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Updated: Sep 16, 2026
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Identification and analysis of mutational hotspots in oncogenes and tumour suppressors
Hanadi Baeissa1, Graeme Benstead-Hume1, Christopher J Richardson2
1School of Life Sciences, University of Sussex, Falmer, Brighton, UK.
Background:
The key to interpreting the contribution of a disease-associated mutation in the development and progression of cancer is an understanding of the consequences of that mutation both on the function of the affected protein and on the pathways in which that protein is involved. Protein domains encapsulate function and position-specific domain based analysis of mutations have been shown to help elucidate their phenotypes.
Results:
In this paper we examine the domain biases in oncogenes and tumour suppressors, and find that their domain compositions substantially differ. Using data from over 30 different cancers from whole-exome sequencing cancer genomic projects we mapped over one million mutations to their respective Pfam domains to identify which domains are enriched in any of three different classes of mutation; missense, indels or truncations. Next, we identified the mutational hotspots within domain families by mapping small mutations to equivalent positions in multiple sequence alignments of protein domainsWe find that gain of function mutations from oncogenes and loss of function mutations from tumour suppressors are normally found in different domain families and when observed in the same domain families, hotspot mutations are located at different positions within the multiple sequence alignment of the domain.
Conclusions:
By considering hotspots in tumour suppressors and oncogenes independently, we find that there are different specific positions within domain families that are particularly suited to accommodate either a loss or a gain of function mutation. The position is also dependent on the class of mutation.We find rare mutations co-located with well-known functional mutation hotspots, in members of homologous domain superfamilies, and we detect novel mutation hotspots in domain families previously unconnected with cancer. The results of this analysis can be accessed through the MOKCa database (http://strubiol.icr.ac.uk/extra/MOKCa).
Insights
Understanding cancer-associated mutations requires analyzing protein domains. This study maps over a million mutations to protein domains, revealing distinct patterns in oncogenes and tumor suppressors, and identifying novel cancer-related mutation hotspots.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Interpreting disease-associated mutations in cancer requires understanding their impact on protein function and pathways.
- Protein domains are key functional units, and analyzing mutations within them helps elucidate phenotypes.
Purpose of the Study:
- To investigate domain biases in oncogenes and tumor suppressors.
- To identify mutation hotspots within protein domain families across various cancer types.
Main Methods:
- Analysis of over one million mutations from whole-exome sequencing data across 30+ cancer types.
- Mapping mutations to Pfam domains and identifying enrichment for missense, indel, or truncation mutations.
- Locating mutational hotspots by aligning mutations to conserved positions within protein domain families.
Main Results:
- Oncogenes and tumor suppressors exhibit significantly different domain compositions.
- Gain-of-function mutations in oncogenes and loss-of-function mutations in tumor suppressors occur in distinct domain families and at different positions within domains.
- Identified novel mutation hotspots in previously unlinked domain families and rare mutations at known hotspot locations.
Conclusions:
- Specific positions within protein domain families are predisposed to either gain- or loss-of-function mutations, dependent on mutation class.
- Domain-based analysis reveals distinct mutational landscapes for oncogenes and tumor suppressors.
- The MOKCa database provides access to these findings for further research.
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