Computational deconvolution of transcriptomic data for the study of tumor-infiltrating immune cells

Abstract

Cancer is a complex disease characterized by a wide array of mutually interacting components constituting the tumor microenvironment (connective tissue, vascular system, immune cells), many of which are targeted therapeutically. In particular, immune checkpoint inhibitors have recently become an established part of the treatment of cancer. Despite great promise, only a portion of the patients display durable response. Current research efforts are concentrated on the determination of tumor-specific biomarkers predictive of response, such as tumor mutational burden, microsatellite instability, and neo-antigen presentation. However, it is clear that several additional characteristics pertaining to the tumor microenvironment play a critical role in the effectiveness of immunotherapy. Here we comment on the computational methods that are used for the analysis of the tumor microenvironment components from transcriptomic data, discuss the critical needs, and foresee potential evolutions in the field.