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Circulating succinate-modifying metabolites accurately classify and reflect the status of fumarate hydratase–deficient renal cell carcinoma
Liang Zheng, … , Jin Zhang, Eyal Gottlieb
Liang Zheng, … , Jin Zhang, Eyal Gottlieb
Published April 13, 2023
Citation Information: J Clin Invest. 2023;133(11):e165028. https://doi.org/10.1172/JCI165028.
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Research Article Metabolism Oncology Article has an altmetric score of 4

Circulating succinate-modifying metabolites accurately classify and reflect the status of fumarate hydratase–deficient renal cell carcinoma

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Abstract

Germline or somatic loss-of-function mutations of fumarate hydratase (FH) predispose patients to an aggressive form of renal cell carcinoma (RCC). Since other than tumor resection there is no effective therapy for metastatic FH-deficient RCC, an accurate method for early diagnosis is needed. Although MRI or CT scans are offered, they cannot differentiate FH-deficient tumors from other RCCs. Therefore, finding noninvasive plasma biomarkers suitable for rapid diagnosis, screening, and surveillance would improve clinical outcomes. Taking advantage of the robust metabolic rewiring that occurs in FH-deficient cells, we performed plasma metabolomics analysis and identified 2 tumor-derived metabolites, succinyl-adenosine and succinic-cysteine, as excellent plasma biomarkers for early diagnosis. These 2 molecules reliably reflected the FH mutation status and tumor mass. We further identified the enzymatic cooperativity by which these biomarkers are produced within the tumor microenvironment. Longitudinal monitoring of patients demonstrated that these circulating biomarkers can be used for reporting on treatment efficacy and identifying recurrent or metastatic tumors.

Authors

Liang Zheng, Zi-Ran Zhu, Tal Sneh, Wei-Tuo Zhang, Zao-Yu Wang, Guang-Yu Wu, Wei He, Hong-Gang Qi, Hang Wang, Xiao-Yu Wu, Jonatan Fernández-García, Ifat Abramovich, Yun-Ze Xu, Jin Zhang, Eyal Gottlieb

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Figure 8

Circulating suc-ado and suc-cys levels can be used to accurately identify FH-deficient RCC.

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Circulating suc-ado and suc-cys levels can be used to accurately identif...
(A) Box plot analysis showing the distribution of plasma metabolites across NC, FH-MT, and FH-WT. Wilcoxon rank-sum test P values with Bonferroni correction were calculated. (B and C) Logistic regression ROCAUC analyses of metabolites in FH-MT versus NC samples (B) and FH-MT versus FH-WT samples (C). (D) Spearman’s correlation coefficient between tumor volume (log2 mm3) and potential plasma biomarker levels (log2 ng/mL). (E) Scatter plot analysis showing the distribution of the levels of plasma metabolites between FH-MT carriers (no tumor), NCs, and patients with FH-WT or FH-MT RCC. All data are presented as the mean ± SEM. **P < 0.01, ***P < 0.001, and ****P < 0.0001, by unpaired, 2-tailed Student’s t test, with P value–adjusted Bonferroni correction. (F) Scatter plot analysis showing the distribution of the levels of plasma metabolites across NCs and patients with FH-WT, FH-MT stage I/II, or FH-MT stage III/IV. All data are presented as the mean ± SEM. ****P < 0.0001, by unpaired, 2-tailed Student’s t test, with P value–adjusted Bonferroni correction.

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ISSN: 0021-9738 (print), 1558-8238 (online)

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