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Protein Network Mutations Impact Revealed in Bowel Cancer

By Labmedica International staff writers
Posted on 22 Sep 2017
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Image: The Dionex Ultimate 3000 high-performance liquid chromatography (HPLC) system (Photo courtesy of the University of Texas at Austin).
Image: The Dionex Ultimate 3000 high-performance liquid chromatography (HPLC) system (Photo courtesy of the University of Texas at Austin).
The role proteins play in predicting how common mutations affect proteins in the cancer cells has been investigated and also whether such proteins are important in predicting the cancer's response to treatment.

Modern mass-spectrometry-based proteomic technologies have the capacity to perform highly reliable analytical measurements of proteins in large numbers of subjects and analytes, providing a powerful tool for the discovery of regulatory associations between genomic features, gene expression patterns, protein networks, and phenotypic traits.

A large team of scientists working with those at the Wellcome Trust Sanger Institute (Cambridge, UK) conducted a very deep, detailed study of the proteins in bowel cancer to investigate whether proteins play a role in predicting the effect of different drugs against the cancer. The team analyzed 9,000 proteins for each of 50 bowel cancer cell lines. Cell pellets were lysed by probe sonication/boiling, and protein extracts were subjected to trypsin digestion.

The tryptic peptides were labeled with the TMT10plex reagents, combined at equal amounts, and fractionated with high-pH C18 high-performance liquid chromatography (HPLC). Phosphopeptide enrichment was performed with immobilized metal ion affinity chromatography (IMAC). Liquid chromatography–mass spectrometry (LC-MS) analysis was performed on the Dionex Ultimate 3000 system, coupled with the Orbitrap Fusion Mass Spectrometer. MS3 level quantification with Synchronous Precursor Selection was used for total proteome measurements, whereas phosphopeptide measurements were obtained with a collision-induced dissociation-higher energy collisional dissociation (CID-HCD) method at the MS2 level.

The scientists performed the robust quantification of over 9,000 proteins and 11,000 phosphopeptides on average enabled the de novo construction of a functional protein correlation network, which ultimately exposed the collateral effects of mutations on protein complexes. CRISPR-cas9 deletion of key chromatin modifiers confirmed that the consequences of genomic alterations can propagate through protein interactions in a transcript-independent manner. Lastly, they leveraged the quantified proteome to perform unsupervised classification of the cell lines and to build predictive models of drug response in colorectal cancer.

Ultan McDermott, MD, PhD, a clinical scientist and a co-author of the study said, “This study is promising for bowel cancer patients. It confirms that this common cancer is actually composed of five different subtypes that may require different drug treatments, and surprisingly suggests that proteins may be more predictive for drug sensitivity than we have previously thought. In the future we may need to test the patient's genome, transcriptome and proteome to fully predict their response to cancer drugs and stratify patients for clinical trials more effectively. We are moving away from one size fits all towards personalized medicine.” The study was published on August 29, 2017, in the journal Cell Reports.

Related Links:
Wellcome Trust Sanger Institute


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