Anticancer immune responses depend on the interplay between different events taking place in the tumor microenvironment, among which: the infiltration of different immune cells; the presentation of mutated neoantigens on tumor Human Leukocyte Antigen (HLA) molecules for recognition by immune cells; and, the presence of co-stimulatory or co-inhibitory signals modulating tumor-immune cell interactions. Next-generation sequencing (NGS) data, originally used only to characterize the transcriptional (RNA sequencing ) and mutational (DNA sequencing) landscape of the tumor alone, can now be mined to dissect this complex kaleidoscope of tumor-immune cell interactions.

Here we propose TIminer, a standalone pipeline enclosing a selection of state-of-the-art tools for the investigation of tumor-immune cell interactions. TIminer allows to perform the following analyses:

Gene expression: Kallisto is used to efficiently and accurately quantify gene expression.
Immune infiltrates: the enrichment of 28 immune cell types is assessed through Gene Set Enrichment Analysis.
Tumor immunogenicity: the expression of genes related to HLA, co-inhibitory or co-stimulatory signals, and infiltration of immune cells, is used to compute an “immunophenogram” and an “immmunophenoscore”, describing tumor antigenicity and mechanisms of immune evasion.
HLA typing: Optitype is used to predict HLA types from RNA or DNA sequencing data.
Neoantigens: mutated proteins are inferred from somatic mutations using VEP. Mutated peptides 8-to-11 amino acids long are analyzed with NetMHCPan 3.0 to predict their binding affinity with HLAs. Candidate neoantigens are finally selected considering only expressed genes.

The full documentation of the TIminer is available under:
Online documentation