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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

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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 3

Lipidomic profiling of clear cell renal cell carcinoma (ccRCC) tumors showed differential levels in the uninvolved renal parenchyma (URP) and ccRCC tissue samples and correlated with fat fraction measures.

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Lipidomic profiling of clear cell renal cell carcinoma (ccRCC) tumors sh...
(A) The data represent the normalized intensity peaks of selected lipid species, with the horizontal bars and whiskers indicating the means ± SEM in ccRCC and URP samples (n = 14 patients). The intensity of each peak was normalized to the total lipid signal and summed to give the intensity of each class as percentage of all identified lipids. The statistical significance of the differences between measurements as indicated in the figure were assessed using an unpaired Mann-Whitney U test. (B) Correlation of fat fraction (FF) assessment using Dixon-based MRI method with lipidomic analysis of 33 targeted tumor samples (n = 14 patients) from the same tumor location. Levels of lipid species were analyzed in fresh targeted tumor samples by mass spectrometry, as indicated in Methods. The Spearman correlation was applied to evaluate correlation between fat fraction and levels of cholesterol (ρ = 0.47, P = 0.006), cholesterol ester (ρ = 0.11, P = 0.5399), triglycerides (ρ =0.56, P < 0.001), free fatty acids (ρ = –0.44, P = 0.01), total phospholipids (ρ = –0.65, P < 0.001), and phosphatidylethanolamine (ρ = –0.65, P < 0.001).

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