A Complex Network of Tumor Microenvironment in Human High-Grade Serous Ovarian Cancer

Development of a prognostic model based on lysosome-related genes for ovarian cancer: insights into tumor microenvironment, mutation patterns, and personalized treatment strategies

BACKGROUND

Ovarian cancer (OC) is often associated with an unfavorable prognosis. Given the crucial involvement of lysosomes in tumor advancement, lysosome-related genes (LRGs) hold promise as potential therapeutic targets.

METHODS

To identify differentially expressed lysosome-related genes (DE-LRGs), we performed a matching analysis between differentially expressed genes (DEGs) in OC and the pool of LRGs. Genes with prognostic significance were analyzed using multiple regression analyses to construct a prognostic risk signature. The model's efficacy was validated through survival analysis in various cohorts. We further explored the model's correlation with clinical attributes, tumor microenvironment (TME), mutational patterns, and drug sensitivity. The quantitative real-time polymerase chain reaction (qRT-PCR) validated gene expression in OC cells.

RESULTS

A 10-gene prognostic risk signature was established. Survival analysis confirmed its predictive accuracy across cohorts. The signature served as an independent prognostic element for OC. The high-risk and low-risk groups demonstrated notable disparities in terms of immune infiltration patterns, mutational characteristics, and sensitivity to therapeutic agents. The qRT-PCR results corroborated and validated the findings obtained from the bioinformatic analyses.

CONCLUSIONS

We devised a 10-LRG prognostic model linked to TME, offering insights for tailored OC treatments.

Unlocking the potential of immunotherapy in platinum-resistant ovarian cancer: rationale, challenges, and novel strategies

Ovarian cancer is a significant global health challenge, with cytoreductive surgery and platinum-based chemotherapy serving as established primary treatments. Unfortunately, most patients relapse and ultimately become platinum-resistant, at which point there are limited effective treatment options. Given the success of immunotherapy in inducing durable treatment responses in several other cancers, its potential in platinum-resistant ovarian cancer (PROC) is currently being investigated. However, in unselected advanced ovarian cancer populations, researchers have reported low response rates to immune checkpoint inhibition, and thus far, no validated biomarkers are predictive of response. Understanding the intricate interplay between platinum resistance, immune recognition, and the tumour microenvironment (TME) is crucial. In this review, we examine the research challenges encountered thus far, the biological rationale for immunotherapy, the underlying mechanisms of immune resistance, and new strategies to overcome resistance.

AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication

BACKGROUND

The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers.

METHODS

We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function.

RESULTS

We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2.

CONCLUSIONS

Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

Spatiotemporal architecture of immune cells and cancer-associated fibroblasts in high-grade serous ovarian carcinoma

High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically diagnosed after it has metastasized and often relapses after standard-of-care platinum-based chemotherapy, likely due to advanced tumor stage, heterogeneity, and immune evasion and tumor-promoting signaling from the tumor microenvironment. To understand how spatial heterogeneity contributes to HGSOC progression and early relapse, we profiled an HGSOC tissue microarray of patient-matched longitudinal samples from 42 patients. We found spatial patterns associated with early relapse, including changes in T cell localization, malformed tertiary lymphoid structure (TLS)-like aggregates, and increased podoplanin-positive cancer-associated fibroblasts (CAFs). Using spatial features to compartmentalize the tissue, we found that plasma cells distribute in two different compartments associated with TLS-like aggregates and CAFs, and these distinct microenvironments may account for the conflicting reports about the role of plasma cells in HGSOC prognosis.

Advances in prognostic models for osteosarcoma risk

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

The copy number and mutational landscape of recurrent ovarian high-grade serous carcinoma

The drivers of recurrence and resistance in ovarian high grade serous carcinoma remain unclear. We investigate the acquisition of resistance by collecting tumour biopsies from a cohort of 276 women with relapsed ovarian high grade serous carcinoma in the BriTROC-1 study. Panel sequencing shows close concordance between diagnosis and relapse, with only four discordant cases. There is also very strong concordance in copy number between diagnosis and relapse, with no significant difference in purity, ploidy or focal somatic copy number alterations, even when stratified by platinum sensitivity or prior chemotherapy lines. Copy number signatures are strongly correlated with immune cell infiltration, whilst diagnosis samples from patients with primary platinum resistance have increased rates of CCNE1 and KRAS amplification and copy number signature 1 exposure. Our data show that the ovarian high grade serous carcinoma genome is remarkably stable between diagnosis and relapse and acquired chemotherapy resistance does not select for common copy number drivers.

ROR1-STAT3 signaling contributes to ovarian cancer intra-tumor heterogeneity

Wnt pathway dysregulation through genetic and non-genetic alterations occurs in multiple cancers, including ovarian cancer (OC). The aberrant expression of the non-canonical Wnt signaling receptor ROR1 is thought to contribute to OC progression and drug resistance. However, the key molecular events mediated by ROR1 that are involved in OC tumorigenesis are not fully understood. Here, we show that ROR1 expression is enhanced by neoadjuvant chemotherapy, and Wnt5a binding to ROR1 can induce oncogenic signaling via AKT/ERK/STAT3 activation in OC cells. Proteomics analysis of isogenic ROR1-knockdown OC cells identified STAT3 as a downstream effector of ROR1 signaling. Transcriptomics analysis of clinical samples (n = 125) revealed that ROR1 and STAT3 are expressed at higher levels in stromal cells than in epithelial cancer cells of OC tumors, and these findings were corroborated by multiplex immunohistochemistry (mIHC) analysis of an independent OC cohort (n = 11). Our results show that ROR1 and its downstream STAT3 are co-expressed in epithelial as well as stromal cells of OC tumors, including cancer-associated fibroblasts or CAFs. Our data provides the framework to expand the clinical utility of ROR1 as a therapeutic target to overcome OC progression.

Characterization of the m6A regulator-mediated methylation modification patterns in oral squamous cell carcinoma

N⁶-methyladenosine (m⁶A) is a form of posttranscriptional modification that plays important roles in cancer including oral squamous cell carcinoma (OSCC). Most studies to date have focused on a limited number of regulators and oncogenic pathways, thus failing to provide comprehensive insight into the dynamic effects of m⁶A modification. In addition, the role of m⁶A modification in shaping immune cell infiltration in OSCC has yet to be clarified. This study was designed to assess m⁶A modification dynamics in OSCC and to understand how such modifications influence clinical immunotherapeutic treatment outcomes. m⁶A modification patterns linked with 23 m⁶A regulators were analyzed in 437 OSCC patients from TCGA and GEO cohorts. These patterns were then quantified through m⁶A score based on algorithms derived from a principal component analysis (PCA) approach. The m⁶A modification patterns of OSCC samples were grouped into two clusters based on the m⁶A regulators expression, and immune cell infiltration was linked with the 5-year survival outcomes of patients in these clusters. 1575 genes associated with OSCC patient prognosis were identified and used to re-cluster these samples into two groups. Patients in clusters exhibiting higher levels of m⁶A regulator expression exhibited poorer overall survival (OS), whereas patients with high m⁶A scores survived for longer (p < 0.001). The overall mortality rates in the groups of patients with low and high m⁶A scores were 55% and 40%, respectively, and the m⁶A score distributions in clusters of patients grouped by m⁶A modification patterns and gene expression further supported the link between a high m⁶A score and better prognostic outcomes. Immunophenoscore (IPS) values for patients in different m⁶A score groups suggested that the use of PD-1-specific antibodies or CTLA-4 inhibitors alone or in combination would yield superior treatment outcomes in patients in the high-m⁶A score group relative to the low-m⁶A score group. m⁶A modification patterns are relevant to heterogeneity in OSCC. Detailed analyses of m⁶A modification patterns may thus offer novel insight regarding immune cell infiltration within the OSCC tumor microenvironment, guiding novel efforts to provide patients with more effective immunotherapeutic interventions.

Interactions between Platelets and Tumor Microenvironment Components in Ovarian Cancer and Their Implications for Treatment and Clinical Outcomes

Platelets, the primary operatives of hemostasis that contribute to blood coagulation and wound healing after blood vessel injury, are also involved in pathological conditions, including cancer. Malignancy-associated thrombosis is common in ovarian cancer patients and is associated with poor clinical outcomes. Platelets extravasate into the tumor microenvironment in ovarian cancer and interact with cancer cells and non-cancerous elements. Ovarian cancer cells also activate platelets. The communication between activated platelets, cancer cells, and the tumor microenvironment is via various platelet membrane proteins or mediators released through degranulation or the secretion of microvesicles from platelets. These interactions trigger signaling cascades in tumors that promote ovarian cancer progression, metastasis, and neoangiogenesis. This review discusses how interactions between platelets, cancer cells, cancer stem cells, stromal cells, and the extracellular matrix in the tumor microenvironment influence ovarian cancer progression. It also presents novel potential therapeutic approaches toward this gynecological cancer.

Dynamic Changes in the Extracellular Matrix in Primary, Metastatic, and Recurrent Ovarian Cancers

Cancer-associated fibroblasts (CAFs) and their extracellular matrix are active participants in cancer progression. While it is known that functionally different subpopulations of CAFs co-exist in ovarian cancer, it is unclear whether certain CAF subsets are enriched during metastatic progression and/or chemotherapy. Using computational image analyses of patient-matched primary high-grade serous ovarian carcinomas, synchronous pre-chemotherapy metastases, and metachronous post-chemotherapy metastases from 42 patients, we documented the dynamic spatiotemporal changes in the extracellular matrix, fibroblasts, epithelial cells, immune cells, and CAF subsets expressing different extracellular matrix components. Among the different CAF subsets, COL11A1+ CAFs were associated with linearized collagen fibers and exhibited the greatest enrichment in pre- and post-chemotherapy metastases compared to matched primary tumors. Although pre- and post-chemotherapy metastases were associated with increased CD8+ T cell infiltration, the infiltrate was not always evenly distributed between the stroma and cancer cells, leading to an increased frequency of the immune-excluded phenotype where the majority of CD8+ T cells are present in the tumor stroma but absent from the tumor parenchyma. Overall, most of the differences in the tumor microenvironment were observed between primary tumors and metastases, while fewer differences were observed between pre- and post-treatment metastases. These data suggest that the tumor microenvironment is largely determined by the primary vs. metastatic location of the tumor while chemotherapy does not have a significant impact on the host microenvironment.

Nucleic acid vaccination strategies for ovarian cancer

High grade serous carcinoma (HGSC) is one of the most lethal ovarian cancers that is characterised by asymptomatic tumour growth, insufficient knowledge of malignant cell origin and sub-optimal detection. HGSC has been recently shown to originate in the fallopian tube and not in the ovaries. Conventional treatments such as chemotherapy and surgery depend upon the stage of the disease and have resulted in higher rates of relapse. Hence, there is a need for alternative treatments. Differential antigen expression levels have been utilised for early detection of the cancer and could be employed in vaccination strategies using nucleic acids. In this review the different vaccination strategies in Ovarian cancer are discussed and reviewed. Nucleic acid vaccination strategies have been proven to produce a higher CD8+ CTL response alongside CD4+ T-cell response when compared to other vaccination strategies and thus provide a good arena for antitumour immune therapy. DNA and mRNA need to be delivered into the intracellular matrix. To overcome ineffective naked delivery of the nucleic acid cargo, a suitable delivery system is required. This review also considers the suitability of cell penetrating peptides as a tool for nucleic acid vaccine delivery in ovarian cancer.

Tumor-Infiltrating Lymphocytes (TILs) in Epithelial Ovarian Cancer: Heterogeneity, Prognostic Impact, and Relationship with Immune Checkpoints

Epithelial ovarian cancers (EOC) are often diagnosed at an advanced stage with carcinomatosis and a poor prognosis. First-line treatment is based on a chemotherapy regimen combining a platinum-based drug and a taxane-based drug along with surgery. More than half of the patients will have concern about a recurrence. To improve the outcomes, new therapeutics are needed, and diverse strategies, such as immunotherapy, are currently being tested in EOC. To better understand the global immune contexture in EOC, several studies have been performed to decipher the landscape of tumor-infiltrating lymphocytes (TILs). CD8+ TILs are usually considered effective antitumor immune effectors that immune checkpoint inhibitors can potentially activate to reject tumor cells. To synthesize the knowledge of TILs in EOC, we conducted a review of studies published in MEDLINE or EMBASE in the last 10 years according to the PRISMA guidelines. The description and role of TILs in EOC prognosis are reviewed from the published data. The links between TILs, DNA repair deficiency, and ICs have been studied. Finally, this review describes the role of TILs in future immunotherapy for EOC.

The m6A-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumor Immune Infiltration in Ovarian Cancer

Background: OV is the most lethal gynecological malignancy. M6A and lncRNAs have a great impact on OV development and patient immunotherapy response. In this paper, we decided to establish a reliable signature of mRLs. Method: The lncRNAs associated with m6A in OV were analyzed and obtained by co-expression analysis of the TCGA-OV database. Univariate, LASSO and multivariate Cox regression analyses were employed to establish the model of mRLs. K-M analysis, PCA, GSEA and nomogram based on the TCGA-OV and GEO database were conducted to prove the predictive value and independence of the model. The underlying relationship between the model and TME and cancer stemness properties were further investigated through immune feature comparison, consensus clustering analysis and pan-cancer analysis. Results: A prognostic signature comprising four mRLs, WAC-AS1, LINC00997, DNM3OS and FOXN3-AS1, was constructed and verified for OV according to the TCGA and GEO database. The expressions of the four mRLs were confirmed by qRT-PCR in clinical samples. Applying this signature, one can identify patients more effectively. The samples were divided into two clusters, and the clusters had different overall survival rates, clinical features and tumor microenvironments. Finally, pan-cancer analysis further demonstrated that the four mRLs were significantly related to immune infiltration, TME and cancer stemness properties in various cancer types. Conclusions: This study provided an accurate prognostic signature for patients with OV and elucidated the potential mechanism of the mRLs in immune modulation and treatment response, giving new insights into identifying new therapeutic targets.

In high grade ovarian carcinoma, platinum-sensitive tumor recurrence and acquired-resistance derive from quiescent residual cancer cells that overexpress CRYAB, CEACAM6 and SOX2

Most High-Grade Ovarian Carcinomas (HGOCs) are sensitive to carboplatin (CBP)-based chemotherapy but frequently recur within 24 months. Recurrent tumors remain CBP-sensitive and acquire resistance only after several treatment rounds. Recurrences arise from a small number of residual tumor cells hardly amenable to investigation in patients. We developed Patient-Derived Xenografts (PDXs) that allow the study of these different stages of CBP-sensitive recurrence and acquisition of resistance. We generated PDX models from CBP-sensitive and intrinsically resistant HGOC. PDXs were CBP- or mock-treated and tumors were sampled, after treatment and at recurrence. We also isolated models with acquired-resistance from CBP-sensitive PDXs. All tumors were characterized at the histological and transcriptome levels. PDX models reproduced treatment response seen in the patients. CBP-sensitive residual tumors contained non-proliferating tumor cells clusters embedded in a fibrotic mesh. In non-treated PDX tumors and treated CBP-resistant tumors fibrotic tissue was not prevalent. Residual tumors had marked differences in gene expression when compared to naïve and recurrent tumors, indicating downregulation of cell cycle and proliferation and upregulation of interferon response and epithelial-mesenchymal transition. This gene expression pattern resembled that described in embryonal diapause and 'drug-tolerant persister' states. Residual and acquired-resistance tumors share the overexpression of three genes: CEACAM6, CRYAB, and SOX2.Immunostaining analysis showed strong CEACAM6, CRYAB, and SOX2 protein expression in CBP-sensitive residual and acquired resistance PDX, thus, confirming RNA profiling results. In HGOC PDX, CBP-sensitive recurrences arise from a small population of quiescent, drug-tolerant, residual cells embedded in a fibrotic mesh. These cells overexpress CEACAM6, CRYAB and SOX2, whose overexpression is also associated with acquired resistance and poor patient prognosis. CEACAM6, CRYAB and SOX2 may, thus, serve as a biomarker to predict recurrence and emergence of resistant disease in CBP-treated HGOC patients. This article is protected by copyright. All rights reserved.

Identification of a Prognostic Signature for Ovarian Cancer Based on the Microenvironment Genes

Background: Ovarian cancer is highly malignant and has a poor prognosis in the advanced stage. Studies have shown that infiltration of tumor microenvironment cells, immune cells and stromal cells has an important impact on the prognosis of cancers. However, the relationship between tumor microenvironment genes and the prognosis of ovarian cancer has not been studied.

Methods: Gene expression profiles and SNP data of ovarian cancer were downloaded from the TCGA database. Cluster analysis, WGCNA analysis and univariate survival analysis were used to identify immune microenvironment genes as prognostic signatures for predicting the survival of ovarian cancer patients. External data were used to evaluate the signature. Moreover, the top five significantly correlated genes were evaluated by immunohistochemical staining of ovarian cancer tissues.

Results: We systematically analyzed the relationship between ovarian cancer and immune metagenes. Immune metagenes expression were associated with prognosis. In total, we identified 10 genes related to both immunity and prognosis in ovarian cancer according to the expression of immune metagenes. These data reveal that high expression of ETV7 (OS, HR = 1.540, 95% CI 1.023–2.390, p = 0.041), GBP4 (OS, HR = 1.834, 95% CI 1.242–3.055, p = 0.004), CXCL9 (OS, HR = 1.613, 95% CI 1.080 –2.471, p = 0.021), CD3E (OS, HR = 1.590, 95% CI 1.049 –2.459, p = 0.031), and TAP1 (OS, HR = 1.766, 95% CI 1.163 –2.723, p = 0.009) are associated with better prognosis in patients with ovarian cancer.

Conclusion: Our study identified 10 immune microenvironment genes related to the prognosis of ovarian cancer. The list of tumor microenvironment-related genes provides new insights into the underlying biological mechanisms driving the tumorigenesis of ovarian cancer.

Co-regulation and function of FOXM1/RHNO1 bidirectional genes in cancer

The FOXM1 transcription factor is an oncoprotein and a top biomarker of poor prognosis in human cancer. Overexpression and activation of FOXM1 is frequent in high-grade serous carcinoma (HGSC), the most common and lethal form of human ovarian cancer, and is linked to copy number gains at chromosome 12p13.33. We show that FOXM1 is co-amplified and co-expressed with RHNO1, a gene involved in the ATR-Chk1 signaling pathway that functions in the DNA replication stress response. We demonstrate that FOXM1 and RHNO1 are head-to-head (i.e., bidirectional) genes (BDG) regulated by a bidirectional promoter (BDP) (named F/R-BDP). FOXM1 and RHNO1 each promote oncogenic phenotypes in HGSC cells, including clonogenic growth, DNA homologous recombination repair, and poly-ADP ribosylase inhibitor resistance. FOXM1 and RHNO1 are one of the first examples of oncogenic BDG, and therapeutic targeting of FOXM1/RHNO1 BDG is a potential therapeutic approach for ovarian and other cancers.

Phenotypic Characterization by Mass Cytometry of the Microenvironment in Ovarian Cancer and Impact of Tumor Dissociation Methods

Simple Summary

High-grade serous ovarian cancer (HGSOC) is the deadliest gynecological malignancy. Despite increasing research on HGSOC, biomarkers for individualized selection of therapy are scarce. In this study, we develop a multiparametric mass cytometry antibody panel to identify differences in the cellular composition of the microenvironment of tumor tissues dissociated to single-cell suspensions. We also investigate how dissociation methods impact results. Application of our antibody panel to HGSOC tissues showed its ability to identify established main cell subsets and subpopulations of these cells. Comparisons between dissociation methods revealed differences in cell fractions for one immune, two stromal, and three tumor cell subpopulations, while functional marker expression was not affected by the dissociation method. The interpatient disparities identified in the tumor microenvironment were more significant than those identified between differently dissociated tissues from one patient, indicating that the panel facilitates the mapping of individual tumor microenvironments in HGSOC patients.

Abstract

Improved molecular dissection of the tumor microenvironment (TME) holds promise for treating high-grade serous ovarian cancer (HGSOC), a gynecological malignancy with high mortality. Reliable disease-related biomarkers are scarce, but single-cell mapping of the TME could identify patient-specific prognostic differences. To avoid technical variation effects, however, tissue dissociation effects on single cells must be considered. We present a novel Cytometry by Time-of-Flight antibody panel for single-cell suspensions to identify individual TME profiles of HGSOC patients and evaluate the effects of dissociation methods on results. The panel was developed utilizing cell lines, healthy donor blood, and stem cells and was applied to HGSOC tissues dissociated by six methods. Data were analyzed using Cytobank and X-shift and illustrated by t-distributed stochastic neighbor embedding plots, heatmaps, and stacked bar and error plots. The panel distinguishes the main cellular subsets and subpopulations, enabling characterization of individual TME profiles. The dissociation method affected some immune (n = 1), stromal (n = 2), and tumor (n = 3) subsets, while functional marker expressions remained comparable. In conclusion, the panel can identify subsets of the HGSOC TME and can be used for in-depth profiling. This panel represents a promising profiling tool for HGSOC when tissue handling is considered.

The canine activated platelet secretome (CAPS): A translational model of thrombin-evoked platelet activation response

BACKGROUND

Domestic dogs represent a translational animal model to study naturally occurring human disease. Proteomics has emerged as a promising tool for characterizing human platelet pathophysiology; thus a detailed characterization of the core canine activated platelet secretome (CAPS) will enhance utilization of the canine model. The objectives of this study were development of a robust, high throughput, label-free approach for proteomic identification and quantification of the canine platelet (i) thrombin releasate proteins, and (ii) the protein subgroup that constitutes CAPS.

METHODS

Platelets were isolated from 10 healthy dogs and stimulated with 50 nmol/L of γ-thrombin or saline. Proteins were in-solution trypsin-digested and analyzed by nano-liquid chromatography-tandem spectrometry. Core releasate proteins were defined as those present in 10 of 10 dogs, and CAPS defined as releasate proteins with a significantly higher abundance in stimulated versus saline controls (corrected P < .05).

RESULTS

A total of 2865 proteins were identified; 1126 releasate proteins were present in all dogs, 650 were defined as CAPS. Among the differences from human platelets were a canine lack of platelet factor 4 and vascular endothelial growth factor C, and a 10- to 20-fold lower concentration of proteins such as haptoglobin, alpha-2 macroglobulin, von Willebrand factor, and amyloid-beta A4. Twenty-eight CAPS proteins, including cytokines, adhesion molecules, granule proteins, and calcium regulatory proteins have not previously been attributed to human platelets.

CONCLUSIONS

CAPS proteins represent a robust characterization of a large animal platelet secretome and a novel tool to model platelet physiology, pathophysiology, and to identify translational biomarkers of platelet-mediated disease.

Changes in the Tumor Immune Microenvironment during Disease Progression in Patients with Ovarian Cancer

Simple Summary

Immunotherapy has been a successful treatment for many cancers. However, no immunotherapy treatment has been approved for ovarian cancer due to low efficacy in this patient group. This study investigated the cellular and molecular changes from primary ovarian tumors, at the time of diagnosis, to recurrence, where the disease returns after surgery and chemotherapies. Here we examined the immune contexture to better understand subdued responses to immunotherapy and identify additional, potentially complimentary, therapeutic targets. Indications of the development of adaptive immune resistance during disease progression were observed, with increases in immune and stromal cell infiltration accompanied by the expression of immune suppressive markers. We observed high gene expression of the immune checkpoint genes LAG3 and HAVCR2 (TIM3) in most tumors and increased expression of the immune checkpoint genes TIGIT and CTLA4 in recurrent tumors, compared to the primaries. These markers may be potential candidates for immunotherapy targeting in ovarian cancer.

Abstract

Anti-PD1/PDL1 therapy has proven efficacious against many cancers but only reached modest objective response rates against recurrent ovarian cancer. A deeper understanding of the tumor microenvironment (TME) may reveal other immunosuppressive mechanisms that warrant investigation as immunotherapeutic targets for this challenging disease. Matched primary and recurrent tumors from patients with high-grade serous ovarian carcinoma (HGSC) were analyzed by multicolor immunohistochemistry/immunofluorescence for the presence of T cells, B cells, macrophages, and for the expression of immunosuppressive and HLA molecules. Cancer- and immune-related gene expression was assessed by NanoString analysis. Recurrent tumors showed increased infiltration by immune cells, displayed higher expression of PDL1, IDO, and HLA molecules, and contained more stromal tissue. NanoString analysis demonstrated increased expression of gene signatures related to chemokines and T cell functions in recurrent tumors. The ovarian tumors showed high gene expression of LAG3 and HAVCR2 (TIM3) and enhanced levels of TIGIT and CTLA4 in recurrent tumors compared to primary tumors. The majority of HGSC developed into a more inflamed phenotype during progression from primary to recurrent disease, including indications of adaptive immune resistance. This suggests that recurrent tumors may be particularly sensitive to inhibition of adaptive immune resistance mechanisms.

The hallmarks of ovarian cancer: Focus on angiogenesis and micro-environment and new models for their characterisation

Cancers develop by sustained growth, migration and invasion properties of tumour cells, supported by complex interactions with stromal cells within the tumour micro-environment. This review is focused on the latest discoveries regarding the highlighted role of angiogenesis and tumour micro-environment in ovarian cancer. This cancer milieu encompasses non-cancerous cells present in the tumour or nearby, including vessel-forming cells, fibroblasts and immune cells amongst others that work in a cooperative way with cancer cells, impacting tumour behaviour. Angiogenesis, migration and invasion, and more recently immune evasion, are cancer hallmarks clearly dependent on these supporting cells. Moreover, these stromal cells are more genetically stable than tumour cells and thus represent an attractive therapeutic target. A better understanding of the stromal cells function, and their complex interplay with cancer cells, will open additional areas to target, as the tumour-host interface.

Deregulation of cell adhesion molecules is associated with progression and poor outcomes in endometrial cancer: Analysis of The Cancer Genome Atlas data

Cell adhesion molecules (CAMs) determine the behavior of cancer cells during metastasis. Although some CAMs are dysregulated in certain types of cancer and are associated with cancer progression, to the best of our knowledge, a comprehensive study of CAMs has not been undertaken, particularly in endometrial cancer (EC). In the present study the expression of 225 CAMs in EC patients with various clinicopathological phenotypes were evaluated by statistical analysis using publicly available data from The Cancer Genome Atlas database. The Kaplan-Meier method, and univariate and multivariate Cox proportional hazards regression models were used for survival analyses. Among the differentially expressed CAMs that were associated with aggressive clinicopathological phenotypes, 10 CAM genes were independent prognostic factors compared with other clinicopathological prognostic factors, including stage, grade, age, lymph node status, peritoneal cytology and histological subtype. A total of six genes (L1 cell adhesion molecule, mucin 15, cell surface associated, cell adhesion associated, oncogene regulated, immunoglobulin superfamily member 9B, protocadherin 9 and protocadherin β1) were selected for integrative analysis. The six-gene signature was demonstrated to be an independent prognostic factor and could effectively stratify patients with different risks. Patients with more high-expression CAMs had a higher risk of poor overall survival (OS) rate. The mortality risk for patients with elevation of >4 CAMs was 11 times of that in those without elevation of these 6 CAMs. Similar results were obtained when relapse-free survival (RFS) time was used during the analysis. Prognostic reliability of the six-gene model was validated using data of an independent cohort from the International Cancer Genome Consortium. In conclusion, a combination of CAM alterations contributed to progression and aggressiveness of EC. The six-gene signature was effective for predicting worse OS and RFS in patients with EC and could be complementary to the present clinical prognostic criteria.

The Many Microenvironments of Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the most common and deadly subtype of ovarian cancer as it is commonly diagnosed after substantial metastasis has already occurred. The past two decades have been an active era in HGSOC research, with new information on the origin and genomic signature of the tumor cell. Additionally, studies have begun to characterize changes in the HGSOC microenvironment and examine the impact of these changes on tumor progression and response to therapies. While this knowledge may provide valuable insight into better prognosis and treatments for HGSOCs, its collection, synthesis, and application are complicated by the number of unique microenvironments in the disease-the initiating site (fallopian tube), first metastasis (ovary), distal metastases (peritoneum), and recurrent/platinum-resistant setting. Here, we review the state of our understanding of these diverse sites and highlight remaining questions.

ALDH1A1-related stemness in high-grade serous ovarian cancer is a negative prognostic indicator but potentially targetable by EGFR/mTOR-PI3K/aurora kinase inhibitors

Poor chemotherapy response remains a major treatment challenge for high-grade serous ovarian cancer (HGSC). Cancer stem cells are the major contributors to relapse and treatment failure as they can survive conventional therapy. Our objectives were to characterise stemness features in primary patient-derived cell lines, correlate stemness markers with clinical outcome and test the response of our cells to both conventional and exploratory drugs. Tissue and ascites samples, treatment-naive and/or after neoadjuvant chemotherapy, were prospectively collected. Primary cancer cells, cultured under conditions favouring either adherent or spheroid growth, were tested for stemness markers; the same markers were analysed in tissue and correlated with chemotherapy response and survival. Drug sensitivity and resistance testing was performed with 306 oncology compounds. Spheroid growth condition HGSC cells showed increased stemness marker expression (including aldehyde dehydrogenase isoform I; ALDH1A1) as compared with adherent growth condition cells, and increased resistance to platinum and taxane. A set of eight stemness markers separated treatment-naive tumours into two clusters and identified a distinct subgroup of HGSC with enriched stemness features. Expression of ALDH1A1, but not most other stemness markers, was increased after neoadjuvant chemotherapy and its expression in treatment-naive tumours correlated with chemoresistance and reduced survival. In drug sensitivity and resistance testing, five compounds, including two PI3K-mTOR inhibitors, demonstrated significant activity in both cell culture conditions. Thirteen compounds, including EGFR, PI3K-mTOR and aurora kinase inhibitors, were more toxic to spheroid cells than adherent cells. Our results identify stemness markers in HGSC that are associated with a decreased response to conventional chemotherapy and reduced survival if expressed by treatment-naive tumours. EGFR, mTOR-PI3K and aurora kinase inhibitors are candidates for targeting this cell population. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A multiscale signalling network map of innate immune response in cancer reveals cell heterogeneity signatures

The lack of integrated resources depicting the complexity of the innate immune response in cancer represents a bottleneck for high-throughput data interpretation. To address this challenge, we perform a systematic manual literature mining of molecular mechanisms governing the innate immune response in cancer and represent it as a signalling network map. The cell-type specific signalling maps of macrophages, dendritic cells, myeloid-derived suppressor cells and natural killers are constructed and integrated into a comprehensive meta map of the innate immune response in cancer. The meta-map contains 1466 chemical species as nodes connected by 1084 biochemical reactions, and it is supported by information from 820 articles. The resource helps to interpret single cell RNA-Seq data from macrophages and natural killer cells in metastatic melanoma that reveal different anti- or pro-tumor sub-populations within each cell type. Here, we report a new open source analytic platform that supports data visualisation and interpretation of tumour microenvironment activity in cancer.

The complexity of the innate immune response to cancer makes interpretation of large data sets challenging. Here, the authors provide an integrated multi-scale map of signalling networks representing the different immune cells and their interactions and show its utility for data interpretation.

Combination therapy targeting both innate and adaptive immunity improves survival in a pre-clinical model of ovarian cancer

Background

Despite major advancements in immunotherapy among a number of solid tumors, response rates among ovarian cancer patients remain modest. Standard treatment for ovarian cancer is still surgery followed by taxane- and platinum-based chemotherapy. Thus, there is an urgent need to develop novel treatment options for clinical translation.

Methods

Our approach was to analyze the effects of standard chemotherapy in the tumor microenvironment of mice harboring orthotopic, syngeneic ID8-Vegf-Defb29 ovarian tumors in order to mechanistically determine a complementary immunotherapy combination. Specifically, we interrogated the molecular and cellular consequences of chemotherapy by analyzing gene expression and flow cytometry data.

Results

These data show that there is an immunosuppressive shift in the myeloid compartment, with increased expression of IL-10 and ARG1, but no activation of CD3⁺ T cells shortly after chemotherapy treatment. We therefore selected immunotherapies that target both the innate and adaptive arms of the immune system. Survival studies revealed that standard chemotherapy was complemented most effectively by a combination of anti-IL-10, 2′3’-cGAMP, and anti-PD-L1. Immunotherapy dramatically decreased the immunosuppressive myeloid population while chemotherapy effectively activated dendritic cells. Together, combination treatment increased the number of activated T and dendritic cells as well as expression of cytotoxic factors. It was also determined that the immunotherapy had to be administered concurrently with the chemotherapy to reverse the acute immunosuppression caused by chemotherapy. Mechanistic studies revealed that antitumor immunity in this context was driven by CD4⁺ T cells, which acquired a highly activated phenotype. Our data suggest that these CD4⁺ T cells can kill cancer cells directly via granzyme B-mediated cytotoxicity. Finally, we showed that this combination therapy is also effective at delaying tumor growth substantially in an aggressive model of lung cancer, which is also treated clinically with taxane- and platinum-based chemotherapy.

Conclusions

This work highlights the importance of CD4⁺ T cells in tumor immunology. Furthermore, the data support the initiation of clinical trials in ovarian cancer that target both innate and adaptive immunity, with a focus on optimizing dosing schedules.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0654-5) contains supplementary material, which is available to authorized users.

Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine

Historically, the term "artificial intelligence" dates to 1956 when it was first used in a conference at Dartmouth College in the US. Since then, the development of artificial intelligence has in part been shaped by the field of neuroscience. By understanding the human brain, scientists have attempted to build new intelligent machines capable of performing complex tasks akin to humans. Indeed, future research into artificial intelligence will continue to benefit from the study of the human brain. While the development of artificial intelligence algorithms has been fast paced, the actual use of most artificial intelligence (AI) algorithms in biomedical engineering and clinical practice is still markedly below its conceivably broader potentials. This is partly because for any algorithm to be incorporated into existing workflows it has to stand the test of scientific validation, clinical and personal utility, application context, and is equitable as well. In this context, there is much to be gained by combining AI and human intelligence (HI). Harnessing Big Data, computing power and storage capacities, and addressing societal issues emergent from algorithm applications, demand deploying HI in tandem with AI. Very few countries, even economically developed states, lack adequate and critical governance frames to best understand and steer the AI innovation trajectories in health care. Drug discovery and translational pharmaceutical research stand to gain from AI technology provided they are also informed by HI. In this expert review, we analyze the ways in which AI applications are likely to traverse the continuum of life from birth to death, and encompassing not only humans but also all animal, plant, and other living organisms that are increasingly touched by AI. Examples of AI applications include digital health, diagnosis of diseases in newborns, remote monitoring of health by smart devices, real-time Big Data analytics for prompt diagnosis of heart attacks, and facial analysis software with consequences on civil liberties. While we underscore the need for integration of AI and HI, we note that AI technology does not have to replace medical specialists or scientists and rather, is in need of such expert HI. Altogether, AI and HI offer synergy for responsible innovation and veritable prospects for improving health care from prevention to diagnosis to therapeutics while unintended consequences of automation emergent from AI and algorithms should be borne in mind on scientific cultures, work force, and society at large.

Patient-derived cell line models revealed therapeutic targets and molecular mechanisms underlying disease progression of high grade serous ovarian cancer

High grade serous ovarian cancer (HGSOC) is the most frequent type of ovarian cancer. Most patients have primary response to platinum-based chemotherapy but frequently relapse, which leads to patient death. A lack of well documented and characterized patient-derived HGSOC cell lines is so far a major barrier to define tumor specific therapeutic targets and to study the molecular mechanisms underlying disease progression. We established 34 patient-derived HGSOC cell lines and characterized them at cellular and molecular level. Particularly, we demonstrated that a cancer-testis antigen PRAME and Estrogen Receptor could serve as therapeutic targets. Notably, data from the cell lines did not demonstrate acquired resistance due to tumor recurrence that matched with clinical observations. Finally, we presented that all HGSOC had no or very low CDKN1A (p21) expression due to loss of wild-type TP53, suggesting that loss of cell cycle control is the determinant for tumorigenesis and progression. In conclusion, patient-derived cell lines reveal that PRAME is a potential tumor specific therapeutic target in HGSOC and counteracting the down-regulation of p21 caused by loss of wild-type TP53 might be the key to impede disease progression.

Interrelations of Sphingolipid and Lysophosphatidate Signaling with Immune System in Ovarian Cancer

The sphingolipid and lysophosphatidate regulatory networks impact diverse mechanisms attributed to cancer cells and the tumor immune microenvironment. Deciphering the complexity demands implementation of a holistic approach combined with higher-resolution techniques. We implemented a multi-modular integrative approach consolidating the latest accomplishments in gene expression profiling, prognostic/predictive modeling, next generation digital pathology, and systems biology for epithelial ovarian cancer. We assessed patient-specific transcriptional profiles using the sphingolipid/lysophosphatidate/immune-associated signature. This revealed novel sphingolipid/lysophosphatidate-immune gene-gene associations and distinguished tumor subtypes with immune high/low context. These were characterized by robust differences in sphingolipid-/lysophosphatidate-related checkpoints and the drug response. The analysis also nominates novel survival models for stratification of patients with CD68, LPAR3, SMPD1, PPAP2B, and SMPD2 emerging as the most prognostically important genes. Alignment of proprietary data with curated transcriptomic data from public databases across a variety of malignancies (over 600 categories; over 21,000 arrays) showed specificity for ovarian carcinoma. Our systems approach identified novel sphingolipid-lysophosphatidate-immune checkpoints and networks underlying tumor immune heterogeneity and disease outcomes. This holds great promise for delivering novel stratifying and targeting strategies.

Expression of the POTE gene family in human ovarian cancer

The POTE family includes 14 genes in three phylogenetic groups. We determined POTE mRNA expression in normal tissues, epithelial ovarian and high-grade serous ovarian cancer (EOC, HGSC), and pan-cancer, and determined the relationship of POTE expression to ovarian cancer clinicopathology. Groups 1 & 2 POTEs showed testis-specific expression in normal tissues, consistent with assignment as cancer-testis antigens (CTAs), while Group 3 POTEs were expressed in several normal tissues, indicating they are not CTAs. Pan-POTE and individual POTEs showed significantly elevated expression in EOC and HGSC compared to normal controls. Pan-POTE correlated with increased stage, grade, and the HGSC subtype. Select individual POTEs showed increased expression in recurrent HGSC, and POTEE specifically associated with reduced HGSC OS. Consistent with tumors, EOC cell lines had significantly elevated Pan-POTE compared to OSE and FTE cells. Notably, Group 1 & 2 POTEs (POTEs A/B/B2/C/D), Group 3 POTE-actin genes (POTEs E/F/I/J/KP), and other Group 3 POTEs (POTEs G/H/M) show within-group correlated expression, and pan-cancer analyses of tumors and cell lines confirmed this relationship. Based on their restricted expression in normal tissues and increased expression and association with poor prognosis in ovarian cancer, POTEs are potential oncogenes and therapeutic targets in this malignancy.

Mechanisms underlying acquired platinum resistance in high grade serous ovarian cancer - a mini review

BACKGROUND

Advanced epithelial ovarian cancer is one of the hardest human malignancies to treat. Standard treatment involves cytoreductive surgery and platinum-based chemotherapy, however, median progression-free survival for patients diagnosed with advanced stage disease (FIGO stages III and IV) is approximately 18 months. There has been little improvement in overall survival over the past decade and less than half of women with advanced stage disease will be living 5 years after diagnosis. A majority of patients initially have a favourable response to platinum-based chemotherapy, but most will eventually relapse and their disease will become platinum resistant.

SCOPE OF REVIEW

Here, we review our current understanding of mechanisms that promote recurrence and acquired resistance in epithelial ovarian cancer with particular focus on studies that describe differences observed between untreated primary tumors and recurrent tumors, post-first-line chemotherapy. Multiple molecular mechanisms contribute to recurrence in patients following initial treatment for advanced epithelial ovarian cancer including those involving the tumor microenvironment, tumor immune status, cancer stem cells, DNA repair/cell survival pathways and extracellular matrix.

MAJOR CONCLUSIONS

Due to the adaptive nature of recurrent tumors, the major contributing and specific resistance pattern may largely depend on the nature of the primary tumor itself.

GENERAL SIGNIFICANCE

Future work that aims to elucidate the complex pattern of acquired resistance will be useful for predicting chemotherapy response/recurrence following primary diagnosis and to develop novel treatment strategies to improve the survival of patients with advanced epithelial ovarian cancer, especially in tumors not harbouring homologous DNA recombination repair deficiencies.

A 3D tumor microenvironment regulates cell proliferation, peritoneal growth and expression patterns

Peritoneal invasion through the mesothelial cell layer is a hallmark of ovarian cancer metastasis. Using tissue engineering technologies, we recreated an ovarian tumor microenvironment replicating this aspect of disease progression. Ovarian cancer cell-laden hydrogels were combined with mesothelial cell-layered melt electrospun written scaffolds and characterized with proliferation and transcriptomic analyses and used as intraperitoneal xenografts. Here we show increased cancer cell proliferation in these 3D co-cultures, which we validated using patient-derived cells and linked to peritoneal tumor growth in vivo. Transcriptome-wide expression analysis identified IGFBP7, PTGS2, VEGFC and FGF2 as bidirectional factors deregulated in 3D co-cultures compared to 3D mono-cultures, which we confirmed by immunohistochemistry of xenograft and patient-derived tumor tissues and correlated with overall and progression-free survival. These factors were further increased upon expression of kallikrein-related proteases. This clinically predictive model allows us to mimic the complexity and processes of the metastatic disease that may lead to therapies that protect from peritoneal invasion or delay the development of metastasis.

Dynamics of the Intratumoral Immune Response during Progression of High-Grade Serous Ovarian Cancer

PURPOSE

Tumor-infiltrating lymphocytes (TILs) have an established impact on the prognosis of high-grade serous ovarian carcinoma (HGSOC), however, their role in recurrent ovarian cancer is largely unknown. We therefore systematically investigated TIL densities and MHC class I and II (MHC1, 2) expression in the progression of HGSOC.

EXPERIMENTAL DESIGN

CD3+, CD4+, CD8+ TILs and MHC1, 2 expression were evaluated by immunohistochemistry on tissue microarrays in 113 paired primary and recurrent HGSOC. TILs were quantified by image analysis. All patients had been included to the EU-funded OCTIPS FP7 project.

RESULTS

CD3+, CD4+, CD8+ TILs and MHC1 and MHC2 expression showed significant correlations between primary and recurrent tumor levels (Spearman rho 0.427, 0.533, 0.361, 0.456, 0.526 respectively; P<.0001 each). Paired testing revealed higher CD4+ densities and MHC1 expression in recurrent tumors (Wilcoxon P=.034 and P=.018). There was also a shift towards higher CD3+ TILs levels in recurrent carcinomas when analyzing platinum-sensitive tumors only (Wilcoxon P=.026) and in pairs with recurrent tumor tissue from first relapse only (Wilcoxon P=.031). High MHC2 expression was the only parameter to be significantly linked to prolonged progression-free survival after first relapse (PFS2, log-rank P=.012).

CONCLUSIONS

This is the first study that analyzed the development of TILs density and MHC expression in paired primary and recurrent HGSOC. The level of the antitumoral immune response in recurrent tumors was clearly dependent on the one in the primary tumor. Our data contribute to the understanding of temporal heterogeneity of HGSOC immune microenvironment and have implications for selection of samples for biomarker testing in the setting of immune-targeting therapeutics.