Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI
Yue Zhang, Durga Udayakumar, Ling Cai, Zeping Hu, Payal Kapur, Eun-Young Kho, Andrea Pavía-Jiménez, Michael Fulkerson, Alberto Diaz de Leon, Qing Yuan, Ivan E. Dimitrov, Takeshi Yokoo, Jin Ye, Matthew A. Mitsche, Hyeonwoo Kim, Jeffrey G. McDonald, Yin Xi, Ananth J. Madhuranthakam, Durgesh K. Dwivedi, Robert E. Lenkinski, Jeffrey A. Cadeddu, Vitaly Margulis, James Brugarolas, Ralph J. DeBerardinis, Ivan Pedrosa
Yue Zhang, Durga Udayakumar, Ling Cai, Zeping Hu, Payal Kapur, Eun-Young Kho, Andrea Pavía-Jiménez, Michael Fulkerson, Alberto Diaz de Leon, Qing Yuan, Ivan E. Dimitrov, Takeshi Yokoo, Jin Ye, Matthew A. Mitsche, Hyeonwoo Kim, Jeffrey G. McDonald, Yin Xi, Ananth J. Madhuranthakam, Durgesh K. Dwivedi, Robert E. Lenkinski, Jeffrey A. Cadeddu, Vitaly Margulis, James Brugarolas, Ralph J. DeBerardinis, Ivan Pedrosa
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Clinical Research and Public Health Metabolism Oncology

Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI

Abstract

BACKGROUND. Dysregulated lipid and glucose metabolism in clear cell renal cell carcinoma (ccRCC) has been implicated in disease progression, and whole tumor tissue–based assessment of these changes is challenged by the tumor heterogeneity. We studied a noninvasive quantitative MRI method that predicts metabolic alterations in the whole tumor. METHODS. We applied Dixon-based MRI for in vivo quantification of lipid accumulation (fat fraction [FF]) in targeted regions of interest of 45 primary ccRCCs and correlated these MRI measures to mass spectrometry–based lipidomics and metabolomics of anatomically colocalized tissue samples isolated from the same tumor after surgery. RESULTS. In vivo tumor FF showed statistically significant (P < 0.0001) positive correlation with histologic fat content (Spearman correlation coefficient, ρ = 0.79), spectrometric triglycerides (ρ = 0.56) and cholesterol (ρ = 0.47); it showed negative correlation with free fatty acids (ρ = –0.44) and phospholipids (ρ = –0.65). We observed both inter- and intratumoral heterogeneity in lipid accumulation within the same tumor grade, whereas most aggressive tumors (International Society of Urological Pathology [ISUP] grade 4) exhibited reduced lipid accumulation. Cellular metabolites in tumors were altered compared with adjacent renal parenchyma. CONCLUSION. Our results support the use of noninvasive quantitative Dixon-based MRI as a biomarker of reprogrammed lipid metabolism in ccRCC, which may serve as a predictor of tumor aggressiveness before surgical intervention. FUNDING. NIH R01CA154475 (YZ, MF, PK, IP), NIH P50CA196516 (IP, JB, RJD, JAC, PK), Welch Foundation I-1832 (JY), and NIH P01HL020948 (JGM).

Authors

Yue Zhang, Durga Udayakumar, Ling Cai, Zeping Hu, Payal Kapur, Eun-Young Kho, Andrea Pavía-Jiménez, Michael Fulkerson, Alberto Diaz de Leon, Qing Yuan, Ivan E. Dimitrov, Takeshi Yokoo, Jin Ye, Matthew A. Mitsche, Hyeonwoo Kim, Jeffrey G. McDonald, Yin Xi, Ananth J. Madhuranthakam, Durgesh K. Dwivedi, Robert E. Lenkinski, Jeffrey A. Cadeddu, Vitaly Margulis, James Brugarolas, Ralph J. DeBerardinis, Ivan Pedrosa

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Figure 2

Clear cell renal cell carcinoma (ccRCC) tumors exhibit heterogeneous lipid accumulation, independent of tumor grade.

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Clear cell renal cell carcinoma (ccRCC) tumors exhibit heterogeneous lip...
(A) Representative T2-weighted MRI images (left) and quantitative fat fraction (FF) maps (middle) of 2 tumors (black and white circular contours on both sets of images, respectively) indicating location of targeted region of interest (tROI, orange circle), and corresponding ex vivo oil red O (ORO) staining for fat content of targeted tumor samples as described in Methods (top panel: Tumor 1, ISUP grade 2; bottom panel: Tumor 2, ISUP grade 3). Color bars in FF maps indicate the percent of fat signal in tumor from 0%–60%. The scale bar values in the ORO staining indicate 100 μm. (B) Spearman correlation analysis between in vivo mean tumor FF and percentage of cells staining with ORO in 27 targeted tumor samples (ρ = 0.79, P < 0.0001). Green circle, Tumor 1 in A (FF = 2%, ORO percentage = 5%); purple circle, Tumor 2 in A (FF = 14%, ORO percentage = 90%). Same-colored data points represent tissue samples obtained at different locations within the same tumor. (C) Distribution of FF across tumor grades from 45 ccRCCs. The x-axis is sectioned in 3 parts representing International Society of Urological Pathology (ISUP) grade, with each point representing 1 individual tumor. The y-axis represents the mean percentage of FF in the whole tumor as measured by Dixon MRI. Vertical whiskers represent the mean ± SD within the individual tumor, indicating substantial intratumoral FF heterogeneity. ccRCCs exhibit heterogeneous intratumoral lipid accumulation among different tumor grades and within each tumor grade. Grade-4 tumors exhibited lower fat content than grade-3 tumors (P = 0.0163), although not different than grade-2 tumors (P = 0.33).