Metabolomic Profiling in Renal Cell Carcinoma

Overview

Antiangiogenics are the mainstay of treatment in patients with metastatic renal cell carcinoma. Conventional clinical end-points, used to measure efficacy with chemotherapeutic agents, have not been helpful in monitoring the efficacy of antiangiogenic therapy. Increasing numbers of predictive and pharmacodynamic biomarkers are being investigated that are useful surrogates for clinical response and also to identify patients early on who will benefit from this class of agents. This is valuable in avoiding unnecessary toxicity in patients and also in reducing cost implications of this expensive group of drugs. The investigators wish to explore the variability of baseline metabolomic profile in the blood and urine of patients with mRCC and characterise the inter-subject and intra-subject variability. The study of the baseline levels has not been performed in this cohort previously. This is extremely important in interpreting the emerging data of changes in the levels of the various biomarkers from various trials. This will in turn help in the development of future targeted therapies, especially Phase I/II studies where an early demonstration of target modulation is vital. This study will also help to identify the number of patients required for appropriate statistical evaluation in pharmacodynamic studies to assess biological activity, optimisation of dosing, and investigation of potential mechanisms of resistance. Study of the urinary and blood metabolomic profile in conjunction will give us an insight into the potential use of urine as a diagnostic and prognostic tool. OBJECTIVES GOAL The main objective of the study is to determine the change from baseline in metabolomic profiling in patients with clear cell renal cell carcinoma 1 month after nephrectomy or antiangiogenic treatment during 2 months

METHODOLOGY STUDY DESIGN. Observational, Prospective, Exploratory, Single centre. STUDY POPULATION Common Inclusion criteria Patients must be older than 18 years in age. Written Informed Consent obtained. Patients previously informed about the objectives. Patients with histologically confirmed renal clear cell carcinoma. Patients before surgery with confirmed renal cell carcinoma or suspected. RCC must be confirmed after surgery. Exclusion criteria Presence of a separate malignant diagnosis, in the last two years, except non-melanoma skin cancer or cervical carcinoma in situ. Prior anti-cancer treatment for RCC other than nephrectomy ENDPOINTS Primary endpoint Determination the changes from baseline in metabolomic profiling Secondary outcomes Time to progression Progression free survival (PFS) /Overall survival (OS) Determination of metabolomic levels during the monitoring period Radiologically measured tumour response (according to investigator assessment) Toxicities Outcome Measures Primary The primary outcome measures are the changes from baseline in metabolomic profiling 1 month after nephrectomy or after antiangiogenic treatment during 2 months Cohort 1. The primary clinical outcome measure is progression-free survival (PFS), the interval from first line therapy to first evidence of progression disease or death from RCC. Cohort 2. The primary clinical outcome measure is to find differences in metabolomic profiles between samples before and after nephrectomy. Secondary The main objective of the study is to determine the metabolomic basal levels in patients with renal cell carcinoma clear cell and try to find out a prognostic profile Metabolomic profile changes during the follow up. Tumour progression and PFS, i.e. the time from surgery/first line treatment to progression RCC specific survival time, i.e. the time from first line treatment to death from RCC Overall survival, i.e. the time from first line treatment to death from any cause, including RCC Best response Toxicity and association with metabolomic profile evaluation. Metabolomic characteristics of resected primary RCC. Tumour samples will be examined for a relevant metabolomic profile, and their association with outcome will be studied. Definitions PFS is defined as the time between the first day of treatment with any drug (sunitinib, pazopanib, etc.) and the date of radiological progressive disease (PD), clear clinical evidence of PD, or death. Patients who had not progressed at database closure will be censored at final follow-up. If the date of PD is unknown, the investigators will censor PFS at the last tumour assessment. Overall survival is defined as the time between the first day of "drug" treatment and the date of death or last date of follow-up. Objective response will be assessed by treating doctors, according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria version 1.1, and classified as complete response, partial response, stable disease, or PD. Timing for assessments will be dictated by individual institution policy. All adverse effects will be graded by the attending doctors according to Common Terminology Criteria for Adverse Events version 4•0. The investigators have initially selected mucositis, hypothyroidism, hand-foot syndrome, hypertension, anaemia, and thrombocytopenia for analysis on the basis of clinical relevance and grading objectiveness, together with grade 3-4 adverse events. The investigators will also record adverse toxic events leading to dose reductions and the date on which they occurred. The investigators will test metabolomic profile against PFS and overall survival with Cox-regression analysis and against RECIST response with logistic regression analysis. The investigators shall perform a multivariable analysis by including clinical factors associated with PFS, overall survival, or response as covariates (clinical factors that will be associated with p\<0•1 with a specific variable will be used as covariates for that specific variable). The investigators will allocate patients to favourable, intermediate, and poor prognosis groups according to the Memorial Sloan-Kettering Cancer Center (MSKCC) prognostic classification, and included this variable in the multivariable analysis. The investigators will further analyse metabolomic profile associated with PFS and overall survival in the multivariable analysis by the Kaplan-Meier method. The investigators will assess metabolomic levels/profile associated with an increased risk of drug dose reduction caused by toxicity with Cox-regression modelling of the number of days of drug treatment until the reduction of dose. Patients with no dose reductions will be censored at final follow-up. For multivariable analysis, the investigators will use clinical factors associated with p\<0•1 with dose reductions as covariates, and the investigators will analyse the metabolomic levels associated to drug dose reduction in the multivariable analysis with the Kaplan-Meier method. The investigators will study associations between specific drug toxicities and metabolomic profiles with logistic regression analysis, with toxicity development as a dichotomous endpoint. The multivariable logistic regression analyses will include clinical factors associated with the corresponding outcome as covariates (factors with p\<0•1). The investigators will test all genotypes with an additive genetic model. The investigators will retain missing data as missing apart from MSKCC prognostic factors. The most likely value, based on the data from the rest of the series, will be assigned to these patients. There will be a general descriptive variables included in the study. Distributions will be presented absolute and relative frequencies of qualitative variables, and measures of central tendency and dispersion (mean standard deviation, median, minimum and maximum) for quantitative variables. They will be presented with the confidence intervals at 95% for the major outcome. No missing data imputed and left as missing. The hypothesis test to be performed will be bilateral with a significance level of 0.05. For variables that do not conform to the normal distribution (or parametric) will be used for non-parametric tests in the analysis of contingency tables and for comparison of proportions and / or frequency distributions, will be used the chi -square (or Fisher's exact where appropriate). Statistical analysis of the data from the study will be conducted by Hutchison/MRC (Medical Research Council) Research Center. Specific aspects of the statistical analysis Analysis goal: Cohort 1: "To determine the baseline metabolomic profiles in urine/blood in patients with renal cell carcinoma clear in order to find a prognostic/predictive model" Appropriate regression models as well as univariate and multivariate statistical tests will be used. Cohort 2: "To determine the changes of metabolomic profiles before and 1 month after nephrectomy" Univariate and multivariate statistical tests for paired setting will be applied to reveal the changes.