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Related Concept Videos

Proteomics01:33

Proteomics

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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...
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Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
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Quantitative single cell and single molecule proteomics for clinical studies.

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  • 1Institute of Chemical Biology, Department of Chemistry, Imperial College London, London SW7 2AZ, United Kingdom. keith.willison@imperial.ac.uk

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Cellular systems biology examines molecular noise. A new MAC chip platform precisely quantifies single-cell protein copy numbers, aiding cancer research and patient outcome prediction.

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Area of Science:

  • Cellular Systems Biology
  • Molecular Biology
  • Biotechnology

Background:

  • Cell-to-cell variability arises from molecular noise in cellular networks.
  • Protein production occurs in stochastic bursts, leading to significant copy number variations.
  • Environmental sensing and signaling networks are particularly affected by this variability.

Purpose of the Study:

  • To develop a precise method for quantifying single-cell protein copy numbers.
  • To investigate molecular noise in circulating tumor cells (CTCs) from cancer patients.
  • To identify biomolecular signatures, like p53, correlating with clinical outcomes.

Main Methods:

  • Development of a label-free, microfluidic antibody capture chip platform (MAC chip).
  • Multiplexed single-assay format for quantifying multiple proteins from a single cell.
  • Isolation of circulating tumor cells (CTCs) from patient biopsies.

Main Results:

  • The MAC chip enables precise quantification of protein copy numbers in single cells.
  • The platform facilitates the identification of biomolecular signatures in CTCs.
  • Potential to correlate protein noise with biological properties and clinical outcomes.

Conclusions:

  • The MAC chip is a powerful tool for studying cellular heterogeneity and molecular noise.
  • This technology can advance the understanding of cancer biology and personalized medicine.
  • Biomolecular signatures identified in CTCs may serve as predictive biomarkers for treatment.