Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data.
Francesca FinotelloClemens MayerChristina PlattnerGerhard LaschoberDietmar RiederHubert HacklAnne KrogsdamZuzana LoncovaWilfried PoschDoris WilflingsederSieghart SopperMarieke IjsselsteijnThomas P BrouwerDouglas JohnsonYaomin XuYu WangMelinda E SandersMonica V EstradaPaula Ericsson-GonzalezPornpimol CharoentongJustin BalkoNoel Filipe da Cunha Carvalho de MirandaZlatko TrajanoskiPublished in: Genome medicine (2019)
We introduce quanTIseq, a method to quantify the fractions of ten immune cell types from bulk RNA-sequencing data. quanTIseq was extensively validated in blood and tumor samples using simulated, flow cytometry, and immunohistochemistry data.quanTIseq analysis of 8000 tumor samples revealed that cytotoxic T cell infiltration is more strongly associated with the activation of the CXCR3/CXCL9 axis than with mutational load and that deconvolution-based cell scores have prognostic value in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture and to reveal immune-cell types that underlie differential patients' responses to checkpoint blockers.Availability: quanTIseq is available at http://icbi.at/quantiseq .
Keyphrases
- single cell
- rna seq
- flow cytometry
- electronic health record
- big data
- end stage renal disease
- ejection fraction
- newly diagnosed
- small molecule
- dna damage
- multidrug resistant
- prognostic factors
- gene expression
- stem cells
- bone marrow
- deep learning
- young adults
- machine learning
- patient reported outcomes
- mesenchymal stem cells
- cell proliferation
- patient reported
- childhood cancer