Harmful somatic amino acid substitutions affect key pathways in cancers
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Updated: Apr 5, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Abhishek Niroula1, Mauno Vihinen2
1Department of Experimental Medical Science, Lund University, BMC B13, SE-22184, Lund, Sweden. abhishek.niroula@med.lu.se.
Background:
Cancer is characterized by the accumulation of large numbers of genetic variations and alterations of multiple biological phenomena. Cancer genomics has largely focused on the identification of such genetic alterations and the genes containing them, known as 'cancer genes'. However, the non-functional somatic variations out-number functional variations and remain as a major challenge. Recurrent somatic variations are thought to be cancer drivers but they are present in only a small fraction of patients.
Methods:
We performed an extensive analysis of amino acid substitutions (AASs) from 6,861 cancer samples (whole genome or exome sequences) classified into 30 cancer types and performed pathway enrichment analysis. We also studied the overlap between the cancers based on proteins containing harmful AASs and pathways affected by them.
Results:
We found that only a fraction of AASs (39.88 %) are harmful even in known cancer genes. In addition, we found that proteins containing harmful AASs in cancers are often centrally located in protein interaction networks. Based on the proteins containing harmful AASs, we identified significantly affected pathways in 28 cancer types and indicate that proteins containing harmful AASs can affect pathways despite the frequency of AASs in them. Our cross-cancer overlap analysis showed that it would be more beneficial to identify affected pathways in cancers rather than individual genes and variations.
Conclusion:
Pathways affected by harmful AASs reveal key processes involved in cancer development. Our approach filters out the putative benign AASs thus reducing the list of cancer variations allowing reliable identification of affected pathways. The pathways identified in individual cancer and overlap between cancer types open avenues for further experimental research and for developing targeted therapies and interventions.
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