Abstract Individuals with germline mutations in the tumor suppressor gene phosphatase and tensin homolog (PTEN), irrespective of clinical presentation, are referred to as PTEN hamartoma tumor syndrome (PHTS). PHTS confers a high risk of breast, thyroid and other cancers. Yet, PTEN mutations are found in up to 20% of individuals with autism spectrum disorder (ASD) and macrocephaly. What remains unclear is why mutations in one gene can lead to seemingly disparate phenotypes. Thus, we sought to identify differences in cancer- vs. ASD-associated PTEN mutations by investigating putative structural effects. We utilized a computational theoretical approach combining protein structure network (PSN), normal mode analysis (NMA), and elastic network models (ENMs) to interrogate 6 PTEN mutations from patients with PHTS-associated cancer, 6 mutations from those with ASD only, 4 mutations shared across both phenotypes, and 1 mutation with both ASD and cancer. Combined with in silico prediction methods we calculated structural stability changes induced by each mutation. All 6 cancer-associated mutations showed decreases in structure stability and increased dynamics across domain interface. In contrast, 5 of 6 ASD-associated mutations showed only localized destabilization. We coupled ENM-NMA with PSN and found PTEN R130G (cancer only) and R173C (shared in patients with both ASD and cancer), play a role in inter-residue signal propagation, indicating both residue positions are crucial to structural stability. Our data suggest that ASD-associated mutations affect local structural dynamics, whereas cancer-associated mutations mediate long-range perturbations significantly altering structural stability and salient communication pathways. These approaches lend insight into altered structural effects of germline PTEN mutations associated with PTEN-ASD and PTEN-cancer, potentially aiding in identification of specific mutations that contribute to each phenotype. Moreover, this work may illuminate the shared and separate molecular features that contribute to autism or cancer – providing a deeper understanding of genotype-phenotype relationships for germline PTEN mutations. The ability to accurately predict PTEN-ASD may spare patients the need to undergo high-risk cancer surveillance that is now performed in all with PHTS. Citation Format: Iris N. Smith, Stetson Thacker, Charis Eng. A structure network approach to predict the dynamics and structural stability effects of germline PTEN mutations associated with cancer versus autism phenotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4283.
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