Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
Year: 2019
Type: article
Abstract: ABSTRACT The immune contexture has a prognostic value in several cancers and the study of its pharmacological modulation could identify drugs acting synergistically with immune checkpoint blockers. However, the quantification of the immune contexture is hampered by the lack of simple and efficient methods. We developed quanTIseq, a deconvolution method that quantifies the densities of ten immune cell types from bulk RNA sequencing data and tissue imaging data. We performed extensive validation using simulated data, flow cytometry data, and immunohistochemistry data from three cancer cohorts. Analysis of 8,000 samples showed that the activation of the CXCR3/CXCL9 axis, rather than the mutational load is associated with cytotoxic T cell infiltration. We also show the prognostic value of deconvolution-based immunoscore and T cell/B cell score in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture, and we suggest that it might have predictive value for immunotherapy.
Source: Genome Medicine
Authors: Francesca Finotello, Clemens Mayer, Christina Plattner, Gerhard Laschober, Dietmar Rieder, Hubert Hackl, Anne Krogsdam, Zuzana Loncova, Wilfried Posch, Doris Wilflingseder, Sieghart Sopper, Marieke Ijsselsteijn, Thomas P. Brouwer, Douglas Johnson, Yaomin Xu, Yu Wang, Melinda E. Sanders, Monica V. Estrada, Paula Ericsson-Gonzalez, Pornpimol Charoentong, Justin Balko, Noel Filipe da Cunha Carvalho de Miranda, Zlatko Trajanoski
Institutions: Innsbruck Medical University, Universität Innsbruck, Leiden University Medical Center, Vanderbilt University, Vanderbilt University Medical Center, German Cancer Research Center, University Hospital Heidelberg, National Center for Tumor Diseases, Austrian Drug Screening Institute (Austria)
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,680
Awards: Protein-protein interaction networks for precision oncology, G2460052287, Predicting and profiling long-term survival after immune checkpoint inhibition, IBDome, G3114638291, G3316174929, G434337789, Therapeutic targeting of EGFR in colorectal cancer as a novel approach to predict and enhance tumor antigenicity and response to checkpoint inhibitors, G5145439004, APERIM: Advanced bioinformatics platform for PERsonalised cancer IMmunotherapy, The tumor-immune interface of human lung cancer, G71631788, SPORE in Breast Cancer, Dusp4 in breast cancer: tumor suppressor biology and therapeutic strategies
OpenAlex ID: W2947554843