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E-MEXP-1468
Arabidopsis thaliana
12 Downloadable Samples
Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)
Description
Arabidopsis etiolated seedlings (4d old) Col-0 wild type compared to det3 mutants under various growth conditions
Publication Title
Reduced V-ATPase activity in the trans-Golgi network causes oxylipin-dependent hypocotyl growth Inhibition in Arabidopsis.
Sample Metadata Fields
Age
View Samples- Homo sapiens
- 168 Downloadable Samples
Illumina HiSeq 4000, Illumina HiSeq 2500
Description
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells. Overall design: Single-cell RNA sequencing was performed on eight donors using the InDrop v2 protocol. For each donor populations of CD45+ immune cells were assayed for trancriptome-wide RNA-sequence. At least one replicate was taken for each donor.
Publication Title
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 29 Downloadable Samples
- NextSeq 500, Illumina HiSeq 2500
Description
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells. Overall design: Single-cell RNA sequencing was performed on three patients using the 10x genomics TCR profiling kits. For each patient, populations of T-cells were assayed for both TCR sequence and trancriptome-wide RNA-sequence. Two donors have a replicate experiment.
Publication Title
Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Sample Metadata Fields
Specimen part, Subject
View Samples