Synthetic RNA-Based Immunomodulatory Gene Circuits for Cancer Immunotherapy.

Despite its success in several clinical trials, cancer immunotherapy remains limited by the rarity of targetable tumor-specific antigens, tumor-mediated immune suppression, and toxicity triggered by systemic delivery of potent immunomodulators. Here, we present a proof-of-concept immunomodulatory gene circuit platform that enables tumor-specific expression of immunostimulators, which could potentially overcome these limitations. Our design comprised de novo synthetic cancer-specific promoters and, to enhance specificity, an RNA-based AND gate that generates combinatorial immunomodulatory outputs only when both promoters are mutually active. These outputs included an immunogenic cell-surface protein, a cytokine, a chemokine, and a checkpoint inhibitor antibody. The circuits triggered selective T cell-mediated killing of cancer cells, but not of normal cells, in vitro. In in vivo efficacy assays, lentiviral circuit delivery mediated significant tumor reduction and prolonged mouse survival. Our design could be adapted to drive additional immunomodulators, sense other cancers, and potentially treat other diseases that require precise immunological programming.

Heterogeneous Tumor-Immune Microenvironments among Differentially Growing Metastases in an Ovarian Cancer Patient.

We present an exceptional case of a patient with high-grade serous ovarian cancer, treated with multiple chemotherapy regimens, who exhibited regression of some metastatic lesions with concomitant progression of other lesions during a treatment-free period. Using immunogenomic approaches, we found that progressing metastases were characterized by immune cell exclusion, whereas regressing and stable metastases were infiltrated by CD8+ and CD4+ T cells and exhibited oligoclonal expansion of specific T cell subsets. We also detected CD8+ T cell reactivity against predicted neoepitopes after isolation of cells from a blood sample taken almost 3 years after the tumors were resected. These findings suggest that multiple distinct tumor immune microenvironments co-exist within a single individual and may explain in part the heterogeneous fates of metastatic lesions often observed in the clinic post-therapy. VIDEO ABSTRACT.

Inhibiting DNA Methylation Causes an Interferon Response in Cancer via dsRNA Including Endogenous Retroviruses.

We show that DNA methyltransferase inhibitors (DNMTis) upregulate immune signaling in cancer through the viral defense pathway. In ovarian cancer (OC), DNMTis trigger cytosolic sensing of double-stranded RNA (dsRNA) causing a type I interferon response and apoptosis. Knocking down dsRNA sensors TLR3 and MAVS reduces this response 2-fold and blocking interferon beta or its receptor abrogates it. Upregulation of hypermethylated endogenous retrovirus (ERV) genes accompanies the response and ERV overexpression activates the response. Basal levels of ERV and viral defense gene expression significantly correlate in primary OC and the latter signature separates primary samples for multiple tumor types from The Cancer Genome Atlas into low versus high expression groups. In melanoma patients treated with an immune checkpoint therapy, high viral defense signature expression in tumors significantly associates with durable clinical response and DNMTi treatment sensitizes to anti-CTLA4 therapy in a pre-clinical melanoma model.

Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system.

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy.

Epithelial ovarian cancer: Evolution of management in the era of precision medicine.

Ovarian cancer is the second most common cause of gynecologic cancer death in women around the world. The outcomes are complicated, because the disease is often diagnosed late and composed of several subtypes with distinct biological and molecular properties (even within the same histological subtype), and there is inconsistency in availability of and access to treatment. Upfront treatment largely relies on debulking surgery to no residual disease and platinum-based chemotherapy, with the addition of antiangiogenic agents in patients who have suboptimally debulked and stage IV disease. Major improvement in maintenance therapy has been seen by incorporating inhibitors against poly (ADP-ribose) polymerase (PARP) molecules involved in the DNA damage-repair process, which have been approved in a recurrent setting and recently in a first-line setting among women with BRCA1/BRCA2 mutations. In recognizing the challenges facing the treatment of ovarian cancer, current investigations are enlaced with deep molecular and cellular profiling. To improve survival in this aggressive disease, access to appropriate evidence-based care is requisite. In concert, realizing individualized precision medicine will require prioritizing clinical trials of innovative treatments and refining predictive biomarkers that will enable selection of patients who would benefit from chemotherapy, targeted agents, or immunotherapy. Together, a coordinated and structured approach will accelerate significant clinical and academic advancements in ovarian cancer and meaningfully change the paradigm of care.

T cell exhaustion and senescence for ovarian cancer immunotherapy.

Ovarian cancer is a common gynecological malignancy, and its treatment remains challenging. Although ovarian cancer may respond to immunotherapy because of endogenous immunity at the molecular or T cell level, immunotherapy has so far not had the desired effect. The functional status of preexisting T cells is an indispensable determinant of powerful antitumor immunity and immunotherapy. T cell exhaustion and senescence are two crucial states of T cell dysfunction, which share some overlapping phenotypic and functional features, but each status possesses unique molecular and developmental signatures. It has been widely accepted that exhaustion and senescence of T cells are important strategies for cancer cells to evade immunosurveillance and maintain the immunosuppressive microenvironment. Herein, this review summarizes the phenotypic and functional features of exhaust and senescent T cells, and describes the key drivers of the two T cell dysfunctional states in the tumor microenvironment and their functional roles in ovarian cancer. Furthermore, we present a summary of the molecular machinery and signaling pathways governing T cell exhaustion and senescence. Possible strategies that can prevent and/or reverse T cell dysfunction are also explored. An in-depth understanding of exhausted and senescent T cells will provide novel strategies to enhance immunotherapy of ovarian cancer through redirecting tumor-specific T cells away from a dysfunctional developmental trajectory.

A platform to deliver single and bi-specific Cas9/guide RNA to perturb genes in vitro and in vivo.

Although CRISPR-Cas9 technology is poised to revolutionize the treatment of diseases with underlying genetic mutations, it faces some significant issues limiting clinical entry. They include low-efficiency in vivo systemic delivery and undesired off-target effects. Here, we demonstrate, by modifying Cas9 with phosphorothioate-DNA oligos (PSs), that one can efficiently deliver single and bi-specific CRISPR-Cas9/guide RNA (gRNA) dimers in vitro and in vivo with reduced off-target effects. We show that PS-Cas9/gRNA-mediated gene knockout preserves chimeric antigen receptor T cell viability and expansion in vitro and in vivo. PS-Cas9/gRNA mediates gene perturbation in patient-derived tumor organoids and mouse xenograft tumors, leading to potent tumor antitumor effects. Further, HER2 antibody-PS-Cas9/gRNA conjugate selectively perturbs targeted genes in HER2+ ovarian cancer xenografts in vivo. Moreover, we created bi-specific PS-Cas9 with two gRNAs to target two adjacent sequences of the same gene, leading to efficient targeted gene disruption ex vivo and in vivo with markedly reduced unintended gene perturbation. Thus, the cell-penetrating PS-Cas9/gRNA can achieve efficient systemic delivery and precision in gene disruption.

Overcoming effector T cell exhaustion in ovarian cancer ascites with a novel adenovirus encoding for a MUC1 bispecific antibody engager and IL-2 cytokine.

T cell-focused cancer immunotherapy including checkpoint inhibitors and cell therapies has been rapidly evolving over the past decade. Nevertheless, there remains a major unmet medical need in oncology generally and immuno-oncology specifically. We have constructed an oncolytic adenovirus, Ad5/3-E2F-d24-aMUC1aCD3-IL-2 (TILT-322), which is armed with a human aMUC1aCD3 T cell engager and IL-2. TILT-322 treatment stimulated T cell cytotoxicity through the increased presence of granzyme B, perforin, and interferon-gamma. Additional immune profiling indicated TILT-322 increased gamma delta T cell activation and impacted other cell types such as natural killer cells and natural killer-like T cells that are traditionally involved in cancer immunotherapy. TILT-322 treatment also decreased the proportion of exhausted CD8+ T cells as demarked by immune checkpoint expression in ovarian ascites samples. Overall, our data showed that TILT-322 treatment led to an enhanced T cell activation and reversed T cell exhaustion translating into high antitumor efficacy when given locally or intravenously. The analysis of blood and tumors isolated from an in vivo patient-derived ovarian cancer xenograft model suggested TILT-322 mediated tumor control through improved T cell functions. Therefore, TILT-322 is a promising novel anti-tumor agent for clinical translation.

Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer.

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Extracellular vesicles as a potential delivery platform for CRISPR-Cas based therapy in epithelial ovarian cancer.

Ovarian Cancer (OC) is the most common gynecological malignancy and the eighth most diagnosed cancer in females worldwide. Presently, it ranks as the fifth leading cause of cancer-related mortality among patients globally. Major factors contributing to the lethality of OC worldwide include delayed diagnosis, chemotherapy resistance, high metastatic rates, and the heterogeneity of subtypes. Despite continuous efforts to develop novel targeted therapies and chemotherapeutic agents, challenges persist in the form of OC resistance and recurrence. In the last decade, CRISPR-Cas-based genome editing has emerged as a powerful tool for modifying genetic and epigenetic mechanisms, holding potential for treating numerous diseases. However, a significant challenge for therapeutic applications of CRISPR-Cas technology is the absence of an optimal vehicle for delivering CRISPR molecular machinery into targeted cells or tissues. Recently, extracellular vesicles (EVs) have gained traction as potential delivery vehicles for various therapeutic agents. These heterogeneous, membrane-derived vesicles are released by nearly all cells into extracellular spaces. They carry a molecular cargo of proteins and nucleic acids within their intraluminal space, encased by a cholesterol-rich phospholipid bilayer membrane. EVs actively engage in cell-to-cell communication by delivering cargo to both neighboring and distant cells. Their inherent ability to shield molecular cargo from degradation and cross biological barriers positions them ideally for delivering CRISPR-Cas ribonucleoproteins (RNP) to target cells. Furthermore, they exhibit higher biocompatibility, lower immunogenicity, and reduced toxicity compared to classical delivery platforms such as adeno-associated virus, lentiviruses, and synthetic nanoparticles. This review explores the potential of employing different CRISPR-Cas systems to target specific genes in OC, while also discussing various methods for engineering EVs to load CRISPR components and enhance their targeting capabilities.

Prognostic and immunotherapeutic potential of regulatory T cell-associated signature in ovarian cancer.

Tumour-induced immunosuppressive microenvironments facilitate oncogenesis, with regulatory T cells (Tregs) serving as a crucial component. The significance of Treg-associated genes within the context of ovarian cancer (OC) remains elucidated insufficiently. Utilizing single-cell RNA sequencing (scRNA-Seq) for the identification of Treg-specific biomarkers, this investigation employed single-sample gene set enrichment analysis (ssGSEA) for the derivation of a Treg signature score. Weighted gene co-expression network analysis (WGCNA) facilitated the identification of Treg-correlated genes. Machine learning algorithms were employed to determine an optimal prognostic model, subsequently exploring disparities across risk strata in terms of survival outcomes, immunological infiltration, pathway activation and responsiveness to immunotherapy. Through WGCNA, a cohort of 365 Treg-associated genes was discerned, with 70 implicated in the prognostication of OC. A Tregs-associated signature (TAS), synthesized from random survival forest (RSF) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms, exhibited robust predictive validity across both internal and external cohorts. Low TAS OC patients demonstrated superior survival outcomes, augmented by increased immunological cell infiltration, upregulated immune checkpoint expression, distinct pathway enrichment and differential response to immunotherapeutic interventions. The devised TAS proficiently prognosticates patient outcomes and delineates the immunological milieu within OC, offering a strategic instrument for the clinical stratification and selection of patients.

Immunotherapy and the ovarian cancer microenvironment: Exploring potential strategies for enhanced treatment efficacy.

Despite progress in cancer immunotherapy, ovarian cancer (OC) prognosis continues to be disappointing. Recent studies have shed light on how not just tumour cells, but also the complex tumour microenvironment, contribute to this unfavourable outcome of OC immunotherapy. The complexities of the immune microenvironment categorize OC as a 'cold tumour'. Nonetheless, understanding the precise mechanisms through which the microenvironment influences the effectiveness of OC immunotherapy remains an ongoing scientific endeavour. This review primarily aims to dissect the inherent characteristics and behaviours of diverse cells within the immune microenvironment, along with an exploration into its reprogramming and metabolic changes. It is expected that these insights will elucidate the operational dynamics of the immune microenvironment in OC and lay a theoretical groundwork for improving the efficacy of immunotherapy in OC management.

Enhancing precision targeting of ovarian cancer tumor cells in vivo through extracellular vesicle engineering.

Extracellular vesicles (EVs) function as natural mediators of intercellular communication, secreted by cells to facilitate cell-cell signaling. Due to their low toxicity, immunogenicity, biodegradability, and potential to encapsulate therapeutic drugs, EVs hold significant therapeutic promise. Nevertheless, their limited targeting ability often diminishes their therapeutic impact. Therefore, enhancing EVs by incorporating targeting units onto their membranes could bolster their targeting capabilities, enabling them to accumulate in specific cells and tissues. In this study, we engineered EVs to fuse ephrin-B2 with the EV membrane protein LAMP2b. This modification aimed to direct the engineered EVs toward the ephrin-B4 receptor expressed on the surface of ovarian cancer cells. The engineered EVs retained their inherent properties, including size, expression of EV membrane proteins, and morphology, upon isolation. In vitro experiments using real-time imaging revealed that EVs engineered with the ephrin-B2 ligand exhibited substantial internalization and uptake by ovarian cancer cells, in stark contrast to native EVs. In vivo, the engineered EVs carrying the ephrin-B2 ligand effectively targeted ovarian cancer cells, surpassing the targeting efficiency of control EVs. This innovative approach establishes a novel targeting system, enhancing the uptake of EVs by ovarian cancer cells. Our findings underscore the potential of using EVs to target cancer cells, thereby enhancing the effectiveness of anti-cancer therapies while minimizing off-target effects and toxicity in normal cells and organs.

Indicators of cure for women living after uterine and ovarian cancers: a population-based study.

This study aims to estimate long-term survival, cancer prevalence, and several cure indicators for Italian women with gynecological cancers. Thirty-one cancer registries, representing 47% of the Italian female population, were included. Mixture cure models were used to estimate net survival, cure fraction, time to cure (when 5-year conditional net survival becomes > 95%), cure prevalence (women who will not die of cancer), and already cured (living longer than time to cure). In 2018, 0.4% (121 704) of Italian women were alive after diagnosis of corpus uteri cancer, 0.2% (52 551) after cervical cancer, and 0.2% (52 153) after ovarian cancer. More than 90% of patients with uterine cancers and 83% with ovarian cancer will not die from their neoplasm (cure prevalence). Women with gynecological cancers have a residual excess risk of death <5% at 5 years after diagnosis. The cure fraction was 69% for corpus uteri, 32% for ovarian, and 58% for cervical cancer patients. Time to cure was ≤10 years for women with gynecological cancers aged <55 years; 74% of patients with cervical cancer, 63% with corpus uteri cancer, and 55% with ovarian cancer were already cured. These results can contribute to improving follow-up programs for women with gynecological cancers and supporting efforts against discrimination of already cured ones. This article is part of a Special Collection on Gynecological Cancers.

Tumour microenvironment characterisation to stratify patients for hyperthermic intraperitoneal chemotherapy in high-grade serous ovarian cancer (OVHIPEC-1).

BACKGROUND: Hyperthermic intraperitoneal chemotherapy (HIPEC) improves survival in patients with Stage III ovarian cancer following interval cytoreductive surgery (CRS). Optimising patient selection is essential to maximise treatment efficacy and avoid overtreatment. This study aimed to identify biomarkers that predict HIPEC benefit by analysing gene signatures and cellular composition of tumours from participants in the OVHIPEC-1 trial. METHODS: Whole-transcriptome RNA sequencing data were retrieved from high-grade serous ovarian cancer (HGSOC) samples from 147 patients obtained during interval CRS. We performed differential gene expression analysis and applied deconvolution methods to estimate cell-type proportions in bulk mRNA data, validated by histological assessment. We tested the interaction between treatment and potential predictors on progression-free survival using Cox proportional hazards models. RESULTS: While differential gene expression analysis did not yield any predictive biomarkers, the cellular composition, as characterised by deconvolution, indicated that the absence of macrophages and the presence of B cells in the tumour microenvironment are potential predictors of HIPEC benefit. The histological assessment confirmed the predictive value of macrophage absence. CONCLUSION: Immune cell composition, in particular macrophages absence, may predict response to HIPEC in HGSOC and these hypothesis-generating findings warrant further investigation. CLINICAL TRIAL REGISTRATION: NCT00426257.

ESGO-ESMO-ESP consensus conference recommendations on ovarian cancer: pathology and molecular biology and early, advanced and recurrent disease.

The European Society of Gynaecological Oncology, the European Society for Medical Oncology (ESMO) and the European Society of Pathology held a consensus conference (CC) on ovarian cancer on 15-16 June 2022 in Valencia, Spain. The CC panel included 44 experts in the management of ovarian cancer and pathology, an ESMO scientific advisor and a methodologist. The aim was to discuss new or contentious topics and develop recommendations to improve and harmonise the management of patients with ovarian cancer. Eighteen questions were identified for discussion under four main topics: (i) pathology and molecular biology, (ii) early-stage disease and pelvic mass in pregnancy, (iii) advanced stage (including older/frail patients) and (iv) recurrent disease. The panel was divided into four working groups (WGs) to each address questions relating to one of the four topics outlined above, based on their expertise. Relevant scientific literature was reviewed in advance. Recommendations were developed by the WGs and then presented to the entire panel for further discussion and amendment before voting. This manuscript focuses on the recommendation statements that reached a consensus, their voting results and a summary of evidence supporting each recommendation.

Metabolism-related gene vaccines and immune infiltration in ovarian cancer: A novel risk score model of machine learning.

BACKGROUND: The present study aims to develop a metabolic gene signature to evaluate the survival rate of ovarian cancer (OC) patients and analyze the potential mechanisms of metabolic genes in OC because the difficulty in early detection of OC often leads to poor treatment outcomes. METHODS: A non-negative matrix factorization algorithm was applied to determine molecular subtypes according to metabolism genes. To build a risk prognosis model, least absolute shrinkage and selection operator multivariate Cox analysis was carried out with weighted correlation network analysis (WCGNA). Glycolytic flux and mitochondrial function were evaluated by conducting seahorse analysis. RESULTS: On the basis of metabolism-related genes, the two subtypes of OC samples present in The Cancer Genome Atlas database were distinguished. An analysis of WGCNA identified 1056 genes. Lastly, a 10-gene signature (CMAS, ADH1B, PLA2G2D, BHMT, CACNA1C, AADAC, ALOX12, CYP2R1, SCN1B and ME1) was constructed that demonstrated promising performance in predicting outcome in patients with OC. The RiskScore of the gene signature was linked to microenvironment cell infiltration and immune checkpoint. Higher RiskScores were associated with poorer results for OC patients. Seahorse analysis shows the influence of CMAS in cell energy metabolism. CONCLUSIONS: In the present study, a novel marker for evaluating the survival of OC patients was developed through the creation of a gene signature incorporating metabolism-related genes. Our knowledge of immunotherapy and microenvironment cell infiltration may be enriched by evaluating metabolism-related gene modification patterns.

Integrative analysis of cuproptosis-associated genes for predicting immunotherapy response in single-cell and multi-cohort studies.

BACKGROUND: The role of genes associated with the cuproptosis cell signaling pathway in prognosis and immunotherapy in ovarian cancer (OC) has been extensively investigated. In this study, we aimed to explore these mechanisms and establish a prognostic model for patients with OC using bioinformatics techniques. METHODS: We obtained the single cell sequencing data of ovarian cancer from the Gene Expression Omnibus (GEO) database and preprocessed the data. We analyzed a variety of factors including cuproptosis cell signal score, transcription factors, tumorigenesis and progression signals, gene set variation analysis (GSVA) and intercellular communication. Differential gene analysis was performed between groups with high and low cuproptosis cell signal scores, as well as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Using bulk RNA sequencing data from The Cancer Genome Atlas, we used the least absolute shrinkage and selection operator (LASSO)-Cox algorithm to develop cuproptosis cell signaling pathword-related gene signatures and validated them with GEO ovarian cancer datasets. In addition, we analyzed the inherent rules of the genes involved in building the model using a variety of bioinformatics methods, including immune-related analyses and single nucleotide polymorphisms. Molecular docking is used to screen potential therapeutic drugs. To confirm the analysis results, we performed various wet experiments such as western blot, cell counting kit 8 (CCK8) and clonogenesis tests to verify the role of the Von Willebrand Factor (VWF) gene in two ovarian cancer cell lines. RESULTS: Based on single-cell data analysis, we found that endothelial cells and fibroblasts showed active substance synthesis and signaling pathway activation in OC, which further promoted immune cell suppression, cancer cell proliferation and metastasis. Ovarian cancer has a high tendency to metastasize, and cancer cells cooperate with other cells to promote disease progression. We developed a signature consisting of eight cuproptosis-related genes (CRGs) (MAGEF1, DNPH1, RARRES1, NBL1, IFI27, VWF, OLFML3 and IGFBP4) that predicted overall survival in patients with ovarian cancer. The validity of this model is verified in an external GEO validation set. We observed active infiltrating states of immune cells in both the high- and low-risk groups, although the specific cells, genes and pathways of activation differed. Gene mutation analysis revealed that TP53 is the most frequently mutated gene in ovarian cancer. We also predict small molecule drugs associated with CRGs and identify several potential candidates. VWF was identified as an oncogene in ovarian cancer, and the protein was expressed at significantly higher levels in tumor samples than in normal samples. The high-score model of the cuproptosis cell signaling pathway was associated with the sensitivity of OC patients to immunotherapy. CONCLUSIONS: Our study provides greater insight into the mechanisms of action of genes associated with the cuproptosis cell signaling pathway in ovarian cancer, highlighting potential targets for future therapeutic interventions.

Construction and validation of molecular subtype and signature of immune cell-related telomeric genes and prediction of prognosis and immunotherapy efficacy in ovarian cancer patients.

BACKGROUND: Ovarian cancer (OVC) has emerged as a fatal gynecological malignancy as a result of a lack of reliable methods for early detection, limited biomarkers and few treatment options. Immune cell-related telomeric genes (ICRTGs) show promise as potential biomarkers. METHODS: ICRTGs were discovered using weighted gene co-expression network analysis (WGCNA). ICRTGs were screened for significant prognosis using one-way Cox regression analysis. Subsequently, molecular subtypes of prognosis-relevant ICRTGs were constructed and validated for OVC, and the immune microenvironment's landscape across subtypes was compared. OVC prognostic models were built and validated using prognosis-relevant ICRTGs. Additionally, chemotherapy susceptibility drugs for OVC patients in the low- and high-risk groups of ICRTGs were screened using genomics of drug susceptibility to cancer (GDSC). Finally, the immunotherapy response in the low- and high-risk groups was detected using the data from GSE78220. We conducted an immune index correlation analysis of ICRTGs with significant prognoses. The MAP3K4 gene, for which the prognostic correlation coefficient is the highest, was validated using tissue microarrays for a prognostic-immune index correlation. RESULTS: WGCNA analysis constructed a gene set of ICRTGs and screened 22 genes with prognostic significance. Unsupervised clustering analysis revealed the best molecular typing for two subtypes. The Gene Set Variation Analysis algorithm was used to calculate telomere scores and validate the molecular subtyping. A prognostic model was constructed using 17 ICRTGs. In the The Cancer Genome Atlas-OVC training set and the Gene Expression Omnibus validation set (GSE30161), the risk score model's predicted risk groups and the actual prognosis were shown to be significantly correlated. GDSC screened Axitinib, Bexarotene, Embelin and the GSE78220 datasets and demonstrated that ICRTGs effectively distinguished the group that responds to immunotherapy from the non-responsive group. Additionally, tissue microarray validation results revealed that MAP3K4 significantly predicted patient prognosis. Furthermore, MAP3K4 exhibited a positive association with PD-L1 and a negative relationship with the M1 macrophage markers CD86 and INOS. CONCLUSIONS: ICRTGs may be reliable biomarkers for the molecular typing of patients with OVC, enabling the prediction of prognosis and immunotherapy efficacy.

Oncolytic vaccinia virus harboring aphrocallistes vastus lectin exerts anti-tumor effects by directly oncolysis and inducing immune response through enhancing ROS in human ovarian cancer.

Aphrocallistes vastus lectin (AVL) is a Ca2+ dependent C-type lectin produced by sponges. Previous studies have demonstrated that oncolytic vaccinia virus harboring AVL (oncoVV-AVL) effectively triggers cell death in various tumors. However, the effects of oncoVV-AVL on human ovarian cancer (OV) remain unknown. This study aims to investigate the mechanism-of-action of oncoVV-AVL in human OV cell lines and in tumor-bearing nude mice. We found that oncoVV-AVL could directly induce apoptosis and autophagy in ovarian cancer cells. Additionally, our results showed that oncoVV-AVL increased the serum levels of mouse IFN-γ (mIFN-γ), leading to the activation of M1-polarized macrophages. Conversely, NADPH, a reducing agent by providing reducing equivalents, reduced the production of mIFN-γ, and suppressed M1-polarization of macrophage. Based on these findings, we propose that oncoVV-AVL not only contributes to direct cytolysis, but also enhances host immune response by promoting ROS levels.