Tobacco smoking induces metabolic reprogramming of renal cell carcinoma
James Reigle, … , Jarek Meller, Maria F. Czyzyk-Krzeska
James Reigle, … , Jarek Meller, Maria F. Czyzyk-Krzeska
Published September 24, 2020
Citation Information: J Clin Invest. 2021;131(1):e140522. https://doi.org/10.1172/JCI140522.
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Clinical Research and Public Health Metabolism Oncology

Tobacco smoking induces metabolic reprogramming of renal cell carcinoma

Abstract

BACKGROUND Clear cell renal cell carcinoma (ccRCC) is the most common histologically defined renal cancer. However, it is not a uniform disease and includes several genetic subtypes with different prognoses. ccRCC is also characterized by distinctive metabolic reprogramming. Tobacco smoking (TS) is an established risk factor for ccRCC, with unknown effects on tumor pathobiology.METHODS We investigated the landscape of ccRCCs and paired normal kidney tissues using integrated transcriptomic, metabolomic, and metallomic approaches in a cohort of white males who were long-term current smokers (LTS) or were never smokers (NS).RESULTS All 3 Omics domains consistently identified a distinct metabolic subtype of ccRCCs in LTS, characterized by activation of oxidative phosphorylation (OXPHOS) coupled with reprogramming of the malate-aspartate shuttle and metabolism of aspartate, glutamate, glutamine, and histidine. Cadmium, copper, and inorganic arsenic accumulated in LTS tumors, showing redistribution among intracellular pools, including relocation of copper into the cytochrome c oxidase complex. A gene expression signature based on the LTS metabolic subtype provided prognostic stratification of The Cancer Genome Atlas ccRCC tumors that was independent of genomic alterations.CONCLUSION The work identified the TS-related metabolic subtype of ccRCC with vulnerabilities that can be exploited for precision medicine approaches targeting metabolic pathways. The results provided rationale for the development of metabolic biomarkers with diagnostic and prognostic applications using evaluation of OXPHOS status. The metallomic analysis revealed the role of disrupted metal homeostasis in ccRCC, highlighting the importance of studying effects of metals from e-cigarettes and environmental exposures.FUNDING Department of Defense, Veteran Administration, NIH, ACS, and University of Cincinnati Cancer Institute.

Authors

James Reigle, Dina Secic, Jacek Biesiada, Collin Wetzel, Behrouz Shamsaei, Johnson Chu, Yuanwei Zang, Xiang Zhang, Nicholas J. Talbot, Megan E. Bischoff, Yongzhen Zhang, Charuhas V. Thakar, Krishnanath Gaitonde, Abhinav Sidana, Hai Bui, John T. Cunningham, Qing Zhang, Laura S. Schmidt, W. Marston Linehan, Mario Medvedovic, David R. Plas, Julio A. Landero Figueroa, Jarek Meller, Maria F. Czyzyk-Krzeska

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Figure 7

Metallomic analysis of TS effects in NKTs and ccRCCs from NS and LTS.

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Metallomic analysis of TS effects in NKTs and ccRCCs from NS and LTS. (A...
(A) Box-whisker plots for the total Cd content and stacked bar graphs for Cd distribution for NKTs and ccRCCs from NS and LTS. (B) Box-whisker plots for the total As content and stacked bar graphs for As distribution for NKTs and ccRCCs from NS and LTS. (C) Box-whisker plots for the total Cu content and stacked bar graphs for Cu distribution for NKTs and ccRCCs from NS and LTS. (D) Saturation of MTs in the indicated tissues. (E) SEC-ICP-MS chromatograms from indicated tissues. Y-axis on the left represents the intensity of signal for the metals. HMW: high molecular weight fraction, LMW: low molecular weight fraction, MT: metallothioneins. Peak 1 corresponds to Cu bound to cytochrome oxidase C, and peak 2 to Cu bound to other proteins. (F) Quantification of Cu in the fraction corresponding to cytochrome C oxidase peak 1 in the indicated tissues. (G) Quantification of Cu in the fraction corresponding to peak 2 in the indicated tissues. (H) UV-Vis isoabsorbance plots. The specific absorption bands at 420 and 600–700 nm are respectively specific for porphyrin rings and CuA-red and CuB-Ox clusters. Scale:1–100 mAU log10. (I) Pie charts show proportion of genes encoding proteins using Cu among the protein-coding genes in RefSeq database and among differentially expressed genes in NKTs and ccRCCs from NS and LTS. P values were determined by 2-sample test for equality of proportion with continuity correction. (J) Schematic representation of As methylation pathway. (K) Stacked bar graphs showing speciation of As in the indicated tissues. MMA: monomethylated As; DMA: demethylated As. P values calculated by Mann-Whitney-Wilcoxon test. Numbers in parentheses indicate number of samples used in each experiment.