EphA2- and HDAC-Targeted Combination Therapy in Endometrial Cancer.

Endometrial cancer is the most frequent malignant tumor of the female reproductive tract but lacks effective therapy. EphA2, a receptor tyrosine kinase, is overexpressed by various cancers including endometrial cancer and is associated with poor clinical outcomes. In preclinical models, EphA2-targeted drugs had modest efficacy. To discover potential synergistic partners for EphA2-targeted drugs, we performed a high-throughput drug screen and identified panobinostat, a histone deacetylase inhibitor, as a candidate. We hypothesized that combination therapy with an EphA2 inhibitor and panobinostat leads to synergistic cell death. Indeed, we found that the combination enhanced DNA damage, increased apoptosis, and decreased clonogenic survival in Ishikawa and Hec1A endometrial cancer cells and significantly reduced tumor burden in mouse models of endometrial carcinoma. Upon RNA sequencing, the combination was associated with downregulation of cell survival pathways, including senescence, cyclins, and cell cycle regulators. The Axl-PI3K-Akt-mTOR pathway was also decreased by combination therapy. Together, our results highlight EphA2 and histone deacetylase as promising therapeutic targets for endometrial cancer.

Combination of EphA2- and Wee1-Targeted Therapies in Endometrial Cancer.

EphA2 tyrosine kinase is upregulated in many cancers and correlated with poor survival of patients, including those with endometrial cancer. EphA2-targeted drugs have shown modest clinical benefit. To improve the therapeutic response to such drugs, we performed a high-throughput chemical screen to discover novel synergistic partners for EphA2-targeted therapeutics. Our screen identified the Wee1 kinase inhibitor, MK1775, as a synergistic partner to EphA2, and this finding was confirmed using both in vitro and in vivo experiments. We hypothesized that Wee1 inhibition would sensitize cells to EphA2-targeted therapy. Combination treatment decreased cell viability, induced apoptosis, and reduced clonogenic potential in endometrial cancer cell lines. In vivo Hec1A and Ishikawa-Luc orthotopic mouse models of endometrial cancer showed greater anti-tumor responses to combination treatment than to either monotherapy. RNASeq analysis highlighted reduced cell proliferation and defective DNA damage response pathways as potential mediators of the combination's effects. In conclusion, our preclinical findings indicate that Wee1 inhibition can enhance the response to EphA2-targeted therapeutics in endometrial cancer; this strategy thus warrants further development.

Biobehavioral factors predict an exosome biomarker of ovarian carcinoma disease progression.

BACKGROUND: Biobehavioral factors such as social isolation and depression have been associated with disease progression in ovarian and other cancers. Here, the authors developed a noninvasive, exosomal RNA profile for predicting ovarian cancer disease progression and subsequently tested whether it increased in association with biobehavioral risk factors. METHODS: Exosomes were isolated from plasma samples from 100 women taken before primary surgical resection or neoadjuvant (NACT) treatment of ovarian carcinoma and 6 and 12 months later. Biobehavioral measures were sampled at all time points. Plasma from 76 patients was allocated to discovery analyses in which morning presurgical/NACT exosomal RNA profiles were analyzed by elastic net machine learning to identify a biomarker predicting rapid (≤6 months) versus more extended disease-free intervals following initial treatment. Samples from a second subgroup of 24 patients were analyzed by mixed-effects linear models to determine whether the progression-predictive biomarker varied longitudinally as a function of biobehavioral risk factors (social isolation and depressive symptoms). RESULTS: An RNA-based molecular signature was identified that discriminated between individuals who had disease progression in ≤6 months versus >6 months, independent of clinical variables (age, disease stage, and grade). In a second group of patients analyzed longitudinally, social isolation and depressive symptoms were associated with upregulated expression of the disease progression propensity biomarker, adjusting for covariates. CONCLUSION: These data identified a novel exosome-derived biomarker indicating propensity of ovarian cancer progression that is sensitive to biobehavioral variables. This derived biomarker may be potentially useful for risk assessment, intervention targeting, and treatment monitoring.

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.