Addressing Metabolic Heterogeneity in Clear Cell Renal Cell Carcinoma with Quantitative Dixon MRI

Overview

Journal JCI Insight

Specialties Biomedical Engineering
General Medicine

Date 2017 Aug 4

PMID 28768909

Citations 22

Authors

Yue Zhang

Durga Udayakumar

Ling Cai

Zeping Hu

Payal Kapur

Eun-Young Kho

Andrea Pavia-Jimenez

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

Affiliations

Soon will be listed here.

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).

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