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Series GSE117570 Query DataSets for GSE117570
Status Public on Apr 30, 2019
Title Reprogramming of Tumor-infiltrating Immune Cells in Early Stage of NSCLC
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Comparing the relative proportions of immune cells in tumor and adjacent normal tissue from NSCLC patients demonstrates the early changes of tumor immunity and provides insights to guide immunotherapy design. We mapped the immune ecosystem using computational deconvolution of bulk transcriptome data from the Cancer Genome Atlas (TCGA) and single cell RNA sequencing (scRNA-seq) data of dissociated tumors from early-stage non-small cell lung cancer (NSCLC) to investigate early immune landscape changes occurring during tumorigenesis. Computational deconvolution of immune infiltrates in 44 NSCLC and matching adjacent normal samples from TCGA showed heterogeneous patterns of alterations in immune cells. The scRNA-seq analyses of 11,485 cells from 4 treatment-naïve NSCLC patients comparing tumor to adjacent normal tissues showed diverse changes of immune cell compositions. Notably, CD8+ T cells and NK cells are present at low levels in adjacent normal tissues, and are further decreased within tumors. Myeloid cells exhibited marked dynamic reprogramming activities, which were delineated with differentiation paths through trajectory analysis. A common differentiation path from CD14+ monocytes to M2 macrophages was identified among the 4 cases, accompanied by up-regulated genes (e.g. ALCAM/CD166, CD59, IL13RA1, IL7R) with enriched functions (adipogenesis, lysosome), and down-regulated genes (e.g. CXCL2, IL1B, IL6R) with enriched functions (TNFa signaling via NF-kB, inflammatory response). Computational deconvolution and single cell sequencing analyses have revealed a highly dynamic immune reprogramming that occurs in early stage NSCLC development, suggesting that normalizing both immune compartments may represent a viable strategy for treatment of early stage cancer and prevention of progression.
 
Overall design Map the immune ecosystem using computational deconvolution of bulk transcriptome data from the Cancer Genome Atlas (TCGA) and single cell RNA sequencing (scRNA-seq) data of dissociated tumors from from early-stage non-small cell lung cancer (NSCLC) to investigate early immune landscape changes occurring during tumorigenesis
 
Contributor(s) Zhang W, Forbes E, Jin G, Song Q
Citation(s) 31033233, 34295900
Submission date Jul 24, 2018
Last update date Jul 28, 2021
Contact name Qianqian Song
E-mail(s) qsong@wakehealth.edu
Phone 3369264972
Organization name Wake Forest Baptist Comprehensive Cancer Center
Department Cancer Genomics and Precision Oncology
Street address 1 Medical Center Boulevard
City Winston-Salem
State/province NC
ZIP/Postal code 27157-1082
Country USA
 
Platforms (1)
GPL18573 Illumina NextSeq 500 (Homo sapiens)
Samples (8)
GSM3304007 P1_Tumor
GSM3304008 P1_Normal
GSM3304009 P2_Tumor
Relations
BioProject PRJNA482529
SRA SRP154973

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
GSE117570_RAW.tar 18.7 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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