Tobacco smoking induces metabolic reprogramming of renal cell carcinoma.

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 prognosis. ccRCC is also characterized by distinguished metabolic reprogramming. Tobacco smoking (TS) is an established risk factor for ccRCC with unknown effects on tumor pathobiology.

We investigated the landscape of ccRCCs and paired normal kidney tissues (NKTs) using integrated transcriptomic, metabolomic and metallomic approaches in a cohort of never smokers (NS) and long-term current smokers (LTS) Caucasian males.

All three Omics domains consistentl 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. Gene expression signature based on the LTS metabolic subtype provided prognostic stratification of The Cancer Genome Atlas (TCGA) ccRCC tumors that was independent from genomic alterations.

The work identifies the TS related metabolic subtype of ccRCC with vulnerabilities that can be exploited for precision medicine approaches targeting metabolic pathways. The results provide rationale for the development of metabolic biomarkers with diagnostic and prognostic applications using evaluation of OxPhos status. The metallomic analysis reveals the role of disrupted metal homeostasis in ccRCC highlighting the importance of studying effects of metals from e-cigarettes and environmental exposures.

The Journal of clinical investigation. 2020 Sep 24 [Epub ahead of print]

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

Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, United States of America., Department of Chemistry, University of Cincinnati College of Arts and Science, Cincinnati, United States of America., Division of Biostatistics and Bioinformatics, University of Cincinnati College of Medicine, Cincinnati, United States of America., Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, United States of America., Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, United States of America., Department of Medicine, University of Cincinnati College of Medicine, Cincinnati, United States of America., Division of Urology, University of Cincinnati College of Medicine, Cincinnati, United States of America., Department of Veterans Affairs, Cincinnati Veteran Affairs Medical Center, Cincinnati, United States of America., Department of Pathology and Laboratory Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, United States of America., Urologic Oncology Branch, National Cancer Institute-Frederick, Frederick, United States of America.