Integration of Lipidomics and Transcriptomics Reveals Reprogramming of the Lipid Metabolism and Composition in Clear Cell Renal Cell Carcinoma.

Giuseppe Lucarelli,Eugenio Maiorano,Matteo Ferro,Daniela Terracciano,Roberto A Perego,Davide Loizzo,Stefano Battaglia,Cristina Bianchi,Giuseppe Castellano,Ottavio De Cobelli,Pasquale Ditonno,Francesco Cantiello,Michele Battaglia,Leonardo Vincenti,Camillo Porta,Angela Gernone,Lauren N Bell

doi:10.3390/metabo10120509

Abstract

Clear cell renal cell carcinoma (ccRCC) is fundamentally a metabolic disease. Given the importance of lipids in many cellular processes, in this study we delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes. Untargeted lipidomic analysis was performed on 20 ccRCC and 20 paired normal tissues, using LC-MS and GC-MS. Different lipid classes were altered in cancer compared to normal tissue. Among the long chain fatty acids (LCFAs), significant accumulations of polyunsaturated fatty acids (PUFAs) were found. Integrated lipidomic and transcriptomic analysis showed that fatty acid desaturation and elongation pathways were enriched in neoplastic tissue. Consistent with these findings, we observed increased expression of stearoyl-CoA desaturase (SCD1) and FA elongase 2 and 5 in ccRCC. Primary renal cancer cells treated with a small molecule SCD1 inhibitor (A939572) proliferated at a slower rate than untreated cancer cells. In addition, after cisplatin treatment, the death rate of tumor cells treated with A939572 was significantly greater than that of untreated cancer cells. In conclusion, our findings delineate a ccRCC lipidomic signature and showed that SCD1 inhibition significantly reduced cancer cell proliferation and increased cisplatin sensitivity, suggesting that this pathway can be involved in ccRCC chemotherapy resistance.

Highlights

Renal cell carcinoma (RCC) accounts for about 2–3% of all malignant diseases in adults.GLOBOCAN 2018 estimates of worldwide cancer incidence and mortality were 403,262 new cases and175,098 deaths for kidney cancer [1]
Untargeted lipidomic analysis was performed on 40 kidney-derived tissues, including 20 Clear cell renal cell carcinoma (ccRCC)
The application of principal component analysis (PCA) to distinguish normal and pathological samples as a function of the global tissue lipidome demonstrated that the two groups were clearly different (Figure 1b)

Summary

Introduction

Renal cell carcinoma (RCC) accounts for about 2–3% of all malignant diseases in adults.GLOBOCAN 2018 estimates of worldwide cancer incidence and mortality were 403,262 new cases and175,098 deaths for kidney cancer [1]. The rediscovery of cancer as a metabolic disorder has led to the identification of specific oncometabolites with an important role in tumor growth and progression [3,4,5,6]. The discovery of novel markers will play an important role in the clinical management of this disease considering that up to 30% of cases have a metastatic disease at diagnosis and that, to date, we have no specific molecular factor for diagnosis and prognostic stratification [8,9,10,11]. Recent studies have shown that RCC is fundamentally a metabolic disease, since many genes that are altered in this tumor play a fundamental role in controlling cell metabolic activities [12,13,14]. We showed that, in clear cell renal cell carcinoma (ccRCC), a metabolic reprogramming occurs, involving the glucose metabolism and the pentose phosphate pathway, and that patients with high levels of glycolytic enzymes had reduced survival rates [15,16,17]

Methods

Results

Conclusion