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 LenkinskiJeffrey A. Cadeddu, Vitaly Margulis, James Brugarolas, Ralph J. DeBerardinis, Ivan Pedrosa

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


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).

Original languageEnglish (US)
JournalJCI Insight
Issue number15
StatePublished - Aug 3 2017


  • Metabolism
  • Oncology

ASJC Scopus subject areas

  • Medicine(all)


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