By Paola Nisticò

Over the past few years, novel anticancer immunotherapy strategies, such as immune checkpoint inhibitors (ICI) and adoptive T-cell therapies, have shown remarkable clinical success across several tumor types, generating a wave of optimism in the oncology field. However, the durable regression of the disease achieved by immunotherapy approaches is currently limited to a subset of patients. The variability in patient response to cancer immunotherapies is due to the dynamic and complex nature of anticancer immunity, the existence of multiple immune-regulatory receptors/ligands and the heterogeneity in immunological composition, localization and function of the tumor immune microenvironment (TIME) cells.

The group is developing a platform comprising of bioinformatics workflows and models that will stem from patient multi-omics integration. This asset will be exploited in future studies to guide optimal selection of best immunotherapeutic strategies for NSCLC patients, also in the framework of ongoing Alliance Against Cancer (ACC) network clinical trials.

In particular, several lines of actions have been pursued:

• In the framework of the ACC Network, we have applied multi-omics platforms (RNAseq, NanoString, HLA typing, TCR-Seq, Whole Exome Sequencing) and deconvolution algorithms to identify biomarkers of response in ICI treated NSCLC patients.
• We posit to identify mechanisms of resistance in ICI non responder patients to design strategies to stimulate a non-immunogenic microenvironment TIME, e.g. radiotherapy.

CAR T-cell therapy is based on the administration of genetically modified T-lymphocytes specifically redirected to the tumor target by the expression on the lymphocyte cell surface of Chimeric Antigen Receptors (CARs). This therapy has been particularly effective in the context of B-cell lymphoproliferative diseases, while in other hematological malignancies and in solid tumors, so far, the efficacy has been much more limited. CAR T-cells therapy remains a challenge in solid tumors due to the presence of a TIME that may act as a physical barrier hampering CAR T-cell trafficking. The group is involved in a research project promoted by the Ministry of Health and developed under the aegis of Alliance Against Cancer. In particular, we are focused on the development of different strategies aiming at modulating the immunosuppressive elements to overcome the inhibition exerted by TIME to CAR T-cell therapy. The group currently carries out the following tasks :

• By bioinformatics methods and Machine Learning techniques we identified CAF-specific RNA signatures responsible of immune exclusion as putative target of CAR T
• We delivered oncolytic viruses in a murine model of head and neck cancer to support CAR T-cell penetration.
• We have planned to identify innovative biomarkers to predict CAR T-cell therapeutic response in human sarcomas