Unknown,Transcriptomics,Genomics,Proteomics

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Spatial transcriptomic analyses of triple negative and luminal A breast ductal carcinoma in situ

ABSTRACT: This experiment includes GeoMx spatial transcriptomic analyses of FFPE tissue from breast ductal carcinoma in situ lesions from 16 patients. All lesions were subject to ER, PR, HER2 and Ki67 immunohistochemistry and assigned a molecular subtype. The main aim was to compare DCIS of the two subtypes Triple Negative and Luminal A. From each patient sample, multiple regions of interest (ROIs) were selected and the synthetics nucleotide oligos attached to RNA probes were sequenced separately. Tumor areas and stromal areas were sequenced separately. The data provided is the raw (unnormalized) count matrix, and Q3 normalized data from tumor and stroma areas separetely in addition to corresponding metadata files to enable linking between patient ID and ROI.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Homo sapiens

SUBMITTER: Helga Bergholtz

PROVIDER: E-MTAB-16918 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Purpose: In all vertebrates, the thymus is necessary and sufficient for production of classic adaptive T cells. The key components of the thymus are cortical and medullary thymic epithelial cells (cTECs and mTECs). Despite the capital role of TECs, our understanding of TEC biology is quite rudimentary. For instance, we ignore what might be the extent of divergence in the functional program of these two TECs populations. It also remains unclear why the number of TECs decreases rapidly with age, thereby leading to progressive thymic insufficiency. Methods: Systems level understanding of cell function begins with gene expression profiling, and the transcriptome is currently the only '-ome' that can be reliably tackled in its entirety in freshly harvested primary cells. In order to gain novel insights into TEC biology, we therefore decided to analyse the whole transcriptome of cTECs, mTECs and skin epithelial cells. We elected to analyse gene expression using RNA-seq rather microarrays because RNA-seq has higher sensitivity and dynamic range coupled to lower technical variations. Results: Our deep sequencing approach provides a unique perspective into the transcriptome of TECs. Consistent with their ability to express ectopic genes, we found that mTECs expressed more genes than other cell populations. Out of a total of 15,069 genes expressed in TECs, 25% were differentially expressed by at least 5-fold in cTECs vs. mTECs. Genes expressed at higher levels in cTECs than mTECs regulate numerous cell functions including cell differentiation, cell movement and microtubule dynamics. Almost all positive regulators of the cell cycle were overexpressed in skin ECs relative to TECs. Conclusions: Our RNA-seq data provide novel insights into the transcriptional landscape of TECs, highlight substantial divergences in the transcriptome of TEC subsets and suggest that cell cycle progression is differentially regulated in TECS and skinECs. We believe that our work will therefore represent a valuable resource and will be of great interest to readers working in biological sciences, particularly in the areas of immunology and systems biology. The mRNA profiles of cTEC, mTEC (from 14 thymi of 7-days old C57BL/6 mice) and skinEC (from the trunk and dorsum of seven newborn mice) were generated by RNA-sequencing using Illumina HiSeq2000.

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Spatial transcriptomic analyses of triple negative and luminal A breast ductal carcinoma in situ

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