NCBI Logo
GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
          Go
Series GSE84789 Query DataSets for GSE84789
Status Public on Oct 11, 2016
Title Single-cell profiling of non small cell lung cancer associated B-cells.
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary 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. 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.
 
Overall design Single-cell comparison of normal and tumor infiltrated B-cells.
 
Contributor(s) Dries R, Lizotte P, Ivanova E
Citation(s) 27699239
Submission date Jul 25, 2016
Last update date Mar 20, 2019
Contact name Ruben Dries
E-mail rubendries@gmail.com
Organization name DFCI
Department Computational Biology
Lab Longwood Center
Street address 360 Longwood Ave
City Boston
ZIP/Postal code 02215
Country USA
 
Platforms (1)
GPL11154 Illumina HiSeq 2000 (Homo sapiens)
Samples (192)
GSM2251214 single cell RNAseq normal B cells [1350A01_Normal_A01]
GSM2251215 single cell RNAseq tumor B cells [1350A01_Tumor_A01]
GSM2251216 single cell RNAseq normal B cells [1350A02_Normal_A02]
This SubSeries is part of SuperSeries:
GSE84799 Multi-parametric profiling of non-small cell lung cancers reveals distinct immunophenotypes
Relations
BioProject PRJNA331162
SRA SRP079684

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE84789_fcount_primary_output.txt.gz 4.6 Mb (ftp)(http) TXT
Processed data is available on Series record
Raw data are available in SRA

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap