Deconvoluting tumor-infiltrating immune cells from RNA-seq data using quanTIseq

Abstract

Tumor-infiltrating immune cells comprise various cells of the innate and the adaptive immune system, which influence tumor growth and response to immunotherapy by exerting anti- and protumorigenic functions. Therefore, the quantification of tumor immune infiltrates is of paramount importance for cancer immunology and immunotherapy. We recently developed quanTIseq, a computational pipeline for the quantification of immune-cell fractions from bulk RNA sequencing (RNA-seq) data from blood or tumor samples. In this chapter, we show the capabilities of quanTIseq by analyzing two publicly available data sets. In the first example, we demonstrate how quanTIseq can be used to quantify circulating immune cells from preprocessed RNA-seq data and how to validate the results using matched flow cytometry data. In the second example, we analyze raw RNA-seq data from bulk tumor samples of melanoma patients collected before and on-treatment with kinase inhibitors to show how quanTIseq can be used to reveal the immunological effects of targeted and conventional drugs.

Keywords: Cancer immunology; Deconvolution; Gene expression; Immune contexture; RNA-seq; TILs.