High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer

Abstract

Non-small cell lung cancer (NSCLC) is characterized by molecular heterogeneity with diverse immune cell infiltration patterns, which has been linked to both, therapy sensitivity and resistance. However, full understanding of how immune cell phenotypes vary across different patient and tumor subgroups is lacking. Here, we dissect the NSCLC tumor microenvironment at high resolution by integrating 1,212,463 single-cells from 538 samples and 309 patients across 29 datasets, including our own dataset capturing cells with low mRNA content. Based on the cellular composition we stratified patients into immune deserted, B cell, T cell, and myeloid cell subtypes. Using bulk samples with genomic and clinical information, we identified specific cellular components associated with tumor histology and genotypes. Analysis of cells with low mRNA content uncovered distinct subpopulations of tissue-resident neutrophils (TRNs) that acquire new functional properties in the tissue microenvironment, providing evidence for the plasticity of TRNs. TRN-derived gene signature was associated with anti-PD-L1 treatment failure in a large NSCLC cohort. In briefSalcher, Sturm, Horvath et al. integrate single-cell datasets to generate the largest transcriptome atlas in NSCLC, refining patient stratification based on tumor immune phenotypes, and revealing associations of histological subtypes and genotypes with specific cellular composition patterns. Coverage of cells with low mRNA content by single-cell sequencing identifies distinct tissue-resident neutrophil subpopulations, which acquire new properties within the tumor microenvironment. Gene signature from tissue-resident neutrophils is associated with immune checkpoint inhibitor treatment failure. The integrated atlas is publicly available online (https://luca.icbi.at), allowing the dissection of tumor-immune cell interactions in NSCLC. HighlightsO_LIHigh-resolution single-cell atlas of the tumor microenvironment (TME) in NSCLC. C_LIO_LIHistological tumor subtypes and driver genes imprint specific cellular TME patterns. C_LIO_LIscRNA-seq of cells with low transcript count identifies distinct tissue-resident neutrophil (TRN) subpopulations and non-canonical functional properties in the TME niche. C_LIO_LITRN gene signature identifies patients who are refractory to treatment with PD-L1 inhibitors. C_LI O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/491204v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@1050b6aorg.highwire.dtl.DTLVardef@3088c8org.highwire.dtl.DTLVardef@6408b8org.highwire.dtl.DTLVardef@1788c22_HPS_FORMAT_FIGEXP M_FIG C_FIG