Article ; Online: ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data.
iScience
2024 Volume 27, Issue 3, Page(s) 109198
Abstract: Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and ... ...
| Abstract | Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or Consensus |
|---|---|
| Language | English |
| Publishing date | 2024-02-12 |
| Publishing country | United States |
| Document type | Journal Article |
| ISSN | 2589-0042 |
| ISSN (online) | 2589-0042 |
| DOI | 10.1016/j.isci.2024.109198 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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