Immune response in ovarian cancer: how is the immune system involved in prognosis and therapy: potential for treatment utilization

Novel immune-related gene signature for risk stratification and prognosis prediction in ovarian cancer

BACKGROUND

The immune system played a multifaceted role in ovarian cancer (OC) and was a significant mediator of ovarian carcinogenesis. Various immune cells and immune gene products played an integrated role in ovarian cancer (OC) progression, proved the significance of the immune microenvironment in prognosis. Therefore, we aimed to establish and validate an immune gene prognostic signature for OC patients' prognosis prediction.

METHODS

Differently expressed Immune-related genes (DEIRGs) were identified in 428 OC and 77 normal ovary tissue specimens from 9 independent GEO datasets. The Cancer Genome Atlas (TCGA) cohort was used as a training cohort, Univariate Cox analysis was used to identify prognostic DEIRGs in TCGA cohort. Then, an immune gene-based risk model for prognosis prediction was constructed using the LASSO regression analysis, and validated the accuracy and stability of the model in 374 and 93 OC patients in TCGA training cohort and International Cancer Genome Consortium (ICGC) validation cohort respectively. Finally, the correlation among risk score model, clinicopathological parameters, and immune cell infiltration were analyzed.

RESULTS

Five DEIRGs were identified to establish the immune gene signature and divided OC patients into the low- and high-risk groups. In TCGA and ICGC datasets, patients in the low-risk group showed a substantially higher survival rate than high-risk group. Receiver operating characteristic (ROC) curves, t-distributed stochastic neighbor embedding (t-SNE) analysis and principal component analysis (PCA) showed the good performance of the risk model. Clinicopathological correlation analysis proved the risk score model could serve as an independent prognostic factor in 2 independent datasets.

CONCLUSIONS

The prognostic model based on immune-related genes can function as a superior prognostic indicator for OC patients, which could provide evidence for individualized treatment and clinical decision making.

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.

Immune Tumor Microenvironment in Ovarian Cancer Ascites

Ovarian cancer (OC) has a specific type of metastasis, via transcoelomic, and most of the patients are diagnosed at advanced stages with multiple tumors spread within the peritoneal cavity. The role of Malignant Ascites (MA) is to serve as a transporter of tumor cells from the primary location to the peritoneal wall or to the surface of the peritoneal organs. MA comprise cellular components with tumor and non-tumor cells and acellular components, creating a unique microenvironment capable of modifying the tumor behavior. These microenvironment factors influence tumor cell proliferation, progression, chemoresistance, and immune evasion, suggesting that MA play an active role in OC progression. Tumor cells induce a complex immune suppression that neutralizes antitumor immunity, leading to disease progression and treatment failure, provoking a tumor-promoting environment. In this review, we will focus on the High-Grade Serous Carcinoma (HGSC) microenvironment with special attention to the tumor microenvironment immunology.

Cancer Immunoediting: Elimination, Equilibrium, and Immune Escape in Solid Tumors

Emphasizing the dynamic processes between cancer and host immune system, the initially discovered concept of cancer immunosurveillance has been replaced by the current concept of cancer immunoediting consisting of three phases: elimination, equilibrium, and escape. Solid tumors composed of both cancer and host stromal cells are an example how the three phases of cancer immunoediting functionally evolve and how tumor shaped by the host immune system gets finally resistant phenotype. The elimination, equilibrium, and escape have been described in this chapter in details, including the role of immune surveillance, cancer dormancy, disruption of the antigen-presenting machinery, tumor-infiltrating immune cells, resistance to apoptosis, as well as the function of tumor stroma, microvesicles, exosomes, and inflammation.

A Combination of Glutaminase Inhibitor 968 and PD-L1 Blockade Boosts the Immune Response against Ovarian Cancer

Programmed cell death 1 ligand (PD-L1) blockade has been used therapeutically in the treatment of ovarian cancer, and potential combination treatment approaches are under investigation to improve the treatment response rate. The increased dependence on glutamine is widely observed in various type of tumors, including ovarian cancer. Kidney-type glutaminase (GLS), as one of the isotypes of glutaminase, is found to promote tumorigenesis. Here, we have demonstrated that the combined treatment with GLS inhibitor 968 and PD-L1 blockade enhances the immune response against ovarian cancer. Survival analysis using the Kaplan–Meier plotter dataset from ovarian cancer patients revealed that the expression level of GLS predicts poor survival and correlates with the immunosuppressive microenvironment of ovarian cancer. 968 inhibits the proliferation of ovarian cancer cells and enhances granzyme B secretion by CD8⁺ T cells as detected by XTT assay and flow cytometry, respectively. Furthermore, 968 enhances the apoptosis-inducing ability of CD8⁺ T cells toward cancer cells and improves the treatment effect of anti-PD-L1 in treating ovarian cancer as assessed by Annexin V apoptosis assay. In vivo studies demonstrated the prolonged overall survival upon combined treatment of 968 with anti-PD-L1 accompanied by increased granzyme B secretion by CD4⁺ and CD8⁺ T cells isolated from ovarian tumor xenografts. Additionally, 968 increases the infiltration of CD3⁺ T cells into tumors, possibly through enhancing the secretion of CXCL10 and CXCL11 by tumor cells. In conclusion, our findings provide a novel insight into ovarian cancer cells influence the immune system in the tumor microenvironment and highlight the potential clinical implication of combination of immune checkpoints with GLS inhibitor 968 in treating ovarian cancer.

Neutrophil-to-lymphocyte ratio and chemotherapy response score as prognostic markers in ovarian cancer patients treated with neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is the recommended approach in patients with advanced epithelial ovarian cancer (EOC). However, most patients eventually relapse despite the initial high response rate to chemotherapy. Neutrophil-to-lymphocyte ratio is a well-known biomarker that reflects severe inflammation, critical illness, and mortality in various diseases. Chemotherapy response score (CRS) and neutrophil-to-lymphocyte ratio (NLR) have been identified as potential biomarkers of platinum resistance and disease prognosis. We retrospectively evaluated 132 patients with stage IIIc or IV ovarian/fallopian tube/primary peritoneal cancer who had received NACT followed by IDS from 01/01/2003 to 31/12/2018. CRS was assessed on omental specimens collected from IDS according to ICCR guidelines.

RESULTS

Median age was 64.57 years (SD: 9.72; range 39.2-87.1). Most ovarian tumors were serous epithelial (90.9%; 120/132). An elevated NLR (defined as > 3) was observed in 72% (95/132) of patients in contrast with 28% (37/132) of patients characterized by low NLR status. Median PFS (mPFS) and median overall survival (mOS) were 13.05 months (95% CI: 11.42-14.67)) and 34.69 months (95% CI: 23.26-46.12) respectively. In univariate analysis, CRS3 score was significantly associated with prolonged mPFS (CRS1/2: 12.79 months vs CRS3: 17.7 months; P = 0.008). CRS score was not associated with mOS (P = 0.876). High NLR was not significantly associated with mPFS (P = 0.128), however it was significantly associated with poor mOS (P = 0.012). In multivariate analysis, only performance of surgery maintained its statistical significance with both PFS (P = 0.001) and OS (P = 0.008).

CONCLUSION

NLR could serve as a useful predictor of OS but not PFS in ovarian cancer patients receiving NACT. In accordance with our previous study, CRS score at omentum was found to be associated with PFS but not OS in ovarian cancer patients treated with NACT and IDS.

A Novel Classifier Based on Urinary Proteomics for Distinguishing Between Benign and Malignant Ovarian Tumors

Background

Preoperative differentiation of benign and malignant tumor types is critical for providing individualized treatment interventions to improve prognosis of patients with ovarian cancer. High-throughput proteomics analysis of urine samples was performed to identify reliable and non-invasive biomarkers that could effectively discriminate between the two ovarian tumor types.

Methods

In total, 132 urine samples from 73 malignant and 59 benign cases of ovarian carcinoma were divided into C1 (training and test datasets) and C2 (validation dataset) cohorts. Mass spectrometry (MS) data of all samples were acquired in data-independent acquisition (DIA) mode with an Orbitrap mass spectrometer and analyzed using DIA-NN software. The generated classifier was trained with Random Forest algorithm from the training dataset and validated in the test and validation datasets. Serum CA125 and HE4 levels were additionally determined in all patients. Finally, classification accuracy of the classifier, serum CA125 and serum HE4 in all samples were evaluated and plotted via receiver operating characteristic (ROC) analysis.

Results

In total, 2,199 proteins were quantified and 69 identified with differential expression in benign and malignant groups of the C1 cohort. A classifier incorporating five proteins (WFDC2, PTMA, PVRL4, FIBA, and PVRL2) was trained and validated in this study. Evaluation of the performance of the classifier revealed AUC values of 0.970 and 0.952 in the test and validation datasets, respectively. In all 132 patients, AUCs of 0.966, 0.947, and 0.979 were achieved with the classifier, serum CA125, and serum HE4, respectively. Among eight patients with early stage malignancy, 7, 6, and 4 were accurately diagnosed based on classifier, serum CA125, and serum HE4, respectively.

Conclusion

The novel classifier incorporating a urinary protein panel presents a promising non-invasive diagnostic biomarker for classifying benign and malignant ovarian tumors.

Long non-coding RNA FOXD2-AS1 promotes proliferation, migration and invasion of ovarian cancer cells via regulating the expression of miR-4492

The aim of the present study was to determine the role of long non-coding RNA (lncRNA) forkhead box D2 antisense 1 (FOXD2-AS1) in the development of ovarian cancer, investigate the underlying mechanisms and provide a potential diagnostic biomarker for ovarian cancer. A total of 39 ovarian cancer patients were included, and the ovarian cancer tissues and paracancer tissues were obtained. The ovarian cancer cell lines SKOV3 and OVCAR3 and the human ovarian normal epithelial cell line IOSE80 were cultured. The expression of lncRNA FOXD2-AS1 and miR-4492 was detected by reverse transcription-quantitative PCR. Small interfering RNA targeting FOXD2-AS1 (si-FOXD2-AS1), microRNA (miR)-4492 mimics, miR-4492 inhibitor and their corresponding controls were transfected into cells. The proliferation was detected with a Cell-Couting-Kit-8 assay, and migration and invasion were determined using Transwell assays. The mutual binding site of lncRNA FOXD2-AS1 and miR-4492 was predicted with the miRDB database and verified by a luciferase reporter assay. Finally, a rescue assay was performed. The results suggested that lncRNA FOXD2-AS1 was upregulated in ovarian cancer tissues and cell lines. si-FOXD2-AS1 was able to inhibit the proliferation, migration and invasion of ovarian cancer cells. lncRNA FOXD2-AS1 was confirmed to directly target miR-4492. The expression of lncRNA FOXD2-AS1 and miR-4492 exhibited a negative correlation. In a rescue experiment, miR-4492 inhibitor abrogated the effect of siFOXD2-AS1 in SKOV3 and OVCAR3 cell lines. In conclusion, lncRNA FOXD2-AS1 promotes the proliferation and invasion of ovarian cancer cells via regulating the expression of miR-4492. It may be a novel potential diagnostic biomarker and therapeutic target for ovarian cancer.

Preoperative neutrophil-to-lymphocyte ratio predicts 30 day postoperative morbidity and survival after primary surgery for ovarian cancer

OBJECTIVE

The preoperative neutrophil-to-lymphocyte ratio has been found to be an independent prognostic indicator for perioperative complications and survival outcomes in patients undergoing oncologic surgery for several malignancies. The objective of this study was to evaluate the role of the preoperative neutrophil-to-lymphocyte ratio in predicting 30-day postoperative morbidity and overall survival in advanced-stage high-grade serous ovarian cancer patients after primary surgery.

METHODS

A retrospective study was conducted on consecutive patients who underwent primary surgery for high-grade serous ovarian cancer between January 2008 and December 2016 at a single tertiary academic institution in Toronto, Canada. Optimal thresholds for preoperative neutrophil-to-lymphocyte ratio were determined using receiver-operator characteristic curve analysis. Cox-proportional hazard models, Kaplan-Meier, and logistic regression analyses were performed.

RESULTS

Of 505 patients with ovarian cancer during the study period, 199 met the inclusion criteria. Receiver-operator characteristic curve analysis generated optimal preoperative neutrophil-to-lymphocyte ratio thresholds of 2.3 and 2.9 for 30-day postoperative morbidity and survival outcomes, respectively. A neutrophil-to-lymphocyte ratio ≥2.3 was predictive of a composite outcome of 30-day postoperative complications (odds ratio 7.3, 95% confidence interval 2.44 to 21.81; p=0.0004), after adjusting for longer operative time and intraoperative complications. Postoperative complications included superficial surgical site infections (p=0.007) and urinary tract infections (p=0.004). A neutrophil-to-lymphocyte ratio ≥29 was associated with worse 5-year overall survival (57.8% vs 77.7%, p=0.003), and suggested no statistically significant difference in progression-free survival (33.8% vs 40.7%, p=0.054). On multivariable analysis, the neutrophil-to-lymphocyte ratio remained an independent predictor for overall survival (p=0.02) when adjusting for suboptimal cytoreduction (p≤0.0001).

DISCUSSION

A preoperative neutrophil-to-lymphocyte ratio ≥2.3 and ≥2.9 is associated with greater risk of 30-day postoperative morbidity and worse overall survival, respectively. This marker may be used in conjunction with other risk assessment strategies to preoperatively identify high-risk patients. Further prospective study is required to investigate its role in clinical decision-making.

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

Ovarian cancer (OvCA) accounts for one of the leading causes of death from gynecologic malignancy. Despite progress in therapy improvements in OvCA, most patients develop a recurrence after first-line treatments, dependent on the tumor and non-tumor complexity/heterogeneity of the neoplasm and its surrounding tumor microenvironment (TME). The TME has gained greater attention in the design of specific therapies within the new era of immunotherapy. It is now clear that the immune contexture in OvCA, here referred as tumor immune microenvironment (TIME), acts as a crucial orchestrator of OvCA progression, thus representing a necessary target for combined therapies. Currently, several advancements of antitumor immune responses in OvCA are based on the characterization of tumor-infiltrating lymphocytes, which have been shown to correlate with a significantly improved clinical outcome. Here, we reviewed the literature on selected TIME components of OvCA, such as macrophages, neutrophils, γδ T lymphocytes, and natural killer (NK) cells; these cells can have a role in either supporting or limiting OvCA, depending on the TIME stimuli. We also reviewed and discussed the major (immune)-therapeutic approaches currently employed to target and/or potentiate macrophages, neutrophils, γδ T lymphocytes, and NK cells in the OvCA context.

Three-Dimensional Cell Culture Based on Magnetic Fields to Assemble Low-Grade Ovarian Carcinoma Cell Aggregates Containing Lymphocytes

There is a limited number of established ovarian cancer cell lines matching the low-grade serous histotype available for research purposes. Three-dimensional (3D) culture systems provide in vitro models with better tissue-like characteristics than two-dimensional (2D) systems. The goal in the study was to characterize the growth of a given low-grade serous ovarian carcinoma cell line in a 3D culture system conducted in a magnetic field. Moreover, the culture system was evaluated in respect to the assembly of malignant cell aggregates containing lymphocytes. CAISMOV24 cell line alone or mixed with human peripheral blood mononuclear cells (PBMC) were cultured using a commercially available 3D culture system designed for 24 well plates. Resulting cell aggregates revealed the intrinsic capacity of CAISMOV24 cells to assemble structures morphologically defined as papillary, and reflected molecular characteristics usually found in ovarian carcinomas. The contents of lymphocytes into co-cultured cell aggregates were significantly higher (p < 0.05) when NanoShuttle-conjugated PBMC were employed compared with non-conjugated PBMC. Moreover, lymphocyte subsets NK, T-CD4, T-CD8 and T-regulatory were successfully retrieved from co-cultured cell aggregates at 72h. Thus, the culture system allowed CAISMOV24 cell line to develop papillary-like cell aggregates containing lymphocytes.

Platelet-lymphocyte ratio as a potential prognostic factor in gynecologic cancers: a meta-analysis

PURPOSE

Cancer-related inflammation plays an important role in tumor development and progression. Platelet-lymphocyte ratio (PLR) has been studied as a biomarker for prognosis in gynecologic cancers. But, the results of previous studies were controversial, so we performed this meta-analysis.

METHODS

We searched the scientific database of PubMed, Embase, Web of Science, Wanfang, and China National Knowledge Infrastructure (CNKI) using free text and MeSH keywords. Crude HR (hazard ratio) with 95% confidence interval was used to evaluate the risk association between PLR and overall survival (OS) or progression-free survival (PFS) in gynecologic neoplasms.

RESULTS

There totally 23 studies, including 6869 patients who were eligible, most of which are published after 2015 or later. PLR greater than the cut-off was associated with poorer survival prognosis in ovarian cancer [OS: HR 1.80 (95% CI 1.37-2.37), p = 0.000; PFS: HR 1.63 (95% CI 1.38-1.91), p = 0.000] and cervical cancer [OS: HR 1.36 (95% CI 1.10-1.68), p = 0.005; PFS: HR 1.40 (95% CI 1.16-1.70), p = 0.002], but not in endometrial cancer [OS: HR 1.95 (95% CI 0.65-5.84), p = 0.234].

CONCLUSIONS

The current meta-analysis revealed that pretreatment PLR was a simple, promising prognostic indicator for OS and PFS in ovarian and cervical cancers. But, its significance of prognosis did not agree with endometrial neoplasm. However, due to the limited number of original studies, future large-scale studies with more well-designed, high-quality studies are still needed.

Key Immunological Functions Involved in the Progression of Epithelial Ovarian Serous Carcinoma Discovered by the Gene Ontology-Based Immunofunctionome Analysis

Serous carcinoma (SC) is the most common and lethal subtype of epithelial ovarian carcinoma; immunotherapy is a potential treatment for SC, however, the global immunological functions of SC as well as their change during the progression of SC have not been investigated in detail till now. We conducted a genome-wide integrative analysis to investigate the immunofunctionomes of SC at four tumor stages by quantifying the immunological functions defined by the Gene Ontology gene sets. DNA microarray gene expression profiles of 1100 SCs and 136 normal ovarian tissue controls were downloaded from the Gene Expression Omnibus database and converted to the functionome. Then the immunofunctionomes were reconstructed by extracting the offspring from the functionome for the four SC staging groups. The key immunological functions extracted from immunofunctionomes with a series of filters revealed that the immunopathy of SC consisted of a group of deregulated functions with the core members including B cell activation and differentiation, regulation of leukocyte chemotaxis/cellular extravasation, antigen receptor mediated signaling pathway, T helper mediated immunity and macrophage activation; and the auxiliary elements included leukocyte mediated immunity, regulation of inflammatory response, T cell differentiation, mononuclear cell migration, megakaryocyte differentiation, complement activation and cytokine production. These deregulated immunological functions reveal the candidates to target in the immunotherapy.

Role of tumor microenvironment in the pathobiology of ovarian cancer: Insights and therapeutic opportunities

Ovarian cancer is the fifth most common cancer affecting women and at present, stands as the most lethal gynecologic malignancy. The poor disease outcome is due to the nonspecific symptoms and the lack of effective treatment at advanced stages. Thus, it is of utmost importance to understand ovarian carcinoma through several lenses and to dissect the role that the unique peritoneal tumor microenvironment plays in ovarian cancer progression and metastasis. This review seeks to highlight several determinants of this unique tumor microenvironment, their influence on disease outcome and ongoing clinical trials targeting these determinants.

A computational framework for complex disease stratification from multiple large-scale datasets

BACKGROUND

Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states.

METHODS

The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification.

RESULTS

We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.

CONCLUSIONS

This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.

The latest animal models of ovarian cancer for novel drug discovery

INTRODUCTION

Epithelial ovarian cancer is a heterogeneous disease classified into five subtypes, each with a different molecular profile. Most cases of ovarian cancer are diagnosed after metastasis of the primary tumor and are resistant to traditional platinum-based chemotherapeutics. Mouse models of ovarian cancer have been utilized to discern ovarian cancer tumorigenesis and the tumor's response to therapeutics. Areas covered: The authors provide a review of mouse models currently employed to understand ovarian cancer. This article focuses on advances in the development of orthotopic and patient-derived tumor xenograft (PDX) mouse models of ovarian cancer and discusses current humanized mouse models of ovarian cancer. Expert opinion: The authors suggest that humanized mouse models of ovarian cancer will provide new insight into the role of the human immune system in combating and augmenting ovarian cancer and aid in the development of novel therapeutics. Development of humanized mouse models will take advantage of the NSG and NSG-SGM3 strains of mice as well as new strains that are actively being derived.

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.

Natural Killer Cells Response to IL-2 Stimulation Is Distinct between Ascites with the Presence or Absence of Malignant Cells in Ovarian Cancer Patients

Peritoneal ascites are a distinguishable feature of patients with advanced epithelial ovarian cancer (EOC). The presence of different lymphocyte subsets has been reported in EOC-associated ascites, which also can or not contain malignant cells. The goal of this study was to analyze the functional characteristics of natural killer (NK) cells from EOC-associated ascites in terms of their expression of activating receptors and ascites’ contents of lymphocyte subtypes, cytokine profile and presence of EOC cells. NK cell function was evaluated by the expression of the degranulation marker CD107a in resting and interleukin (IL)-2 stimulated NK cells from ascites and blood. Degranulation of NK cells from EOC cell-free ascites was significantly (p < 0.05) higher than all the other groups, either in their resting state or after IL-2 stimulation, suggesting a previous local stimulation. In contrast, treatment with IL-2 had no effect on NK cells from ascites with EOC cells. The amount of regulatory T cells was significantly higher in ascites with EOC cells compared to EOC cell-free ascites. Ascites with EOC cells also had higher levels of tumor necrosis factor (TNF)-α, suggesting inflammation related to the malignancy. In conclusion, the functional performance of NK cells was distinct between EOC cell-free ascites and ascites with EOC cells. The impairment of NK cell response to IL-2 in ascites with EOC cells was consistent with an immunosuppressive tumor microenvironment.

Effect of Th1/Th2 cytokine administration on proinflammatory SKOV-3 cell activation

INTRODUCTION

Interleukin(IL)-1β, IL-6 and IL-12 might associate with inflammatory processes in a tumor progression and create a specific microenvironment for tumor growth. The aim of the study was to assess whether the Th1 and Th2 type cytokines, such as IL-2 and IL-10, affect ovarian carcinoma continuous cell line (SKOV-3) pro-inflammatory activation.

MATERIAL AND METHODS

SKOV-3 ovarian cells and peripheral blood mononuclear cells (PBMCs) were stimulated by IL-2 and IL-10. Additionally, SKOV-3 ovarian cells and PBMCs were co-cultured together. Proinflammatory activation of cancer cells was evaluated by measurement of IL-1β and IL-6 levels in culture fluid after 72 h of incubation.

RESULTS

SKOV-3 cells and PBMCs secreted IL-1β and IL-6. After stimulation by IL-2 and IL-10, secretion of studied parameters was changed in a dose-dependent manner. The addition of a higher IL-2 level gave rise to an increase of IL-1β, IL-6 and IL-12 secretion in SKOV-3 cells. Stimulation by IL-10 increased only IL-1β secretion in SKOV-3 cells. However, IL-6 secretion decreased after stimulation with 25 ng/ml IL-10. Activatory effects of IL-2 and inhibitory effects of IL-10 in co-culture of SKOV-3 and PBMCs were observed.

CONCLUSIONS

Our results suggested that Th1/Th2 type of cytokines might influence pro-inflammatory activation of SKOV-3 ovarian cells. Co-cultures of SKOV-3 and PBMCs showed significant changes in cross-talk between cancer and immune cells.

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND

Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer.

METHODS

In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.

RESULTS

The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).

CONCLUSIONS

Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.

AID/APOBEC-network reconstruction identifies pathways associated with survival in ovarian cancer

BACKGROUND

Building up of pathway-/disease-relevant signatures provides a persuasive tool for understanding the functional relevance of gene alterations and gene network associations in multifactorial human diseases. Ovarian cancer is a highly complex heterogeneous malignancy in respect of tumor anatomy, tumor microenvironment including pro-/antitumor immunity and inflammation; still, it is generally treated as single disease. Thus, further approaches to investigate novel aspects of ovarian cancer pathogenesis aiming to provide a personalized strategy to clinical decision making are of high priority. Herein we assessed the contribution of the AID/APOBEC family and their associated genes given the remarkable ability of AID and APOBECs to edit DNA/RNA, and as such, providing tools for genetic and epigenetic alterations potentially leading to reprogramming of tumor cells, stroma and immune cells.

RESULTS

We structured the study by three consecutive analytical modules, which include the multigene-based expression profiling in a cohort of patients with primary serous ovarian cancer using a self-created AID/APOBEC-associated gene signature, building up of multivariable survival models with high predictive accuracy and nomination of top-ranked candidate/target genes according to their prognostic impact, and systems biology-based reconstruction of the AID/APOBEC-driven disease-relevant mechanisms using transcriptomics data from ovarian cancer samples. We demonstrated that inclusion of the AID/APOBEC signature-based variables significantly improves the clinicopathological variables-based survival prognostication allowing significant patient stratification. Furthermore, several of the profiling-derived variables such as ID3, PTPRC/CD45, AID, APOBEC3G, and ID2 exceed the prognostic impact of some clinicopathological variables. We next extended the signature-/modeling-based knowledge by extracting top genes co-regulated with target molecules in ovarian cancer tissues and dissected potential networks/pathways/regulators contributing to pathomechanisms. We thereby revealed that the AID/APOBEC-related network in ovarian cancer is particularly associated with remodeling/fibrotic pathways, altered immune response, and autoimmune disorders with inflammatory background.

CONCLUSIONS

The herein study is, to our knowledge, the first one linking expression of entire AID/APOBECs and interacting genes with clinical outcome with respect to survival of cancer patients. Overall, data propose a novel AID/APOBEC-derived survival model for patient risk assessment and reconstitute mapping to molecular pathways. The established study algorithm can be applied further for any biologically relevant signature and any type of diseased tissue.

Comparative study of various subpopulations of cytotoxic cells in blood and ascites from patients with ovarian carcinoma

AIM OF THE STUDY

A number of observations have indicated that the immune system plays a significant role in patients with epithelial ovarian cancer (EOC). In cases of EOC, the prognostic significance of tumour infiltrating lymphocytes has not been clearly explained yet. The aim is to determine the phenotype and activation molecules of cytotoxic T cell and NK cell subpopulations and to compare their representation in malignant ascites and peripheral blood in patients with ovarian cancer.

MATERIAL AND METHODS

Cytotoxic cells taken from blood samples of the cubital vein and malignant ascites were obtained from 53 patients with EOC. Their surface and activation characteristics were determined by means of a flow cytometer. Immunophenotype multiparametric analysis of peripheral blood lymphocytes (PBLs) and tumour infiltrating lymphocytes (TILs) was carried out.

RESULTS

CD3(+) T lymphocytes were the main population of TILs (75.9%) and PBLs (70.9%). The number of activating T cells was significantly higher in TILs: CD3(+)/69(+) 6.7% vs. 0.8% (p < 0.001). The representation of (CD3(-)/16(+)56(+)) NK cells in TILs was significantly higher: 11.0% vs. 5.6% (p = 0.041); likewise CD56(bright) and CD-56(bright) from CD56(+) cells were higher in TILs (both p < 0.001). The activation receptor NKG2D was present in 45.1% of TILs vs. 32.3% of PBLs (p = 0.034), but we did not find a significant difference in the numbers of CD56(+)/NKG2D(+) in TILs and PBLs.

CONCLUSIONS

These results prove that the characteristics and intensity of anti-tumour responses are different in compared compartments (ascites/PBLs). The knowledge of phenotype and functions of effector cells is the basic precondition for understanding the anti-tumour immune response.

Ovarian cancer microenvironment: implications for cancer dissemination and chemoresistance acquisition

Ovarian adenocarcinoma is characterized by a late detection, dissemination of cancer cells into the whole peritoneum, and the frequent acquisition of chemoresistance. If these particularities can be explained in part by intrinsic properties of ovarian cancer cells, an increased number of studies show the importance of the tumor microenvironment in tumor progression. Ovarian cancer cells can regulate the composition of their stroma in promoting the formation of ascitic fluid, rich in cytokines and bioactive lipids, and in stimulating the differentiation of stromal cells into a pro-tumoral phenotype. In return, cancer-associated fibroblasts, cancer-associated mesenchymal stem cells, tumor-associated macrophages, or other peritoneal cells, such as adipocytes and mesothelial cells can regulate tumor growth, angiogenesis, dissemination, and chemoresistance. This review focuses on the current knowledge about the roles of stromal cells and the associated secreted factors on tumor progression. We also summarize the different studies showing that targeting the microenvironment represents a great potential for improving the prognosis of patients with ovarian adenocarcinoma.

Tumor stratification by a novel graph-regularized bi-clique finding algorithm

Due to involved disease mechanisms, many complex diseases such as cancer, demonstrate significant heterogeneity with varying behaviors, including different survival time, treatment responses, and recurrence rates. The aim of tumor stratification is to identify disease subtypes, which is an important first step towards precision medicine. Recent advances in profiling a large number of molecular variables such as in The Cancer Genome Atlas (TCGA), have enabled researchers to implement computational methods, including traditional clustering and bi-clustering algorithms, to systematically analyze high-throughput molecular measurements to identify tumor subtypes as well as their corresponding associated biomarkers. In this study we discuss critical issues and challenges in existing computational approaches for tumor stratification. We show that the problem can be formulated as finding densely connected sub-graphs (bi-cliques) in a bipartite graph representation of genomic data. We propose a novel algorithm that takes advantage of prior biology knowledge through a gene-gene interaction network to find such sub-graphs, which helps simultaneously identify both tumor subtypes and their corresponding genetic markers. Our experimental results show that our proposed method outperforms current state-of-the-art methods for tumor stratification.

High-throughput sequencing of T-cell receptors reveals a homogeneous repertoire of tumour-infiltrating lymphocytes in ovarian cancer

The cellular adaptive immune system mounts a response to many solid tumours mediated by tumour-infiltrating T lymphocytes (TILs). Basic measurements of these TILs, including total count, show promise as prognostic markers for a variety of cancers, including ovarian and colorectal. In addition, recent therapeutic advances are thought to exploit this immune response to effectively fight melanoma, with promising studies showing efficacy in additional cancers. However, many of the basic properties of TILs are poorly understood, including specificity, clonality, and spatial heterogeneity of the T-cell response. We utilize deep sequencing of rearranged T-cell receptor beta (TCRB) genes to characterize the basic properties of TILs in ovarian carcinoma. Due to somatic rearrangement during T-cell development, the TCR beta chain sequence serves as a molecular tag for each T-cell clone. Using these sequence tags, we assess similarities and differences between infiltrating T cells in discretely sampled sections of large tumours and compare to T cells from peripheral blood. Within the limits of sensitivity of our assay, the TIL repertoires show strong similarity throughout each tumour and are distinct from the circulating T-cell repertoire. We conclude that the cellular adaptive immune response within ovarian carcinomas is spatially homogeneous and distinct from the T-cell compartment of peripheral blood.

Recent technological advances in using mouse models to study ovarian cancer

Serous epithelial ovarian cancer (SEOC) is the most lethal gynecological cancer in the United States with disease recurrence being the major cause of morbidity and mortality. Despite recent advances in our understanding of the molecular mechanisms responsible for the development of SEOC, the survival rate for women with this disease has remained relatively unchanged in the last two decades. Preclinical mouse models of ovarian cancer, including xenograft, syngeneic, and genetically engineered mice, have been developed to provide a mechanism for studying the development and progression of SEOC. Such models strive to increase our understanding of the etiology and dissemination of ovarian cancer in order to overcome barriers to early detection and resistance to standard chemotherapy. Although there is not a single model that is most suitable for studying ovarian cancer, improvements have led to current models that more closely mimic human disease in their genotype and phenotype. Other advances in the field, such as live animal imaging techniques, allow effective monitoring of the microenvironment and therapeutic efficacy. New and improved preclinical mouse models, combined with technological advances to study such models, will undoubtedly render success of future human clinical trials for patients with SEOC.

The role of interleukin-6 in the evolution of ovarian cancer: clinical and prognostic implications--a review

An increasing number of studies emphasize the role of inflammation and metabolic changes in the induction of cancer-related symptoms, which can affect cancer evolution and prognosis. These changes result from the interactions between the tumor and the host. To date, however, markers of this peculiar condition, which can help clinicians to manage patients better, have still not been identified with certainty. Epithelial ovarian cancer (EOC) appears to be particularly appropriate to study these interactions because of its biological characteristics, its peculiar evolution, and the relevant scientific evidence available. Immunosuppression, anemia, depression, and weight loss affect the evolution of EOC and appear to be directly related to the immune-metabolic changes. In light of the aforementioned evidence, our review will focus on interleukin-6 (IL-6) and its role as potential marker of the patients' immune-metabolic status, to better monitor disease outcome and identify the most appropriate therapeutic strategy in EOC. Furthermore, leptin will be discussed as a sensor of the changes of energy metabolism induced by IL-6.

Interferon regulation factor-3 is a critical regulator of the mature of dendritic cells from mice

Interferon regulatory factor-3 (IRF-3) plays an important role in virus and double-stranded RNA-mediated induction of type I interferon and RANTES (regulated on activation normal T cell expressed and secreted), DNA damage signalling, tumour suppression and virus-induced apoptosis. IRF-3 had recently been shown to contribute to T-cell activation in response to pathogens, which implicated an extensive immunological role for IRF-3. Dendritic cells (DCs) played critical roles as professional APCs in the development of immune responses. However, it was unclear whether IRF-3 had any effect on phenotype or function of DCs. In this study, it was shown that IRF-3 acted as a promoter of DC maturation. The level of IRF-3 expression was transiently upregulated and accumulated in the nucleus in TNF-α-induced immune maturation of mice DC cells. Knockdown of IRF-3 by small interfering RNA in DC cells resulted in both phenotypic and functional immaturation, even without TNF-α treatment. Overall, our data demonstrated for the first time that IRF-3 was a critical regulator of mice DC maturation.

Immune response evaluation through determination of type 1, type 2, and type 17 patterns in patients with epithelial ovarian cancer

Innate and adaptive immune cells secrete different cytokines, which participate through distinct mechanisms in cell-mediated immunity and humoral immune responses. The aim of this study was to evaluate the immune response through analysis of type 1 (Th1), Th2, and Th17 cells in patients with epithelial ovarian cancer (EOC). Our study included 44 patients with EOC (study group) and 32 gynecological patients with no ovarian disease (control group). Fragments of ovarian tissue and blood samples were collected in both groups and aliquots of intracystic fluid and peritoneal fluid were recovered from the EOC patient group. Interleukin (IL)-2/IL-4/IL-6/IL-10/IL-17/tumor necrosis factor (TNF)-α/interferon (IFN)-γ levels were measured by cytometric bead array. Statistical analysis included chi-squared, Student t, Mann-Whitney, Kruskal-Wallis tests, and Cox regression model. Patients with EOC were associated with higher levels of TNF-α/IL-4/IL-6/IL-10 compared to the control group. Both IL-10 and TNF-α concentrations were higher in patients with stage III/IV EOC and also associated with higher levels of cancer antigen 125. Higher Th1-mediated immune response was observed when the cytoreduction was considered optimal. However, patients with EOC with unsatisfactory cytoreductive surgery and undifferentiated tumors were associated with higher concentrations of Th2 cytokines in the 4 sites studied. Higher IL-6/IL-10 and lower IFN-γ concentrations were also associated with a lower overall survival rate in patients with EOC. The EOC group presented a predominantly Th2 response and an immunosuppressant standard and had association between IL-6/IL-10/IFN-γ and prognosis.

Multifaceted therapeutic targeting of ovarian peritoneal carcinomatosis through virus-induced immunomodulation

Immunosuppression associated with ovarian cancer (OC) and resultant peritoneal carcinomatosis (PC) hampers the efficacy of many promising treatment options, including immunotherapies. It is hypothesized that oncolytic virus-based therapies can simultaneously kill OC and mitigate immunosuppression. Currently, reovirus-based anticancer therapy is undergoing phase I/II clinical trials for the treatment of OC. Hence, this study was focused on characterizing the effects of reovirus therapy on OC and associated immune microenvironment. Our data shows that reovirus efficiently killed OC cells and induced higher expression of the molecules involved in antigen presentation including major histocompatibility complex (MHC) class I, β2-microglobulin (β2M), TAP-1, and TAP-2. In addition, in the presence of reovirus, dendritic cells (DCs) overcame the OC-mediated phenotypic suppression and successfully stimulated tumor-specific CD8+ T cells. In animal studies, reovirus targeted local and distal OC, alleviated the severity of PC and significantly prolonged survival. These therapeutic effects were accompanied by decreased frequency of suppressive cells, e.g., Gr1.1+, CD11b+ myeloid derived suppressor cells (MDSCs), and CD4+, CD25+, FOXP3+ Tregs, tumor-infiltration of CD3+ cells and higher expression of Th1 cytokines. Finally, reovirus therapy during early stages of OC also resulted in the postponement of PC development. This report elucidates timely information on a therapeutic approach that can target OC through clinically desired multifaceted mechanisms to better the outcomes.

BTN3A2 expression in epithelial ovarian cancer is associated with higher tumor infiltrating T cells and a better prognosis

BTN3A2/BT3.2 butyrophilin mRNA expression by tumoral cells was previously identified as a prognostic factor in a small cohort of high grade serous epithelial ovarian cancer (HG-EOC). Here, we evaluated the prognostic value of BT3.2 at the protein level in specimen from 199 HG-EOC patients. As the only known role of butyrophilin proteins is in immune regulation, we evaluated the association between BT3.2 expression and intratumoral infiltration of immune cells by immunohistochemistry with specific antibodies against BT3.2, CD3, CD4, CD8, CD20, CD68 and CD206. Epithelial BT3.2 expression was significantly associated with longer overall survival and lower risk of disease progression (HR=0.651, p=0.006 and HR=0.642, p=0.002, respectively) and significantly associated with a higher density of infiltrating T cells, particularly CD4+ cells (0.272, p<0.001). We also observed a strong association between the relative density of CD206+ cells, as evaluated by the ratio of intratumoral CD206+/CD68+ expression, and risk of disease progression (HR=1.355 p=0.044, respectively). In conclusion, BT3.2 protein is a potential prognostic biomarker for the identification of HG-EOC patients with better outcome. In contrast, high CD206+/CD68+ expression is associated with high risk of disease progression. While the role of BT3.2 is still unknown, our result suggest that BT3.2 expression by epithelial cells may modulates the intratumoral infiltration of immune cells.

BTN3A2 expression in epithelial ovarian cancer is associated with higher tumor infiltrating T cells and a better prognosis

BTN3A2/BT3.2 butyrophilin mRNA expression by tumoral cells was previously identified as a prognostic factor in a small cohort of high grade serous epithelial ovarian cancer (HG-EOC). Here, we evaluated the prognostic value of BT3.2 at the protein level in specimen from 199 HG-EOC patients. As the only known role of butyrophilin proteins is in immune regulation, we evaluated the association between BT3.2 expression and intratumoral infiltration of immune cells by immunohistochemistry with specific antibodies against BT3.2, CD3, CD4, CD8, CD20, CD68 and CD206. Epithelial BT3.2 expression was significantly associated with longer overall survival and lower risk of disease progression (HR = 0.651, p = 0.006 and HR = 0.642, p = 0.002, respectively) and significantly associated with a higher density of infiltrating T cells, particularly CD4+ cells (0.272, p<0.001). We also observed a strong association between the relative density of CD206+ cells, as evaluated by the ratio of intratumoral CD206+/CD68+ expression, and risk of disease progression (HR = 1.355 p = 0.044, respectively). In conclusion, BT3.2 protein is a potential prognostic biomarker for the identification of HG-EOC patients with better outcome. In contrast, high CD206+/CD68+ expression is associated with high risk of disease progression. While the role of BT3.2 is still unknown, our result suggest that BT3.2 expression by epithelial cells may modulates the intratumoral infiltration of immune cells.

Inflammation and ovarian cancer

Epithelial ovarian cancer (EOC) is a highly lethal gynecological cancer for which overall prognosis has remained poor over the past few decades. A number of theories have been postulated in an effort to explain the etiology of EOC. Noteworthy, these theories likely are not mutually exclusive, as they all converge more or less on the role of inflammation in promoting ovarian tumorigenesis and cancer progression. The tumor milieu in which ovarian carcinoma develops has been described as one enriched with a broad spectrum of pro-inflammatory cytokines and chemokines. In particular, several of these cytokines, such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β and IL-6, produced by tumor itself or/and activated immune cells, besides stimulating cancer cell growth, have been shown to influence clinical disease status and prognosis, by reducing responsiveness to chemotherapy and inducing symptoms such as anorexia, altered energy metabolism, anemia, weight loss, depression and fatigue. Recent data show that cytokine antagonists may have a role to play in the treatment of ovarian cancer. Their action by inhibiting both production and activity of inflammatory cytokines seems to obtain the control of angiogenetic and apoptotic events, the reversal of chemoresistance, the improvement of systemic symptoms and prognosis. In the light of our scientific research and the most recent experimental and clinical advances, our review will discuss the most relevant and recent findings on the role of proinflammatory cytokines in the pathogenesis and prognosis of ovarian cancer and the possible therapeutic implications.

Optimizing molecular-targeted therapies in ovarian cancer: the renewed surge of interest in ovarian cancer biomarkers and cell signaling pathways

The hallmarks of ovarian cancer encompass the development of resistance, disease recurrence and poor prognosis. Ovarian cancer cells express gene signatures which pose significant challenges for cancer drug development, therapeutics, prevention and management. Despite enhancements in contemporary tumor debulking surgery, tentative combination regimens and abdominal radiation which can achieve beneficial response rates, the majority of ovarian cancer patients not only experience adverse effects, but also eventually relapse. Therefore, additional therapeutic possibilities need to be explored to minimize adverse events and prolong progression-free and overall response rates in ovarian cancer patients. Currently, a revival in cancer drug discovery is devoted to identifying diagnostic and prognostic ovarian cancer biomarkers. However, the sensitivity and reliability of such biomarkers may be complicated by mutations in the BRCA1 or BRCA2 genes, diverse genetic risk factors, unidentified initiation and progression elements, molecular tumor heterogeneity and disease staging. There is thus a dire need to expand existing ovarian cancer therapies with broad-spectrum and individualized molecular targeted approaches. The aim of this review is to profile recent developments in our understanding of the interrelationships among selected ovarian tumor biomarkers, heterogeneous expression signatures and related molecular signal transduction pathways, and their translation into more efficacious targeted treatment rationales.