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Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...

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Related Experiment Video

Updated: Jun 3, 2026

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
08:08

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

Published on: February 27, 2015

Quantitative proteomic analysis in breast cancer.

A Tabchy1, B T Hennessy, A M Gonzalez-Angulo

  • 1Department of Breast Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA. atabchy@mdanderson.org

Drugs of Today (Barcelona, Spain : 1998)
|March 25, 2011
PubMed
Summary

Functional proteomics, using reverse-phase protein microarrays (RPPA), overcomes limitations in protein-level tumor characterization. This approach offers crucial insights for targeted cancer medicine and patient monitoring.

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Last Updated: Jun 3, 2026

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Area of Science:

  • Cancer Research
  • Proteomics
  • Molecular Medicine

Background:

  • Genomic and transcriptional tumor characterization has advanced significantly.
  • Protein-level characterization historically faced challenges in reproducibility, scalability, and robustness.

Purpose of the Study:

  • To highlight the advancements in protein-level characterization using functional proteomics.
  • To emphasize the utility of reverse-phase protein microarrays (RPPA) in studying cellular protein states.
  • To demonstrate the potential of RPPA in providing critical information for cancer diagnostics and therapeutics.

Main Methods:

  • Utilized protein microarrays to examine global protein levels and activated states, including phosphorylation.
  • Employed reverse-phase protein microarrays (RPPA) for high-throughput analysis of signal transduction networks.
  • Applied RPPA to small biological samples, such as human biopsy material.

Main Results:

  • RPPA enables accurate and reproducible portrayal of global and active cellular protein states.
  • RPPA can map activated protein pathways and networks within cells.
  • Initial successes in breast cancer indicate the clinical relevance of RPPA-derived information.

Conclusions:

  • Functional proteomics, particularly RPPA, provides a crucial link to genomic and gene expression data for a comprehensive understanding of cancer.
  • RPPA offers a powerful tool for therapeutic decision-making and patient monitoring in targeted molecular medicine.
  • The application of RPPA in cancer research promises significant advancements in clinical relevance and patient care.