Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data
By Francesca Finotello, Clemens Mayer, C. Plattner, G. Laschober, Dietmar Rieder, Hubert Hackl, A. Krogsdam, Zuzana Loncova, W. Posch, D. Wilflingseder and 13 more. Genome Medicine, 2017
1,232 citations recorded by the source corpus.
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.
Subfields: Immunology, Oncology
View Paper: https://www.semanticscholar.org/paper/6abab71a1d9bca326131a904031359e3a1ee9dae
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Citations in the corpus
- GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA (2021, methodology): “,c) is the absolute proportion, it is comparable in an intra-sample (same sample with different cell types) or inter-sample (same cell type with different samples) manner (8,10).”
- IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures (2020, methodology): “The quanTIseq method enumerates 10 immune cell subsets from bulk RNAseq data (14).”
- Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology (2019, background): “(2015) through personal communication from the quanTIseq authors (Finotello et al., 2017). We obtained bulk RNA-seq and FACS data for four metastatic melanoma samples from Racle et al. (2017) through GEO accession number GSE93722.”
- TIMER2.0 for analysis of tumor-infiltrating immune cells (2020, methodology): “0 utilizes the immunedeconv (16), an R package which integrates six state-of-the-art algorithms, including TIMER (9), xCell (7), MCP-counter (8), CIBERSORT (10), EPIC (11) and quanTIseq (12).”