PURPOSE: Temsirolimus is an effective treatment for renal cell carcinoma. It is associated with increases in serum cholesterol, triglyceride, and glucose. We investigated whether changes of these biomarkers could predict its efficacy.
EXPERIMENTAL DESIGN: We examined serial measurements of cholesterol, triglycerides, and glucose from patients randomized to IFN or temsirolimus in the Global Advanced Renal Cell Carcinoma Trial. Using time-dependent proportional hazards models, we quantified the association between changes in these biomarkers from baseline with overall survival (OS) and progression-free survival (PFS). We also assess the extent to which changes of these biomarkers predict the effects of temsirolimus on survival.
RESULTS: Temsirolimus was associated with larger mean increases in cholesterol (1.02 mmol/L; P < 0.0001), triglycerides (0.32 mmol/L; P = 0.0008), and glucose (1.28 mmol/L; P < 0.0001) compared with IFN and improved survival rate (OS: HR = 0.76, P = 0.02; PFS: HR = 0.70, P = 0.001). Cholesterol increase during study was associated with longer survival (OS: HR = 0.77 per mmol/L, P < 0.0001; PFS: HR = 0.81 per mmol/L; P < 0.0001). Temsirolimus effect on cholesterol predicted its effect on survival with no additional survival advantage observed after adjusting for cholesterol change during study (OS: HR = 1.14, P = 0.37; PFS: HR = 0.88, P = 0.35). Temsirolimus effect on triglycerides or glucose did not predict its effect on survival, with survival advantage in favor of temsirolimus still observed after adjusting for these factors (P = 0.003 and P = 0.002).
CONCLUSION: Cholesterol increase is a potential predictor for temsirolimus efficacy. Longer survival in patients treated with temsirolimus was observed in those with larger increases in cholesterol. Prospectively designed biomarker studies of temsirolimus or other mTOR inhibitors are recommended.
Written by:
Lee CK, Marschner IC, Simes RJ, Voysey M, Egleston B, Hudes G, de Souza P Are you the author?
NHMRC Clinical Trials Centre, University of Sydney; Department of Statistics, Macquarie University; University of Western Sydney School of Medicine, Sydney, New South Wales, Australia; Centre for Statistics in Medicine, University of Oxford, Oxford, United Kingdom; and Fox Chase Cancer Center, Philadelphia, Pennsylvania
Reference: Clin Cancer Res. 2012 Jun 1;18(11):3188-96
doi: 10.1158/1078-0432.CCR-11-3137
PubMed Abstract
PMID: 22472176