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1.
Cell ; 170(3): 577-592.e10, 2017 Jul 27.
Artigo em Inglês | MEDLINE | ID: mdl-28753431

RESUMO

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.


Assuntos
Neoplasias/genética , Neoplasias/patologia , Interferência de RNA , Linhagem Celular Tumoral , Biblioteca Gênica , Redes Reguladoras de Genes , Humanos , Complexos Multiproteicos/metabolismo , Neoplasias/metabolismo , Oncogenes , RNA Interferente Pequeno , Transdução de Sinais , Fatores de Transcrição/metabolismo
2.
bioRxiv ; 2024 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-39091817

RESUMO

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci.

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