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Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Annotated proteome of a human T-cell lymphoma
David K Crockett1, Charles E Seiler, Kojo S J Elenitoba-Johnson
1ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, Utah, USA.
Journal of Biomolecular Techniques : JBT
|March 9, 2006
Summary
Researchers identified over 1100 proteins in T-cell lymphoma using mass spectrometry and bioinformatics tools. This automated method aids in discovering new diagnostic and pathogenetic markers for lymphoma.
Area of Science:
- Proteomics
- Bioinformatics
- Cell Biology
Background:
- Tandem mass spectrometry (MS/MS) is crucial for protein identification.
- Characterizing large proteomic datasets remains a significant challenge.
- Identifying novel markers for T-cell lymphoma is clinically important.
Purpose of the Study:
- To survey the proteome of a human T-cell lymphoma cell line.
- To develop an automated method for annotating protein lists.
- To identify novel pathogenetic and diagnostic markers for T-cell lymphoma.
Main Methods:
- Proteins from cytoplasmic, membrane, and nuclear fractions of SUDHL-1 cells were analyzed.
- Proteins were resolved by SDS-PAGE, digested, and analyzed by tandem mass spectrometry.
- Data were processed using SEQUEST, INTERACT, ProteinProphet, and GOMiner for annotation.
Main Results:
- A total of 1105 unique proteins were identified and annotated.
- Numerous proteins previously uncharacterized in lymphoma were discovered.
- Identified proteins were involved in cell adhesion, migration, signaling, and stress response.
Conclusions:
- Bioinformatics tools enable robust, batchwise identification and annotation of large protein datasets.
- The study provides a foundation for identifying novel T-cell lymphoma markers.
- This approach facilitates comprehensive proteomic analysis in cancer research.
