Therapy of renal cell carcinoma (RCC) has been transformed in recent years by the efficacy of targeted agents that inhibit kinases involved in critical cellular signaling pathways and VEGF, a primary driver of tumor angiogenesis. However, patient response to these therapeutics is highly variable and currently cannot be predicted based on clinical or pathological data or available laboratory/genetic testing. The goal of this proposal is to develop predictors of therapeutic response for patients with the most common subtype of RCC, clear cell (ccRCC), based on novel tests. Our approach is based primarily on the hypothesis that the targeted agents used in ccRCC therapy - bevacizumab, sunitinib and sorafenib - inhibit tumor vessel activation and that the activation status and stability of tumor vessels are major determinants of response. We also hypothesize that the phenotype of ccRCC tumor vessels is linked to the molecular pathobiology of the tumor cells. In particular, as these drugs also can inhibit tumor cell signaling and modulate their behavior, ccRCC tumor cell signaling, HIF-1/HIF-2 (hypoxia-inducible factor) expression and VHL function are potential determinants of response. To examine parameters of vascular phenotype, tumor cell phenotype and VHL genotype as predictors of response to therapy, ccRCC specimens will undergo multiplex immunostaining for the appropriate biomarker antigens and be analyzed by a novel computer-assisted image analysis system that objectively quantifies analyte staining on a cellular (cytometric) basis as well as by traditional pixel-based analysis. These studies will be performed on tumors of ccRCC patients treated with single-agent bevacizumab, sunitinib or sorafenib in ongoing multi-institutional phase II (ECOG2804) and phase III (ECOG2805) clinical trials, using tumor blocks from a subset of 90, 170 and 170 appropriate ccRCC patients for therapy with the respective drugs.
The specific aims of this proposal are (Aim 1) to analyze the vascular and endothelial cell activation phenotype and vessel pericyte coverage in ccRCC tumors;
(Aim 2) to analyze tumor cell signaling, HIF phenotype and VHL genotype in ccRCC tumors;
and (Aim 3) to correlate parameters quantified in the prior aims for relationships to each other, to therapeutic outcome and to develop parsimonious predictive models of therapeutic response using biostatistical and bioinformatics approaches. The results of these studies should allow identification of the most appropriate drugs for treating individual patients with ccRCC and assist in the rational development of second-line and combination drug therapies. Beyond ccRCC, the targeted agents under study are used in the therapy of an ever expanding number of cancers, and the response predictors developed for ccRCC, where these agents are best studied because they are used as single-agents, may be useful for predicting response of these other cancers to combination therapy incorporating the targeted agents.
Novel targeted cancer therapy agents have shown success in the treatment of kidney cancer (renal cell carcinoma), a cancer that is increasing in incidence and newly diagnosed in over 50,000 Americans a year. Studies in this project will characterize the tumor blood vessel characteristics and genetic defect of renal cell carcinomas and correlate them with therapeutic response to identify factors that can predict whether they will respond to treatment. Discovering features of kidney cancer that predict therapeutic response can then be used to stratify patients to different therapies in the future and will provide lessons that are likely to be applicable to many other cancers being treated with the same novel drugs.
|Haas, Naomi B; Nathanson, Katherine L (2014) Hereditary kidney cancer syndromes. Adv Chronic Kidney Dis 21:81-90|
|Padmanabhan, Raghav K; Somasundar, Vinay H; Griffith, Sandra D et al. (2014) An active learning approach for rapid characterization of endothelial cells in human tumors. PLoS One 9:e90495|
|Couch, Fergus J; Nathanson, Katherine L; Offit, Kenneth (2014) Two decades after BRCA: setting paradigms in personalized cancer care and prevention. Science 343:1466-70|
|Isse, Kumiko; Lesniak, Andrew; Grama, Kedar et al. (2013) Preexisting epithelial diversity in normal human livers: a tissue-tethered cytometric analysis in portal/periportal epithelial cells. Hepatology 57:1632-43|
|Isse, K; Lesniak, A; Grama, K et al. (2012) Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis. Am J Transplant 12:27-37|
|Dondeti, Vijay R; Wubbenhorst, Bradley; Lal, Priti et al. (2012) Integrative genomic analyses of sporadic clear cell renal cell carcinoma define disease subtypes and potential new therapeutic targets. Cancer Res 72:112-21|
|Lassoued, Wiem; Murphy, Danielle; Tsai, Jeff et al. (2011) Effect of VEGF and VEGF Trap on vascular endothelial cell signaling in tumors. Cancer Biol Ther 10:1326-33|
|Al-Kofahi, Yousef; Lassoued, Wiem; Grama, Kedar et al. (2011) Cell-based quantification of molecular biomarkers in histopathology specimens. Histopathology 59:40-54|
|Isse, Kumiko; Grama, Kedar; Abbott, Isaac Morse et al. (2010) Adding value to liver (and allograft) biopsy evaluation using a combination of multiplex quantum dot immunostaining, high-resolution whole-slide digital imaging, and automated image analysis. Clin Liver Dis 14:669-85|