Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreLung cancer is the leading cause of cancer-related deaths in the US, and alterations in the tumor suppressor gene TP53 are the most frequent somatic mutation among all histologic subtypes of lung cancer. Mutations in TP53 frequently result in a protein that exhibits not only loss of tumor suppressor capability but also gain of oncogenic function (GOF). The canonical p53 hotspot mutants R175H and R273H, for example, confer upon tumors a metastatic phenotype in murine models of mutant p53. To our knowledge, GOF phenotypes of the less often studied V157, R158, and A159 mutants which occur with higher frequency in lung cancer compared with other solid tumors have not been defined. In this study, we aimed to define whether the lung mutants are simply equivalent to full loss of the p53 locus, or whether they additionally acquire the ability to drive new downstream effector pathways. Using a publicly available human lung cancer dataset, we characterized patients with V157, R158, and A159 p53 mutations. Additionally, we show here that cell lines with mutant p53-V157F, p53-R158L, and p53-R158P exhibit a loss of expression of canonical wildtype p53 target genes. Furthermore, these lung-enriched p53 mutants regulate genes not previously linked to p53 function including PLAU. Paradoxically, mutant p53 represses genes associated with increased cell viability, migration, and invasion. These findings collectively represent the first demonstration that lung-enriched p53 mutations at V157 and R158 regulate a novel transcriptome in human lung cancer cells and may confer de novo function. SOURCE: Priyankara,J,Wickramasinghe (priyaw@wistar.org) - Genomics The Wistar Institute
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team