Redetermination of PD-L1 expression after chemio-radiation in locally advanced PDL1 negative NSCLC patients: retrospective multicentric analysis.

Background: Chemoradiation therapy (CRT) is the treatment of choice for locally advanced non-small cell lung cancer (LA-NSCLC). Several clinical trials that combine programmed cell death 1 (PD1) axis inhibitors with radiotherapy are in development for patients with LA-NSCLC. However, the effect of CRT on tumor cells programmed cell death ligand-1 (PD-L1) expression is unknown. Methods: In this multicentric retrospective study, we analyzed paired NSCLC specimens that had been obtained pre- and post-CRT. PD-L1 expression on tumor cells was studied by immunohistochemistry. The purpose of this study was to evaluate the feasibility, risk of complications, and clinical relevance of performing re-biopsy after CRT in patients with PD-L1 negative LA-NSCLC. Results: Overall, 31 patients from 6 centers with PD-L1 negative LA-NSCLC were analyzed. The percentage of tumor cells with PD-L1 expression significantly increased between pre- and post-CRT specimens in 14 patients (45%). Nine patients had unchanged PD-L1 expression after CRT, in five patients the rebiopsy material was insufficient for PD-L1 analysis and in two patients no tumor cells at rebiopsy were found. The post-rebiopsy complication rate was very low (6%). All patients with positive PD-L1 re-biopsy received Durvalumab maintenance after CRT, except one patient who had a long hospitalization for tuberculosis reactivation. Median PFS of patients with unchanged or increased PD-L1 expression was 10 and 16.9 months, respectively. Conclusion: CRT administration can induce PD-L1 expression in a considerable fraction of PD-L1 negative patients at baseline, allowing them receiving the maintenance Durvalumab in Europe. Hence, after a definitive CRT, PD-L1 redetermination should be considered in patients with LA-NSCLC PD-L1 negative, to have a better selection of maintenance Durvalumab candidates.

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). METHODS AND OBJECTIVES: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. CONCLUSION: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project.

Clinical evidence and adverse event management update of patients with RET- rearranged advanced non-small-cell lung cancer (NSCLC) treated with pralsetinib.

Current non-small cell lung cancer (NSCLC) management relies on genome-driven precision oncology thus shifting treatment paradigm towards biomarker-guided tumor-agnostic approaches. Recently, rearranged during transfection (RET) has been endorsed as tissue-agnostic target with sensitivity to RET inhibition. There are currently two selective RET tyrosine kinase inhibitors, pralsetinib and selpercatinib. The recent introduction of pralsetinib in the treatment algorithm of RET-rearranged tumor along with the mounting clinical evidence of pralsetinib durable activity from both randomized and observational studies holds the potential to disclose new avenues in the management of RET fusion positive NSCLC patients. Our narrative review aims to discuss the available clinical evidence on pralsetinib efficacy, particularly on brain metastases, and tolerability profile. In addition, our work explores the relevance of detecting RET fusions upfront in the disease history of patients with NSCLC.