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Published on: November 5, 2019
Protein domain-level landscape of cancer-type-specific somatic mutations
Fan Yang1, Evangelia Petsalaki2, Thomas Rolland3
1Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada; Donnelly Centre, University of Toronto, Toronto, Ontario, Canada; Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital, Toronto, Ontario, Canada.
Abstract:
Identifying driver mutations and their functional consequences is critical to our understanding of cancer. Towards this goal, and because domains are the functional units of a protein, we explored the protein domain-level landscape of cancer-type-specific somatic mutations. Specifically, we systematically examined tumor genomes from 21 cancer types to identify domains with high mutational density in specific tissues, the positions of mutational hotspots within these domains, and the functional and structural context where possible. While hotspots corresponding to specific gain-of-function mutations are expected for oncoproteins, we found that tumor suppressor proteins also exhibit strong biases toward being mutated in particular domains. Within domains, however, we observed the expected patterns of mutation, with recurrently mutated positions for oncogenes and evenly distributed mutations for tumor suppressors. For example, we identified both known and new endometrial cancer hotspots in the tyrosine kinase domain of the FGFR2 protein, one of which is also a hotspot in breast cancer, and found new two hotspots in the Immunoglobulin I-set domain in colon cancer. Thus, to prioritize cancer mutations for further functional studies aimed at more precise cancer treatments, we have systematically correlated mutations and cancer types at the protein domain level.
Insights
Researchers mapped cancer mutations to protein domains, revealing tissue-specific mutation hotspots in both oncogenes and tumor suppressors. This domain-level analysis aids in prioritizing mutations for targeted cancer therapies.
Area of Science:
- Genomics
- Oncology
- Structural Biology
Background:
- Identifying cancer driver mutations and their functional impact is crucial for understanding cancer.
- Protein domains are the fundamental functional units of proteins, making them key targets for mutation analysis.
Purpose of the Study:
- To systematically explore the protein domain-level landscape of cancer-type-specific somatic mutations.
- To identify domains with high mutational density and pinpoint mutational hotspots within these domains across various cancer types.
Main Methods:
- Systematic examination of tumor genomes from 21 cancer types.
- Analysis of mutation density and hotspot locations within protein domains.
- Correlation of mutation patterns with protein function and structure.
Main Results:
- Identified tissue-specific domains with high mutation rates.
- Observed distinct mutation patterns within domains for oncogenes (recurrent hotspots) and tumor suppressors (evenly distributed mutations).
- Discovered known and novel endometrial cancer hotspots in FGFR2 tyrosine kinase domain, with one also present in breast cancer; identified new hotspots in colon cancer's Immunoglobulin I-set domain.
Conclusions:
- Protein domain-level analysis provides a framework for understanding cancer mutation patterns.
- This systematic approach helps prioritize mutations for functional studies and the development of precise cancer treatments.
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