Computational approaches applied to cancer genetics, immunogenomics, and immuno-oncology

Cancer is a disease of the genome initiated by the accumulation of somatic alterations. These genetic alterations provide the fuel for continuous evolution allowing cancer cells to develop new phenotypes, often referred to as cancer hallmarks. One of these hallmarks is the capacity to hide from the immune system and avoid immune-mediated cell death. Such a process has been defined as immunoediting and its extent, the underlying biological mechanism, and its consequences remain poorly understood. Recent technologies have provided us with an incredible amount of “multi-omic” data enabling the study of the relationship between the immune system and cancer. Among these technologies, there are sequencing-based approaches, such as standard whole-exome and whole-genome sequencing, TCR-seq, ATAC-seq, and RNA-seq, at bulk or single-cell resolution, and image-based techniques such as digital pathology, immunohistochemistry, x-ray, and optical imaging. The increasing amount of information, and how to make sense of it, represents one of the biggest challenges of the decade. Thus, there is an urgent need to develop new computational and statistical approaches, especially in the field of cancer immunology.

The aim of this research topic is to provide an updated overview of computational approaches applied to understand the interaction between the immune system and cancer cells.

Scope and information for authors:

For this topic, we are interested in manuscripts that have developed a computational method applied to immuno-oncology or that have used substantial analytical approaches to study the impact of the immune system on tumor evolution, metastasis, or response to immunotherapies.

The topic aims to cover but is not restricted to, the following themes:

• Computational methods or strategies to predict antigens, MHC-complex binding affinity, and HLA-peptide immunogenicity
• New approaches to determine the genetic make-up involved in the immune response (HLA alleles, Genetic markers, TCR clonotype diversity, predisposition genes, variants on the antigen presentation machinery)
• Computational or experimental approaches to describe the landscape of antigenic peptides in cancer (immunopeptidomics) and cancer immunoediting
• Mechanisms of resistance/evasion to immunotherapies
• Development of computational/mathematical/statistical models for understanding the co-evolutionary dynamics between the immune system and cancer cells
• Genetic determinants associated with immunotherapeutic response
• Impact of the HLA genetic make-up on the diversity of TCR repertoires
• The interplay between cancer and the human immune system during tumor progression
• Computational approaches for TCR-peptide-HLA recognition
• New methods to deconvolute the tumor microenvironment and detect immune subpopulations

MSK has licensed the use of TMB for the identification of patients who benefit from immune checkpoint therapy to PGDx. Diego Chowell receives royalties as part of this licensing agreement.