The routine use of cross-sectional imaging has resulted in a dramatic increase in the age-adjusted incidence of renal cell carcinoma (RCC) over the last decades. However, this has not translated into a decrease in cancer specific deaths, which suggests over treatment of potentially indolent renal tumors. Thus, active surveillance (AS) of RCC is now accepted as a management option for renal tumors, particularly in patients with comorbidities. Although AS in larger tumors has been reported to be safe (i.e. very low risk of metastasis), the natural history of these tumors remains unknown and percutaneous biopsies may be limited in assessing tumor grade due to intrinsic heterogeneity. Tumor angiogenesis and lipogenesis have been correlated with prognosis and metastatic potential in clear cell RCC (ccRCC), the most common and aggressive type of RCC. Inactivation of the VHL gene, HIF upregulation, and VEGF over-expression form the molecular basis of the enhanced angiogenesis associated with ccRCC. More recently, progress has been made in recognizing the distinct role of HIF-1 and HIF-2 transcription factors in tumor progression and inhibition of HIF-2, the main driver of angiogenesis, is now been tested in humans. Similarly, upregulation of lipogenic enzymes has been recognized as an aggressive metabolic phenotype in ccRCC. Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) method for measuring blood flow by manipulating the signal from inflowing arterial blood. ASL blood flow correlates tightly to vascularity in ccRCC. Dixon-based techniques have been extensively validated for quantification of hepatic lipids. Diffusion weighted imaging (DWI) provides an indirect non-invasive estimate of tumor cellularity. We seek to identify cellularity, vascular, and lipid MRI measures in ccRCC in vivo that correlate to spatially-co-localized molecular alterations promoting angiogenesis and lipogenesis and predict aggressive behavior. The spatial co-localization of various tissue-based analyses with in vivo alterations in tumor perfusion and lipogenesis may help develop more robust imaging biomarkers to predict the biologic behavior of ccRCC. If successful, these imaging biomarkers will be immediately applicable to clinical practice and will help selecting patients for active surveillance thus decreasing the number of unnecessary surgeries.
The aim of the proposed research is to investigate the correlation between in vivo magnetic resonance imaging (MRI) measures of cellularity, blood flow and fat accumulation with the recently discovered molecular alterations in the angiogenic and lipogenic pathways that are associated to aggressive behavior in clear cell renal cell carcinoma (RCC). Quantitative measures of cellularity, blood flow and fat fraction will be obtained with diffusion weighted imaging (DWI), arterial spin labeling (ASL) and Dixon-based MRI techniques, respectively.
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