Year: 2024
Type: article
Abstract: Many human diseases have a strong association with diverse types of genetic alterations. These diseases include cancer, in which tumor genomes often harbor a complex spectrum of single-nucleotide alterations and chromosomal rearrangements that can perturb gene function in ways that remain poorly understood. Some cancer-associated genes exhibit a tremendous degree of mutational heterogeneity, which may impact disease initiation, progression, and therapy responses. For example, TP53 , the most frequently mutated gene in cancer, shows extensive allelic variation that leads to the generation of altered proteins that can produce functionally distinct phenotypes. Whether distinct variants of TP53 and other genes encode proteins with loss-of-function, gain-of-function, or otherwise neomorphic phenotypes remains both controversial and technically challenging to assess, particularly at the endogenous level. Here, we present a high-throughput prime editing “sensor” strategy to quantitatively assess the functional impact of diverse types of endogenous genetic variants. We used this strategy to screen the largest collection of endogenous cancer-associated TP53 variants assembled to date, identifying both known and novel alleles that impact p53 function in mechanistically diverse ways. Intriguingly, we find that certain types of endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. These include disease-relevant variants found in humans with cancer predisposition syndromes that encode altered proteins with unique molecular properties. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein-protein interactions, highlight the dangers of using exogenous overexpression systems to interpret pathogenic alleles, and establish a powerful computational and experimental framework for studying diverse types of genetic variants in their endogenous sequence context at scale.
Source: Nature Biotechnology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,290
Funders: National Science Foundation, Howard Hughes Medical Institute, U.S. Department of Health and Human Services, V Foundation for Cancer Research, Massachusetts Institute of Technology, Edward P. Evans Foundation, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, National Institutes of Health, Ludwig Center for Molecular Oncology, Ludwig Center at Harvard, National Human Genome Research Institute, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases
Awards: G2056243947, G2360436881, G3405342043, G418671524, Expanding the Scope of Base Editing, G4774430914, G5108852245, G6299160300, G6855349143, G818497676, G8824228350, G8863986071, Cancer Center Support Grant, Pre-doctoral Training in Fundamental Approaches to Biochemistry and Cell and Molecular Biology, Cancer Center Support (Core) Grant, Integrating Chemistry and Evolution to Illuminate Biology and Enable Novel Therapeutics, Center for Genomic Editing and Recording: Development and Application of Next-Generation Genome and Epigenome Editing Methods to Advance the Study and Treatment of Human Disease, Mutant p53 in Tumorigenesis, Invasion, and Metastasis
OpenAlex ID: W4392705635