Grade-dependent lipid storage in ccRCC cells: molecular and functional study performed in primary cell cultures

Cristina Bianchi1, Chiara Meregalli1, Silvia Bombelli1, Barbara Torsello1, Sofia De Marco1, Francesco Salerno1, Ingrid Cifola2, Eleonora Mangano2, Cristina Battaglia3, Giorgio Bovo4, Paolo Viganò5, Guido Strada5, Roberto A Perego1
  • 1 Università Milano-Bicocca, Dipartimento di Medicina e Chirurgia (Monza)
  • 2 Istituto di Tecnologie Biomediche - CNR (Segrate)
  • 3 Università degli Studi di Milano, Dipartimento di Biotecnologie Mediche e Medicina Translazionale (Segrate)
  • 4 Ospedale San Gerardo, Unità di Anatomia patologica (Monza )
  • 5 Ospedale Bassini - A.O. ICP, Unità di Urologia (Cinisello Balsamo)

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common (80-90%) and lethal subtype of renal cell carcinoma, which accounts for 80% of all kidney cancers (1).
The most striking morphological feature of ccRCC cells is their clear cytoplasm mainly due to lipid accumulation (2). These intracellular storages suggest the involvement of altered fatty acid metabolism in the development of ccRCC. In fact, transcriptomic, proteomic and metabolomic profiling of ccRCC tissues revealed the presence of a metabolic reprogramming characterized also by increased fatty acid synthesis and by down-regulation of fatty acid b-oxidation (3-4). Of note, gene expression profiling and pathway analysis of ccRCC tissues also evidenced an enrichment of the PPARa pathway that, through the transcription of genes involved in fatty acid mitochondrial uptake (i.e. CPT1) and b-oxidation, is a master regulator of fatty acid metabolism (5). Interestingly, inhibition of ccRCC cell line growth has been obtained by targeting PPARa in vitro and in a xenograft mouse model (6). More recently, by using different –omics approaches, several groups revealed that specific metabolic alterations might correlate with tumor aggressiveness and poor survival in ccRCC patients. In particular, a decrease of specific fatty acid oxidation enzyme expression has been also found to correlate with the increase of tumour stage, size and grade and with the decrease of survival (7). By combining proteomics and metabolomics analysis, we collaborated to reveal a grade-dependent metabolic reprogramming in ccRCC tissues involving also fatty acid metabolism (4). Even if many approved targeted therapeutics have been recently developed (8), at present there is no grade-specific therapy addressing this metabolic reprogramming in ccRCC. For this purpose, an in vitro model of ccRCC that maintains the metabolic features of tumor tissue might be useful. Thus, we established primary cell cultures (PCC) from normal cortex and ccRCC tissue specimens that have been extensively characterized demonstrating to retain, at the early passages, the phenotypic, genomic, proteomic and transcriptomic profile of the corresponding tissues (9-12).
Here we aimed to investigate by cytological, molecular and functional analyses of these PCC: 1) the presence of grade-dependent lipid storages in ccRCC cells; 2) the involvement of PPARa and/or its target CPT1 in these storages; 3) the effect of CPT1 inhibition by Etomoxir on ATP production and cell viability of ccRCC PCC.

Materials and Methods

PCC established from ccRCC and normal cortex tissue samples were characterized by FACS analysis (10). Functional enrichment analysis of KEGG and Reactome pathways was performed by Cytoscape ClueGO plug-in on transcriptome profiling of ccRCC PCC previously obtained (12). Neutral lipid storage in Fuhrman low- and high-grade tissues and corresponding PCC was evaluated by Oil Red “O” staining and lipid droplet marker PLIN2 expression evaluated by western blot. PPARa expression was evaluated by western blot. Inhibition of CPT1 activity was performed by treatment with 50 uM Etomoxir. ATP production and cell viability in untreated and treated cells were evaluated by a specific commercial kit and FACS analysis after Annexin V/PI staining, respectively.

Results

The analysis performed on ccRCC PCC transcriptomic profiling evidenced a significant enrichment of several metabolic pathways mainly related to lipid metabolism and PPARa signaling. Notably, ccRCC cultures maintain at the first passage the lipid storages observed in corresponding tissues and, like in corresponding tissues, the lipid storages were also more abundant in low- (G1-G2) than in high-grade (G3-G4) ccRCC PCC. Moreover, PPARa protein expression was significantly increased in high-grade with respect to low-grade ccRCC PCC, as also described in corresponding tissues (13). Inhibition of CPT1 by Etomoxir induced a significant decrease of ATP production and cell viability only in high-grade ccRCC cells.

Discussions

Our data show that the PCC maintain the grade-dependent lipid storage of ccRCC tissues and this storage correlates with PPARaļ” expression. Because PPARa regulates fatty acid uptake into mitochondria through CPT1 gene transcription, the increased accumulation of lipids observed in low-grade ccRCC cells might be due to a decreased PPARa-dependent CPT1 expression, which evaluation is in progress. Moreover, the decrease of ATP production induced by CPT1 inhibition with Etomoxir and observed only in high-grade ccRCC cells suggests that PPARa, likely through CPT1 expression modulation, plays a role also in grade-dependent energy metabolism differences in ccRCC. The cytotoxic effect induced only in high-grade ccRCC cells by Etomoxir-dependent CPT1 inhibition also highlights the grade-dependent role of mitochondrial fatty acid uptake and/or metabolism in ccRCC viability and suggests the feasibility of a grade-specific therapeutic approach in ccRCC.

Conclusion

These ccRCC PCC, retaining also the metabolic features of corresponding tissues, are a useful tool to shed light on the complex molecular mechanisms involved in grade-dependent metabolic reprogramming and lipid storage of ccRCC. Moreover, the grade-dependent impact of lipid metabolism inhibition on ccRCC cell viability suggests the feasibility of a grade-specific metabolic targeted therapy in ccRCC.

Reference

1. Rini et al., Lancet 2009
2. Gebhard et al., J Lipid Res 1987
3. Cancer Genome Atlas Research Network, Nature 2013
4. Wettersten et al., Cancer Res 2015
5. Tun et al., PLOS one 2013
6. Abu Aboud et al., Am J Physiol Cell Physiol 2015
7. Zhao et al., Tumor Biology 2016
8. van der Mijn et al., Cancer and Metabolism 2016
9. Perego et al., J Proteome Res 2005
10. Bianchi et al., Am J Pathol 2010
11. Cifola et al., BMC Cancer 2011
12. Di Stefano et al., Am J Pathol 2016.
13. Abu Aboud et al., PLOS one 2013

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