PI: Marcello Maugeri Saccà
Other IRE Principal Collaborators Involved: Federico Capuzzo, Isabella Sperduti, Irene Terrenato, Maddalena Barba, Eriseld Krasniqi, Vincenzo Pio Di Noia

Project duration: 24 months

Project code: PNRR-MCNT2-2023-12377963

Immune-checkpoint inhibitors have revamped the interest surrounding the manipulation of the immune system for cancer treatment. Nevertheless, the limited accuracy of companion diagnostics is a major hurdle in clinical practice. Our preliminary data indicate that a KEAP1 mutant-like state, stemming from aberrant NRF2 transcriptional activity, evolves across a variety of cancer types that do not harbor mutations in the KEAP1/NRF2 axis (KEAPness). The present project aims to decipher how this molecular configuration shapes immunotherapy sensitivity/resistance in order to develop a novel molecular diagnostic tool for tailored anti-cancer immunotherapy.

Clinical sequencing is revolutionizing the therapeutic landscape of solid tumors by uncovering novel actionable alterations beyond established drivers. Nevertheless, this approach captures a snapshot of a tumor, overlooking the highly dynamic nature of cancers. Indeed, multiple intertwined factors, such as transcriptional plasticity, epistatic interactions, genomic instability, inter-clonal competition, host-related factors and pharmacological pressure, drive phenotypical changes in an unpredictable way. This overarching conceptual framework lays the foundation for this project, where massive sequencing and preclinical models are harmonized in a patient-centered experimental design in an attempt of predicting the efficacy of immunotherapy and uncover novel therapeutic strategies. All the data collected throughout the project, and the related computational methods, will be made freely available to the scientific community. This will enable researchers to recapitulate our methods, and apply our analytical workflow to other settings, diseases and treatments in the attempt of improving the outcomes of patients with other tumor types. Overall, the project aims to:

• Develop a molecular assay for the prediction of immune checkpoint inhibitors (ICIs) efficacy in NSCLC, and potentially transferable to other tumor types, relying on a new conceptual approach (KEAP1-loss phenocopies). Indeed, the most common outcome of immunotherapy in NSCLC falls into a large grey zone of no efficacy/marginal benefit, that is still unpredictable. Moreover, the massive characterization efforts underlying the present proposal, coupled with the wealth of clinical trials carried out at the two participating Institutes, may allow the inclusion of some patients in state-of-the-art clinical trials during the project time-span.
• Clarify the phenotypic drivers of the KEAPness state, their clonal dynamics, and the related composition of the TIME.
• Identify pharmacological strategies for the selective targeting of NRF2 transcriptional addiction, which still represents an orphan disease entity.

Improved Prediction of ICI Efficacy: The project aims to develop a molecular assay based on KEAPness that can accurately predict which patients with NSCLC (and potentially other cancers) will benefit from ICIs. This will address the significant "grey zone" of unpredictable ICI response.

Understanding of KEAPness Mechanisms: The research will provide a detailed understanding of the genetic and evolutionary processes that give rise to KEAPness and how it interacts with the TIME. This will provide insights into how tumors evade immune responses.

Identification of New Therapeutic Targets: The project will identify potential drug targets and therapeutic strategies to specifically target tumors with KEAPness. This could lead to new treatments for patients who are resistant to current immunotherapies.

Data and Resource Sharing: All data and computational methods generated by the project will be made freely available to the scientific community, fostering further research and collaboration.

Potential for Clinical Trial Inclusion: The extensive characterization efforts and clinical trial infrastructure at the participating institutions may enable the inclusion of some patients in cutting-edge clinical trials during the project.