Single-cell profiling of non small cell lung cancer associated B-cells.
Transcriptomics Dataset
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General Information
AccessionGSE84789
TitleSingle-cell profiling of non small cell lung cancer associated B-cells.
DescriptionBackground: Immune checkpoint blockade improves survival in a subset of patients with non-small cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. Methods: We performed comprehensive flow-cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). Results: Cytometric profiling identified an immunologically hot cluster with abundant CD8+ T cells expressing high levels of the PD-1 and TIM-3, and an immunologically cold cluster with lower relative abundance of CD8+ T cells and expression of inhibitory markers. The hot cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function, and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the hot cluster. Additionally, ~20%% of cases had high B cell infiltrates with a subset producing IL-10. Conclusions: Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer. Background: Immune checkpoint blockade improves survival in a subset of patients with non-small cell lung cancer (NSCLC), but robust biomarkers that predict response to PD-1 pathway inhibitors are lacking. Furthermore, our understanding of the diversity of the NSCLC tumor immune microenvironment remains limited. Methods: We performed comprehensive flow-cytometric immunoprofiling on both tumor and immune cells from 51 NSCLCs and integrated this analysis with clinical and histopathologic characteristics, next generation sequencing, mRNA expression, and PD-L1 immunohistochemistry (IHC). Results: Cytometric profiling identified an immunologically hot cluster with abundant CD8+ T cells expressing high levels of the PD-1 and TIM-3, and an immunologically cold cluster with lower relative abundance of CD8+ T cells and expression of inhibitory markers. The hot cluster was highly enriched for expression of genes associated with T cell trafficking and cytotoxic function, and high PD-L1 expression by IHC. There was no correlation between immunophenotype and KRAS or EGFR mutation, or patient smoking history, but we did observe an enrichment of squamous subtype and tumors with higher mutation burden in the hot cluster. Additionally, ~20%% of cases had high B cell infiltrates with a subset producing IL-10. Conclusions: Our results support the use of immune-based metrics to study response and resistance to immunotherapy in lung cancer.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84789
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE84789
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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