ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data
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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 TME . We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.
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Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 1× · see citing works
“20 Thus, there remains a paucity of data investigating the applicability of these signatures for characterizing cellular admixture withinproteomedata in HGSOCtissues.”
BackgroundProteoform: a single term describing protein complexity
The Consortium for Top Down Proteomics, Smith, L. M., & Kelleher, N. L. (2013) · Nature Methods · doi:10.1038/nmeth.2369 · Cited by 1,528 · cited 1× · see citing works
“Pro-teoforms can reflect variations of protein modification states, such as due to post-translational modifications, 32 and incorporation of proteo-form-level abundances could further clarify the relationships between global protein and transcript-level abundances and will be the focus of future…”
BackgroundTumor microenvironment in ovarian cancer: function and therapeutic strategy
Yang, Y., Yang, Y., Yang, J., Zhao, X., & Wei, X. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.00758 · Cited by 218 · see citing works
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- Authors
- Teng, P.-N., Schaaf, J. P., Abulez, T., Hood, B. L., Wilson, K. N., Litzi, T. J., Mitchell, D., Conrads, K. A., Hunt, A. L., Olowu, V., Oliver, J., Park, F. S., Edwards, M., Chiang, A., Wilkerson, M. D., Raj-Kumar, P.-K., Tarney, C. M., Darcy, K. M., Phippen, N. T., Maxwell, G. L., Conrads, T. P., & Bateman, N. W.
- Affiliations
- Henry M. Jackson Foundation (US)
- Inova Health System (US)
- Uniformed Services University of the Health Sciences (US)
- Windber Research Institute (US)
- Corresponding author
- Conrads, Thomas P.
- Bateman, Nicholas W.
- ORCID
- Venue
- iScience
- Publisher
- Elsevier BV
- Published
- 2024-03
- Volume
- 27
- Issue
- 3
- Pages
- 109198
- ISSN
- 2589-0042 (ISSN-L)
- PMC
- PMC10910246
- OpenAlex
- W4391755943
- Cited by
- 21
- References
- 3
- Citations by year
- 2026: 1 · 2025: 10 · 2024: 10
- FWCI
- 2.99
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- iScience (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Defense Health Agency Consortium
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- cell type deconvolution, high-grade serous ovarian cancer, tumor microenvironment, immune cell proportions, proteomic signatures, transcript-protein correlation, laser microdissection, estimates
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