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accession-icon SRP154973
Reprogramming of Tumor-infiltrating Immune Cells in Early Stage of NSCLC
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

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

Publication Title

Dissecting intratumoral myeloid cell plasticity by single cell RNA-seq.

Sample Metadata Fields

Sex, Specimen part, Disease, Race, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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