Metabolic and Lipidomic Reprogramming in Renal Cell Carcinoma Subtypes Reflects Regions of Tumor Origin

Abstract

Background: Renal cell carcinoma (RCC) consists of prognostic distinct subtypes derived from different cells of origin (eg, clear cell RCC [ccRCC], papillary RCC [papRCC], and chromophobe RCC [chRCC]). ccRCC is characterized by lipid accumulation and metabolic alterations, whereas data on metabolic alterations in non-ccRCC are limited.

Objective: We assessed metabolic alterations and the lipid composition of RCC subtypes and ccRCC-derived metastases. Moreover, we elucidated the potential of metabolites/lipids for subtype classification and identification of therapeutic targets.

Design, setting, and participants: Metabolomic/lipidomic profiles were quantified in ccRCC (n=58), chRCC (n=19), papRCC (n=14), corresponding nontumor tissues, and metastases (n=9) through a targeted metabolomic approach. Transcriptome profiling was performed in corresponding samples and compared with expression data of The Cancer Genome Atlas cohorts (patients with ccRCC, n=452; patients with papRCC, n=260; and patients with chRCC, n=59).

Outcome measurements and statistical analysis: In addition to cluster analyses, metabolomic/transcriptomic data were analyzed to evaluate metabolic differences of ccRCC and chRCC using Welch's t test or paired t test as appropriate. Where indicated, p values were adjusted for multiple testing using Bonferroni or Benjamini-Hochberg correction.

Results and limitations: Based on their metabolic profiles, RCC subtypes clustered into two groups separating ccRCC and papRCC from chRCC, which mainly reflected the different cells of origin. ccRCC-derived metastases clustered with primary ccRCCs. In addition to differences in certain lipids (lysophosphatidylcholines and sphingomyelins), the coregulation network of lipids differed between ccRCC and chRCC. Consideration of metabolic gene expression indicated, for example, alterations of the polyamine pathway at metabolite and transcript levels. In vitro treatment of RCC cells with the ornithine-decarboxylase inhibitor difluoromethylornithine resulted in reduced cell viability and mitochondrial activity. Further evaluation of clinical utility was limited by the retrospective study design and cohort size.

Conclusions: In summary, we provide novel insight into the metabolic profiles of ccRCC and non-ccRCC, thereby confirming the different ontogeny of RCC subtypes. Quantification of differentially regulated metabolites/lipids improves classification of RCC with an impact on the identification of novel therapeutic targets.

Patient summary: Several subtypes of renal cell carcinoma (RCC) with different metastatic potentials and prognoses exist. In the present study, we provide novel insight into the metabolism of these different subtypes, which improves classification of subtypes and helps identify novel targets for RCC therapy.

Keywords: Chromophobe renal cell carcinoma; Clear cell renal cell carcinoma; Lipidomics; Metabolomics; Metastasis; Renal cell carcinoma.