Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

Abstract

◥Purpose: Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell carcinoma (ccRCC) and is a confounding factor for therapy selection. Most approaches to evaluate ITH are limited by two-dimensional ex vivo tissue analyses. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can noninvasively assess the spatial landscape of entire tumors in their natural milieu. To assess the potential of DCE-MRI, we developed a vertically integrated radiogenomics colocalization approach for multi-region tissue acquisition and analyses. We investigated the potential of spatial imaging features to predict molecular subtypes using histopathologic and transcriptome correlatives.Experimental Design: We report the results of a prospective study of 49 patients with ccRCC who underwent DCE-MRI prior to nephrectomy. Surgical specimens were sectioned to match the MRI acquisition plane. RNA sequencing data from multi-region tumor sampling (80 samples) were correlated with percent enhancement on DCE-MRI in spatially colocalized regions of the tumor. Independently, we evaluated clinical applicability of our findings in 19 patients with metastatic RCC (39 metastases) treated with first-line antiangiogenic drugs or checkpoint inhibitors.Results: DCE-MRI identified tumor features associated with angiogenesis and inflammation, which differed within and across tumors, and likely contribute to the efficacy of antiangiogenic drugs and immunotherapies. Our vertically integrated analyses show that angiogenesis and inflammation frequently coexist and spatially anti-correlate in the same tumor. Furthermore, MRI contrast enhancement identifies phenotypes with better response to antiangiogenic therapy among patients with metastatic RCC.Conclusions: These findings have important implications for decision models based on biopsy samples and highlight the potential of more comprehensive imaging-based approaches.

K-means clustering of hyperpolarised13C-MRI identifies intratumoural perfusion/metabolism mismatch in renal cell carcinoma as best predictor of highest grade

“…Similarly, Xi et al reported the larger area of high Gd-enhanced k-means cluster within a tumour to be most predictive of higher grade across a cohort of 18 patients with T1b ccRCC 48 ; however, these results relied on a single postsurgical grade for the whole tumour rather than examining grade variation across the entire tumour. Udayakumar et al correlated the intratumoral variation in early nephrogenic enhancement with angiogenic and immune transcriptomic signatures of biopsies the same regions 49 and Yao et al reported two types of microvessels which are differentially expressed between low and high grade ccRCCs, indicating the complexity of ccRCC perfusion 50 . These results indicate that tumour perfusion is an important determinant of aggressiveness but used alone is insufficient to fully and accurately characterise the tumour grade non-invasively.…”

Transcriptome mapping of renal clear cell carcinoma revealed by machine learning algorithm based on enhanced computed tomography images

“…In recent years, many studies have found that inflammatory cells and factors play an important role in the development, transformation and metastasis of tumors, including inflammatory cells, chemokines, their receptors and downstream signaling pathways 31–34 . ccRCC is a typical immunogenic tumor with abundant immune cell infiltration 35 .…”

“…[26][27][28][29][30] In recent years, many studies have found that inflammatory cells and factors play an important role in the development, transformation and metastasis of tumors, including inflammatory cells, chemokines, their receptors and downstream signaling pathways. [31][32][33][34] ccRCC is a typical immunogenic tumor with abundant immune cell infiltration. 35 Immunogenicity, the ability to induce an adaptive immune response, is determined by tumor antigens, extent of immune cell infiltration and type and number of immunomodulatory molecules emerging in the TME.…”

The SIRT7-mediated deacetylation of CHD1L amplifies HIF-2α-dependent signal that drives renal cell carcinoma progression and sunitinib resistance

“…Effective therapeutic strategies suppressing RCC progression are still limited. The intratumor cellular heterogeneity or distinctive molecular characteristics dictates the main challenges [ 30 , 31 ]. Hypoxia signaling is a well-investigated contributor to RCC that drives tumor growth or metastasis [ 32 , 33 ].…”