKGROUND

Failure of immunotherapy in high-grade serous ovarian cancer (HGSC) may be due to high levels of transforming growth factor-β (TGF-β) in ascites or tumour immune microenvironment (TIME). Here, we test whether coordinated blockade of TGF-β and PD-L1 with bintrafusp alfa (BA) can provoke anti-tumour immune responses in preclinical HGSC models.

METHODS

BA is a first-in-class bifunctional inhibitor of TGF-β and PD-L1, and was tested for effects on overall survival and altered TIME in syngeneic HGSC models.

RESULTS

Using a mouse ID8-derived HGSC syngeneic model with IFNγ-inducible PD-L1 expression, BA treatments significantly reduced ascites development and tumour burden. BA treatments depleted TGF-β and VEGF in ascites, and skewed the TIME towards cytotoxicity compared to control. In the BR5 HGSC syngeneic model, BA treatments increased tumour-infiltrating CD8 T cells with effector memory and cytotoxic markers, as well as cytolytic NK cells. Extended BA treatments in the BR5 model produced ∼50% BA-cured mice that were protected from re-challenge. These BA-cured mice had increased peritoneal T-effector memory and NK cells compared to controls.

CONCLUSIONS

Our preclinical studies of BA in advanced ovarian cancer models support further testing of BA as an improved immunotherapy option for patients with advanced ovarian cancer.

Tissue damage from chronic liver injury inhibits peripheral NK cell abundance and proinflammatory function

One of the difficulties in the treatment of hepatocellular carcinoma is that it is impossible to eliminate the inhibitory effect of the tumor microenvironment on immune response. Therefore, it is particularly important to understand the formation process of the tumor microenvironment. Chronic inflammation is the core factor of cancer occurrence and the leading stage of inflammation-cancer transformation, and the natural killer cell subsets play an important role in it. Our study confirmed that in the stage of chronic liver injury, the local immunosuppressive microenvironment of the liver (i.e. the damaged microenvironment) has been formed, but this inhibitory effect is only for peripheral natural killer cells and has no effect on tissue-resident natural killer subsets. The markers of damage microenvironment are the same as those of tumor microenvironment.

Long non-coding RNA RAD51-AS1 promotes the tumorigenesis of ovarian cancer by elevating EIF5A2 expression

PURPOSE

The present study aims to determine the molecular mechanism mediated by RAD51 antisense RNA 1 (RAD51-AS1) in ovarian cancer (OvCA).

METHODS

The data associated with RAD51-AS1 in OvCA were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Relative expression of RAD51-AS1 was detected. Determination of cell proliferation, metastasis, and invasion was performed by cell counting, colony formation, would-healing, and transwell invasion assays. Protein levels were detected by western blotting. The molecular mechanism mediated by RAD51-AS1 was predicted by bioinformatics analysis and verified by dual-luciferase reporter assays. Subcutaneous tumorigenesis models were used to confirm the function of RAD51-AS1 in vivo.

RESULTS

Data from TCGA and GEO showed that RAD51-AS1 was associated with poor prognosis in OvCA patients and DNA repair, cell cycle, focal adhesion, and apoptosis in SKOV3.ip cells. High levels of RAD51-AS1 were detected in OvCA cells. Overexpressing RAD51-AS1 enhanced the proliferative, invading, and migratory capabilities of OvCA cells in vitro while silencing RAD51-AS1 exhibited the opposite effects. Mechanically, RAD51-AS1 elevated eukaryotic initiation factor 5A2 (EIF5A2) expression as a sponge for microRNA (miR)-140-3p. Finally, the role of RAD51-AS1 was verified by subcutaneous tumorigenesis models.

CONCLUSION

RAD51-AS1 promoted OvCA progression by the regulation of the miR-140-3p/EIF5A2 axis, which illustrated the potential therapeutic target for OvCA.

Let-7i enhances anti-tumour immunity and suppresses ovarian tumour growth

Cancer immunotherapy has seen significant success in the last decade for cancer management by enhancing endogenous cancer immunity. However, immunotherapies developed thus far have seen limited success in the majority of high-grade serous carcinoma (HGSC) ovarian cancer patients. This is largely due to the highly immunosuppressive tumour microenvironment of HGSC and late-stage identification. Thus, novel treatment interventions are needed to overcome this immunosuppression and complement existing immunotherapies. Here, we have identified through analysis of > 600 human HGSC tumours a critical role for Let-7i in modulating the tumoural immune network. Tumoural expression of Let-7i had high positive correlation with anti-cancer immune signatures in HGSC patients. Confirming this role, enforced Let-7i expression in murine HGSC tumours resulted in a significant decrease in tumour burden with a significant increase in tumour T cell numbers in tumours. In concert with the improved tumoural immunity, Let-7i treatment also significantly increased CD86 expression in antigen presenting cells (APCs) in the draining lymph nodes, indicating enhanced APC activity. Collectively, our findings highlight an important role of Let-7i in anti-tumour immunity and its potential use for inducing an anti-tumour effect in HGSC.

Role of Tumor-Associated Macrophages in Cervical Cancer: Integrating Classical Perspectives with Recent Technological Advances

Tumor-associated macrophages (TAMs) play a pivotal role in the tumor microenvironment, influencing cancer progression and contributing to poor prognosis. However, in cervical cancer (CC), their significance and involvement are relatively less studied than in other gynecological cancers such as ovarian and endometrial cancer. This review aims to provide an overview of TAMs, covering their origins and phenotypes and their impact on CC progression, along with major TAM-targeted therapeutic approaches. Furthermore, we advocate for the integration of cutting-edge research methodologies, such as single-cell RNA sequencing and spatial RNA sequencing, to enable in-depth and comprehensive investigations into TAMs in CC, which would be beneficial in leading to more personalized and effective immunotherapy strategies for patients with CC.

Preoperative neutrophil/lymphocyte ratio as prognostic factor in epithelial ovarian cancer

Objectives

To determine if there is an association between the neutrophil to lymphocyte ratio (NLR) and prognosis in patients with epithelial ovarian cancer (EOC) diagnosed and treated in a Spanish population.

Material and methods

Retrospective cohort of patients with epithelial ovarian cancer who had neutrophil and lymphocyte values in complete blood count before the histopathological diagnosis and survival of at least three months, in an intermediate complexity hospital. Convenience sampling. Measured variables included age, menopausal stage, parity, International Federation of Gynecology and Obstetrics (FIGO) stage, treatment type, residual tumor, lymph node involvement, presence of ascites, cytology, histologic type, differentiation grade, and CA-125 values. Additionally, outcomes, overall survival, disease/progression-free survival were also measured. Bivariate inferential and Cox regression analyses were performed.

Results

Out of 78 candidates, 60 women with EOC were included. Of them, 24 (40%) had a low NLR (≤ 2,9) while 36 (60%) had a high NLR (> 2,9). An association was found between high NLR levels and suboptimal cytoreductive surgery. High NLR ratios were associated with lower overall survival (Hazard ratio (HR): 4.1; 95% CI: 1.4-11.8) and lower 5-year disease-free survival (HR: 2.6; 95% CI: 1.2-5.7).

Conclusions

A plasma neutrophil to lymphocyte ratio of more than 2.9 was associated with poor prognosis in patients with epithelial ovarian cancer in our setting. There is a need to establish the optimal cut-off point and conduct prospective studies with larger patient numbers in order to support this information.

Innate immune cells: Key players of orchestra in modulating tumor microenvironment (TME)

The tumor microenvironment (TME) with vital role in cancer progression is composed of various cells such as endothelial cells, immune cells, and mesenchymal stem cells. In particular, innate immune cells such as macrophages, dendritic cells, myeloid-derived suppressor cells, neutrophils, innate lymphoid cells, γδT lymphocytes, and natural killer cells can either promote or suppress tumor progression when present in the TME. An increase in research on the cross-talk between the TME and innate immune cells will lead to new approaches for anti-tumoral therapeutic interventions. This review primarily focuses on the biology of innate immune cells and their main functions in the TME. In addition, it summarizes several innate immune-based immunotherapies that are currently tested in clinical trials.

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.

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

Background

Ovarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust.

Methods

420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed.

Results

64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes.

Conclusion

Our study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.

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.

Boosting cytotoxicity of adoptive allogeneic NK cell therapy with an oncolytic adenovirus encoding a human vIL-2 cytokine for the treatment of human ovarian cancer

Despite good results in the treatment of hematological malignancies, Natural killer (NK) cells have shown limited effectiveness in solid tumors, such as ovarian cancer (OvCa). Here, we assessed the potential of an oncolytic adenovirus expressing a variant interleukin-2 (vIL-2) cytokine, Ad5/3-E2F-d24-vIL2 (vIL-2 virus), also known as TILT-452, to enhance NK cell therapy efficacy in human OvCa ex vivo. Human OvCa surgical specimens were processed into single-cell suspensions and NK cells were expanded from healthy blood donors. OvCa sample digests were co-cultured ex vivo with NK cells and vIL-2 virus and cancer cell killing potential assessed in real time through cell impedance measurement. Proposed therapeutic combination was evaluated in vivo with an OvCa patient-derived xenograft (PDX) in mice. Addition of vIL-2 virus significantly enhanced NK cell therapy killing potential in treated OvCa co-cultures. Similarly, vIL-2 virus in combination with NK cell therapy promoted the best in vivo OvCa tumor control. Mechanistically, vIL-2 virus induced higher percentages of granzyme B in NK cells, and CD8+ T cells, while T regulatory cell proportions remained comparable to NK cell monotherapy in vivo. Ad5/3-E2F-d24-vIL2 virus treatment represents a promising strategy to boost adoptive NK cell therapeutic effect in human OvCa.

Exploring the promising potential of induced pluripotent stem cells in cancer research and therapy

The advent of iPSCs has brought about a significant transformation in stem cell research, opening up promising avenues for advancing cancer treatment. The formation of cancer is a multifaceted process influenced by genetic, epigenetic, and environmental factors. iPSCs offer a distinctive platform for investigating the origin of cancer, paving the way for novel approaches to cancer treatment, drug testing, and tailored medical interventions. This review article will provide an overview of the science behind iPSCs, the current limitations and challenges in iPSC-based cancer therapy, the ethical and social implications, and the comparative analysis with other stem cell types for cancer treatment. The article will also discuss the applications of iPSCs in tumorigenesis, the future of iPSCs in tumorigenesis research, and highlight successful case studies utilizing iPSCs in tumorigenesis research. The conclusion will summarize the advancements made in iPSC-based tumorigenesis research and the importance of continued investment in iPSC research to unlock the full potential of these cells.

Improving the cytotoxic response of tumor-infiltrating lymphocytes towards advanced stage ovarian cancer with an oncolytic adenovirus expressing a human vIL-2 cytokine

While the presence of tumor-infiltrating lymphocytes (TILs) associates with improved survival prognosis in ovarian cancer (OvCa) patients, TIL therapy benefit is limited. Here, we evaluated an oncolytic adenovirus coding for a human variant IL-2 (vIL-2) cytokine, Ad5/3-E2F-d24-vIL2 (vIL-2 virus), also known as TILT-452, as an immunotherapeutic strategy to enhance TIL responsiveness towards advanced stage OvCa tumors. Fragments of resected human OvCa tumors were processed into single-cell suspensions, and autologous TILs were expanded from said samples. OvCa tumor specimens were co-cultured with TILs plus vIL-2 virus, and cell killing was assessed in real time through cell impedance measurement. Combination therapy was further evaluated in vivo through a patient-derived xenograft (PDX) ovarian cancer murine model. The combination of vIL-2 virus plus TILs had best cancer cell killing ex vivo compared to TILs monotherapy. These results were supported by an in vivo experiment, where the best OvCa tumor control was obtained when vIL-2 virus was added to TIL therapy. Furthermore, the proposed therapy induced a highly cytotoxic phenotype demonstrated by increased granzyme B intensity in NK cells, CD4+ T, and CD8+ T cells in treated tumors. Our results demonstrate that Ad5/3-E2F-d24-vIL2 therapy consistently improved TILs therapy cytotoxicity in treated human OvCa tumors.

KRT19 is a Promising Prognostic Biomarker and Associates with Immune Infiltrates in Serous Ovarian Cystadenocarcinoma

Background

Ovarian cancer (OV) is the highest prevalent gynecologic tumor with complicated pathogenesis; high-grade serous ovarian cystadenocarcinoma (HGSOC) is the most epidemiological and malignant subtype of OV. Keratin type I cytoskeleton 19 (KRT19) is an intermediate filament protein which plays essential roles in the maintenance of epithelial cells. However, its role in OV remains largely unknown.

Methods

Bioinformatic analysis with various databases was conducted in this study. In details, KRT19 expression was assessed using databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and Human Protein Atlas (HPA). GO-KEGG and GSEA analysis were performed by R packages. The biological function of KRT19 was analyzed based on the single-cell sequencing information from CancerSEA database. The association of KRT19 expression with immunomodulator and chemokine was predicted via the TISIDB database.

Results

The expression of KRT19 was significantly upregulated in ovarian samples compared with normal controls. KRT19 expression was negatively associated with prognosis in OV, and further analysis revealed that KRT19 had promising diagnostic significance in distinguishing OV cancer from normal samples. GO-KEGG and GSEA analysis indicated that KRT19 was associated with multiple biological functions and pathways including epidermis development, apical junction, inflammatory response, and epithelial mesenchymal transition. By using different GEO series, we found that KRT19 was differentially expressed in OV-associated tissues. Furthermore, the increased KRT19 expression was positively correlated with the immune infiltration levels of the most immune cells in OV.

Conclusion

This study demonstrated that KRT19 is a promising prognosis and diagnosis biomarker that determines cancer progression and is correlated with tumor immune cells infiltration in OV, suggesting being a molecular target for immunotherapies.

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.

Anti-PD-1 antibody armored γδ T cells enhance anti-tumor efficacy in ovarian cancer

γδ T cells have the unique ability to detect a wide range of tumors with low mutation burdens, making them attractive candidates for CAR-T-cell therapy. Unlike αβ T cells and other immune cells, γδ T cells are superior in MHC non-restriction, selective cell recruitment, and rapid activation. However, clinical trials have shown limited clinical benefits, and the adoptive transplantation of γδ T cells has often fallen short of expectations. We hypothesized that the limited effectiveness of γδ T cells in eradicating tumor cells may be attributed to the inhibitory tumor microenvironment induced by the suppressive PD-1/PD-L1 axis. Herein, we constructed novel armored γδ T cells capable of secreting humanized anti-PD-1 antibodies, referred to as "Lv-PD1-γδ T cells. Lv-PD1-γδ T cells showed improved proliferation and enhanced cytotoxicity against tumor cells, resulting in augmented therapeutic effects and survival benefits in ovarian tumor-bearing mice. These engineered cells demonstrated a prolonged in vivo survival of more than 29 days, without any potential for tumorigenicity in immunodeficient NOD/SCID/γ null mice. We also found that Lv-PD1-γδ T cells exhibited excellent tolerance and safety in humanized NOD/SCID/γ null mice. With attenuated or eliminated immunosuppression and maximized cytotoxicity efficacy by the local secretion of anti-PD1 antibodies in tumors, Lv-PD1-γδ T cells can serve as a promising "off-the-shelf" cell therapy against cancers.

CT radiomics prediction of CXCL9 expression and survival in ovarian cancer

BACKGROUND

C-X-C motif chemokine ligand 9 (CXCL9), which is involved in the pathological processes of various human cancers, has become a hot topic in recent years. We developed a radiomic model to identify CXCL9 status in ovarian cancer (OC) and evaluated its prognostic significance.

METHODS

We analyzed enhanced CT scans, transcriptome sequencing data, and corresponding clinical characteristics of CXCL9 in OC using the TCIA and TCGA databases. We used the repeat least absolute shrinkage (LASSO) and recursive feature elimination(RFE) methods to determine radiomic features after extraction and normalization. We constructed a radiomic model for CXCL9 prediction based on logistic regression and internal tenfold cross-validation. Finally, a 60-month overall survival (OS) nomogram was established to analyze survival data based on Cox regression.

RESULTS

CXCL9 mRNA levels and several other genes involving in T-cell infiltration were significantly relevant to OS in OC patients. The radiomic score (rad_score) of our radiomic model was calculated based on the five features for CXCL9 prediction. The areas under receiver operating characteristic (ROC) curves (AUC-ROC) for the training cohort was 0.781, while that for the validation cohort was 0.743. Patients with a high rad_score had better overall survival (P < 0.001). In addition, calibration curves and decision curve analysis (DCA) showed good consistency between the prediction and actual observations, demonstrating the clinical utility of our model.

CONCLUSION

In patients with OC, the radiomics signature(RS) of CT scans can distinguish the level of CXCL9 expression and predict prognosis, potentially fulfilling the ultimate purpose of precision medicine.

MUC16 stimulates neutrophils to an inflammatory and immunosuppressive phenotype in ovarian cancer

BACKGROUND

MUC16 (CA125) is a commonly used tumor marker for ovarian cancer screening and reported to be an immunosuppressive factor by acting on the sialic acid-binding immunoglobulin-like lectin-9 (Siglec-9) on the surface of natural killer cells (NK cells), B cells, and monocytes. However, the role of MUC16 on neutrophils in the tumor microenvironment remains to be further explored.

METHODS

The correlation between the proportion and count of peripheral blood cells, serum inflammatory-related factors and serum MUC16 (CA125) level in patients was constructed based on clinical samples. RNAseq data was obtained from TCGA and sequencing of ovarian cancer tissues, followed by TIMER immune cell infiltration and correlation analysis. Ovarian cancer organoid was constructed to stimulate neutrophils with immunophenotype identification by qPCR and flow cytometry. MUC16 protein stimulation to neutrophils validated the role of MUC16 under the analysis of RNA sequencing and inhibition of NK cytotoxicity in vitro.

RESULTS

The serum MUC16 level was positively correlated with the proportion and count of peripheral blood neutrophils, neutrophil-to-lymphocyte ratio (NLR) and inflammatory factors IL-6, IL-8, IL-10 and IL-2R. Siglec-9, the receptor of MUC16, was expressed on neutrophils and was positively correlated to neutrophil infiltration in ovarian cancer. After the stimulation of ovarian cancer organoids and MUC16 respectively, the proportions of CD11b+, CD66b+, and ICAM-1+ neutrophils were significantly increased, while the proportion of CXCR4+ neutrophils was slightly decreased, with increasing of of inflammatory factors MMP9, IL-8, OSM, IL-1β, TNF-α, CXCL3, and ROS. RNA-sequencing analysis revealed that inflammatory response, TNFA signaling pathway, and IL6-related pathway were upregulated in MUC16-stimulated neutrophils, accompanied by high expression of immunosuppression-related factors HHLA2, IL-6, TNFRSF9, ADORA2A, CD274 (PD-L1), and IDO1. NK cytotoxicity was decreased when treated by supernanant of MUC16-stimulated neutrophils in vitro.

CONCLUSION

MUC16 acted on neutrophils by Siglec-9 leading to an inflammatory and immunosuppressive phenotype in ovarian cancer.

Bortezomib-loaded mixed micelles realize a "three-in-one" effect for enhanced breast cancer treatment

Comprehensively regulating the TME is now regarded as a promising approach for cancer treatment. Herein, a novel "three-in-one" effect is presented for simultaneously killing tumor cells, inhibiting the EMT of CAFs, and improving immune responses. In this study, bortezomib (BTZ) is selected for the treatment of breast cancer; it has multiple pharmacological mechanisms for killing tumor cells through the NF-κB signaling pathway, inhibiting the activity of CAFs by activating caspase-3, and enhancing the function of CD8+ T cells by regulating the expression of immune-stimulating factors. To improve the druggability of BTZ in solid tumors, BTZ-loaded lipid/glycocholic acid mixed micelles (BTZ-LGs) were prepared to verify the "three-in-one" effect in killing tumor cells, inhibiting CAFs, and improving immune responses. In the present work, BTZ-LGs were verified to show enhanced in vitro cytotoxicity in both 4T1 cells and 4T1/NIH3T3 co-cultured cells, as well as a superior in vivo treatment effect in different tumor-bearing mouse models. Additionally, BTZ-LGs could regulate the expression of α-SMA, caspase-3, E-cadherin, and N-cadherin, indicating their good inhibiting ability on both tumor cells and CAFs. More importantly, immunological analysis revealed that BTZ-LGs promoted the expression of the immunostimulatory factor IL-2 in tumor tissues, activated anti-tumor T cells, and overcame tumor-induced CD8+ T cell dysfunction. All these findings suggest that BTZ-LGs can achieve a "three-in-one" effect in terms of killing tumor cells, suppressing CAFs, and improving immune responses. This simple and multi-effective therapeutic strategy offers a promising approach for cancer therapy.

PD-1/PD-L1 immune checkpoint blockade in ovarian cancer: dilemmas and opportunities

Immune checkpoint inhibitors (ICIs) have revolutionized treatment in oncology. Antibodies against PD-1/PD-L1 and ICI-based combinations are under clinical investigations in multiple cancers, including ovarian cancer. However, the success of ICIs has not materialized in ovarian cancer, which remains one of the few malignancies where ICIs exhibit modest efficacy as either monotherapy or combination therapy. In this review, we summarize completed and ongoing clinical trials of PD-1/PD-L1 blockade in ovarian cancer, categorize the underlying mechanisms of resistance emergence, and introduce candidate approaches to rewire the tumor microenvironment (TME) to potentiate anti-PD-1/PD-L1 antibodies. Teaser: The intrinsic resistance of ovarian cancer to PD-1/PD-L1 blockade could be overcome by advanced understanding of underlying mechanisms and discoveries of new actionable targets for combinatory treatment.

Aptamers Versus Vascular Endothelial Growth Factor (VEGF): A New Battle against Ovarian Cancer

Cancer is one of the diseases that causes a high mortality as it involves unregulated and abnormal cell growth proliferation that can manifest in any body region. One of the typical ovarian cancer symptoms is damage to the female reproductive system. The death rate can be reduced through early detection of the ovarian cancer. Promising probes that can detect ovarian cancer are suitable aptamers. Aptamers, i.e., so-called chemical antibodies, have a strong affinity for the target biomarker and can typically be identified starting from a random library of oligonucleotides. Compared with other probes, ovarian cancer targeting using aptamers has demonstrated superior detection effectiveness. Various aptamers have been selected to detect the ovarian tumor biomarker, vascular endothelial growth factor (VEGF). The present review highlights the development of particular aptamers that target VEGF and detect ovarian cancer at its earliest stages. The therapeutic efficacy of aptamers in ovarian cancer treatment is also discussed.

The joint role of methylation and immune-related lncRNAs in ovarian cancer: Defining molecular subtypes and developing prognostic signature

INTRODUCTION

Complex outcome of ovarian cancer (OC) stems from the tumor immune microenvironment (TIME) influenced by genetic and epigenetic factors. This study aimed to comprehensively explored the subclasses of OC through lncRNAs related to both N6-methyladenosine (m6A)/N1-methyladenosine (m1A)/N7-methylguanosine (m7G)/5-methylcytosine (m5C) in terms of epigenetic variability and immune molecules and develop a new set of risk predictive systems.

MATERIAL AND METHODS

The lncRNA data of OC were collected from TCGA. Spearman correlation analysis on lncRNA data of OC with immune-related gene expression and with m6A/m5C/m1A/m7G were respectively conducted. The m6A/m5C/m1A/m7G-related m6A/m5C/m1A/m7G related immune lncRNA subtypes were identified on the basis of the prognostic lncRNAs. Heterogeneity among subtypes was evaluated by tumor mutation analysis, tumor microenvironment (TME) component analysis, response to immune checkpoint blocked (ICB) and chemotherapeutic drugs. A risk predictive system was developed based on the results of Cox regression analysis and random survival forest analysis of the differences between each specific cluster and other clusters.

RESULTS

Three m6A/m5C/m1A/m7G-related immune lncRNA subtypes of OC showing distinct differences in prognosis, mutation pattern, TIME components, immunotherapy and chemotherapy response were identified. A set of risk predictive system consisting of 10 lncRNA for OC was developed, according to which the risk score of samples in each OC dataset was calculated and risk type was defined.

CONCLUSIONS

This study classified three m6A/m5C/m1A/m7G-related immune lncRNA subtypes with distinct heterogeneous mutation patterns, TME components, ICB therapy and immune response, and provided a set of risk predictive system consisted of 10 lncRNA for OC.

Paxillin is a potential prognostic biomarker associated with immune cell infiltration in ovarian cancer

Objective

To investigate the expression, prognosis, and underlying mechanism of Paxillin (PXN) in ovarian cancer.

Materials and methods

By comprehensive use of various bioinformatics tools, we analyzed the expression of PXN and its prognostic value in ovarian cancer. Then, the enrichment analyses were conducted to determine the possible regulatory pathways PXN involved in ovarian cancer. Finally, the associations of PXN expression with immune cell infiltration and immune checkpoints were analyzed.

Results

PXN was highly expressed in ovarian cancer and its expression could independently predict the overall survival of ovarian cancer patients. More importantly, PXN had a superior ability in predicting long-term survival than age and tumor residual disease in ovarian cancer patients. In addition, PXN was positively related to adherens junction and tight junction pathways. Significant negative relationships between PXN expression and immune infiltrates were observed, however, PXN was positively connected with immune checkpoint (VSIR) in ovarian cancer.

Conclusions

PXN serves as a reliable prognostic biomarker and may be a potent therapeutic target for ovarian cancer. Moreover, high PXN expression may affect ovarian cancer progression via positive regulation of metastasis-related pathways.

Tumor microenvironment in ovarian cancer peritoneal metastasis

Ovarian cancer (OC) is one of the most common gynecological malignancies with high morbidity and mortality. The peritoneum is one of the most common metastatic sites in ovarian cancer, involving large amounts of ascites. However, its mechanism is unclear. The peritoneal microenvironment composed of peritoneal effusion and peritoneum creates favorable conditions for ovarian cancer progression and metastasis. Here, we reviewed the peritoneal metastasis patterns and molecular mechanisms of ovarian cancer, as well as major components of the peritoneal microenvironment, peritoneal effusion, and immune microenvironment, and investigated the relationship between the peritoneal microenvironment and ovarian cancer metastasis.

Immunostaining of stromal CD56 cells in ovarian malignancies

OBJECTIVES

The aim of this study was to evaluate CD56 immunostaining in the stroma of benign and malignant ovarian epithelial neoplasms and associate the CD56 immunostaining with prognostic factors and survival in ovarian cancer.

METHODS

Patients with ovarian epithelial neoplasia (n=77) were studied with a prospective cohort. The CD56 immunostaining was evaluated in the peritumoral stroma. Two groups were evaluated: benign ovarian neoplasms (n=40) and malignant ovarian neoplasms (n=37). Data were recorded for histological type and grade, International Federation of Gynecology and Obstetrics staging, molecular subtype, and lymph node metastases. Fisher's exact test and Kaplan-Meier survival curves were used, with a significance level of ≤0.05.

RESULTS

We found greater CD56 stromal immunostaining in malignant neoplasms when compared to the group of benign neoplasms (p=0.00001). There was no significant difference in relation to the prognostic factors and survival.

CONCLUSION

Malignant ovarian neoplasms showed higher stromal CD56 immunostaining. As the prognostic value of natural killer in ovarian cancer is controversial, knowing the specific function of each cell present both in the tumor tissue and systemically may help guide successful immunotherapies in the near future.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

A Nanomedicine Structure-Activity Framework for Research, Development, and Regulation of Future Cancer Therapies

Despite their clinical success in drug delivery applications, the potential of theranostic nanomedicines is hampered by mechanistic uncertainty and a lack of science-informed regulatory guidance. Both the therapeutic efficacy and the toxicity of nanoformulations are tightly controlled by the complex interplay of the nanoparticle's physicochemical properties and the individual patient/tumor biology; however, it can be difficult to correlate such information with observed outcomes. Additionally, as nanomedicine research attempts to gradually move away from large-scale animal testing, the need for computer-assisted solutions for evaluation will increase. Such models will depend on a clear understanding of structure-activity relationships. This review provides a comprehensive overview of the field of cancer nanomedicine and provides a knowledge framework and foundational interaction maps that can facilitate future research, assessments, and regulation. By forming three complementary maps profiling nanobio interactions and pathways at different levels of biological complexity, a clear picture of a nanoparticle's journey through the body and the therapeutic and adverse consequences of each potential interaction are presented.

Research progress on anti-ovarian cancer mechanism of miRNA regulating tumor microenvironment

Ovarian cancer is the most deadly malignancy among women, but its complex pathogenesis is unknown. Most patients with ovarian cancer have a poor prognosis due to high recurrence rates and chemotherapy resistance as well as the lack of effective early diagnostic methods. The tumor microenvironment mainly includes extracellular matrix, CAFs, tumor angiogenesis and immune-associated cells. The interaction between tumor cells and TME plays a key role in tumorigenesis, progression, metastasis and treatment, affecting tumor progression. Therefore, it is significant to find new tumor biomarkers and therapeutic targets. MicroRNAs are non-coding RNAs that post-transcriptionally regulate the expression of target genes and affect a variety of biological processes. Studies have shown that miRNAs regulate tumor development by affecting TME. In this review, we summarize the mechanisms by which miRNAs affect ovarian cancer by regulating TME and highlight the key role of miRNAs in TME, which provides new targets and theoretical basis for ovarian cancer treatment.

Emerging perspectives on growth factor metabolic relationships in the ovarian cancer ascites environment

The ascites ecosystem in ovarian cancer is inhabited by complex cell types and is bathed in an environment rich in cytokines, chemokines, and growth factors that directly and indirectly impact metabolism of cancer cells and tumor associated cells. This milieu of malignant ascites, provides a 'rich' environment for the disease to thrive, contributing to every aspect of advanced ovarian cancer, a devastating gynecological cancer with a significant gap in targeted therapeutics. In this perspective we focus our discussions on the 'acellular' constituents of this liquid malignant tumor microenvironment, and how they influence metabolic pathways. Growth factors, chemokines and cytokines are known modulators of metabolism and have been shown to impact nutrient uptake and metabolic flexibility of tumors, yet few studies have explored how their enrichment in malignant ascites of ovarian cancer patients contributes to the metabolic requirements of ascites-resident cells. We focus here on TGF-βs, VEGF and ILs, which are frequently elevated in ovarian cancer ascites and have all been described to have direct or indirect effects on metabolism, often through gene regulation of metabolic enzymes. We summarize what is known, describe gaps in knowledge, and provide examples from other tumor types to infer potential unexplored roles and mechanisms for ovarian cancer. The distribution and variation in acellular ascites components between patients poses both a challenge and opportunity to further understand how the ascites may contribute to disease heterogeneity. The review also highlights opportunities for studies on ascites-derived factors in regulating the ascites metabolic environment that could act as a unique signature in aiding clinical decisions in the future.

Immunobiology of high-grade serous ovarian cancer: lessons for clinical translation

Treatment of high-grade serous ovarian cancer (HGSOC) remains challenging. Although HGSOC can potentially be responsive to immunotherapy owing to endogenous immunity at the molecular or T cell level, immunotherapy for this disease has fallen short of expectations to date. This Review proposes a working classification for HGSOC based on the presence or absence of intraepithelial T cells, and elaborates the putative mechanisms that give rise to such immunophenotypes. These differences might explain the failures of existing immunotherapies, and suggest that rational therapeutic approaches tailored to each immunophenotype might meet with improved success. In T cell-inflamed tumours, treatment could focus on mobilizing pre-existing immunity and strengthening the activation of T cells embedded in intraepithelial tumour myeloid niches. Conversely, in immune-excluded and immune-desert tumours, treatment could focus on restoring inflammation by reprogramming myeloid cells, stromal cells and vascular epithelial cells. Poly(ADP-ribose) polymerase (PARP) inhibitors, low-dose radiotherapy, epigenetic drugs and anti-angiogenesis therapy are among the tools available to restore T cell infiltration in HGSOC tumours and could be implemented in combination with vaccines and redirected T cells.

Therapeutic implications of the tumor microenvironment in ovarian cancer patients receiving PD-1/PD-L1 therapy

Epithelial ovarian cancer (EOC) ranks as the second most common cause of gynecologic cancer death. The conventional treatment for patients with EOC is postoperative therapy along with platinum chemotherapy. However, a more efficient treatment regimen is of great need for these patients diagnosed with advanced disease (FIGO stages III-IV), whose survival is approximately 29%. Immunotherapy seems to be an encouraging therapeutic strategy for EOC. Given the crucial role in the complicated interactions between tumor cells and other cells, the tumor microenvironment (TME) influences the response to immunotherapy. In this review, we discuss feasible strategies for EOC immunotherapy by exploiting the reciprocity of cancer cells and the constituents of the TME.

Efficacy evaluation of multi-immunotherapy in ovarian cancer: From bench to bed

Ovarian cancer, one of the most common gynecological malignancies, is characterized by high mortality and poor prognosis. Cytoreductive surgery and chemotherapy remain the mainstay of ovarian cancer treatment, and most women experience recurrence after standard care therapies. There is compelling evidence that ovarian cancer is an immunogenic tumor. For example, the accumulation of tumor-infiltrating lymphocytes is associated with increased survival, while increases in immunosuppressive regulatory T cells are correlated with poor clinical outcomes. Therefore, immunotherapies targeting components of the tumor microenvironment have been gradually integrated into the existing treatment options, including immune checkpoint blockade, adoptive cell therapy, and cancer vaccines. Immunotherapies have changed guidelines for maintenance treatment and established a new paradigm in ovarian cancer treatment. Despite single immunotherapies targeting DNA repair mechanisms, immune checkpoints, and angiogenesis bringing inspiring efficacy, only a subset of patients can benefit much from it. Thus, the multi-immunotherapy investigation remains an active area for ovarian cancer treatment. The current review provides an overview of various clinically oriented forms of multi-immunotherapy and explores potentially effective combinational therapies for ovarian cancer.

Human RNASET2: A Highly Pleiotropic and Evolutionary Conserved Tumor Suppressor Gene Involved in the Control of Ovarian Cancer Pathogenesis

Ovarian cancer represents one of the most malignant gynecological cancers worldwide, with an overall 5-year survival rate, being locked in the 25-30% range in the last decade. Cancer immunotherapy is currently one of the most intensively investigated and promising therapeutic strategy and as such, is expected to provide in the incoming years significant benefits for ovarian cancer treatment as well. Here, we provide a detailed survey on the highly pleiotropic oncosuppressive roles played by the human RNASET2 gene, whose protein product has been consistently reported to establish a functional crosstalk between ovarian cancer cells and key cellular effectors of the innate immune system (the monocyte/macrophages lineage), which is in turn able to promote the recruitment to the cancer tissue of M1-polarized, antitumoral macrophages. This feature, coupled with the ability of T2 ribonucleases to negatively affect several cancer-related parameters in a cell-autonomous manner on a wide range of ovarian cancer experimental models, makes human RNASET2 a very promising candidate to develop a "multitasking" therapeutic approach for innovative future applications for ovarian cancer treatment.

A novel tumor mutational burden-based risk model predicts prognosis and correlates with immune infiltration in ovarian cancer

Tumor mutational burden (TMB) has been reported to determine the response to immunotherapy, thus affecting the patient’s prognosis in many cancers. However, it is unclear whether TMB or TMB-related signature could be used as prognostic indicators for ovarian cancer (OC), as its potential association with immune infiltration remains poorly understood. Therefore, this study aimed to develop a novel TMB-related risk model (TMBrisk) to predict the prognosis of OC patients on the basis of exploring TMB-related genes, and to explore the potential association between TMB/TMBrisk and immune infiltration. The mutational landscape, TMB scores, and correlations between TMB and clinical characteristics and immune infiltration were investigated in The Cancer Genome Atlas (TCGA)-OV cohort. Differentially expressed gene (DEG) analyses and weighted gene co-expression network analysis (WGCNA) were performed to derive TMB-related genes. TMBrisk was constructed by Cox regression and further validated in Gene Expression Omnibus (GEO) datasets. The mRNA and protein expression levels and biological functions of TMBrisk hub genes were verified through Gene Expression Profiling Interactive Analysis (GEPIA), GSCA Lite, the Human Protein Atlas (HPA) database, and RT-qPCR. TMBrisk-related biological phenotypes were analyzed in function enrichment and tumor immune infiltration signature. Potential therapeutic regimens were inferred utilizing the Genomics of Drug Sensitivity in Cancer (GDSC) database and connectivity map (CMap). According to our results, higher TMB was associated with better survival and higher CD8+ T cell, regulatory T cell, and NK cell infiltration. TMBrisk was developed based on CBWD1, ST7L, RFX5-AS1, C3orf38, LRFN1, LEMD1, and HMGB1. High TMBrisk was identified as a poor factor for prognosis in TCGA and GEO datasets; the high-TMBrisk group comprised more higher-grade (G2 and G3) and advanced clinical stage (stage III/IV) tumors. Meanwhile, higher TMBrisk was associated with an immunosuppressive phenotype, with less infiltration of a majority of immunocytes and less expression of several genes of the human leukocyte antigen (HLA) family. Moreover, a nomogram containing TMBrisk showed a strong predictive ability demonstrated by time-dependent ROC analysis. Overall, this novel TMB-related risk model (TMBrisk) could predict prognosis, evaluate immune infiltration, and discover new therapeutic regimens in OC, which is very promising in clinical promotion.

Downregulated Dual-Specificity Protein Phosphatase 1 in Ovarian Carcinoma: A Comprehensive Study With Multiple Methods

Introduction: We aimed to explore the abnormal expression of dual-specificity protein phosphatase 1 (DUSP1) and its latent molecular mechanisms in ovarian carcinoma (OVCA).

Materials and Methods: Two clinical cohorts collected from two different hospitals were used to evaluate the expression of DUSP1 protein in OVCA tissues. RNA-sequencing and microarray datasets were utilised to verify DUSP1 expression at mRNA levels in both OVCA tissues and in the peripheral blood of OVCA patients. Furthermore, an integrated calculation was performed to pool the standard mean difference (SMD) from each cohort in order to comprehensively assess the expression of DUSP1 in OVCA. Furthermore, we examined the relationship among DUSP1, tumour microenvironment (TME), and chemotherapy resistance in OVCA. Moreover, we used pathway enrichment analysis to explore the underlying mechanisms of DUSP1 in OVCA.

Results: A pooled SMD of −1.19 (95% CI [−2.00, −0.38], p = 0.004) with 1,240 samples revealed that DUSP1 was downregulated in OVCA at both mRNA and protein levels. The area under the receiver operating characteristic curve of 0.9235 indicated the downregulated DUSP1 in peripheral blood may have a non-invasive diagnostic value in OVCA. Through six algorithms, we identified that DUSP1 may related to tumour-infiltrating T cells and cancer associated fibroblasts (CAFs) in OVCA. Pathway enrichment demonstrated that DUSP1 might participate in the mitogen-activated protein kinase (MAPK) signalling pathway. Furthermore, DUSP1 may have relations with chemotherapy resistance, and a favourable combining affinity was observed in the paclitaxel-DUSP1 docking model.

Conclusion: DUSP1 was downregulated in OVCA, and this decreasing trend may affect the infiltration of CAFs. Finally, DUSP1 may have a targeting relation with paclitaxel and participate in MAPK signaling pathways.

The Immune Subtype Contributes to Distinct Overall Survival for Ovarian Cancer Patients With Platinum-Based Adjuvant Therapy

Objective

Nowadays, platinum-based therapy has been widely used as the first-line therapy of ovarian cancer. However, the effect of the tumor microenvironment on platinum-based therapy remains unclear. In this study, we aim to investigate the relationship between immune microenvironment subtypes and the prognosis of platinum-based therapy in ovarian cancer.

Methods

We integrated 565 ovarian cancer samples from two datasets and obtained the immune subtypes (ISs) by consistent clustering of 1190 immune-related gene expressions. The proportional hazards regression model was used to assess the relationship between ISs and the prognosis of platinum-based adjuvant therapy including progression-free survival (PFS) and overall survival (OS). The prognostic contribution of ISs was validated in three additional cohorts. Non-parametric tests were used to assess genomic characteristics, the proportion of immune cells, and immune-related signature differences among ISs.

Results

We identified and validated five ISs associated with different clinical outcomes of the platinum-based adjuvant therapy in ovarian cancer patients. These differences were only found in OS rather than PFS. An immune subtype had the worst OS. Those patients mainly derived from the mesenchymal subtype had the lowest tumor purity with a high leukocyte fraction as well as stromal fraction and had the highest TGF-β response signaling. By contrast, an immune subtype characterized by immunoreactive status with the highest CD8+T cell infiltration and elevated IFN-γ response signaling had the best prognosis. Other subtypes with more diverse immunologic features such as lowest macrophage regulation signaling showed intermediate prognoses. Notably, the contribution of ISs to OS was independent of the clinical response to platinum-based drugs.

Conclusion

Our analysis revealed the association between different immune characteristics and platinum-based adjuvant therapy, indicating the combination of ISs and chemotherapy could optimize the treatment strategy of OC patients.

A methylation-driven genes prognostic signature and the immune microenvironment in epithelial ovarian cancer

Aberrant gene methylation has been implicated in the development and progression of tumors. In this study, we aimed to identity methylation driven genes involved in epithelial ovarian cancer (EOC) to establish a prognostic signature for patients with EOC. We identified and verified 6 MDGs that are closely related to the prognosis of ovarian cancer. A prognostic risk score model and nomogram for predicting the prognosis of ovarian cancer were constructed based on the six MDGs. It can also effectively reflect the immune environment and immunotherapy response of ovarian cancer. These MDGs have great significance to the implementation of individualized treatment and disease monitoring of ovarian cancer patients.

Identification of a novel lipid metabolism-related gene signature within the tumour immune microenvironment for breast cancer

Background

Systemic factors can strongly affect how tumour cells behave, grow, and communicate with other cells in breast cancer. Lipid metabolic reprogramming is a systemic process that tumour cells undergo; however, the formation and dynamics of lipids associated with the tumour immune microenvironment (TIME) remain unclear. The investigation of the sophisticated bidirectional crosstalk of tumour cells with cancer metabolism, gene expression, and TIME could have the potential to identify novel biomarkers for diagnosis, prognosis, and immunotherapy. This study aimed to construct a prognostic signature to detect the bicrosstalk between the lipid metabolic system and the TIME of breast cancer.

Methods

To detect the expression of LRGs and execute GO/KEGG analysis, the R program was chosen. Considering the clinical information and pathological features, a prognostic gene signature was constructed by LASSO Cox regression analysis. TMB, MSI, and immune infiltration analyses were performed, and consensus cluster analysis of LRGs was also performed.

Results

These 16 lipid metabolism-related genes (LRGs) were mainly involved in the process of lipid metabolism and fatty acid binding in breast cancer. Prognosis analysis identified the prognostic value of FABP7(Fatty acid binding protein 7) and NDUFAB1(NADH:ubiquinone oxidoreductase subunit AB1) in breast cancer patients. The prognostic gene signature constructed with FABP7 and NDUFAB1 was significantly related to immune cell infiltration and could predict the overall survival rate with above average correctness of breast cancer patients. FABP7 and NDUFAB1 were proven to have relevance in immune cell infiltration and tumour mutation burden (TMB). Consensus cluster analysis identified that the upregulated mRNAs were mostly related to the oncogenesis process, while the downregulated mRNAs were associated with immune-related signalling pathways.

Conclusion

A comprehensive analysis was performed to evaluate the lipid metabolic system and identified a signature constructed by two prognostic genes for immunotherapies in breast cancer. The results also revealed evidence of vulnerabilities in the interplay between the lipid metabolic system and the TIME in breast cancer. Further data with clinical studies and experiments are warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01651-9.

Immune Subtypes Characterization Identifies Clinical Prognosis, Tumor Microenvironment Infiltration, and Immune Response in Ovarian Cancer

Objective: Because of the modest immunotherapeutic response among ovarian carcinoma (OC) patients, it is significant to evaluate antitumor immune response and develop more effective precision immunotherapeutic regimens. Here, this study aimed to determine diverse immune subtypes of OC.

Methods: This study curated the expression profiles of prognostic immunologically relevant genes and conducted consensus clustering analyses for determining immune subtypes among OC patients in TCGA cohort. With Boruta algorithm, characteristic genes were screened for conducting an immune scoring system through principal component analysis algorithm. The single-sample gene set enrichment analysis and ESTIAMTE methods were adopted for quantifying the immune infiltrates and responses to chemotherapeutic agents were estimated with pRRophetic algorithm. Two immunotherapeutic cohorts were used for investigating the efficacy of immune score in predicting therapeutic benefits.

Results: Two immune subtypes were conducted among 377 OC patients. Immune subtype 2 was characterized by worse clinical prognosis, more frequent genetic variations and mutations, enhanced immune infiltrates, and increased expression of MHC molecules and programmed cell death protein 1/programmed death ligand 1 (PD-1/PD-L1). In total, 30 prognosis-relevant characteristic immune subtype–derived genes were identified for constructing the immune score of OC patients. High immune score was linked with more dismal prognosis, decreased immune infiltrations, and expression of MHC molecules. High immune score presented favorable sensitivity to doxorubicin and vinorelbine and reduced sensitivity to cisplatin. In addition, immune score possessed the potential in predicting benefits from anti–PD-1/PD-L1 therapy.

Conclusion: Collectively, our findings propose two complex and diverse immune subtypes of OC. Quantitative assessment of immune subtypes in individual patients strengthens the understanding of tumor microenvironment features and promotes more effective immunotherapeutic regimens.

Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling

Ovarian cancer (OC) grows and interacts constantly with a complex microenvironment, in which immune cells, fibroblasts, blood vessels, signal molecules and the extracellular matrix (ECM) coexist. This heterogeneous environment provides structural and biochemical support to the surrounding cells and undergoes constant and dynamic remodeling that actively promotes tumor initiation, progression, and metastasis. Despite the fact that traditional 2D cell culture systems have led to relevant medical advances in cancer research, 3D cell culture models could open new possibilities for the development of an in vitro tumor microenvironment more closely reproducing that observed in vivo. The implementation of materials science and technology into cancer research has enabled significant progress in the study of cancer progression and drug screening, through the development of polymeric scaffold-based 3D models closely recapitulating the physiopathological features of native tumor tissue. This article provides an overview of state-of-the-art in vitro tumor models with a particular focus on 3D OC cell culture in pre-clinical studies. The most representative OC models described in the literature are presented with a focus on hydrogel-based scaffolds, which guarantee soft tissue-like physical properties as well as a suitable 3D microenvironment for cell growth. Hydrogel-forming polymers of either natural or synthetic origin investigated in this context are described by highlighting their source of extraction, physical-chemical properties, and application for 3D ovarian cancer cell culture.

A Systematic Comparative Assessment of the Response of Ovarian Cancer Cells to the Chemotherapeutic Cisplatin in 3D Models of Various Structural and Biochemical Configurations-Does One Model Type Fit All?

Simple Summary

Epithelial Ovarian Cancer is considered to be a ‘silent killer’ and a challenge for gynaecological health across the world due to its asymptotic nature in the early stages, its late-stage diagnosis, high recurrence rate and resistance to currently available treatment methods (chemotherapy). These disheartening figures highlight the need for extensive in vitro studies to better understand this disease. A number of in vitro 3D models are currently available to aid in the study of ovarian cancer and its response to therapeutic methods. In this work, we report, for the first time, a comprehensive comparative study of three widely used 3D in vitro models for ovarian cancer, along with chemotherapy assessment of primary and metastatic cells. Our study highlights the importance of selecting an appropriate 3D in vitro platform, which is based on multiple factors including the origin of cells used, experimental time period and experimental design, even for one specific disease.

Abstract

Epithelial Ovarian Cancer (EOC) is a silent, deadly and aggressive gynaecological disease with a relatively low survival rate. This has been attributed, to some extent, to EOC’s high recurrence rate and resistance to currently available platinum-based chemotherapeutic treatment methods. Multiple groups have studied and reported the effect of chemotherapeutic agents on various EOC 3D in vitro models. However, there are very few studies wherein a direct comparative study has been carried out between the different in vitro 3D models of EOC and the effect of chemotherapy within them. Herein, we report, for the first time, a direct comprehensive systematic comparative study of three different 3D in vitro platforms, namely (i) spheroids, (ii) synthetic PeptiGels/hydrogels of various chemical configurations and (iii) polymeric scaffolds with coatings of various extracellular matrices (ECMs) on the cell growth and response to the chemotherapeutic (Cisplatin) for ovary-derived (A2780) and metastatic (SK-OV-3) EOC cell lines. We report that all three 3D models are able to support the growth of EOC, but for different time periods (varying from 7 days to 4 weeks). We have also reported that chemoresistance to Cisplatin, in vitro, observed especially for metastatic EOC cells, is platform-dependent, in terms of both the structural and biochemical composition of the model/platform. Our study highlights the importance of selecting an appropriate 3D platform for in vitro tumour model development. We have demonstrated that the selection of the best platform for producing in vitro tumour models depends on the cancer/cell type, the experimental time period and the application for which the model is intended.

Cancer Stem Cells in Ovarian Cancer-A Source of Tumor Success and a Challenging Target for Novel Therapies

Ovarian cancer is the most lethal neoplasm of the female genital organs. Despite indisputable progress in the treatment of ovarian cancer, the problems of chemo-resistance and recurrent disease are the main obstacles for successful therapy. One of the main reasons for this is the presence of a specific cell population of cancer stem cells. The aim of this review is to show the most contemporary knowledge concerning the biology of ovarian cancer stem cells (OCSCs) and their impact on chemo-resistance and prognosis in ovarian cancer patients, as well as to present the treatment options targeted exclusively on the OCSCs. The review presents data concerning the role of cancer stem cells in general and then concentrates on OCSCs. The surface and intracellular OCSCs markers and their meaning both for cancer biology and clinical prognosis, signaling pathways specifically activated in OCSCs, the genetic and epigenetic regulation of OCSCs function including the recent studies on the non-coding RNA regulation, cooperation between OCSCs and the tumor microenvironment (ovarian cancer niche) including very specific environment such as ascites fluid, the role of shear stress, autophagy and metabolic changes for the function of OCSCs, and finally mechanisms of OCSCs escape from immune surveillance, are described and discussed extensively. The possibilities of anti-OCSCs therapy both in experimental settings and in clinical trials are presented, including the recent II phase clinical trials and immunotherapy. OCSCs are a unique population of cancer cells showing a great plasticity, self-renewal potential and resistance against anti-cancer treatment. They are responsible for the progression and recurrence of the tumor. Several completed and ongoing clinical trials have tested different anti-OCSCs drugs which, however, have shown unsatisfactory efficacy in most cases. We propose a novel approach to ovarian cancer diagnosis and therapy.

Cell-based immunotherapies in gynecologic cancers

PURPOSE OF REVIEW

This review provides an update on recent developments in cell-based immunotherapy in gynecologic cancers.

RECENT FINDINGS

Chimeric antigen receptor (CAR) technology has made significant progress allowing now for not only expressing CARs on T-cells, but also on other immune effector cells, such as natural killer cells and macrophages. Cell-based vaccines have started to show promising results in clinical trials.

SUMMARY

Cell-based immunotherapies in gynecologic cancers continue to evolve with promising clinical efficacy in select patients.

PD-L1 near Infrared Photoimmunotherapy of Ovarian Cancer Model

(1) Background: Despite advances in surgical approaches and drug development, ovarian cancer is still a leading cause of death from gynecological malignancies. Patients diagnosed with late-stage disease are treated with aggressive surgical resection and chemotherapy, but recurrence with resistant disease is often observed following treatment. There is a critical need for effective therapy for late-stage ovarian cancer. Photoimmunotherapy (PIT), using an antibody conjugated to a near infrared (NIR) dye, constitutes an effective theranostic strategy to detect and selectively eliminate targeted cell populations. (2) Methods: Here, we are targeting program death ligand 1 (PD-L1) using NIR-PIT in a syngeneic mouse model of ovarian cancer. PD-L1 PIT-mediated cytotoxicity was quantified in RAW264.7 macrophages and ID8-Defb29-VEGF cells in culture, and in vivo with orthotopic ID8-Defb29-VEGF tumors. (3) Results: Treatment efficacy was observed both in vitro and in vivo. (4) Conclusions: Our data highlight the need for further investigations to assess the potential of using NIR-PIT for ovarian cancer therapy to improve the treatment outcome of ovarian cancer.

Significance of CD47 and Its Association With Tumor Immune Microenvironment Heterogeneity in Ovarian Cancer

Background

It was reported that tumor heterogeneity and the surrounding tumor microenvironment (TME) in ovarian cancer affects immunotherapy efficacy and patient outcomes. And the TME of ovarian cancer is intrinsically heterogeneous. CD47 plays vital roles in cell functional behavior and immune homeostasis relating to cancer prognosis. But how it affects TME and its contribution to heterogeneity in ovarian cancer has not been fully illustrated. Therefore, we aimed to identify a prognostic biomarker which may help explain tumor immune microenvironment heterogeneity of ovarian cancer.

Methods

Cancer single-cell state atlas (CancerSEA) was used to evaluate functional role of CD47. Several bioinformatics database including Oncomine, Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), The Human Protein Atlas (HPA), Ualcan and Kaplan-Meier plotter (KM plotter) were applied to illustrate correlation of CD47 with ovarian cancer prognosis and immune infiltration. Tumor Immune Single-cell Hub (TISCH) single cell database was employed to evaluate correlation of CD47 with tumor microenvironment. GeneMANIA was implemented to identify regulation networks of CD47. Differentially expressed genes (DEGs) between CD47 high and low expression groups were analyzed with R package DESeq2. Kyoto encyclopedia of genes and genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were utilized to explore how CD47 affect the immune related cell signaling pathway.

Results

CD47 expression was upregulated and connected to worse OS and PFS in ovarian cancer. Close relation was found between CD47 expression level and immune infiltration in ovarian cancer, especially with Treg cells, Monocytes, Macrophages and T cell exhaustion (P<0.05). The CD47 expression level was relatively low in plasma cells, dendritic cells and Mono/Macro cells of OV_GSE115007, in myofibroblasts, fibroblasts and endothelial cells of OV_GSE118828, compared to malignant cells of OV_GSE118828 dataset. The cell components and distribution in primary and metastatic ovarian cancer are quite distinct, which may lead to TME heterogeneity of ovarian cancer.

Conclusion

Our results indicated that CD47 is closely correlated to ovarian cancer immune microenvironment and might induce ovarian cancer heterogeneity. Therefore, CD47 may be used as a candidate prognostic biomarker and provide us with new insights into potential immunotherapy in ovarian cancer patients.

Comprehensive Analysis of the Potential Immune-Related Biomarker Transporter Associated With Antigen Processing 1 That Inhibits Metastasis and Invasion of Ovarian Cancer Cells

Transporter associated with antigen processing 1 (TAP1) is a protein related immune regulation and plays a role in several malignant tumors. However, the effect of TAP1 on immune infiltration, immunotherapy, and metastasis in different cancers has not been reported till date. The cancer genome atlas database, the tumor immune estimation resource database, and the estimation of stromal and immune cells in malignant tumors using expression (ESTIMATE) algorithm were used to determine the correlation between TAP1 expression and the prognosis of a variety of cancers, immune infiltration, immune checkpoint genes, DNA methylation, and neoantigens. Various enrichment analyses were used to study the correlation between TAP1 and key transcription factors using the Kyoto encyclopedia of genes and genomes (KEGG) pathway in ovarian cancer. Immunological methods were used to evaluate the expression of TAP1 protein in ovarian and cervical cancer, and Kaplan-Meier analysis was used to analyze the prognostic value of TAP1. RNA interference (RNAi) was used to verify the effect of TAP1 on ovarian cancer. Compared with normal tissues, cancer tissues showed a significant increase in the expression of TAP1, and TAP1 expression was related to the poor prognosis of cancers such as ovarian cancer. The expression level of TAP1 was correlated with immune checkpoint genes, DNA methylation, tumor mutation burden, microsatellite instability, and neoantigens in various cancers. Our results showed that TAP1 was upregulated in ovarian cancer cell lines and was associated with poor prognosis. Further, we verified the expression of TAP1-related transcription factors (MEF2A and LEF1) and found that TAP1 was closely related to ovarian cancer metastasis in vitro and in vivo. These results indicated that TAP1 could be used as a biomarker for the diagnosis and prognosis of cancer and as a new therapeutic target.

Barriers to Immunotherapy in Ovarian Cancer: Metabolic, Genomic, and Immune Perturbations in the Tumour Microenvironment

A lack of explicit early clinical signs and effective screening measures mean that ovarian cancer (OC) often presents as advanced, incurable disease. While conventional treatment combines maximal cytoreductive surgery and platinum-based chemotherapy, patients frequently develop chemoresistance and disease recurrence. The clinical application of immune checkpoint blockade (ICB) aims to restore anti-cancer T-cell function in the tumour microenvironment (TME). Disappointingly, even though tumour infiltrating lymphocytes are associated with superior survival in OC, ICB has offered limited therapeutic benefits. Herein, we discuss specific TME features that prevent ICB from reaching its full potential, focussing in particular on the challenges created by immune, genomic and metabolic alterations. We explore both recent and current therapeutic strategies aiming to overcome these hurdles, including the synergistic effect of combination treatments with immune-based strategies and review the status quo of current clinical trials aiming to maximise the success of immunotherapy in OC.