Clinical-Molecular Prospective Cohort Study in Non-Small Cell Lung Cancer (PROMOLE study): A Comprehensive Approach to Identify New Predictive Markers of Pharmacological Response.

Lung cancers account for over 90% of thoracic malignancies and the rapid development of specific cytotoxic drugs and molecular therapies requires a detailed identification of the different histologies, gene drivers or immune microenvironment biomarkers. Nevertheless, the heterogeneous clonal evolution, the emergency of drug-induced resistance and the limited occurrence of genetic alterations claim the need of a deep integration of the tumor's and the patient's biological features. The aim of the present study is to generate a tecnological platform for precision medicine in order to set predictive personalized algorithms for patient diagnosis and therapy. All resectable patients having histologically confirmed stage IB-IIIA non-small cell lung cancer will be enrolled for tissue sampling. A large biobank of lung cancer samples and the corresponding healthy tissues and biological components (ie, blood, stools, etc.) with complete clinical, pathological and molecular information will be collected. The platform will include: a) digital patient data collection; b) whole NGS molecular analyses (exome, transcriptome, methylome) for tumor characterization; c) exploitation and collection of organoids from tissue patients; d) Surface Amplified Raman Spectroscopy; e) microfluidic-based technological drug screening; f) preclinical in vivo models based on patient-derived xenografts; g) generation of specific predictive algorithms taking into account all collected multiparameters. The project will lay the basis of a knowledge hub and qualified technology aimed not only at answering the medical and scientific community's questions, but also meant to be useful to individual patients by predicting the response to adjuvant and second-line drugs in case of relapse of the disease.

A Monte Carlo approach to the microdosimetric kinetic model to account for dose rate time structure effects in ion beam therapy with application in treatment planning simulations.

PURPOSE: Advanced ion beam therapeutic techniques, such as hypofractionation, respiratory gating, or laser-based pulsed beams, have dose rate time structures which are substantially different from those found in conventional approaches. The biological impact of the time structure is mediated through the ß parameter in the linear quadratic (LQ) model. The aim of this study was to assess the impact of changes in the value of the ß parameter on the treatment outcomes, also accounting for noninstantaneous intrafraction dose delivery or fractionation and comparing the effects of using different primary ions. METHODS: An original formulation of the microdosimetric kinetic model (MKM) is used (named MCt-MKM), in which a Monte Carlo (MC) approach was introduced to account for the stochastic spatio-temporal correlations characteristic of the irradiations and the cellular repair kinetics. A modified version of the kinetic equations, validated on experimental cell survival in vitro data, was also introduced. The model, trained on the HSG cells, was used to evaluate the relative biological effectiveness (RBE) for treatments with acute and protracted fractions. Exemplary cases of prostate cancer irradiated with different ion beams were evaluated to assess the impact of the temporal effects. RESULTS: The LQ parameters for a range of cell lines (V79, HSG, and T1) and ion species (H, He, C, and Ne) were evaluated and compared with the experimental data available in the literature, with good results. Notably, in contrast to the original MKM formulation, the MCt-MKM explicitly predicts an ion and LET-dependent ß compatible with observations. The data from a split-dose experiment were used to experimentally determine the value of the parameter related to the cellular repair kinetics. Concerning the clinical case considered, an RBE decrease was observed, depending on the dose, ion, and LET, exceeding up to 3% of the acute value in the case of a protraction in the delivery of 10 min. The intercomparison between different ions shows that the clinical optimality is strongly dependent on a complex interplay between the different physical and biological quantities considered. CONCLUSIONS: The present study provides a framework for exploiting the temporal effects of dose delivery. The results show the possibility of optimizing the treatment outcomes accounting for the correlation between the specific dose rate time structure and the spatial characteristic of the LET distribution, depending on the ion type used.