Targeting tumor microenvironment in ovarian cancer: Premise and promise

Construction of ROS-Responsive Hyaluronic Acid Modified Paclitaxel and Diosgenin Liposomes and Study on Synergistic Enhancement of Anti-Ovarian Cancer Efficacy

Purpose

Ovarian cancer is a fatal gynecologic malignancy with a high rate of abdominal metastasis. Chemotherapy still has a poor clinical prognosis for ovarian cancer patients, with cell proliferation and angiogenesis leading to invasion, migration, and recurrence. To overcome these obstacles, we constructed a novel HA-modified paclitaxel and diosgenin liposome (PEG-TK-HA-PDLPs) using two novel functional materials, DSPE-PEG2000-HA and DSPE-PEG2000-TK-PEG5000, to specifically deliver the drugs to the tumor site in order to reduce OC cell proliferation and anti-angiogenic generation, thereby inhibiting invasion and migration.

Methods and Results

PEG-TK-HA-PDLPs were prepared by film dispersion, with ideal physicochemical properties and exhibits active targeting for enhanced cellular uptake. The ZIP synergy score for PTX and Dios was calculated using the online SynergyFinder software to be 3.15, indicating synergy. In vitro results showed that PEG-TK-HA-PDLPs were highly cytotoxic to ID8 cells, induced ID8 cell apoptosis, and inhibited ID8 cell migration and invasion. In vivo studies showed that PEG-TK-HA-PDLPs could prolong the circulation time in the blood, accumulate significantly in the tumor site, and effectively fight against angiogenesis with significant anti-tumor effects.

Conclusion

The production of PEG-TK-HA-PDLPs is an effective strategy for the treatment of OC.

NDC80 Kinetochore Complex Serves as a Potential Prognostic Predictor and Correlates with Immune Infiltrates in Epithelial Ovarian Cancer Patients

Purpose

This study focuses on evaluating the prognostic value of the NDC80 kinetochore complex in ovarian cancer (OC) using the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database and reveals the relationship between the NDC80 complex and immune infiltrates in OC.

Methods

We collected data on NDC80 complex expression levels in both OC tissues and non-OC ovarian tissues from the University of California Santa Cruz Xena and GEO databases. The clinicopathological characteristics correlated with overall survival were analyzed using Cox regression and the Kaplan-Meier method. Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis and CIBERSORT were performed using data from TCGA database. Immunohistochemical staining was used to verify the higher expression level of NUF2 protein in OC in vitro. Meanwhile, we utilized the Tumor Immune Estimation Resource to analyze the correlation between the NDC80 complex and immunocyte infiltration.

Results

The NDC80 complex expression level was prominently higher in OC tissues than in non-OC ovarian tissues and correlated with advanced histologic grade characteristics. Gene expression profiling interactive analysis and the Kaplan-Meier survival curve uncovered a close relationship between high expression of the NDC80 complex and poor overall survival in OC patients. The univariate Cox regression hazard model produced age, pathologic stage, tumor status, primary therapy outcome, SPC24 expression level, and Karnofsky performance score as prognostic factors for OC patients. NDC80 complex expression levels were highly associated with immune cell infiltration, showing NK CD56 bright cells and NK cells with a negative correlation and T helper 2 cells with a positive correlation (P<0.05).

Conclusion

These findings provide evidence that an increased expression level of the NDC80 complex is closely associated with the progression of OC and could also serve as a novel target of immunotherapy in OC.

Integration of single-cell RNA-seq and bulk RNA-seq data to construct and validate a cancer-associated fibroblast-related prognostic signature for patients with ovarian cancer

BACKGROUND

To establish a prognostic risk profile for ovarian cancer (OC) patients based on cancer-associated fibroblasts (CAFs) and gain a comprehensive understanding of their role in OC progression, prognosis, and therapeutic efficacy.

METHODS

Data on OC single-cell RNA sequencing (scRNA-seq) and total RNA-seq were collected from the GEO and TCGA databases. Seurat R program was used to analyze scRNA-seq data and identify CAFs clusters corresponding to CAFs markers. Differential expression analysis was performed on the TCGA dataset to identify prognostic genes. A CAF-associated risk signature was designed using Lasso regression and combined with clinicopathological variables to develop a nomogram. Functional enrichment and the immune landscape were also analyzed.

RESULTS

Five CAFs clusters were identified in OC using scRNA-seq data, and 2 were significantly associated with OC prognosis. Seven genes were selected to develop a CAF-based risk signature, primarily associated with 28 pathways. The signature was a key independent predictor of OC prognosis and relevant in predicting the results of immunotherapy interventions. A novel nomogram combining CAF-based risk and disease stage was developed to predict OC prognosis.

CONCLUSION

The study highlights the importance of CAFs in OC progression and suggests potential for innovative treatment strategies. A CAF-based risk signature provides a highly accurate prediction of the prognosis of OC patients, and the developed nomogram shows promising results in predicting the OC prognosis.

Angiogenesis and Apoptosis: Data Comparison of Similar Microenvironments in the Corpus Luteum and Tumors

The corpus luteum is a temporary endocrine gland formed in the ovary after ovulation, and it plays a critical role in animal reproductive processes. Tumors rely on the development of an adequate blood supply to ensure the delivery of nutrients and oxygen and the removal of waste products. While angiogenesis occurs in various physiological and pathological contexts, the corpus luteum and tumors share similarities in terms of the signaling pathways that promote angiogenesis. In the corpus luteum and tumors, apoptosis plays a crucial role in controlling cell numbers and ensuring proper tissue development and function. Interestingly, there are similarities between the apoptotic-regulated signaling pathways involved in apoptosis in the corpus luteum and tumors. However, the regulation of apoptosis in both can differ due to their distinct physiological and pathological characteristics. Thus, we reviewed the biological events of the corpus luteum and tumors in similar microenvironments of angiogenesis and apoptosis.

SLAMF7 predicts prognosis and correlates with immune infiltration in serous ovarian carcinoma

OBJECTIVE

Signaling lymphocytic activation molecule family members (SLAMFs) play a critical role in immune regulation of malignancies. This study aims to investigate the prognostic value and function of SLAMFs in ovarian cancer (OC).

METHODS

The expression analysis of SLAMFs was conducted based on The Cancer Genome Atlas Ovarian Cancer Collection (TCGA-OV) and Gene Expression Omnibus (GEO) databases. Immunohistochemistry (IHC) was further performed on tissue arrays (n=98) to determine the expression of SLAMF7. Kaplan-Meier plotter and multivariate Cox regression model were used to evaluate the correlation of SLAMF7 expression with survival outcomes of patients. The molecular function of SLAMF7 in OC was further investigated using Gene Set Enrichment Analysis (GSEA).

RESULTS

SLAMF7 mRNA expression were significantly upregulated in OC tumor tissue compared to normal tissue. IHC revealed that SLAMF7 expression was located in the interstitial parts of tumor tissue, and higher SLAMF7 expression was associated with favorable survival outcomes. GSEA demonstrated that SLAMF7 is involved immune-related pathways. Further analysis showed that SLAMF7 had a strong correlation with the T cell-specific biomarker (CD3) but not with the B cell (CD19, CD22, and CD23) and natural killer cell-specific biomarkers (CD85C, CD336, and CD337). Furthermore, IHC analysis confirmed that SLAMF7 was expressed in tumor-infiltrating T cells, and the IHC score of SLAMF7 was positively correlated with CD3 (r=0.85, p<0.001).

CONCLUSION

SLAMF7 is expressed in the interstitial components of clinical OC tissue, and higher SLAMF7 expression indicated a favorable prognosis for patients with OC. Additionally, SLAMF7 is involved in T-cell immune infiltration in OC.

Peritumoral MRI Radiomics Features Increase the Evaluation Efficiency for Response to Chemotherapy in Patients With Epithelial Ovarian Cancer

BACKGROUND

It remains unclear whether extracting peritumoral volume (PTV) radiomics features are useful tools for evaluating response to chemotherapy of epithelial ovarian cancer (EOC).

PURPOSE

To evaluate MRI radiomics signatures (RS) capturing subtle changes of PTV and their added evaluation performance to whole tumor volume (WTV) for response to chemotherapy in patients with EOC.

STUDY TYPE

Retrospective.

POPULATION

219 patients aged from 15 to 79 years were enrolled.

FIELD STRENGTH/SEQUENCE

3.0 or 1.5T, axial fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (CE-T1WI).

ASSESSMENT

MRI features were extracted from the four axial sequences and six different volumes of interest (VOIs) (WTV and WTV + PTV (WPTV)) with different peritumor sizes (PS) ranging from 1 to 5 mm. Those features underwent preprocessing, and the most informative features were selected using minimum redundancy maximum relevance and least absolute shrinkage and selection operator to construct the RS. The optimal RS, with the highest area under the curve (AUC) of receiver operating characteristic was then integrated with independent clinical characteristics through multivariable logistic regression to construct the radiomics-clinical model (RCM).

STATISTICAL TESTS

Mann-Whitney U test, chi-squared test, DeLong test, log-rank test. P < 0.05 indicated a significant difference.

RESULTS

All the RSs constructed on WPTV exhibited higher AUCs (0.720-0.756) than WTV (0.671). Of which, RS with PS = 2 mm displayed a significantly better performance (AUC = 0.756). International Federation of Gynecology and Obstetrics (FIGO) stage was identified as the exclusive independent clinical evaluation characteristic, and the RCM demonstrated higher AUC (0.790) than the RS, but without statistical significance (P = 0.261).

DATA CONCLUSION

The radiomics features extracted from PTV could increase the efficiency of WTV radiomics for evaluating the chemotherapy response of EOC. The cut-off of 2 mm PTV was a reasonable value to obtain effective evaluation efficiency.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

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.

Development and verification of a novel immunogenic cell death-related signature for predicting the prognosis and immune infiltration in triple-negative breast cancer

BACKGROUND

Insufficient understanding of the pathogenesis and tumor immunology of triple-negative breast cancer (TNBC) has limited the development of immunotherapy. The importance of tumor microenvironment (TME) in immunotyping, prognostic assessment and immunotherapy efficacy of cancer has been emphasized, however, potential immunogenic cell death (ICD) related genes function in TME of TNBC has been rarely investigated.

AIMS

To initially explore the role and related mechanisms of ICD in TNBC, especially the role played in the TME of TNBC, and to identify different relevant subtypes based on ICD, and then develop an ICD-related risk score to predict each TNBC patient TME status, prognosis and immunotherapy response.

METHODS AND RESULTS

In this study, we identified distinct ICD-related modification patterns based on 158 TNBC cases in the TCGA-TNBC cohort. We then investigated the possible correlation between ICD-related modification patterns and TME cell infiltration characteristics in TNBC. By using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis, we created a risk scoring system (ICD score) to quantifiably evaluate the impact of ICD-related modification patterns in individual TNBC patient. Two different ICD-related modification patterns were found with significant differences in immune infiltration. Lower ICD score was correlated with higher immune infiltration, tumor mutational burden and significantly enriched in immune-related pathways, indicating a strong ability to activate immune response, which might account for relatively favorable prognosis of TNBC patients and could serve as a predictor to select suitable candidates for immunotherapy. We used two independent cohorts, GSE58812 cohort and Metabric cohort to validate prognosis and immunohistochemistry for preliminary in vitro validation.

CONCLUSION

This study evidenced that the ICD-related modification patterns might exert pivotal roles in the immune infiltration landscape of TNBC and ICD score might act as potential predictors of prognostic assessment and immunotherapy response. This research provides unique insights for individualize immune treatment strategies and promising immunotherapy candidates screening.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers

The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p < 0.05). SERPINE2 was found to be positively associated with memory B cells, while CPT1B correlated positively with CD8 T cells. Immunohistochemical assessments indicated that SERPINE2 was more prominently expressed in OS tissues relative to adjacent non-tumorous tissues. Conversely, CPT1B expression was elevated in the adjacent non-tumorous tissues compared to OS tissues. Lymphocyte counts from routine blood evaluations exhibited marked differences between normal and OS groups (p < 0.001). The study highlights SERPINE2 and CPT1B as crucial biomarkers for OS prognosis and suggests that dysregulation of lymphocytes plays a significant role in OS pathogenesis. Both SERPINE2 and CPT1B have potential utility as prognostic biomarkers for OS.

HIF-2α-dependent TGFBI promotes ovarian cancer chemoresistance by activating PI3K/Akt pathway to inhibit apoptosis and facilitate DNA repair process

Hypoxia-mediated chemoresistance plays a crucial role in the development of ovarian cancer (OC). However, the roles of hypoxia-related genes (HRGs) in chemoresistance and prognosis prediction and theirs underlying mechanisms remain to be further elucidated. We intended to identify and validate classifiers of hub HRGs for chemoresistance, diagnosis, prognosis as well as immune microenvironment of OC, and to explore the function of the most crucial HRG in the development of the malignant phenotypes. The RNA expression and clinical data of HRGs were systematically evaluated in OC training group. Univariate and multivariate Cox regression analysis were applied to construct hub HRGs classifiers for prognosis and diagnosis assessment. The relationship between classifiers and chemotherapy response and underlying pathways were detected by GSEA, CellMiner and CIBERSORT algorithm, respectively. OC cells were cultured under hypoxia or transfected with HIF-1α or HIF-2α plasmids, and the transcription levels of TGFBI were assessed by quantitative PCR. TGFBI was knocked down by siRNAs in OC cells, CCK8 and in vitro migration and invasion assays were performed to examine the changes in cell proliferation, motility and metastasis. The difference in TGFBI expression was examined between cisplatin-sensitive and -resistant cells, and the effects of TGFBI interference on cell apoptosis, DNA repair and key signaling molecules of cisplatin-resistant OC cells were explored. A total of 179 candidate HRGs were extracted and enrolled into univariate and multivariate Cox regression analysis. Six hub genes (TGFBI, CDKN1B, AKAP12, GPC1, TGM2 and ANGPTL4) were selected to create a HRGs prognosis classifier and four genes (TGFBI, AKAP12, GPC1 and TGM2) were selected to construct diagnosis classifiers. The HRGs prognosis classifier could precisely distinguish OC patients into high-risk and low-risk groups and estimate their clinical outcomes. Furthermore, the high-risk group had higher percentage of Macrophages M2 and exhibited higher expression of immunecheckpoints such as PD-L2. Additionally, the diagnosis classifiers could accurately distinguish OC from normal samples. TGFBI was further verified as a specific key target and demonstrated that its high expression was closely correlated with poor prognosis and chemoresistance of OC. Hypoxia upregulated the expression level of TGFBI. The hypoxia-induced factor HIF-2α but not HIF-1α could directly bind to the promoter region of TGFBI, and facilitate its transcription level. TGFBI was upregulated in cisplatin-sensitive and resistant ovarian cancer cells in a cisplatin time-dependent manner. TGFBI interference downregulated DNA repair-related markers (p-p95/NBS1, RAD51, p-DNA-PKcs, DNA Ligase IV and Artemis), apoptosis-related marker (BCL2) and PI3K/Akt pathway-related markers (PI3K-p110 and p-Akt) in cisplatin-resistant OC cells. In summary, the HRGs prognosis risk classifier could be served as a predictor for OC prognosis and efficacy evaluation. TGFBI, upregulated by HIF-2α as an HRG, promoted OC chemoresistance through activating PI3K/Akt pathway to reduce apoptosis and enhance DNA damage repair pathway.

Carboplatin, paclitaxel, and pembrolizumab followed by pembrolizumab maintenance for primary treatment of incompletely resected epithelial ovarian cancer

Objective

Incompletely resected epithelial ovarian cancer represents a poor prognostic subset of patients. Novel treatment strategies are needed to improve outcomes for this population. We evaluated a treatment strategy combining platinum-based chemotherapy with pembrolizumab followed by pembrolizumab maintenance therapy in the first-line treatment after incomplete resection of epithelial ovarian cancer patients.

Methods

This was a single-arm, non-randomized pilot study of carboplatin, taxane, and immune checkpoint inhibitor, pembrolizumab, followed by 12 months of maintenance pembrolizumab in patients with incompletely resected epithelial ovarian cancer (EOC).

Results

A total of 29 patients were enrolled and evaluated for efficacy and safety. The best response to therapy was complete response in 16 (55%) patients, partial response in 9 (31%) patients, and 3 (10%) patients with progression of disease. The median progression-free survival (PFS) was 13.2 months. Grade 3 and 4 toxicities occurred in 20% of patients. In all, 7 patients discontinued therapy due to adverse events. Quality-of-life scores remained high during therapy. Response to therapy did not correlate with PD-L1 tumor expression.

Conclusions

Combination platinum-taxane therapy with pembrolizumab did not increase median progression-free survival in this cohort of patients.

Key message

EOC is an immunogenic disease, but immune checkpoint inhibitor therapy has yet to impact outcomes. The current study utilized pembrolizumab in combination with standard chemotherapy followed by a maintenance treatment strategy in incompletely resected EOC. Progression-free survival was not extended in this poor prognostic group with combined chemotherapy and immunotherapy.

Clinical trial registration

https://clinicaltrials.gov/, identifier NCT 027766582.

Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer

BACKGROUND

The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance.

METHODS

The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset.

RESULTS

PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer.

CONCLUSION

In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

LOXL1 promotes tumor cell malignancy and restricts CD8 + T cell infiltration in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a leading cause of cancer mortality globally. Lymph node metastasis and immunosuppression are main factors of poor prognosis in CRC patients. Lysyl oxidase like 1 (LOXL1), part of the lysyl oxidase (LOX) family, plays a yet unclear role in CRC. This study aimed to identify effective biomarkers predictive of prognosis and efficacy of immunotherapy in CRC patients, and to elucidate the prognostic value, clinical relevance, functional and molecular features, and immunotherapy predictive role of LOXL1 in CRC and pan-cancer.

METHODS

Weighted gene co-expression network analysis (WGCNA) was employed to explore gene modules related to tumor metastasis and CD8 + T cell infiltration. LOXL1 emerged as a hub gene through differential gene expression and survival analysis. The molecular signatures, functional roles, and immunological characteristics affected by LOXL1 were analyzed in multiple CRC cohorts, cell lines and clinical specimens. Additionally, LOXL1's potential as an immunotherapy response indicator was assessed, along with its role in pan-cancer.

RESULTS

Turquoise module in WGCNA analysis was identified as the hub module associated with lymph node metastasis and CD8 + T cell infiltration. Aberrant elevated LOXL1 expression was observed in CRC and correlated with poorer differentiation status and prognosis. Molecular and immunological characterization found that LOXL1 might mediate epithelial-mesenchymal transition (EMT) process and immunosuppressive phenotypes of CRC. Functional study found that LOXL1 enhanced tumor cell proliferation, migration and invasion. Moreover, high LOXL1 levels corresponded to reduced CD8 + T cell infiltration and predicted poor clinical outcomes of immunotherapy. Similar trends were also observed at the pan-cancer level.

CONCLUSIONS

Our findings underscore the critical role of LOXL1 in modulating both malignancy and immunosuppression in CRC. This positions LOXL1 as a promising biomarker for predicting prognosis and the response to immunotherapy in CRC patients.

Copine 1 predicts poor clinical outcomes by promoting M2 macrophage activation in ovarian cancer

OBJECTIVE

Copine 1 (CPNE1), a membrane-binding protein, influences the prognosis of various cancers. According to cBioPortal, CPNE1 amplification is a prevalent genetic mutation in ovarian cancer but with unknown oncogenic mechanism.

METHODS

This study analysed the CPNE1 expression in ovarian cancer using online datasets, as validated by immunohistochemistry (IHC), quantitative polymerase chain reaction (qPCR) and western blotting. Concurrently, the prognostic value of CPNE1 was accessed. Cell Counting Kit-8, colony formation, transwells and xenograft experiments were performed to evaluate the functions of CPNE1 during ovarian cancer carcinogenesis. CPNE1 and its related genes were analysed by g:Profiler and Tumour Immune Estimation Resource. Furthermore, human monocytic THP-1 cells were co-cultured with ES2 cells to investigate the effect of CPNE1 on macrophage polarization.

RESULTS

The results of bioinformatic analysis, IHC, qPCR and western blotting indicated a higher CPNE1 in ovarian cancer. CPNE1 overexpression demonstrated an association with a poor prognosis of ovarian cancer. Functionally, CPNE1 overexpression increased ES2 and SKOV3 cell proliferation, invasion and migration in vitro and promoted ovarian tumour xenograft growth in vivo, while CPNE1 knockdown led to opposite effects. Additionally, CPNE1 expression demonstrated an association with immune cell infiltration in ovarian cancer, especially macrophage. CPNE1 promoted protumour M2 macrophage polarization by upregulating cluster of differentiation 163 (CD163), CD206 and interleukin-10.

CONCLUSIONS

Our study revealed that CPNE1 mediated M2 macrophage polarization and provided a therapeutic target for ovarian cancer.

Lysine demethylase 3A in hypoxic macrophages promotes ovarian cancer development through regulation of the vascular endothelial growth factor A/Akt signaling

BACKGROUND

Hypoxia is a vital feature of the tumor microenvironment of OC. Previous evidence exposes that tumor-associated macrophages (TAMs) are connected with the development of ovarian cancer (OC), whereas the accurate regulatory mechanism of hypoxic macrophages regulating tumor advancement remains unclear. Herein, we examined whether the lysine demethylase 3 A (KDM3A) in hypoxic macrophages expedited the development of OC cells.

METHODS

The contents of hypoxia inducible factor-1α (HIF-1α), CD163, CD80, KDM3A, and p-Akt/Akt were detected by western blot. Genomic Spatial Event 4630, Molecular Signatures Database, and Comparative Toxicogenomics Database were utilized for correlated gene prediction. The OC cells viability was scrutinized by cell counting kit-8 assay. The cell proliferation was inspected by 5-Ethynyl-2'-deoxyuridine assay. The vascular endothelial growth factor A (VEGF) level was detected by Enzyme-linked immunosorbent assay.

RESULTS

M2 polarization of TAMs was associated with poor prognosis in sufferers with OC. The OC sufferers with high level of CD163 or low level of CD80 were linked with poor overall survival and disease specific survival. Hypoxia induced THP-1-derived macrophages M2 polarization. KDM3A was high-expressed in hypoxia induced macrophages. Upregulated KDM3A in hypoxic macrophages facilitated OC cell proliferation. KDM3A upregulation in hypoxic macrophages stimulated Akt signaling activation in OC cells. KDM3A in hypoxic macrophages promoted VEGF secretion to activate Akt signaling in OC cells. VEGF inhibition or Akt signaling inactivation reversed the effects of KDM3A in hypoxic macrophages on OC cells viability and proliferation.

CONCLUSION

The KDM3A content and M2 polarization were enhanced in hypoxic macrophages, and KDM3A in hypoxic macrophages promoted OC development through regulation of the VEGF/Akt signaling pathway.

Efficacy and safety of intraperitoneal bevacizumab combined with hyperthermic intraperitoneal chemotherapy in the treatment of patients with ovarian cancer and peritoneal effusion and the effect on serum lncRNA H19 and VEGF levels

Peritoneal effusion is a common event in ovarian cancer (OC) patients. LncRNA H19 and vascular endothelial growth factor (VEGF) are implicated in cancer progression. The study evaluated the curative effect and safety of bevacizumab combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in OC patients with peritoneal effusion and the effect on serum lncRNA H19/VEGF levels. Totally 248 OC patients with peritoneal effusion were treated with intraperitoneal bevacizumab + HIPEC (observation group) or abdominal paracentesis without HIPEC (control group). The clinical efficacy, quality of life, and adverse reactions were evaluated after two treatment cycles. The serum lncRNA H19 and VEGF levels pre-/post-treatment were determined by RT-qPCR and ELISA. The observation group exhibited better clinical efficacy than the control group, evidenced by a higher partial response rate, response rate, and disease control rate. The observation group exhibited reduced physical/cognitive/role/social/emotional function scores and total adverse reactions. LncRNA H19/VEGF levels showed no significant difference between the two groups before treatment but were significantly downregulated in the observation group after treatment. Summarily, intraperitoneal bevacizumab + HIPEC has significant efficacy in treating peritoneal effusion, improves the quality of life, and reduces serum lncRNA H19 and VEGF levels in OC patients, with fewer adverse reactions and higher safety.Impact statementWhat is already known on this subject? The utilization of hyperthermic intraperitoneal chemotherapy (HIPEC) as an emerging treatment option for abdominal malignancies has garnered the attention of numerous researchers over the years, which has significant clinical effects on peritoneal effusion in ovarian cancer and can control patients' conditions and improve their signs and symptoms to a certain extent.What do the results of this study add? In this paper, we investigated the efficacy and safety of intraperitoneal bevacizumab combined with hyperthermic intraperitoneal chemotherapy in the treatment of peritoneal effusion in ovarian cancer. Meanwhile, we compared serum lncRNA H19 and VEGF levels before and after treatment.What are the implications of these findings for clinical practice and/or further research? Our findings may provide a clinically worthy method for the treatment of peritoneal effusion in ovarian cancer. The treatment method reduces serum lncRNA H19 and VEGF levels in patients, which provides a theoretical basis for further research.

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.

Extracellular vesicles targeting tumor microenvironment in ovarian cancer

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

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Adipocyte Microenvironment in Ovarian Cancer: A Critical Contributor?

Ovarian cancer is one of the most common gynecological malignancies and has low survival rates. One of the main determinants of this unfavorable prognosis is the high rate of peritoneal metastasis at diagnosis, closely related to its morbidity and mortality. The mechanism underlying peritoneal carcinomatosis is not clearly defined, but a clear preference for omental spread has been described. Growing evidence suggests that adipose tissue plays a role in promoting cancer onset and progression. Moreover, obesity can lead to changes in the original functions of adipocytes, resulting in metabolic and inflammatory changes in the adipose tissue microenvironment, potentially increasing the risk of tumor growth. However, the specific roles of adipocytes in ovarian cancer have not yet been fully elucidated. Due to the undeniable link between obesity and cancer, the adipose tissue microenvironment could also present a promising therapeutic target that warrants further research. This review discusses the complex relationship between ovarian cancer and the adipose tissue microenvironment.

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

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

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer

Background

Ovarian cancer (OC) is the leading cause of gynecological cancer death and the fifth most common cause of cancer-related death in women in America. Programmed cell death played a vital role in tumor progression and immunotherapy response in cancer.

Methods

The prognostic cell death signature (CDS) was constructed with an integrative machine learning procedure, including 10 methods, using TCGA, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082 datasets. Several methods and single-cell analysis were used to explore the correlation between CDS and the ecosystem and therapy response of OC patients.

Results

The prognostic CDS constructed by the combination of StepCox (n = both) + Enet (alpha = 0.2) acted as an independent risk factor for the overall survival (OS) of OC patients and showed stable and powerful performance in predicting the OS rate of OC patients. Compared with tumor grade, clinical stage, and many developed signatures, the CDS had a higher C-index. OC patients with low CDS score had a higher level of CD8+ cytotoxic T, B cell, and M1-like macrophage, representing a related immunoactivated ecosystem. A low CDS score indicated a higher PD1 and CTLA4 immunophenoscore, higher tumor mutation burden score, lower tumor immune dysfunction and exclusion score, and lower tumor escape score in OC, demonstrating a better immunotherapy response. OC patients with high CDS score had a higher gene set score of cancer-related hallmarks, including angiogenesis, epithelial-mesenchymal transition, hypoxia, glycolysis, and notch signaling.

Conclusion

The current study constructed a novel CDS for OC, which could serve as an indicator for predicting the prognosis, ecosystem, and immunotherapy benefits of OC patients.

A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning

BACKGROUND

Ovarian cancer ranks the leading cause of gynecologic cancer-related death in the United States and the fifth most common cause of cancer-related mortality among American women. Increasing evidences have highlighted the vital role of macrophages M2/M1 proportion in tumor progression, prognosis and immunotherapy.

METHODS

Weighted gene co-expression network analysis (WGCNA) was performed to identify macrophages related markers. Integrative procedure including 10 machine learning algorithms were performed to develop a prognostic macrophage related signature (MRS) with TCGA, GSE14764, GSE140082 datasets. The role of MRS in tumor microenvironment (TME) and therapy response was evaluated with the data of CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER and EPIC, GSE91061 and IMvigor210 dataset.

RESULTS

The optimal MRS developed by the combination of CoxBoost and StepCox[forward] algorithm served as an independent risk factor in ovarian cancer. Compared with stage, grade and other established prognostic signatures, the current MRS had a better performance in predicting the overall survival rate of ovarian cancer patients. Low risk score indicated a higher TME score, higher level of immune cells, higher immunophenoscore, higher tumor mutational burden, lower TIDE score and lower IC50 value in ovarian cancer. The survival prediction nomogram had a good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of ovarian cancer patients.

CONCLUSION

All in all, the current study constructed a powerful prognostic MRS for ovarian cancer patients using 10 machine learning algorithms. This MRS could predict the prognosis and drug sensitivity in ovarian cancer.

Recovery of the Decreased Phagocytic Function of Peripheral Monocytes and Neutrophil Granulocytes following Cytoreductive Surgery in Advanced Stage Epithelial Ovarian Cancer

(1) Monocytes and neutrophil granulocytes are the phagocytic cells of the innate immune system, playing a crucial role in recognizing and eliminating tumor-transformed cells. Our objective was to assess the impact of advanced-stage epithelial ovarian cancer (EOC) and cytoreductive surgery on the phagocytic function of peripheral monocytes and neutrophil granulocytes. We aimed to compare the pre- and postoperative phagocytic function of these immune cells in EOC patients with healthy control women. Additionally, we aimed to examine the influence of surgery on phagocytic function by comparing pre- and postoperative samples from patients with benign gynecological tumors. (2) We examined peripheral blood samples from 20 patients with FIGO IIIC stage high-grade serous EOC and 16 patients with benign gynecological tumors as surgical controls, collected before and seven days after tumor removal surgery, and from 14 healthy women. After separation, the cells were incubated with Zymosan-A particles, and the phagocytic index (PI) was assessed using immunofluorescence microscopy. One-way ANOVA, the Kruskal-Wallis H-test, and the paired samples t-test were used for the statistical analysis of the data. A significance level of p < 0.05 was applied. (3) Peripheral monocytes and neutrophils from EOC patients exhibited significantly lower preoperative PI values compared to healthy controls (p < 0.001; p < 0.001, respectively). Following cytoreductive surgery, the PI values of immune cells in EOC patients significantly increased by the 7th postoperative day (p < 0.001; p < 0.001), reaching levels comparable to those of healthy controls (p = 0.700 and p = 0.991). In contrast, there was no significant disparity in the PI values of cells obtained from pre- and postoperative blood samples of surgical controls when compared to healthy women (monocytes: p = 0.361 and p = 0.303; neutrophils: p = 0.150 and p = 0.235). (4) EOC and/or its microenvironment may produce factors that reduce the phagocytic function of monocytes and neutrophils, and the production of these factors may be reduced or eliminated after tumor removal.

High Tumor-Infiltrating Lymphocyte Count Is Associated with Distinct Gene Expression Profile and Longer Patient Survival in Advanced Ovarian Cancer

Cancer-related immunity plays a significant role in the outcome of ovarian cancer, but the exact mechanisms are not fully explored. A retrospective, real-life observational study was conducted including 57 advanced ovarian cancer patients. Immunohistochemistry for CD4+, CD8+, and CD45+ was used for assessing tumor-infiltrating immune cells. Furthermore, an immune-related gene expression assay was performed on 12-10 samples from patients with less than and more than 1-year overall survival (OS), respectively. A higher number of CD4+ (p = 0.0028) and CD45+ (p = 0.0221) immune cells within the tumor microenvironment were associated with longer OS of patients. In a multivariate setting, higher CD4+ T cell infiltration predicted longer OS (p = 0.0392). Twenty-three differentially expressed genes-involved in antigen presentation, costimulatory signaling, matrix remodeling, metastasis formation, and myeloid cell activity-were found when comparing the prognostic groups. It was found that tumor-infiltrating immune cell counts are associated with peculiar gene expression patterns and bear prognostic information in ovarian cancer. SOX11 expression emerged and was validated as a predictive marker for OS.

Prognostic risk factors of serous ovarian carcinoma based on mesenchymal stem cell phenotype and guidance for therapeutic efficacy

BACKGROUND

Epithelial ovarian cancer is the leading cause of death from gynecologic cancer, in which serous ovarian carcinoma (SOC) is the most common histological subtype. Although PARP inhibitors (PARPi) and antiangiogenics have been accepted as maintenance treatment in SOC, response to immunotherapy of SOC patients is limited.

METHODS

The source of transcriptomic data of SOC was from the Cancer Genome Atlas database and Gene Expression Omnibus. The abundance scores of mesenchymal stem cells (MSC scores) were estimated for each sample by xCell. Weighted correlation network analysis is correlated the significant genes with MSC scores. Based on prognostic risk model construction with Cox regression analysis, patients with SOC were divided into low- and high-risk groups. And distribution of immune cells, immunosuppressors and pro-angiogenic factors in different risk groups was achieved by single-sample gene set enrichment analysis. The risk model of MSC scores was further validated in datasets of immune checkpoint blockade and antiangiogenic therapy. In the experiment, the mRNA expression of prognostic genes related to MSC scores was detected by real-time polymerase chain reaction, while the protein level was evaluated by immunohistochemistry.

RESULTS

Three prognostic genes (PER1, AKAP12 and MMP17) were the constituents of risk model. Patients classified as high-risk exhibited worse prognosis, presented with an immunosuppressive phenotype, and demonstrated high micro-vessel density. Additionally, these patients were insensitive to immunotherapy and would achieve a longer overall survival with antiangiogenesis treatment. The validation experiments showed that the mRNA of PER1, AKAP12, and MMP17 was highly expressed in normal ovarian epithelial cells compared to SOC cell lines and there was a positive correlation between protein levels of PER1, AKAP12 and MMP17 and metastasis in human ovarian serous tumors.

CONCLUSION

This prognostic model established on MSC scores can predict prognosis of patients and provide the guidance for patients receiving immunotherapy and molecular targeted therapy. Because the number of prognostic genes was fewer than other signatures of SOC, it will be easily accessible on clinic.

Recent Insight about HE4 Role in Ovarian Cancer Oncogenesis

Currently, ovarian cancer (OC) is a target of intense biomarkers research because of its frequent late diagnosis and poor prognosis. Serum determination of Human epididymis protein 4 (HE4) is a very important early detection test. Most interestingly, HE4 plays a unique role in OC as it has been implicated not only in OC diagnosis but also in the prognosis and recurrence of this lethal neoplasm, actually acting as a clinical biomarker. There are several evidence about the predictive power of HE4 clinically, conversely less has been described concerning its role in OC oncogenesis. Based on these considerations, the main goal of this review is to clarify the role of HE4 in OC proliferation, angiogenesis, metastatization, immune response and also in the development of targeted therapy. Through a deeper understanding of its functions as a key molecule in the oncogenetic processes underlying OC, HE4 could be possibly considered as an essential resource not only for diagnosis but also for prognosis and therapy choice.

Establishment of highly metastatic ovarian cancer model with omental tropism via in vivo selection

Epithelial ovarian cancer (OC) is often diagnosed at an advanced stage with peritoneal metastasis, and preclinical models mimicking the natural course of OC peritoneal metastasis are essential to improve treatment. We implanted ES2 and ID8 cells in the ovaries of mice and obtained highly metastatic (HM) sublines from their omental metastases after three cycles in vivo selection. Orthotopic xenografts derived from the HM sublines showed enhanced omental tropism and more extensive metastasis with earlier onset. The HM cells exhibited increased in vitro migration and invasion properties, and RNA sequencing revealed that the genes related to epithelial-mesenchymal transition and extracellular matrix regulation were significantly altered in the HM cells. Among them, the upregulated genes were significantly associated with poorer survival in OC patients. In conclusion, these HM sublines can be leveraged to establish spontaneous metastatic OC mouse models, which may serve as ideal preclinical models for anti-metastasis therapy for OC patients.

Downregulation of HHLA2 inhibits ovarian cancer progression via the NF-κB signaling pathway and suppresses the expression of CA9

HHLA2 has been recently demonstrated to play multifaceted roles in several types of cancers. However, its underlying mechanism in the progression of human ovarian cancer (OC) remains largely unexplored. In the present study, we aimed to determine whether downregulation of HHLA2 inhibited malignant phenotypes of human OC cells and explore its specific mechanism. Our results revealed that downregulation of HHLA2 by transfection with a lentiviral vector significantly suppressed the viability, invasion, and migration of OC cells. Interaction study showed that downregulation of HHLA2 in OC cells reduced the expression of CA9 and increased the expressions of p-IKKβ and p-RelA. Conversely, the viability, invasion, and migration of HHLA2-depleted OC cells were increased when CA9 was upregulated. In vivo, we found that downregulation of HHLA2 significantly inhibited tumor growth, which was reversed by CA9 overexpression. In addition, downregulation of HHLA2 inhibited the OC progression via activating the NF-κB signaling pathway and decreasing the expression of CA9. Collectively, our data suggested a link between HHLA2 and NF-κB axis in the pathogenesis of OC, and these findings might provide valuable insights into the development of novel potential therapeutic targets for OC.

CircNFIX stimulates the proliferation, invasion, and stemness properties of ovarian cancer cells by enhancing SH3RF3 mRNA stability via binding LIN28B

We aimed to study the regulatory roles and mechanism of circular nuclear factor IX (circNFIX) in cancer growth and stemness properties of ovarian cancer (OC). CircNFIX and SH3RF3 levels in OC tissues and cells were tested by quantitative real-time PCR. RNase R treatment quantified circNFIX RNA stability. Molecular interaction among circNFIX, LIN28B, and SH3RF3 was predicted by bioinformatics software and validated through RNA immunoprecipitation (RIP) assay. The gain- or loss-experiments of circNFIX on capabilities of metastasis and stemness in vitro were assessed using Cell Counting Kit-8, Transwell, western blot, and sphere-formation assays. CircNFIX and SH3RF3 were markedly elevated in OC tissues and OC cells. Knocking down circNFIX repressed the proliferation, migration, invasion, and stemness properties of A2780 and SKOV3 cells. The RIP assay verified the direct binding relationship between LIN28B, circNFIX, and SH3RF3. Additionally, overexpression of circNFIX elevated the SH3RF3 expression, while this effect was reversed by LIN28B silence. Rescue experiments demonstrated that the overexpression of SH3RF3 reversed the knockdown of circNFIX on OC cells' proliferation, metastasis, and stemness properties. CircNFIX improved the mRNA stability and translation of SH3RF3 via recruiting LIN28B, thus promoting the proliferation, invasion, and stemness properties of OC cells in vitro.

TIPE2 acts as a tumor suppressor and correlates with tumor microenvironment immunity in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is one of the deadliest gynecologic cancers. The etiology of EOC has still not been elucidated thoroughly. Tumor necrosis factor-α-induced protein 8-like2 (TNFAIP8L2, TIPE2), an important regulator of inflammation and immune homeostasis, plays a critical role in the progression of various cancers. This study aims to investigate the role of TIPE2 in EOC.

METHODS

Expression of TIPE2 protein and mRNA in EOC tissues and cell lines was examined using Western blot and quantitative real-time PCR (qRT-PCR). The functions of TIPE2 in EOC were investigated by cell proliferation assay, colony assay, transwell assay, and apoptosis analysis in vitro. To further investigate the regulatory mechanisms of TIPE2 in EOC, RNA-seq and western blot were performed. Finally, the CIBERSORT algorithm and databases including Tumor Immune Single-cell Hub (TISCH), Tumor Immune Estimation Resource (TIMER), Tumor-Immune System Interaction (TISIDB), and The Gene Expression Profiling Interactive Analysis (GEPIA) were used to elucidate its potential role in regulating tumor immune infiltration in the tumor microenvironment (TME).

RESULTS

TIPE2 expression was shown to be considerably lower in both EOC samples and cell lines. Overexpression of TIPE2 suppressed EOC cell proliferation, colony formation, and motility in vitro. Mechanistically, TIPE2 suppressed EOC by blocking the PI3K/Akt signaling pathway, according to bioinformatics analysis and western blot in TIPE2 overexpression EOC cell lines, and the anti-oncogenic potentials of TIPE2 in EOC cells could be partially abrogated by the PI3K agonist, 740Y-P. Finally, TIPE2 expression was positively associated with various immune cells and possibly involved in the regulation of macrophage polarization in ovarian cancer.

CONCLUSIONS

We detail the regulatory mechanism of TIPE2 in EOC carcinogenesis, as well as how it correlates with immune infiltration, emphasizing its potential as a therapeutic target in ovarian cancer.

GATA3 Encapsulated by Tumor-Associated Macrophage-Derived Extracellular Vesicles Promotes Immune Escape and Chemotherapy Resistance of Ovarian Cancer Cells by Upregulating the CD24/Siglec-10 Axis

Tumor-associated macrophages (TAMs) possess great potential in the development of ovarian cancer (OC). Aberrant GATA-binding protein-3 (GATA3) expression has been found in TAM-derived extracellular vesicles (EVs). This study is intended to investigate the regulatory mechanism of TAM-derived EVs, expressing GATA3 in immune escape and chemotherapy resistance of OC cells. In silico analysis was employed to identify differentially expressed genes. The expression of GATA3, CD24, and sialic acid-binding igg-like lectin 10 (Siglec-10) in OC tissues and cells was characterized, with their correlation verified. OC cells were co-cultured with TAM-derived EVs and CD8⁺T cells. The functional significance of GATA3/CD24/Siglec-10 in immune escape and chemotherapy resistance of OC cells was assayed by the gain and loss of function experiments. In vivo experiments were also performed for further validation. High expressions of GATA3, CD24, and Siglec-10 were observed in OC tissues and cells. GATA3 could be transferred by TAM-derived EVs into OC cells, which facilitated immune escape and resistance to cisplatin of OC cells. GATA3 up-regulated CD24 to increase Siglec-10 expression. The in vivo assay confirmed the promoting effect of GATA3 delivered by TAM-derived EVs on OC through activation of the CD24/Siglec-10 axis. Collectively, TAM-derived EVs harboring GATA3 played a tumor-promoting role in immune escape and chemotherapy resistance of OC cells via the CD24/Siglec-10 axis.

Gene signature of m6A-related targets to predict prognosis and immunotherapy response in ovarian cancer

PURPOSE

The aim of the study was to construct a risk score model based on m6A-related targets to predict overall survival and immunotherapy response in ovarian cancer.

METHODS

The gene expression profiles of 24 m6A regulators were extracted. Survival analysis screened 9 prognostic m6A regulators. Next, consensus clustering analysis was applied to identify clusters of ovarian cancer patients. Furthermore, 47 phenotype-related differentially expressed genes, strongly correlated with 9 prognostic m6A regulators, were screened and subjected to univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression. Ultimately, a nomogram was constructed which presented a strong ability to predict overall survival in ovarian cancer.

RESULTS

CBLL1, FTO, HNRNPC, METTL3, METTL14, WTAP, ZC3H13, RBM15B and YTHDC2 were associated with worse overall survival (OS) in ovarian cancer. Three m6A clusters were identified, which were highly consistent with the three immune phenotypes. What is more, a risk model based on seven m6A-related targets was constructed with distinct prognosis. In addition, the low-risk group is the best candidate population for immunotherapy.

CONCLUSION

We comprehensively analyzed the m6A modification landscape of ovarian cancer and detected seven m6A-related targets as an independent prognostic biomarker for predicting survival. Furthermore, we divided patients into high- and low-risk groups with distinct prognosis and select the optimum population which may benefit from immunotherapy and constructed a nomogram to precisely predict ovarian cancer patients' survival time and visualize the prediction results.

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.

Pan-cancer analysis of the prognostic and immunological role of Fanconi anemia complementation group E

Fanconi anemia (FA) genes contribute to tumorigenesis by regulating DNA repair. Despite its importance for assembly and functionality of the FA core complex, no pan-cancer analysis of FANCE was performed. We aimed to provide a comprehensive understanding of the role of FANCE in cancers. Based on The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Genotype Tissue-Expression (GTEx), Human Protein Atlas (HPA), Gene Expression Omnibus (GEO), and Cancer Single-cell Atlas (CancerSEA) databases, we investigated the carcinogenicity of FANCE using various bioinformatics methods, including FANCE expression and prognosis, immune invasion, tumor mutation burden, microsatellite instability, and neoantigens. We monitored Fance mutations in mice that caused tumorigenesis. FANCE expression and activity scores were upregulated in 15 and 21 cancers. High expression of FANCE affected shorter overall survival (OS) in seven cancers and longer overall survival in three cancers. It was correlated with shorter overall survival and progression-free interval (PFI) in endometrial cancer and longer overall survival and PFI in cervical cancer. FANCE expression negatively correlated with stromal/immune scores in 21 cancers including cervical cancer, endometrial cancer, and ovarian cancer. FANCE expression negatively correlated with CD8 T cells in endometrial cancer and positively correlated with M1 macrophages in cervical cancer, possibly related to cancer prognosis. FANCE positively correlated with immune checkpoint inhibitors PD-1, PD-L1, and CTLA4 in endometrial cancer and ovarian cancer. FANCE expression positively correlated with microsatellite instability, tumor mutational burden, and neoantigens in 7, 22, and five cancers, especially in endometrial cancer, potentially increasing the effectiveness of immunotherapy. Single-cell sequencing data showed FANCE was primarily expressed in cancer cells in cervical and ovarian cancer, and in fibroblasts in endometrial cancer. Fance heterozygous mutant mice had increased tumor incidences and shorter overall survival and tumor-free survival (TFS) than Fance homozygous mutant mice and wild-type mice. Conclusively, FANCE potential to serve as a biomarker for cancer prognosis and may predict cancer immunotherapy responses. Fance heterozygous mutant resulted in increased tumorigenesis and poor prognosis in mice.

Exploring prognostic indicators in the pathological images of ovarian cancer based on a deep survival network

Background: Tumor pathology can assess patient prognosis based on a morphological deviation of tumor tissue from normal. Digitizing whole slide images (WSIs) of tissue enables the use of deep learning (DL) techniques in pathology, which may shed light on prognostic indicators of cancers, and avoid biases introduced by human experience. Purpose: We aim to explore new prognostic indicators of ovarian cancer (OC) patients using the DL framework on WSIs, and provide a valuable approach for OC risk stratification. Methods: We obtained the TCGA-OV dataset from the NIH Genomic Data Commons Data Portal database. The preprocessing of the dataset was comprised of three stages: 1) The WSIs and corresponding clinical data were paired and filtered based on a unique patient ID; 2) a weakly-supervised CLAM WSI-analysis tool was exploited to segment regions of interest; 3) the pre-trained model ResNet50 on ImageNet was employed to extract feature tensors. We proposed an attention-based network to predict a hazard score for each case. Furthermore, all cases were divided into a high-risk score group and a low-risk one according to the median as the threshold value. The multi-omics data of OC patients were used to assess the potential applications of the risk score. Finally, a nomogram based on risk scores and age features was established. Results: A total of 90 WSIs were processed, extracted, and fed into the attention-based network. The mean value of the resulting C-index was 0.5789 (0.5096-0.6053), and the resulting p-value was 0.00845. Moreover, the risk score showed a better prediction ability in the HRD + subgroup. Conclusion: Our deep learning framework is a promising method for searching WSIs, and providing a valuable clinical means for prognosis.

Identification of Potentially Functional Circular RNA/Long Noncoding RNA-MicroRNA-mRNA Regulatory Networks Associated with Vascular Injury in Type 2 Diabetes Mellitus by Integrated Microarray Analysis

This research is aimed at figuring out the potential circular RNA (circRNA)/long noncoding RNA- (lncRNA-) microRNA- (miRNA-) mRNA regulatory networks associated with a vascular injury in type 2 diabetes mellitus (T2DM). Differentially expressed genes (DEGs) screened in T2DM-related expression datasets were intersected with genes associated with vascular injury in T2DM to obtain candidate DEGs, followed by the construction of an interaction network of DEGs. The upstream miRNAs of candidate genes were predicted by mirDIP, miRWalk, and DIANA TOOLS databases, and the upstream lncRNAs/circRNAs of miRNAs by DIANA-LncBase/circBank database, followed by the construction of circRNA/lncRNA-miRNA-mRNA regulatory networks. Peripheral blood was attained from T2DM patients with macroangiopathy for clinical validation of expression and correlation of key factors. Differential analysis screened 37 candidate DEGs correlated with vascular injury in T2DM. Besides, MAPK3 was a core gene associated with vascular injury in T2DM. Among the predicted upstream miRNAs of MAPK3, miR-4270, miR-92a-2-5p, miR-423-5p, and miR-613 ranked at the top according to binding scores. The upstream lncRNAs and circRNAs of the 4 miRNAs were further predicted, obtaining 11 candidate lncRNAs and 3 candidate circRNAs. Moreover, KCNQ1OT1, circ_0020316, and MAPK3 were upregulated, but miR-92a-2-5p was downregulated in the peripheral blood of T2DM patients with macroangiopathy. Mechanistically, KCNQ1OT1 and circ_0020316 bound to miR-92a-2-5p that inversely targeted MAPK3. Collectively, KCNQ1OT1/circ_0020316-miR-92a-2-5p-MAPK3 coexpression regulatory networks might promote vascular injury in T2DM.

Molecular Features, Prognostic Value, and Cancer Immune Interactions of Angiogenesis-Related Genes in Ovarian Cancer

Angiogenesis is crucial to tumor growth and metastasis; it plays a key role in various cancers development and progression. However, the potential effects of angiogenesis-related genes (ARGs) in ovarian cancer (OC) remain to be further investigated. We discussed the characteristics changes of ARGs in 784 OC samples from genomic and transcriptional levels, as well as their expression patterns based on four distinct datasets. First, 784 OC patients were divided into three molecular subtypes, and the findings indicated that ARG changes were correlated with clinicopathological parameters, prognosis, and immune cell-infiltrating tumor microenvironment (TME). OC patients were subsequently divided into two gene subtypes depending on differentially expressed genes (DEGs) of the abovementioned molecular subtypes. We also established an ARGs-related score (ARGs score) model for evaluating overall survival (OS) and determining the immunological landscape of OC patients, therefore predicting patients' prognosis and therapeutic responses. A lower ARGs' score accompanied by a high mutation frequency implies a higher probability of survival. Furthermore, the ARG score was correlated with the cancer stem cell (CSC) index and chemotherapeutic sensitivity. The significant involvement of ARGs in the tumor-immune-stromal microenvironment, clinicopathological characteristics, and prognosis were established in our systematic investigation of ARGs for OC patients. These discoveries might help us to better understand the role of ARGs in OC, as well as give new insight for predicting the prognosis and providing promising immunotherapy.

Structure-based virtual screening identified novel FOXM1 inhibitors as the lead compounds for ovarian cancer

Ovarian cancer (OC) is a gynecological tumor with possibly the worst prognosis, its 5-year survival rate being only 47.4%. The first line of therapy prescribed is chemotherapy consisting of platinum and paclitaxel. The primary reason for treatment failure is drug resistance. FOXM1 protein has been found to be closely associated with drug resistance, and inhibition of FOXM1 expression sensitizes cisplatin-resistant ovarian cancer cells. Combining existing first-line chemotherapy drugs with FOXM1 prolongs the overall survival of patients, therefore, FOXM1 is considered a potential therapeutic target in ovarian cancer. Previous research conducted by our team revealed a highly credible conformation of FOXM1 which enables binding by small molecules. Based on this conformation, the current study conducted virtual screening to determine a new structural skeleton for FOXM1 inhibitors which would enhance their medicinal properties. DZY-4 showed the highest affinity towards FOXM1, and its inhibitory effect on proliferation and migration of ovarian cancer at the cellular level was better than or equal to that of cisplatin, while its efficacy was equivalent to that of cisplatin in a nude mouse model. In this study, the anti-tumor effect of DZY-4 is reported for the first time. DZY-4 shows potential as a drug that can be used for ovarian cancer treatment, as well as a drug lead for future research.

A comprehensive pan-cancer analysis of necroptosis molecules in four gynecologic cancers

Background

In recent years, it has been proved that necroptosis plays an important role in the occurrence, development, invasion, metastasis and drug resistance of malignant tumors. Hence, further evaluation and targeting of necroptosis may be of clinical benefit for gynecologic cancers (GCs).

Methods

To compare consistency and difference, we explored the expression pattern and prognostic value of necroptosis-related genes (NRGs) in pan-GC analysis through Linear regression and Empirical Bayesian, Univariate Cox analysis, and public databases from TCGA and Genotype-Tissue Expression (GTEx), including CESC, OV, UCEC, and UCS. We explored the copy number variation (CNV), methylation level and enrichment pathways of NRGs in the four GCs. Based on LASSO Cox regression analysis or principal component analysis, we established the prognostic NRG-signature or necroptosis-score for the four GCs. In addition, we predicted and compared functional pathways, tumor mutational burden (TMB), somatic mutation features, immunity status, immunotherapy, chemotherapeutic drug sensitivity of the NRG-signature based on NRGs. We also examined the expression level of several NRGs in OV samples that we collected using Quantitative Real-time PCR.

Results

We confirmed the presence of NRGs in expression, prognosis, CNV, and methylation for four GCs, thus comparing the consistency and difference among the four GCs. The prognosis and independent prognostic value of the risk signatures based on NRGs were determined. Through the results of subclass mapping, we found that GC patients with lower risk score may be more sensitive to PDL1 response and more sensitive to immune checkpoint blockade therapy. Drug susceptibility analysis showed that, 51, 45, 64, and 29 drugs with differences between risk groups were yielded in CESC, OV, UCEC, and UCS respectively. For OV, the expression differences of several NRGs in the tissues we collected were similar to that in TCGA.

Conclusion

Our comprehensive analysis of NRGs and NRG-signature demonstrated their similarity and difference, as well as their potential roles in prognosis and could guide therapeutic strategies, thus improving the outcome of GC patients.

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.

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.

Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma

Liver cancer is the main reason of cancer deaths globally, with an unfavorable prognosis. DNA methylation is one of the epigenetic modifications and maintains the right adjustment of gene expression and steady gene silencing. We aim to explore the novel signatures for prognosis by using DNA methylation-driven genes. To acquire the DNA methylation-driven genes, we perform the difference analysis from the gene expression data and DNA methylation data in TCGA or GEO databases. And we obtain the 31 DNA methylation-driven genes. Subsequently, consensus clustering analysis was utilized to identify the molecular subtypes based on the 31 DNA methylation-driven genes. So, two molecular subtypes were identified to perform those analyses: Survival, immune cell infiltration, and tumor mutation. Results showed that two subtypes were clustered with distinct prognoses, tumor-infiltrating immune cell and tumor mutation burden. Furthermore, the 31 DNA methylation-driven genes were applied to perform the survival analysis to select the 14 survival-related genes. Immediately, a five methylation-driven genes risk model was built, and the patients were divided into high and low-risk groups. The model was established with TCGA as the training cohort and GSE14520 as the validation cohort. According to the risk model, we perform the systematical analysis, including survival, clinical feature, immune cell infiltration, somatic mutation status, underlying mechanisms, and drug sensitivity. Results showed that the high and low groups possessed statistical significance. In addition, the ROC curve was utilized to measure the accuracy of the risk model. AUCs at 1-year, 3-years, and 5-years were respectively 0.770, 0.698, 0.676 in training cohort and 0.717, 0.649, 0.621 in validation cohort. Nomogram was used to provide a better prediction for patients’ survival. Risk score increase the accuracy of survival prediction in HCC patients. In conclusion, this study developed a novel risk model of five methylation-driven genes based on the comprehensive bioinformatics analysis, which accurately predicts the survival of HCC patients and reflects the immune and mutation features of HCC. This study provides novel insights for immunotherapy of HCC patients and promotes medical progress.