Rosser, Charles J.

Abstract Background: Improvements in the noninvasive clinical evaluation of patients at risk for bladder cancer would be of benefit both to individuals and to health care systems. We investigated the potential utility of a hybrid nomogram that combined key demographic features with the results of a multiplex urinary biomarker assay in hopes of identifying patients at risk of harboring bladder cancer. Methods: Logistic regression analysis was used to model the probability of bladder cancer burden in a cohort of 686 subjects (394 with bladder cancer) using key demographic features alone, biomarker data alone, and the combination of demographic features and key biomarker data. We examined discrimination, calibration, and decision curve analysis techniques to evaluate prediction model performance. Results: Area under the receiver operating characteristic curve (AUC) analyses revealed that demographic features alone predicted tumor burden with an accuracy of 0.806 [95% confidence interval (CI), 0.76–0.85], while biomarker data had an accuracy of 0.835 (95% CI, 0.80–0.87). The addition of molecular data into the nomogram improved the predictive performance to 0.891 (95% CI, 0.86–0.92). Decision curve analyses showed that the hybrid nomogram performed better than demographic or biomarker data alone. Conclusion: A nomogram construction strategy that combines key demographic features with biomarker data may facilitate the accurate, noninvasive evaluation of patients at risk of harboring bladder cancer. Further research is needed to evaluate the bladder cancer risk nomogram for potential clinical utility. Impact: The application of such a nomogram may better inform the decision to perform invasive diagnostic procedures. Cancer Epidemiol Biomarkers Prev; 25(9); 1361–6. ©2016 AACR.

Abstract Sphingosine kinase 1 (SphK1) phosphorylates pro-apoptotic sphingosine to form pro-survival sphingosine-1-phosphate (S1P), leading to cancer progression. In breast cancer, high levels of SphK1 mRNA are found in 80% of the patients, with average increase of 2-fold in breast tumors compared with normal tissue from the same patient. Recent studies suggest that SphK1 expression is associated with disease-free survival in ER-negative and HER2-positive breast tumors. In addition, inhibition of SphK1 in HER2-positive breast cancer cell line reduced S1P-induced HER2 and ERK1/2 activation. While these evidences suggest that SphK1 may play an important role in HER2-positive breast cancer, the exact role of SphK1 in breast tumorigenesis remains unclear. The aim of this project is to define the role of SphK1 in HER2-positive breast tumorigenesis and to investigate whether the pathway components are potential target for breast cancer prevention and therapies. Here, we report that SphK1 is required for HER2/neu-induced breast tumorigenesis and SphK1 regulates claudin-2 (CLDN2) to promote tumor development perhaps by mediating HER2. In MMTV-neu transgenic mouse model, genetic deletion of SphK1, which was accompanied by reduced S1P and increased C16-ceramide levels, significantly inhibited breast tumor development, with reduced incidence (SphK1-/-, 19%; SphK1+/-, 26%; and SphK1+/+, 57%; p < 0.05) and multiplicity (SphK1-/-, 0.27 ± 0.13; SphK1+/-, 0.32 ± 0.07; and SphK1+/+, 0.67 ± 0.14 tumors per animal; p < 0.05). Unexpectedly, SphK1 deletion did not affect tumor growth as results showed no differences in tumor volume. However, this is not surprising when considering the fact that the tumors were allowed to grow until tumor reached 20 mm in longer diameter, at which they were sacrificed regardless of age. Interestingly, whole genome expression analysis by Illumina MouseWG-6 v2.0 Expression BeadChip Array revealed significant reduction of CLDN2 expression in tumors from SphK1 deficient mice (p < 0.0001). In support to these findings, overexpression of SphK1 in MDA-MB-453 human breast cancer cells, which HER2 is amplified but lacks hormone receptors, lead to increase in CLDN2 expression (p < 0.05). Furthermore, overexpression of SphK1 in MDA-MB-453 cells also enhanced cell proliferation, colony formation, and migration/invasion, and drug resistance to cisplatin. The relevance of this finings in humans was confirmed by immunostaining of SphK1 and CLDN2 in HER2-positive breast cancer tumors and normal tissues (n = 93 and 35 subjects, respectively). The results showed that the expression of SphK1 was higher in tumors compared to adjacent normal tissue (p < 0.0001). Furthermore, higher SphK1 expression was observed in high grade tumors (vs low grade; p < 0.001) and ER-PR- tumors (vs ER+PR+; p < 0.0001). Interestingly, we observed similar staining pattern of CLDN2 proteins, where CLDN2 expression was high in tumors (p < 0.0001), particularly in high grade tumors (p < 0.01) and ER-PR- tumors (p < 0.0001). Moreover, we found a strong correlation between SphK1 and CLDN2 expressions in tumors but not in normal tissues, confirming the results obtained in animal study. Taken together, these findings suggest that SphK1 may play a pivotal role in HER2-positive breast carcinogenesis, and targeting SphK1 and/or CLDN2 may represent a novel approach for HER2-positive breast cancer chemoprevention and/or treatment. Citation Format: Yoshiko Shimizu, Hideki Furuya, Paulette M. Tamashiro, Steve Goodison, Owen Chan, Ian Pagano, Kayoko Iino, Rafael Peres, Kanani Hokutan, Lenora W.M. Loo, Brenda Hernandez, Aung Naing, Charles J. Rosser, Toshihiko Kawamori. Genetic deletion of sphingosine kinase 1 suppresses mouse breast tumor development in MMTV-neu transgenic model. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr B17.

Abstract Background: Because of the faltering sensitivity and/or specificity, urine-based assays currently have a limited role in the management of patients with bladder cancer. The aim of this study was to externally validate our previously reported protein biomarker panel from multiple sites in the United States and Europe. Methods: This multicenter external validation study included a total of 320 subjects (bladder cancer = 183). The 10 biomarkers (IL8, MMP9, MMP10, SERPINA1, VEGFA, ANG, CA9, APOE, SDC1, and SERPINE1) were measured using commercial ELISA assays in an external laboratory. The diagnostic performance of the biomarker panel was assessed using receiver operator curves (ROC) and descriptive statistical values. Results: Utilizing the combination of all 10 biomarkers, the area under the ROC for the diagnostic panel was noted to be 0.847 (95% confidence interval, 0.796–0.899), outperforming any single biomarker. The multiplex assay at optimal cutoff value achieved an overall sensitivity of 0.79, specificity of 0.79, positive prediction value of 0.73, and negative prediction value of 0.84 for bladder cancer classification. Sensitivity values of the diagnostic panel for high-grade bladder cancer, low-grade bladder cancer, muscle invasive bladder cancer, and non-muscle invasive bladder cancer were 0.81, 0.90, 0.95, and 0.77, respectively. Conclusions: Urinary levels of the biomarker panel enabled discrimination of patients with bladder cancer and controls, and the levels of biomarker subsets were associated with advancing tumor grade and stage. Impact: If proven to be reliable, urinary diagnostic biomarker assays can detect bladder cancer in a timely manner such that the patient can expect improvements in overall survival and quality of life. Cancer Epidemiol Biomarkers Prev; 23(9); 1804–12. ©2014 AACR.

Abstract Background: Up to 70% of patients with non–muscle-invasive bladder cancer (NMIBC) experience disease recurrence, making it one of the most prevalent cancers in the United States. The purpose of this study was to test the performance of a multiplex urinary biomarker assay for the monitoring of voided urine for recurrent bladder cancer. Methods: This retrospective, multicenter study included a total of 125 subjects with a history of bladder cancer. Voided urine specimens were collected before procedure from these subjects (53 with confirmed tumor recurrence and 72 with confirmed non-tumor recurrence) for analysis. A prediction rule generated from the performance characteristics of 10 single biomarkers (IL8, MMP9, MMP10, SERPINA1, VEGFA, ANG, CA9, APOE, SERPINE1, and SDC1) was measured using ELISA. The diagnostic performance of the biomarker panel was assessed using receiver operator curves (ROC) and descriptive statistical values (e.g., sensitivity and specificity). Results: The combination of all 10 biomarkers outperformed any single biomarker with a calculated AUROC for the diagnostic panel of 0.904 [95% confidence interval (CI), 0.853–0.956]. The multiplex assay achieved an overall sensitivity of 79% and specificity of 88% for recurrent bladder cancer and significantly outperformed the Urovysion cytogenetic assay (sensitivity 42%, specificity 94%) and voided urinary cytology (sensitivity 33%, specificity 90%). Conclusions: A diagnostic panel of 10 urinary biomarkers that accurately detects primary bladder cancer also performs well for the detection of recurrent bladder cancer. Impact: The identification of a reliable urine-based surveillance and detection assay would be of benefit to both patients and the healthcare system. Cancer Epidemiol Biomarkers Prev; 23(7); 1340–5. ©2014 AACR.

Abstract The canonical function of plasminogen activator inhibitor-1 (PAI-1/SERPINE1) is as an inhibitor of urokinase-type plasminogen activator for blood clot maintenance, but it is now also considered a pleiotropic factor that can exert diverse cellular and tumorigenic effects. However, the mechanism controlling its pleiotropic effects is far from being understood. To elucidate the tumorigenic role of PAI-1, we tested the effects of PAI-1 after manipulation of its expression or through the use of a small-molecule inhibitor, tiplaxtinin. Downregulation of PAI-1 significantly reduced cellular proliferation through an inability to progress from the G0–G1 phase of the cell cycle. Accordingly, overexpression of PAI-1 augmented proliferation by encouraging S-phase entry. Biochemically, cell-cycle arrest was associated with the depletion of the G1-phase transition complexes, cyclin D3/cdk4/6 and cyclin E/cdk2, in parallel with the upregulation of the cell-cycle inhibitors p53, p21Cip1/Waf1, and p27Kip1. PAI-1 depletion significantly decreased the tumor size of urothelial T24 and UM-UC-14 xenografts, and overexpression of PAI-1 substantially increased the tumor size of HeLa xenografts. Finally, immunohistochemical analysis of human bladder and cervical tumor tissue microarrays revealed increased expression of PAI-1 in cancerous tissue, specifically in aggressive tumors, supporting the relevance of this molecule in human tumor biology. Implications: Targeting PAI-1 has beneficial antitumoral effects and should be further investigated clinically. Mol Cancer Res; 12(3); 322–34. ©2014 AACR.

Abstract Bladder cancer is the fifth most commonly diagnosed malignancy in the United States and one of the most prevalent worldwide. It harbors a probability of recurrence of >50%; thus, rigorous, long-term surveillance of patients is advocated. Flexible cystoscopy coupled with voided urine cytology is the primary diagnostic approach, but cystoscopy is an uncomfortable, invasive procedure and the sensitivity of voided urine cytology is poor in all but high-grade tumors. Thus, improvements in noninvasive urinalysis assessment strategies would benefit patients. We applied gene expression microarray analysis to exfoliated urothelia recovered from bladder washes obtained prospectively from 46 patients with subsequently confirmed presence or absence of bladder cancer. Data from microarrays containing 56,000 targets was subjected to a panel of statistical analyses to identify bladder cancer-associated gene signatures. Hierarchical clustering and supervised learning algorithms were used to classify samples on the basis of tumor burden. A differentially expressed geneset of 319 gene probes was associated with the presence of bladder cancer (P < 0.01), and visualization of protein interaction networks revealed vascular endothelial growth factor and angiotensinogen as pivotal factors in tumor cells. Supervised machine learning and a cross-validation approach were used to build a 14-gene molecular classifier that was able to classify patients with and without bladder cancer with an overall accuracy of 76%. Our results show that it is possible to achieve the detection of bladder cancer using molecular signatures present in exfoliated tumor urothelia. Further investigation and validation of the cancer-associated profiles may reveal important biomarkers for the noninvasive detection and surveillance of bladder cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(2):444–53)