Mutational Analysis
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB36236 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:TP53, encoding for the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, have remained enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We generated isogenic human leukemia cell lines of the most common TP53 missense mutations using CRISPR/Cas9. Functional, DNA binding, and transcriptional analyses revealed loss-of-function (LOF) without GOF effects of missense mutations. Comprehensive mutational scanning of p53 single amino acid variants demonstrated that DNA-binding domain missense variants exert dominant-negative effects (DNE). In mice, DNE of p53 missense variants confer a selective advantage on hematopoietic cells upon DNA damage in vivo. Clinical outcomes in acute myeloid leukemia patients showed no evidence of GOF for TP53 missense mutations. These findings establish dominant-negativity as the primary unit of selection for TP53 missense mutations in myeloid malignancies.
2019-08-30 | GSE131592 | GEO
Project description:TP53, encoding for the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, have remained enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We generated isogenic human leukemia cell lines of the most common TP53 missense mutations using CRISPR/Cas9. Functional, DNA binding, and transcriptional analyses revealed loss-of-function (LOF) without GOF effects of missense mutations. Comprehensive mutational scanning of p53 single amino acid variants demonstrated that DNA-binding domain missense variants exert dominant-negative effects (DNE). In mice, DNE of p53 missense variants confer a selective advantage on hematopoietic cells upon DNA damage in vivo. Clinical outcomes in acute myeloid leukemia patients showed no evidence of GOF for TP53 missense mutations. These findings establish dominant-negativity as the primary unit of selection for TP53 missense mutations in myeloid malignancies.
2019-08-30 | GSE131484 | GEO
Project description:More than half of disease-causing missense variants are thought to lead to protein degradation, but the molecular mechanism of how these variants are recognized by the cell remains enigmatic. To approach this issue we have applied deep mutational scanning experiments to test the degradation of thousands of missense protein variants in large multiplexed experiments in cultured human cells. As a model protein we selected the ubiquitin-protein ligase Parkin, where known missense variants result in an autosomal recessive early onset Parkinsonism. The resulting mutational map comprises 9219 out of the 9300 (>99%) possible single-amino-acid substitution and nonsense Parkin variants. With a few notable exceptions, the majority of the destabilizing mutations are located within the structured domains of the protein, while the flexible linker regions are more tolerant to mutations. The cellular abundance data correlate with Parkin structural stability, evolutionary conservation, and separates known disease-linked variants from benign variants. Systematic mapping of degradation signals (degrons) shows that inherent primary degrons in Parkin largely overlap with regions that are highly sensitive to mutations. We identify a degron region proximal to the ACT element, which is enhanced by substitutions to hydrophobic residues. The vast majority of unstable Parkin variants are degraded through the ubiquitin-proteasome system and are stabilized at lowered temperatures. In conclusion, in addition to providing a diagnostic tool for rare genetic disorders, deep mutational scanning technologies have the potential to reveal both protein specific and general information on the specificity of the protein quality control network and the ubiquitin-proteasome system.
2024-01-31 | GSE254618 | GEO
Project description:Mutational classification of colorectal cancer
| PRJNA319429 | ENA
Project description:Mutational analysis of IVT mRNAs
| PRJNA924758 | ENA
Project description:Drug efflux is a common resistance mechanism found in bacteria and cancer cells. Although several structures of drug efflux pumps are available, they provide only limited functional information on the phenomenon of drug efflux. Here, we performed deep mutational scanning (DMS) on the bacterial ATP binding cassette (ABC) transporter EfrCD from Enterococcus faecalis to determine the drug efflux activity profile of more than 1400 single variants
2021-11-25 | GSE189399 | GEO
Project description:We report the transcriptome data produced from isogenic polymorphic p53 codon 72 iPSCs under doxorubicin treatment. By inserting BAC DNA into one allele of the heterozygous polymorphic p53 codon 72, each clone expressed a p53 protein encoding P72 or R72 from another allele in which it was not inserted. The transcriptional regulation of p53 target genes was compared between the isogenic lines under doxorubicin treatment.
2021-09-10 | GSE183668 | GEO
Project description:Immune checkpoint inhibitors are used to restore or augment antitumor immune response and show great promise in treatment of melanoma and other types of cancers. However, only a relatively small percentage of patients are fully responsive to immune checkpoint inhibition, mostly due to tumor heterogeneity and primary resistance to therapy. Both of these features are largely driven by accumulation of patient-specific mutations, pointing to the need for personalized approaches in diagnostics and immunotherapy. Proteogenomics integrates patient-specific genomic and proteomic data to study cancer development and resistance mechanisms, as well as tumor heterogeneity in individual patients. Here, we use a proteogenomic approach to characterize the mutational landscape of samples derived from four clinical melanoma patients at the genomic, proteomic and phosphoproteomic level. Integration of datasets enabled identification and quantification of an extensive number of sample-specific amino acid variants, among them many were not previously reported in melanoma. We detected a disproportional number of alternate peptides between treated and untreated (naïve) samples with a high potential to influence signal transduction. This is one of the first proteogenomic study designed to study the mutational landscape of patient-derived melanoma tissue samples in response to immunotherapy.
2022-02-16 | PXD028700 | Pride
Project description:Mutational inactivation of TP53 is a common event in cancer. Germline mutations in TP53 that inactivate this protein also occur in Li Fraumeni syndrome, which predisposes to early-onset cancer. In addition, there are dozens of other germline variants in TP53 that do not completely inactivate the function of this protein. In many cases studies have shown strong support for an impact of these lesser-functioning hypomorphs with increased cancer risk in humans and mouse models; however, the majority of these hypomorphs have yet to be categorized as pathogenic in clinical genetics databases. There is thus need for a functional assay to distinguish lesser-functioning hypomorphic p53 variants from wild type p53, or benign, fully-functional, variants. We report the surprising finding that two different African-centric genetic hypomorphs of p53, which occur in distinct functional domains of the protein, share common activities. We show that the Pro47Ser variant in the transactivation domain and the Tyr107His variant in the DNA binding domain both share increased propensity to misfold into a conformation specific for mutant p53. Moreover, cells and tissues with these variants show increased NF-B activity. We have identified a common gene signature from unstressed lymphocyte cell lines that is shared between these two, and other, genetic missense hypomorphs of TP53. We show that this gene signature successfully distinguishes wild type p53 and a benign p53 variant from lesser-functioning hypomorphic variants. These findings should allow us to better understand how hypomorphic variants contribute to cancer risk, and to better inform cancer risk in hypomorph carriers.
2023-03-01 | GSE209837 | GEO