Clonal drivers of resistance to immune checkpoint blockade in liver malignancies

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PROJECT SUMMARY Background and relevance to NIH mission. Immune checkpoint blockade based therapy has quickly become the treatment paradigm for several advanced cancer including liver malignancies providing the clinical oncologist with a formidable weapon to achieve dramatic and durable tumor response. The widespread clinical use of modulators of the immune checkpoint, however, has clearly shown that a subset of patients are intrinsically poorly responsive to such treatments, while others might develop recurrent disease after an initial response. While this phenomenon is widely recognized the mechanisms underlying intrinsic and acquired resistance to immune therapy are still poorly understood, posing an urgent need for the development of novel technological tools to study and predict which clones within a tumor will likely drive recurrence. Research design. To investigate the cancer cell intrinsic mechanisms of adaptation and the tumor clonal dynamics in response to immune-checkpoint blockade in an autochthonous experimental model of cancer we will barcode somatic mosaic GEM models of liver cancer to look into the clonal drivers of resistance to immune- checkpoint blockade leveraging a CRISPR-Cas9 based clonal recovery method. Methods. We have generated somatic mosaic cancer models which faithfully recapitulate the biological behavior, the genomic complexity and functional heterogeneity of human disease. To investigate the clonal response to immune therapy malignant cells will be transduced with a dual reporter/suicide cassette barcoded lentiviral library that enables the precise recovery and expansion of any given barcoded clone by using a CRISPR/Cas9 based “fishing” method. These novel technology will be instrumental in the isolation and characterization of those clones/malignant cell populations that are intrinsically prone to evade the immune response or that stochastically acquire the ability to evade the adaptive immune response in the context of immune competent models of cancer. Genetic, molecular and metabolic characterization of such populations will shed light on the mechanisms driving the evasion from immune checkpoint blockade. Ultimately, we will gain fundamental information about clonal dynamics during disease progression in renal malignancies, in addition, by enabling the recovery of single clones and the generation of clonal avatars, this approach would help understanding the relative contribution of intrinsic cell plasticity vs. stochastic genetic events in driving disease recurrence. The technology would eventually demonstrate broader applications in the field of cancer biology and provide novel knowledge and valuable research tools to tackle different cancer types, particularly those characterized by a poor response to immune checkpoints modulation.