Structural and Dynamic Analyses of Pathogenic Variants in PIK3R1 Reveal a Shared Mechanism Associated among Cancer, Undergrowth, and Overgrowth Syndromes

Life (Basel). 2024 Feb 23;14(3):297. doi: 10.3390/life14030297.

Abstract

The PI3K enzymes modify phospholipids to regulate cell growth and differentiation. Somatic variants in PI3K are recurrent in cancer and drive a proliferative phenotype. Somatic mosaicism of PIK3R1 and PIK3CA are associated with vascular anomalies and overgrowth syndromes. Germline PIK3R1 variants are associated with varying phenotypes, including immunodeficiency or facial dysmorphism with growth delay, lipoatrophy, and insulin resistance associated with SHORT syndrome. There has been limited study of the molecular mechanism to unify our understanding of how variants in PIK3R1 drive both undergrowth and overgrowth phenotypes. Thus, we compiled genomic variants from cancer and rare vascular anomalies and sought to interpret their effects using an unbiased physics-based simulation approach for the protein complex. We applied molecular dynamics simulations to mechanistically understand how genetic variants affect PIK3R1 and its interactions with PIK3CA. Notably, iSH2 genetic variants associated with undergrowth destabilize molecular interactions with the PIK3CA receptor binding domain in simulations, which is expected to decrease activity. On the other hand, overgrowth and cancer variants lead to loss of inhibitory interactions in simulations, which is expected to increase activity. We find that all disease variants display dysfunctions on either structural characteristics or intermolecular interaction energy. Thus, this comprehensive characterization of novel mosaic somatic variants associated with two opposing phenotypes has mechanistic importance and biomedical relevance and may aid in future therapeutic developments.

Keywords: PI3K; PROS; genomic data interpretation; genomics; overgrowth; precision medicine; undergrowth.

Grants and funding

This research was partly completed with computational resources and technical support provided by the Research Computing Center at the Medical College of Wisconsin. This publication was supported in part by The Linda T. and John A. Mellowes Endowed Innovation and Discovery Fund and the Genomic Sciences and Precision Medicine Center of Medical College of Wisconsin.