Abstract
663 Background: Intratumoral heterogeneity (ITH) relates to aggressiveness in clear cell renal cell carcinoma (ccRCC), the most common and aggressive subtype of kidney cancer. Percutaneous biopsies have high diagnostic accuracy. However, ITH lowers their reliability in larger, heterogeneous tumors. Haralick texture features extracted from a gray level co-occurrence matrix (GLCM) is a robust method to assess intrinsic tumor imaging characteristics. Some of these features, including entropy as a measure of ITH, have recently been used in differentiating malignant from benign tumors in various organs. We aim to understand how tumor entropy extracted from magnetic resonance (MR) imaging correlate with tumor grade (aggressiveness) and gene expression heterogeneity in ccRCC. Methods: This IRB-approved, prospective study included T2-weighted (T2W) and arterial spin labeled (ASL) MR images of 62 patients with ccRCC. The GLCM was constructed for regions-of interest (ROI) within the tumor and 13 Haralick texture features were estimated. Correlations between texture features and tumor grade were evaluated by logistic regression and quantified by the area under the receiving operating characteristic (ROC) curve (AUC). RNA sequencing of 182 tumor samples in 49 resected tumors was performed. Entropy was correlated with standard deviation (SD) of normalized gene expression levels in multiple samples from the same tumor. Spearman correlation (rho) was computed for each gene. False discovery rate q values < 0.05 were considered statistically significant. Results: Entropy was higher in high-grade than low-grade tumors (11.28 ± 0.52 vs. 10.95 ± 0.65) on T2W (q = 0.028) and ASL (10.45 ± 1.15 vs. 9.65 ± 1.29) (q = 0.013). Entropy had an AUC of 0.70 (T2) for high-grade prediction and was weakly correlated with tumor size (R2 = 0.2). Higher T2 and ASL entropy correlated with higher SD of gene expression. Gene ontology analysis of top correlated genes revealed strong enrichment of genes in metabolic processes. Conclusions: Higher MRI entropy predicts high tumor grade and correlates with increased heterogeneity in gene expression of metabolic processes.
Published Version
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