SIK2 inhibition enhances PARP inhibitor activity synergistically in ovarian and triple-negative breast cancers

Poly(ADP-ribose) polymerase inhibitors (PARP inhibitors) have had an increasing role in the treatment of ovarian and breast cancers. PARP inhibitors are selectively active in cells with homologous recombination DNA repair deficiency caused by mutations in BRCA1/2 and other DNA repair pathway genes. Cancers with homologous recombination DNA repair proficiency respond poorly to PARP inhibitors. Cancers that initially respond to PARP inhibitors eventually develop drug resistance. We have identified salt-inducible kinase 2 (SIK2) inhibitors, ARN3236 and ARN3261, which decreased DNA double-strand break (DSB) repair functions and produced synthetic lethality with multiple PARP inhibitors in both homologous recombination DNA repair deficiency and proficiency cancer cells. SIK2 is required for centrosome splitting and PI3K activation and regulates cancer cell proliferation, metastasis, and sensitivity to chemotherapy. Here, we showed that SIK2 inhibitors sensitized ovarian and triple-negative breast cancer (TNBC) cells and xenografts to PARP inhibitors. SIK2 inhibitors decreased PARP enzyme activity and phosphorylation of class-IIa histone deacetylases (HDAC4/5/7). Furthermore, SIK2 inhibitors abolished class-IIa HDAC4/5/7–associated transcriptional activity of myocyte enhancer factor-2D (MEF2D), decreasing MEF2D binding to regulatory regions with high chromatin accessibility in FANCD2, EXO1, and XRCC4 genes, resulting in repression of their functions in the DNA DSB repair pathway. The combination of PARP inhibitors and SIK2 inhibitors provides a therapeutic strategy to enhance PARP inhibitor sensitivity for ovarian cancer and TNBC

Modulation of MicroRNA-194 and cell migration by HER2-targeting trastuzumab in breast cancer

Conceived and designed the experiments: XFL GAC RCB. Performed the experiments: XFL MIA WM RS MSN SZ. Analyzed the data: XFL SR. Contributed reagents/materials/analysis tools: YW GAC. Wrote the paper: XFL RCB.Trastuzumab, a humanized monoclonal antibody directed against the extracellular domain of the HER2 oncoprotein, can effectively target HER2-positive breast cancer through several mechanisms. Although the effects of trastuzumab on cancer cell proliferation, angiogenesis and apoptosis have been investigated in depth, the effect of trastuzumab on microRNA (miRNA) has not been extensively studied. We have performed miRNA microarray profiling before and after trastuzumab treatment in SKBr3 and BT474 human breast cancer cells that overexpress HER2. We found that trastuzumab treatment of SKBr3 cells significantly decreased five miRNAs and increased three others, whereas treatment of BT474 cells significantly decreased two miRNAs and increased nine. The only change in miRNA expression observed in both cell lines following trastuzumab treatment was upregulation of miRNA-194 (miR-194) that was further validated in vitro and in vivo. Forced expression of miR-194 in breast cancer cells that overexpress HER2 produced no effect on apoptosis, modest inhibition of proliferation, significant inhibition of cell migration/invasion in vitro and significant inhibition of xenograft growth in vivo. Conversely, knockdown of miR-194 promoted cell migration. Increased miR-194 expression markedly reduced levels of the cytoskeletal protein talin2 and specifically inhibited luciferase reporter activity of a talin2 wild-type 39-untranslated region, but not that of a mutant reporter, indicating that talin2 is a direct downstream target of miR-194. Trastuzumab treatment inhibited breast cancer cell migration and reduced talin2 expression in vitro and in vivo. Knockdown of talin2 inhibited cell migration/invasion. Knockdown of trastuzumab-induced miR-194 expression with a miR-194 inhibitor compromised trastuzumab-inhibited cell migration in HER2-overexpressing breast cancer cells. Consequently, trastuzumab treatment upregulates miR-194 expression and may exert its cell migration-inhibitory effect through miR-194-mediated downregulation of cytoskeleton protein talin2 in HER2-overexpressing human breast cancer cells.This work was supported by the Anne and Henry Zarrow Foundation, kind gifts from Stuart and Gaye Lynn Zarrow and from Mrs. Delores Wilkenfeld, the Laura and John Arnold Foundation, the RGK Foundation, and the MD Anderson NCI CCSG P30 CA16672. G.A.C. is supported as a Fellow at the University of Texas MD Anderson Research Trust, as a University of Texas System Regents Research Scholar and by the CLL Global Research Foundation

Amino Acid Deprivation-Induced Autophagy Requires Upregulation of DIRAS3 through Reduction of E2F1 and E2F4 Transcriptional Repression

Failure to cure ovarian cancer relates to the persistence of dormant, drug-resistant cancer cells following surgery and chemotherapy. “Second look” surgery can detect small, poorly vascularized nodules of persistent ovarian cancer in ~50% of patients, where >80% are undergoing autophagy and express DIRAS3. Autophagy is one mechanism by which dormant cancer cells survive in nutrient poor environments. DIRAS3 is a tumor suppressor gene downregulated in >60% of primary ovarian cancers by genetic, epigenetic, transcriptional and post-transcriptional mechanisms, that upon re-expression can induce autophagy and dormancy in a xenograft model of ovarian cancer. We examined the expression of DIRAS3 and autophagy in ovarian cancer cells following nutrient deprivation and the mechanism by which they are upregulated. We have found that DIRAS3 mediates autophagy induced by amino acid starvation, where nutrient sensing by mTOR plays a central role. Withdrawal of amino acids downregulates mTOR, decreases binding of E2F1/4 to the DIRAS3 promoter, upregulates DIRAS3 and induces autophagy. By contrast, acute amino acid deprivation did not affect epigenetic regulation of DIRAS3 or expression of miRNAs that regulate DIRAS3. Under nutrient poor conditions DIRAS3 can be transcriptionally upregulated, inducing autophagy that could sustain dormant ovarian cancer cells

A novel radiomics based on multi-parametric magnetic resonance imaging for predicting Ki-67 expression in rectal cancer: a multicenter study

Abstract Background To explore the value of multiparametric MRI markers for preoperative prediction of Ki-67 expression among patients with rectal cancer. Methods Data from 259 patients with postoperative pathological confirmation of rectal adenocarcinoma who had received enhanced MRI and Ki-67 detection was divided into 4 cohorts: training (139 cases), internal validation (in-valid, 60 cases), and external validation (ex-valid, 60 cases) cohorts. The patients were divided into low and high Ki-67 expression groups. In the training cohort, DWI, T2WI, and contrast enhancement T1WI (CE-T1) sequence radiomics features were extracted from MRI images. Radiomics marker scores and regression coefficient were then calculated for data fitting to construct a radscore model. Subsequently, clinical features with statistical significance were selected to construct a combined model for preoperative individualized prediction of rectal cancer Ki-67 expression. The models were internally and externally validated, and the AUC of each model was calculated. Calibration and decision curves were used to evaluate the clinical practicality of nomograms. Results Three models for predicting rectal cancer Ki-67 expression were constructed. The AUC and Delong test results revealed that the combined model had better prediction performance than other models in three chohrts. A decision curve analysis revealed that the nomogram based on the combined model had relatively good clinical performance, which can be an intuitive prediction tool for clinicians. Conclusion The multiparametric MRI radiomics model can provide a noninvasive and accurate auxiliary tool for preoperative evaluation of Ki-67 expression in patients with rectal cancer and can support clinical decision-making

Deep learning–based radiomic nomograms for predicting Ki67 expression in prostate cancer

Abstract Background To explore the value of a multiparametric magnetic resonance imaging (MRI)-based deep learning model for the preoperative prediction of Ki67 expression in prostate cancer (PCa). Materials The data of 229 patients with PCa from two centers were retrospectively analyzed and divided into training, internal validation, and external validation sets. Deep learning features were extracted and selected from each patient’s prostate multiparametric MRI (diffusion-weighted imaging, T2-weighted imaging, and contrast-enhanced T1-weighted imaging sequences) data to establish a deep radiomic signature and construct models for the preoperative prediction of Ki67 expression. Independent predictive risk factors were identified and incorporated into a clinical model, and the clinical and deep learning models were combined to obtain a joint model. The predictive performance of multiple deep-learning models was then evaluated. Results Seven prediction models were constructed: one clinical model, three deep learning models (the DLRS-Resnet, DLRS-Inception, and DLRS-Densenet models), and three joint models (the Nomogram-Resnet, Nomogram-Inception, and Nomogram-Densenet models). The areas under the curve (AUCs) of the clinical model in the testing, internal validation, and external validation sets were 0.794, 0.711, and 0.75, respectively. The AUCs of the deep models and joint models ranged from 0.939 to 0.993. The DeLong test revealed that the predictive performance of the deep learning models and the joint models was superior to that of the clinical model (p < 0.01). The predictive performance of the DLRS-Resnet model was inferior to that of the Nomogram-Resnet model (p < 0.01), whereas the predictive performance of the remaining deep learning models and joint models did not differ significantly. Conclusion The multiple easy-to-use deep learning–based models for predicting Ki67 expression in PCa developed in this study can help physicians obtain more detailed prognostic data before a patient undergoes surgery

Survival Predictors for Severe ARDS Patients Treated with Extracorporeal Membrane Oxygenation: A Retrospective Study in China.

Extracorporeal membrane oxygenation (ECMO) is increasingly being applied as life support for acute respiratory distress syndrome (ARDS) patients. However, the outcomes of this procedure have not yet been characterized in severe ARDS patients. The aim of this study was to evaluate the outcomes of severe ARDS patients supported with ECMO and to identify potential predictors of mortality in these patients. A total of 38 severe ARDS patients (aged 51.39±13.27 years, 32 males) who were treated with ECMO in the specialized medical intensive care unit of Guangzhou Institute of Respiratory Diseases from July 2009 to December 2014 were retrospectively reviewed. The clinical data of the patients on the day before ECMO initiation, on the first day of ECMO treatment and on the day of ECMO removal were collected and analyzed. All patients were treated with veno-venous ECMO after a median mechanical ventilation duration of 6.4±7.6 days. Among the 20 patients (52.6%) who were successfully weaned from ECMO, 16 patients (42.1%) survived to hospital discharge. Of the identified pre-ECMO factors, advanced age, a long duration of ventilation before ECMO, a higher Acute Physiology and Chronic Health Evaluation II (APACHE II) score, underlying lung disease, and pulmonary barotrauma prior to ECMO were associated with unsuccessful weaning from ECMO. Furthermore, multiple logistic regression analysis indicated that both barotrauma pre-ECMO and underlying lung disease were independent predictors of hospital mortality. In conclusion, for severe ARDS patients treated with ECMO, barotrauma prior to ECMO and underlying lung disease may be major predictors of ARDS prognosis based on multivariate analysis

A Novel Salt Inducible Kinase 2 Inhibitor, ARN-3261, Sensitizes Ovarian Cancer Cell Lines and Xenografts to Carboplatin

Salt-induced kinase 2 (SIK2) is a serine-threonine kinase that regulates centrosome splitting, activation of PI3 kinase and phosphorylation of class IIa HDACs, affecting gene expression. Previously, we found that inhibition of SIK2 enhanced sensitivity of ovarian cancer cells to paclitaxel. Carboplatin and paclitaxel constitute first-line therapy for most patients with ovarian carcinoma, producing a 70% clinical response rate, but curing &lt;20% of patients with advanced disease. We have asked whether inhibition of SIK2 with ARN-3261 enhances sensitivity to carboplatin in ovarian cancer cell lines and xenograft models. ARN-3261-induced DNA damage and apoptosis were measured with &gamma;-H2AX accumulation, comet assays, and annexin V. ARN-3261 inhibited growth of eight ovarian cancer cell lines at an IC50 of 0.8 to 3.5 &micro;M. ARN-3261 significantly enhanced sensitivity to carboplatin in seven of eight ovarian cancer cell lines and a carboplatin-resistant cell line tested. Furthermore, ARN-3261 in combination with carboplatin produced greater inhibition of tumor growth than carboplatin alone in SKOv3 and OVCAR8 ovarian cancer xenograft models. ARN-3261 enhanced DNA damage and apoptosis by downregulating expression of survivin. Thus, a SIK2 kinase inhibitor enhanced carboplatin-induced therapy in preclinical models of ovarian cancer and deserves further evaluation in clinical trials

Structure-Based Design of Stapled Peptides That Bind GABARAP and Inhibit Autophagy

The LC3/GABARAP family of proteins are involved in nearly every stage of autophagy. Inhibition of LC3/GABARAP proteins is a promising approach to blocking autophagy, which sensitizes advanced cancers to DNA-damaging chemotherapy. Here, we report the structure-based design of stapled peptides that inhibit GABARAP with nanomolar affinities. Small changes in staple structure produced stapled peptides with very different binding modes and functional differences in LC3/GABARAP paralog selectivity, ranging from highly GABARAP-specific to broad inhibition of both subfamilies. The stapled peptides exhibited considerable cytosolic penetration and resistance to biological degradation. They also reduced autophagic flux in cultured ovarian cancer cells and sensitized ovarian cancer cells to cisplatin. These small, potent stapled peptides represent promising autophagy-modulating compounds that can be developed as novel cancer therapeutics and novel mediators of targeted protein degradation