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 III, 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 & 5 others Jeffrey A Cadeddu, Vitaly Margulis, James B Brugarolas, Ralph J DeBerardinis, Ivan Pedrosa

Research output: Contribution to journalArticle

13 Citations (Scopus)

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).

Original languageEnglish (US)
JournalJCI insight
Volume2
Issue number15
DOIs
StatePublished - Aug 3 2017

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Renal Cell Carcinoma
Neoplasms
Fats
Lipids
Lipid Metabolism
Metabolomics
Nonesterified Fatty Acids
Disease Progression
Mass Spectrometry
Phospholipids
Triglycerides
Biomarkers
Cholesterol
Pathology
Kidney
Glucose

Keywords

  • Metabolism
  • Oncology

Cite this

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

In: JCI insight, Vol. 2, No. 15, 03.08.2017.

Research output: Contribution to journalArticle

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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).",
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author = "Yue Zhang and Durga Udayakumar and Ling Cai and Zeping Hu and Payal Kapur and Kho, {Eun Young} and Andrea Pav{\'i}a-Jim{\'e}nez and Michael Fulkerson and {Diaz De Leon III}, Alberto and Qing Yuan and Dimitrov, {Ivan E.} and Takeshi Yokoo and Jin Ye and Mitsche, {Matthew A} and Hyeonwoo Kim and McDonald, {Jeffrey G} and Yin Xi and Madhuranthakam, {Ananth J} and Dwivedi, {Durgesh K.} and Lenkinski, {Robert E} and Cadeddu, {Jeffrey A} and Vitaly Margulis and Brugarolas, {James B} and DeBerardinis, {Ralph J} and Ivan Pedrosa",
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T1 - Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI

AU - Zhang, Yue

AU - Udayakumar, Durga

AU - Cai, Ling

AU - Hu, Zeping

AU - Kapur, Payal

AU - Kho, Eun Young

AU - Pavía-Jiménez, Andrea

AU - Fulkerson, Michael

AU - Diaz De Leon III, Alberto

AU - Yuan, Qing

AU - Dimitrov, Ivan E.

AU - Yokoo, Takeshi

AU - Ye, Jin

AU - Mitsche, Matthew A

AU - Kim, Hyeonwoo

AU - McDonald, Jeffrey G

AU - Xi, Yin

AU - Madhuranthakam, Ananth J

AU - Dwivedi, Durgesh K.

AU - Lenkinski, Robert E

AU - Cadeddu, Jeffrey A

AU - Margulis, Vitaly

AU - Brugarolas, James B

AU - DeBerardinis, Ralph J

AU - Pedrosa, Ivan

PY - 2017/8/3

Y1 - 2017/8/3

N2 - 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).

AB - 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).

KW - Metabolism

KW - Oncology

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