Evaluating a lipid panel for clear cell renal cell carcinoma prognosis

MARÍA E. MONGE; MALENA MANZI; NICOLAS ZABALEGUI

Simposio; 10th International Singapore Lipid Symposium; 2022

Kidney cancer is accepted to be a metabolic disease. Renal cell carcinoma (RCC) is the main type of kidney cancer with more than 50% of cases incidentally diagnosed. Surgery is the most promising treatment for curation when the disease is detected at early stages, since it is inherently resistant to chemotherapy and radiotherapy. Clear cell RCC (ccRCC) is the most common histological subtype, and is characterized for being lipid and glycogen-laden, exhibiting abnormal cholesterol metabolism and fat storage. Our research group has recently interrogated serum samples from a cohort including patients with different ccRCC stages (I, II, III, IV; n=112) and controls (n=52) with a lipidomics-machine learning approach. [1] A 16-lipid panel, including cholic acid, undecylenic acid, lauric acid, linoleic acid, LPC(16:0/0:0), and PC(18:2/18:2), allowed discriminating ccRCC patients from controls with 77.1% accuracy in an independent test set.[1] This 16-lipid panel was further evaluated as a signature for metabolic response after surgery in paired serum samples. Changes in the lipid signature of samples collected before and after surgery were investigated and compared with those fingerprints obtained from controls. Results suggest that ccRCC-associated lipid phenotypes may be used for the evaluation of phenoconversion to a healthy status, and contribute to patient prognosis stratification. Serum samples were provided by the public oncologic serum biobank ?Biobanco Público de Muestras Séricas Oncológicas? (BPMSO) from ?Instituto de Oncologıá A. H. Roffo? (IOAHR).