Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics.

Importance: Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics. Objective: To develop and characterize a gross morphologic classification system for HGSOC. Design, Setting, and Participants: This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021. Exposures: Gross tumor morphologic characteristics. Main Outcomes and Measures: Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared. Results: Of 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes. Conclusions and Relevance: This study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.

Molecular Analysis of Short- versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma.

Despite having similar histologic features, patients with high-grade serous ovarian carcinoma (HGSC) often experience highly variable outcomes. The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples was collected (12 LTS and 12 STS) and analyzed at DNA, RNA, and protein levels. OVCAR5 and OVCAR8 cell lines were used for in vitro validation studies. For in vivo studies, we injected OVCAR8 cells into the peritoneal cavity of female athymic nude mice. From RNAseq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change > 2; false discovery rate < 0.01). In the subsequent validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. CIBERSORT analysis showed that T cells (follicular helper) were found at higher levels in tumors from LTS than STS groups. In vitro data using OVCAR5 and OVCAR8 cells showed decreased proliferation with TMEM62 overexpression and positive correlation with a longevity-regulating pathway (KEGG HSA04213) at the RNA level. In vivo analysis using the OVCAR8-TMEM62-TetON model showed decreased tumor burden in mice with high- vs. low-expressing TMEM62 tumors. Our results demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes

Rational Combination of CRM1 Inhibitor Selinexor and Olaparib Shows Synergy in Ovarian Cancer Cell Lines and Mouse Models.

CRM1 inhibitors have demonstrated antitumor effects in ovarian and other cancers; however, rational combinations are largely unexplored. We performed a high-throughput drug library screen to identify drugs that might combine well with selinexor in ovarian cancer. Next, we tested the combination of selinexor with the top hit from the drug screen in vitro and in vivo Finally, we assessed for mechanisms underlying the identified synergy using reverse phase protein arrays (RPPA). The drug library screen assessing 688 drugs identified olaparib (a PARP inhibitor) as the most synergistic combination with selinexor. Synergy was further demonstrated by MTT assays. In the A2780luc ip1 mouse model, the combination of selinexor and olaparib yielded significantly lower tumor weight and fewer tumor nodules compared with the control group (P < 0.04 and P < 0.03). In the OVCAR5 mouse model, the combination yielded significantly fewer nodules (P = 0.006) and markedly lower tumor weight compared with the control group (P = 0.059). RPPA analysis indicated decreased expression of DNA damage repair proteins and increased expression of tumor suppressor proteins in the combination treatment group. Collectively, our preclinical findings indicate that combination with selinexor to expand the utility and efficacy of PARP inhibitors in ovarian cancer warrants further exploration.

CD63-mediated cloaking of VEGF in small extracellular vesicles contributes to anti-VEGF therapy resistance.

Despite wide use of anti-vascular endothelial growth factor (VEGF) therapy for many solid cancers, most individuals become resistant to this therapy, leading to disease progression. Therefore, new biomarkers and strategies for blocking adaptive resistance of cancer to anti-VEGF therapy are needed. As described here, we demonstrate that cancer-derived small extracellular vesicles package increasing quantities of VEGF and other factors in response to anti-VEGF therapy. The packaging process of VEGF into small extracellular vesicles (EVs) is mediated by the tetraspanin CD63. Furthermore, small EV-VEGF (eVEGF) is not accessible to anti-VEGF antibodies and can trigger intracrine VEGF signaling in endothelial cells. eVEGF promotes angiogenesis and enhances tumor growth despite bevacizumab treatment. These data demonstrate a mechanism where VEGF is partitioned into small EVs and promotes tumor angiogenesis and progression. These findings have clinical implications for biomarkers and therapeutic strategies for ovarian cancer.

Peritoneal Spread of Ovarian Cancer Harbors Therapeutic Vulnerabilities Regulated by FOXM1 and EGFR/ERBB2 Signaling.

Peritoneal spread is the primary mechanism of metastasis of ovarian cancer, and survival of ovarian cancer cells in the peritoneal cavity as nonadherent spheroids and their adherence to the mesothelium of distant organs lead to cancer progression, metastasis, and mortality. However, the mechanisms that govern this metastatic process in ovarian cancer cells remain poorly understood. In this study, we cultured ovarian cancer cell lines in adherent and nonadherent conditions in vitro and analyzed changes in mRNA and protein levels to identify mechanisms of tumor cell survival and proliferation in adherent and nonadherent cells. EGFR or ERBB2 upregulated ZEB1 in nonadherent cells, which caused resistance to cell death and increased tumor-initiating capacity. Conversely, Forkhead box M1 (FOXM1) was required for the induction of integrin ß1, integrin-α V, and integrin-α 5 for adhesion of cancer cells. FOXM1 also upregulated ZEB1, which could act as a feedback inhibitor of FOXM1, and caused the transition of adherent cells to nonadherent cells. Strikingly, the combinatorial treatment with lapatinib [dual kinase inhibitor of EGFR (ERBB1) and ERBB2] and thiostrepton (FOXM1 inhibitor) reduced growth and peritoneal spread of ovarian cancer cells more effectively than either single-agent treatment in vivo. In conclusion, these results demonstrate that FOXM1 and EGFR/ERBB2 pathways are key points of vulnerability for therapy to disrupt peritoneal spread and adhesion of ovarian cancer cells. SIGNIFICANCE: This study describes the mechanism exhibited by ovarian cancer cells required for adherent cell transition to nonadherent form during peritoneal spread and metastasis. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/24/5554/F1.large.jpg.

GnRH-R-Targeted Lytic Peptide Sensitizes BRCA Wild-type Ovarian Cancer to PARP Inhibition.

EP-100 is a synthetic lytic peptide that specifically targets the gonadotropin-releasing hormone receptor on cancer cells. To extend the utility of EP-100, we aimed to identify effective combination therapies with EP-100 for ovarian cancer and explore potential mechanisms of this combination. A series of in vitro (MTT assay, immunoblot analysis, reverse-phase protein array, comet assay, and immunofluorescence staining) and in vivo experiments were carried out to determine the biological effects of EP-100 alone and in combination with standard-of-care drugs. EP-100 decreased the viability of ovarian cancer cells and reduced tumor growth in orthotopic mouse models. Of five standard drugs tested (cisplatin, paclitaxel, doxorubicin, topotecan, and olaparib), we found that the combination of EP-100 and olaparib was synergistic in ovarian cancer cell lines. Further experiments revealed that combined treatment of EP-100 and olaparib significantly increased the number of nuclear foci of phosphorylated histone H2AX. In addition, the extent of DNA damage was significantly increased after treatment with EP-100 and olaparib in comet assay. We performed reverse-phase protein array analyses and identified that the PI3K/AKT pathway was inhibited by EP-100, which we validated with in vitro experiments. In vivo experiment using the HeyA8 mouse model demonstrated that mice treated with EP-100 and olaparib had lower tumor weights (0.06 ± 0.13 g) than those treated with a vehicle (1.19 ± 1.09 g), EP-100 alone (0.62 ± 0.78 g), or olaparib alone (0.50 ± 0.63 g). Our findings indicate that combining EP-100 with olaparib is a promising therapeutic strategy for ovarian cancer.

Predicting Novel Therapies and Targets: Regulation of Notch3 by the Bromodomain Protein BRD4.

Systematic approaches for accurate repurposing of targeted therapies are needed. We developed and aimed to biologically validate our therapy predicting tool (TPT) for the repurposing of targeted therapies for specific tumor types by testing the role of Bromodomain and Extra-Terminal motif inhibitors (BETi) in inhibiting BRD4 function and downregulating Notch3 signaling in ovarian cancer.Utilizing established ovarian cancer preclinical models, we carried out in vitro and in vivo studies with clinically relevant BETis to determine their therapeutic effect and impact on Notch3 signaling.Treatment with BETis or siRNA-mediated BRD4 knockdown resulted in decreased cell viability, reduced cell proliferation, and increased cell apoptosis in vitro. In vivo studies with orthotopic mouse models demonstrated that treatment with BETi decreased tumor growth. In addition, knockdown of BRD4 with doxycycline-inducible shRNA increased survival up to 50% (P < 0.001). Treatment with either BETis or BRD4 siRNA decreased Notch3 expression both in vitro and in vivo BRD4 inhibition also decreased the expression of NOTCH3 targets, including HES1 Chromatin immunoprecipitation revealed that BRD4 was present at the NOTCH3 promoter.Our findings provide biological validation for the TPT by demonstrating that BETis can be an effective therapeutic agent for ovarian cancer by downregulating Notch3 expression.The TPT could rapidly identify candidate drugs for ovarian or other cancers along with novel companion biomarkers.

Sustained Adrenergic Signaling Promotes Intratumoral Innervation through BDNF Induction.

Mounting clinical and preclinical evidence supports a key role for sustained adrenergic signaling in the tumor microenvironment as a driver of tumor growth and progression. However, the mechanisms by which adrenergic neurotransmitters are delivered to the tumor microenvironment are not well understood. Here we present evidence for a feed-forward loop whereby adrenergic signaling leads to increased tumoral innervation. In response to catecholamines, tumor cells produced brain-derived neurotrophic factor (BDNF) in an ADRB3/cAMP/Epac/JNK-dependent manner. Elevated BDNF levels in the tumor microenvironment increased innervation by signaling through host neurotrophic receptor tyrosine kinase 2 receptors. In patients with cancer, high tumor nerve counts were significantly associated with increased BDNF and norepinephrine levels and decreased overall survival. Collectively, these data describe a novel pathway for tumor innervation, with resultant biological and clinical implications.Significance: Sustained adrenergic signaling promotes tumor growth and metastasis through BDNF-mediated tumoral innervation. Cancer Res; 78(12); 3233-42. ©2018 AACR.

Targeting Stromal Glutamine Synthetase in Tumors Disrupts Tumor Microenvironment-Regulated Cancer Cell Growth.

Reactive stromal cells are an integral part of tumor microenvironment (TME) and interact with cancer cells to regulate their growth. Although targeting stromal cells could be a viable therapy to regulate the communication between TME and cancer cells, identification of stromal targets that make cancer cells vulnerable has remained challenging and elusive. Here, we identify a previously unrecognized mechanism whereby metabolism of reactive stromal cells is reprogrammed through an upregulated glutamine anabolic pathway. This dysfunctional stromal metabolism confers atypical metabolic flexibility and adaptive mechanisms in stromal cells, allowing them to harness carbon and nitrogen from noncanonical sources to synthesize glutamine in nutrient-deprived conditions existing in TME. Using an orthotopic mouse model for ovarian carcinoma, we find that co-targeting glutamine synthetase in stroma and glutaminase in cancer cells reduces tumor weight, nodules, and metastasis. We present a synthetic lethal approach to target tumor stroma and cancer cells simultaneously for desirable therapeutic outcomes.

A miR-192-EGR1-HOXB9 regulatory network controls the angiogenic switch in cancer.

A deeper mechanistic understanding of tumour angiogenesis regulation is needed to improve current anti-angiogenic therapies. Here we present evidence from systems-based miRNA analyses of large-scale patient data sets along with in vitro and in vivo experiments that miR-192 is a key regulator of angiogenesis. The potent anti-angiogenic effect of miR-192 stems from its ability to globally downregulate angiogenic pathways in cancer cells through regulation of EGR1 and HOXB9. Low miR-192 expression in human tumours is predictive of poor clinical outcome in several cancer types. Using 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) nanoliposomes, we show that miR-192 delivery leads to inhibition of tumour angiogenesis in multiple ovarian and renal tumour models, resulting in tumour regression and growth inhibition. This anti-angiogenic and anti-tumour effect is more robust than that observed with an anti-VEGF antibody. Collectively, these data identify miR-192 as a central node in tumour angiogenesis and support the use of miR-192 in an anti-angiogenesis therapy.

Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism.

Cancer-associated fibroblasts (CAFs) are a major cellular component of tumor microenvironment in most solid cancers. Altered cellular metabolism is a hallmark of cancer, and much of the published literature has focused on neoplastic cell-autonomous processes for these adaptations. We demonstrate that exosomes secreted by patient-derived CAFs can strikingly reprogram the metabolic machinery following their uptake by cancer cells. We find that CAF-derived exosomes (CDEs) inhibit mitochondrial oxidative phosphorylation, thereby increasing glycolysis and glutamine-dependent reductive carboxylation in cancer cells. Through 13C-labeled isotope labeling experiments we elucidate that exosomes supply amino acids to nutrient-deprived cancer cells in a mechanism similar to macropinocytosis, albeit without the previously described dependence on oncogenic-Kras signaling. Using intra-exosomal metabolomics, we provide compelling evidence that CDEs contain intact metabolites, including amino acids, lipids, and TCA-cycle intermediates that are avidly utilized by cancer cells for central carbon metabolism and promoting tumor growth under nutrient deprivation or nutrient stressed conditions.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

The ZNF304-integrin axis protects against anoikis in cancer.

Ovarian cancer (OC) is a highly metastatic disease, but no effective strategies to target this process are currently available. Here, an integrative computational analysis of the Cancer Genome Atlas OC data set and experimental validation identifies a zinc finger transcription factor ZNF304 associated with OC metastasis. High tumoral ZNF304 expression is associated with poor overall survival in OC patients. Through reverse phase protein array analysis, we demonstrate that ZNF304 promotes multiple proto-oncogenic pathways important for cell survival, migration and invasion. ZNF304 transcriptionally regulates ß1 integrin, which subsequently regulates Src/focal adhesion kinase and paxillin and prevents anoikis. In vivo delivery of ZNF304 siRNA by a dual assembly nanoparticle leads to sustained gene silencing for 14 days, increased anoikis and reduced tumour growth in orthotopic mouse models of OC. Taken together, ZNF304 is a transcriptional regulator of ß1 integrin, promotes cancer cell survival and protects against anoikis in OC.

Genome-wide perturbations by miRNAs map onto functional cellular pathways, identifying regulators of chromatin modifiers.

BACKGROUND: Regulation of gene expression by microRNAs (miRNAs) is critical for determining cellular fate and function. Dysregulation of miRNA expression contributes to the development and progression of multiple diseases. miRNA can target multiple mRNAs, making deconvolution of the effects of miRNA challenging and the complexity of regulation of cellular pathways by miRNAs at the functional protein level remains to be elucidated. Therefore, we sought to determine the effects of expression of miRNAs in breast and ovarian cancer cells on cellular pathways by measuring systems-wide miRNA perturbations to protein and phosphoproteins. METHODS: We measure protein level changes by reverse-phase protein array (RPPA) in MDA-MB-231, SKOV3.ip1 and HEYA8 cancer cell lines transfected by a library of 879 human miRNA mimics. RESULTS: The effects of multiple miRNAs-protein networks converged in five broad functional clusters of miRNA, suggesting a broad overlap of miRNA action on cellular pathways. Detailed analysis of miRNA clusters revealed novel miRNA/cell cycle protein networks, which we functionally validated. De novo phosphoprotein network estimation using Gaussian graphical modeling, using no priors, revealed known and novel protein interplay, which we also observed in patient ovarian tumor proteomic data. We identified several miRNAs that have pluripotent activities across multiple cellular pathways. In particular we studied miR-365a whose expression is associated with poor survival across several cancer types and demonstrated that anti-miR-365 significantly reduced tumor formation in animal models. CONCLUSIONS: Mapping of miRNA-induced protein and phosphoprotein changes onto pathways revealed new miRNA-cellular pathway connectivity, paving the way for targeting of dysregulated pathways with potential miRNA-based therapeutics.

A pan-cancer proteomic perspective on The Cancer Genome Atlas.

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyse 3,467 patient samples from 11 TCGA 'Pan-Cancer' diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome.

Metabolic shifts toward glutamine regulate tumor growth, invasion and bioenergetics in ovarian cancer.

Glutamine can play a critical role in cellular growth in multiple cancers. Glutamine-addicted cancer cells are dependent on glutamine for viability, and their metabolism is reprogrammed for glutamine utilization through the tricarboxylic acid (TCA) cycle. Here, we have uncovered a missing link between cancer invasiveness and glutamine dependence. Using isotope tracer and bioenergetic analysis, we found that low-invasive ovarian cancer (OVCA) cells are glutamine independent, whereas high-invasive OVCA cells are markedly glutamine dependent. Consistent with our findings, OVCA patients' microarray data suggest that glutaminolysis correlates with poor survival. Notably, the ratio of gene expression associated with glutamine anabolism versus catabolism has emerged as a novel biomarker for patient prognosis. Significantly, we found that glutamine regulates the activation of STAT3, a mediator of signaling pathways which regulates cancer hallmarks in invasive OVCA cells. Our findings suggest that a combined approach of targeting high-invasive OVCA cells by blocking glutamine's entry into the TCA cycle, along with targeting low-invasive OVCA cells by inhibiting glutamine synthesis and STAT3 may lead to potential therapeutic approaches for treating OVCAs.

2'-OMe-phosphorodithioate-modified siRNAs show increased loading into the RISC complex and enhanced anti-tumour activity.

Improving small interfering RNA (siRNA) efficacy in target cell populations remains a challenge to its clinical implementation. Here, we report a chemical modification, consisting of phosphorodithioate (PS2) and 2'-O-Methyl (2'-OMe) MePS2 on one nucleotide that significantly enhances potency and resistance to degradation for various siRNAs. We find enhanced potency stems from an unforeseen increase in siRNA loading to the RNA-induced silencing complex, likely due to the unique interaction mediated by 2'-OMe and PS2. We demonstrate the therapeutic utility of MePS2 siRNAs in chemoresistant ovarian cancer mouse models via targeting GRAM domain containing 1B (GRAMD1B), a protein involved in chemoresistance. GRAMD1B silencing is achieved in tumours following MePS2-modified siRNA treatment, leading to a synergistic anti-tumour effect in combination with paclitaxel. Given the previously limited success in enhancing siRNA potency with chemically modified siRNAs, our findings represent an important advance in siRNA design with the potential for application in numerous cancer types.

Mapping network motif tunability and robustness in the design of synthetic signaling circuits.

Cellular networks are highly dynamic in their function, yet evolutionarily conserved in their core network motifs or topologies. Understanding functional tunability and robustness of network motifs to small perturbations in function and structure is vital to our ability to synthesize controllable circuits. In establishing core sets of network motifs, we selected topologies that are overrepresented in mammalian networks, including the linear, feedback, feed-forward, and bifan circuits. Static and dynamic tunability of network motifs were defined as the motif ability to respectively attain steady-state or transient outputs in response to pre-defined input stimuli. Detailed computational analysis suggested that static tunability is insensitive to the circuit topology, since all of the motifs displayed similar ability to attain predefined steady-state outputs in response to constant inputs. Dynamic tunability, in contrast, was tightly dependent on circuit topology, with some motifs performing superiorly in achieving observed time-course outputs. Finally, we mapped dynamic tunability onto motif topologies to determine robustness of motif structures to changes in topology and identify design principles for the rational assembly of robust synthetic networks.