Citations

Abstract Background: Aurora-A (AURKA) belongs to the family of serine-threonine kinases that are crucial for cell cycle control. In particular, AURKA controls centrosome function, mitotic spindle formation, and proper chromosome segregation. In contrast to the well-defined function of AURKA in normal cells, the role of AURKA in malignant transformation and cancer progression is still under investigation. Here, we report that AURKA directly interacts with MEK1/2 kinase and induces chemotaxis of breast cancer cells. Results: We demonstrated that overexpression of AURKA in luminal ER+ MCF-7 cells (MCF-7AURKA) resulted in over 10-fold increase in the number of cells displaying chemotactic response upon stimulation with growth factors when compared to parental MCF-7 cells. Both AURKA inhibitor MLN8237 and MEK1/2 inhibitor PD0325901 reduced migratory properties of MCF-7AURKA cells. In contrast, treatment with the pan RAF inhibitor TAK-632 did not affect chemotactic response of MCF-7AURKA cells. We demonstrated colocalization of AURKA and MEK1/2 immunofluorescence signals in MCF-7AURKA and triple-negative BT549 cells. In situ proximity ligation assay (PLA) revealed the presence of AURKA-MEK1/2 complexes in MCF-7AURKA and BT549 cells, and the notion that AURKA and MEK1/2 formed cellular complexes was confirmed with co-immunoprecipitation experiments. In vitro kinase assays with recombinant AURKA and MEK1 proteins showed that AURKA kinase could directly phosphorylate MEK1. Incubation of MCF-7AURKA and BT549 cells with the AURKA-specific inhibitors MLN8237 or MK8745 resulted in over a 2-fold increase in the level of pERK1/2 compared to the untreated controls. Treatment with the pan RAF inhibitor TAK-632 did not diminish MLN8237-induced pERK1/2, whereas treatment with the MEK1/2 specific inhibitor PD0325901 completely abrogated MLN8237-induced activation of ERK1/2. Conclusions: Our data present a novel AURKA-MEK1/2 interaction that contributes to the increased chemotaxis of breast cancer cells. The results suggest that AURKA negatively regulates MEK1 through a novel, direct phosphorylation event, possibly leading to constitutive activation of MEK2 and increased chemotaxis. The combined treatment of AURKA and MEK1/2 inhibitors represents a new therapeutic approach to decrease metastatic potential of breast cancer cells and delay tumor progression. The in-depth analysis of the AURKA-MEK1/2 complexes as well as in vivo studies testing the efficacy of combining AURKA and MEK1/2 inhibitors on patient-derived xenografts are currently in progress. Citation Format: Malgorzata Gil, Archana Chidambaram, Thaer Khoury, Kazuaki Takabe, Igor Puzanov, Irwin H. Gelman, Antonino B. D’Assoro, Evanthia Galanis, Mateusz Opyrchal. AURKA interaction with MEK1/2 complex and its role in promoting breast cancer cell metastasis [abstract]. In: Proceedings of the AACR Special Conference: Advances in Breast Cancer Research; 2017 Oct 7-10; Hollywood, CA. Philadelphia (PA): AACR; Mol Cancer Res 2018;16(8_Suppl):Abstract nr A60.

AbstractBackground: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP).Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan–Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes.Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR.Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients.Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP. Cancer Epidemiol Biomarkers Prev; 27(11); 1376–83. ©2018 AACR.

Abstract Purpose: In phase I testing, alisertib tablets with irinotecan and temozolomide showed significant antitumor activity in patients with neuroblastoma. This study sought to confirm activity of this regimen; evaluate an alisertib oral solution; and evaluate biomarkers of clinical outcomes. Patients and Methods: We conducted a two-stage phase II trial of alisertib tablets (60 mg/m2/dose × 7 days), irinotecan (50 mg/m2/dose i.v. × 5 days), and temozolomide (100 mg/m2/dose orally × 5 days) in patients with relapsed or refractory neuroblastoma. The primary endpoint was best objective response. A separate cohort was treated with alisertib at 45 mg/m2 using oral solution instead of tablets. Exploratory analyses sought to identify predictors of toxicity, response, and progression-free survival (PFS) using pooled data from phase I, phase II, and oral solution cohorts. Results: Twenty and 12 eligible patients were treated in the phase II and oral solution cohorts, respectively. Hematologic toxicities were the most common adverse events. In phase II, partial responses were observed in 19 evaluable patients (21%). The estimated PFS at 1 year was 34%. In the oral solution cohort, 3 patients (25%) had first cycle dose-limiting toxicity (DLT). Alisertib oral solution at 45 mg/m2 had significantly higher median Cmax and exposure compared with tablets at 60 mg/m2. Higher alisertib trough concentration was associated with first cycle DLT, whereas MYCN amplification was associated with inferior PFS. Conclusions: This combination shows antitumor activity, particularly in patients with MYCN nonamplified tumors. Data on an alisertib oral solution expand the population able to be treated with this agent.

SummaryCD38 is expressed on Waldenström macroglobulinaemia (WM) cells, but its role as a therapeutic target remains undefined. With recent approval of the anti‐CD38 monoclonal antibody, daratumumab (Dara), we hypothesized that blocking CD38 would be lethal to WM cells.In vitroDara treatment of WM cells (including ibrutinib‐resistant lines) elicited antibody‐dependent cellular cytotoxicity (ADCC), complement‐dependent cytotoxicity (CDC), antibody‐dependent cell phagocytosis (ADCP) and direct apoptosis.In vivo, Dara treatment was well tolerated and delayed tumour growth in RPCI‐WM1‐xenografted mice. CD38 is reported to augment B‐cell receptor (BCR) signalling; we noted that Dara significantly attenuated phosphorylated SYK, LYN, BTK, PLCγ2, ERK1/2, AKT, mTOR, and S6 levels, and this effect was augmented by cotreatment with ibrutinib. Indeed, WM cells, including ibrutinib‐resistant WM cell lines treated with the ibrutinib + Dara combination, showed significantly more cell death through ADCC, CDC, ADCP and apoptosis relative to single‐agent Dara or ibrutinib. In summary, we are the first to report thein vitroandin vivoanti‐WM activity of Dara. Furthermore, we show a close connection between BCR and CD38 signalling, which can be co‐targeted with ibrutinib + Dara to induce marked WM cell death, irrespective of acquired resistance to ibrutinib.

AbstractWe aimed to validate the prognostic association of p16 expression in ovarian high‐grade serous carcinomas (HGSC) and to explore it in other ovarian carcinoma histotypes. p16 protein expression was assessed by clinical‐grade immunohistochemistry in 6525 ovarian carcinomas including 4334 HGSC using tissue microarrays from 24 studies participating in the Ovarian Tumor Tissue Analysis consortium. p16 expression patterns were interpreted as abnormal (either overexpression referred to as block expression or absence) or normal (heterogeneous). CDKN2A (which encodes p16) mRNA expression was also analyzed in a subset (n = 2280) mostly representing HGSC (n = 2010). Association of p16 expression with overall survival (OS) was determined within histotypes as was CDKN2A expression for HGSC only. p16 block expression was most frequent in HGSC (56%) but neither protein nor mRNA expression was associated with OS. However, relative to heterogeneous expression, block expression was associated with shorter OS in endometriosis‐associated carcinomas, clear cell [hazard ratio (HR): 2.02, 95% confidence (CI) 1.47–2.77, p < 0.001] and endometrioid (HR: 1.88, 95% CI 1.30–2.75, p = 0.004), while absence was associated with shorter OS in low‐grade serous carcinomas (HR: 2.95, 95% CI 1.61–5.38, p = 0.001). Absence was most frequent in mucinous carcinoma (50%), and was not associated with OS in this histotype. The prognostic value of p16 expression is histotype‐specific and pattern dependent. We provide definitive evidence against an association of p16 expression with survival in ovarian HGSC as previously suggested. Block expression of p16 in clear cell and endometrioid carcinoma should be further validated as a prognostic marker, and absence in low‐grade serous carcinoma justifies CDK4 inhibition.

Abstract Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P &lt; 2.2 × 10−6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10−7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P &lt; 1.47 × 10−3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419–30. ©2018 AACR.

Purpose Molecular characterization of prostate cancer, including The Cancer Genome Atlas, has revealed distinct subtypes with underlying genomic alterations. One of these core subtypes, SPOP (speckle-type POZ protein) mutant prostate cancer, has previously only been identifiable via DNA sequencing, which has made the impact on prognosis and routinely used risk stratification parameters unclear. Methods We have developed a novel gene expression signature, classifier (Subclass Predictor Based on Transcriptional Data), and decision tree to predict the SPOP mutant subclass from RNA gene expression data and classify common prostate cancer molecular subtypes. We then validated and further interrogated the association of prostate cancer molecular subtypes with pathologic and clinical outcomes in retrospective and prospective cohorts of 8,158 patients. Results The subclass predictor based on transcriptional data model showed high sensitivity and specificity in multiple cohorts across both RNA sequencing and microarray gene expression platforms. We predicted approximately 8% to 9% of cases to be SPOP mutant from both retrospective and prospective cohorts. We found that the SPOP mutant subclass was associated with lower frequency of positive margins, extraprostatic extension, and seminal vesicle invasion at prostatectomy; however, SPOP mutant cancers were associated with higher pretreatment serum prostate-specific antigen (PSA). The association between SPOP mutant status and higher PSA level was validated in three independent cohorts. Despite high pretreatment PSA, the SPOP mutant subtype was associated with a favorable prognosis with improved metastasis-free survival, particularly in patients with high-risk preoperative PSA levels. Conclusion Using a novel gene expression model and a decision tree algorithm to define prostate cancer molecular subclasses, we found that the SPOP mutant subclass is associated with higher preoperative PSA, less adverse pathologic features, and favorable prognosis. These findings suggest a paradigm in which the interpretation of common risk stratification parameters, particularly PSA, may be influenced by the underlying molecular subtype of prostate cancer.