Dual-energy SPEctral CT to Evaluate Response to First-line Therapies in Patients With Metastatic Clear Cell REnal Cancer

Overview

To evaluate the utility of dual-energy spectral computed tomography (CT) scan in monitoring treatment in patients with metastatic clear cell carcinoma of the kidney. In particular, to analyze the use of spectral CT in patients who are candidates to receive first-line treatment based on combinations of immunotherapy and molecularly targeted drugs. In particular, the parameters derived from the use of this technology and their variation during therapy will be analyzed together with some possible molecular alterations highlighted by the analysis of the tumor tissue previously taken from the patient, relating them to the response to first-line therapy with immuno-combinations.

In the field of kidney cancer, where PET with FDG or other tracers is not valid due to the high number of false negatives, new techniques for radiological evaluation of the disease are a clinical necessity. The evaluation of parameters derived from the use of dual-energy spectral computed tomography (CT), such as IC and Zeffective, at baseline and after 3 and 6 months of systemic treatment, could provide useful information on how tumor structure (in particular vascularization) evolves during therapy with IO+IO or IO+TKI. In addition, the variation of these parameters could be associated with different outcomes in terms of ORR, PFS and OS. One aspect evaluated is the existence of a correlation between the presence of abundant tumor vascularization (or on the contrary poor vascularization), determined by dual-energy spectral CT, and the response in terms of ORR and PFS at 3 and 6 months to combinations containing IO+TKI or immunotherapy alone. For prognostic and predictive purposes, the study also intends to verify whether there is a correlation between the presence of gene alterations, CT-derived parameters and response to therapies. The prognostic role of some molecular alterations (ATM, BAP1, KDM5C, MET, MTOR, NF2, PBRM1, PIK3CA, PTEN, SETD2, SMARCB1, TP53, TSC1, TSC2, VHL) will be evaluated and their potential predictive value will be analyzed to understand whether a given mutational structure may be more or less responsive to specific types of treatment.

Conditions