Our aim is to delineate the interactions of melanoma cells with the immune system. Our extended collaborations with leading laboratories in the field of melanoma research allowed us the setting up of a broad genetic database and a pipeline to identify and characterize neoantigens using whole-exome and whole genome sequencing in order to further understand its functional implications (Nat Med 2013; J. Immunol. 2013; Clin. Can. Res 2014; Nature Genetics 2015; Scientific Report 2018). We recently developed novel tools to identify the mutated HLA-class-I and -II peptidome (Oncotarget 2016). Using this method, we extensively mapped the neoantigenic and T cell receptor landscape, their immune reactivity and corresponding T cell identities (Cancer Discovery 2018). Further, using HLA peptidomics, combined with novel bioinformatics tools, we recently identified a recurrent immune-reactive NRAS neoantigen.
Our search for novel biomarkers for immunotherapy identified that the immunoproteosome subunits PSMB8 and PSMB9 are amplified in melanoma patients and are predictive of better survival and improved response to immune-checkpoint inhibitors (Nature Communications, In Revision). Our study aims to identify recurrent neoantigens, evaluate their influence on T cell reactivity, profile the relevant T cell receptors, and perform melanoma-specific systematic functional assessment of the requirements for immune cell reactivity.
TILs have emerged in recent decades as powerful effector cells. Likewise, the query for tumor-associated antigens (TAAs) and neoantigens as a therapeutic approach has been the focus of cancer immunology for the past twenty years. Surprisingly, to date only a handful of neoantigen-specific TILs have been identified in human patients.
Our goal in this study is to map both the antigenic and T cell receptor landscape encompassing both the TAAs and neoantigen signatures, their immune reactivity and corresponding T cell identities – thus providing the first comprehensive analysis of the cancer cell-T cell co-signatures. In order to achieve this goal, we use HLA-peptidomics and bioinformatics tools, to unbiasedly identify TAAs and neo-antigens from tumor samples, derived from melanoma patients.
The insights gathered through this analysis strengthen the notion that identification of few targetable antigens could guide personalized cancer immunotherapy.
Figure legend. Multifaceted investigation of melanoma-T cell interactions.
A schematic diagram of our pipeline.
Kalaora et al & Samuels, cancer Discovery, 2018
Mutational load and intra-tumor heterogeneity (ITH) are possibly related to response to treatment. However, little is known regarding the mechanistic relationship between ITH and the immune response in melanoma.
Despite past attempts to model the effect of an increased mutational load on the anti-tumor immune response, no attempts were made to study the causative effects of ITH and mutational load on the anti-tumor immune response and immunotherapies in a comparative manner.
In order to systematically explore intra-tumor heterogeneity and mutational load on immune responses against melanoma, we established a quantitative, controlled setting to study tumor heterogeneity and its effect on tumor growth and anti-tumor immunity. Our findings suggest that both clone number and their genetic diversity mediate tumor growth and rejecion. Therefore, tumor heterogeneity is linked with patient survival and checkpoint blockade response (Cell, in press).
Figure legend. (A) Experimental design scheme. (B) Phylogenetic tree analysis of the UVB-irradiated cell line.
Wolf et al., Cell, 2019