Description
The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin–DNA–RNA–protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor–positive and –negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology.
PMID: 29921600 (Table S5 and Table S7)
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Cancer
Contact
Principal Investigators:
(in alphabetical order)
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Dr. Rama Khoka / Dr. Thomas Kislinger
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TKislinger
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Number of distinct conditions across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct condition labels are counted across all files submitted in the "Metadata" category
having a "Condition" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct biological replicates across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct replicate labels are counted across all files submitted in the "Metadata" category
having a "BioReplicate" or "Replicate" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct technical replicates across all analyses (original submission and reanalyses)
associated with this dataset.
The technical replicate count is defined as the maximum number of times any one distinct
combination of condition and biological replicate was analyzed across all files submitted in the
"Metadata" category. In the case of fractionated experiments, only the first fraction is
considered.
"N/A" means no results of this type were submitted.
Originally identified proteins that were automatically
remapped by MassIVE to proteins in the
SwissProt
human reference database.
"N/A" means no results of this type were submitted.
Number of distinct protein accessions reported across all analyses (original submission and
reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct unmodified peptide sequences reported across all analyses (original
submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct peptide sequences (including modified variants or peptidoforms) reported
across all analyses (original submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all
analyses (original submission and reanalyses) associated with this dataset.
"N/A" means no results of this type were submitted.
Number of distinct proteins quantified across all analyses (original submission and reanalyses)
associated with this dataset.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison
across all analyses (original submission and reanalyses) associated with this dataset.
A protein is differentially abundant if its change in abundance across conditions is found
to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated
with statistical tests for differential abundance.
Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE.
It has been imported to MassIVE for reanalysis purposes, so its spectra data here may
consist solely of processed peak lists suitable for reanalysis with most software.