ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Teng, Pang-ning; Schaaf, Joshua P.; Abulez, Tamara; Hood, Brian L.; Wilson, Katlin N.; Litzi, Tracy J.; Mitchell, David; Conrads, Kelly A.; Hunt, Allison L.; Olowu, Victoria; Oliver, Julie; Park, Fred S.; Edwards, Marshé; Chiang, AiChun; Wilkerson, Matthew D.; Raj-Kumar, Praveen-Kumar; Tarney, Christopher M.; Darcy, Kathleen M.; Phippen, Neil T.; Maxwell, G. Larry; Conrads, Thomas P.; Bateman, Nicholas W.

doi:10.1016/j.isci.2024.109198

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Preprint1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Gene prioritization-based active bio-module identification for bioinformatics

Soni,

Bhatt,

Asenso

et al. 2024

Scientific African

View full text Add to dashboard Cite

Gene prioritization-based active bio-module identification for bioinformatics

Soni,

Bhatt,

Asenso

et al. 2024

Scientific African

View full text Add to dashboard Cite

Integrating Functional Protein Drug Target Data into a Precision Oncology Molecular Tumor Board

Hunt,

Randall,

Mansukhani

et al. 2024

Preprint

View full text Add to dashboard Cite

Collaborative review of molecular profiling data by multidisciplinary molecular tumor boards (MTB) is increasingly important for improving patient management and outcomes, though currently relies nearly exclusively on nucleic acid next-generation sequencing (NGS) and limited panels of immunohistochemistry-based protein abundance data. We examined the feasibility of incorporating real-time laser microdissection (LMD) enrichment of tumor epithelium and commercial CLIA-based reverse phase protein array (RPPA) protein drug target expression/activation profiling into our cancer center MTB to complement standard clinical NGS-based profiling. The LMD-RPPA workflow was performed within a therapeutically permissive timeframe with a median dwell time of nine days, during which specimens were processed outside of standard clinical workflows. The RPPA-generated data supported additional and/or alternative therapeutic considerations for 54% of profiled patients following review by the MTB. These findings suggest that integrating proteomic/phosphoproteomic and NGS-based genomic data creates opportunities to further personalize clinical decision-making for precision oncology.

show abstract

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Cited by 2 publications

References 41 publications

Gene prioritization-based active bio-module identification for bioinformatics

Gene prioritization-based active bio-module identification for bioinformatics

Integrating Functional Protein Drug Target Data into a Precision Oncology Molecular Tumor Board

Contact Info

Product

Resources

About