Moonbase
← Back to Awards
NATIONAL CANCER INSTITUTENIH · NATIONAL CANCER INSTITUTENIH

Core 1: Functional Genomics and Proteomics

Krogan, Nevan J (Contact)·UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, CA·2022–2027·ACTIVE
Donate

INSTITUTION

UNIVERSITY OF CALIFORNIA, SAN FRANCISCO, CA

PRINCIPAL INVESTIGATOR

Krogan, Nevan J (Contact)

FUNDING

$266K

YEAR

2022

MOONBASE SCORE

Still being scored

LOADING MOONBASE SCORE

Abstract

CCMI v2.0 Core 1: Functional Genomics and Proteomics Core Core Lead: Nevan Krogan; Co-Investigator: Prashant Mali SUMMARY Systematic characterization of protein-protein interactions (PPIs) and genetic interaction networks of cancer drivers is critical for the identification of functional complexes for patient stratification and targeted cancer therapies. Proteomic approaches that determine PPIs and protein complex stoichiometry and topology can provide strategic insight into the dynamic cancer landscape and help guide tailored genetic screens to assess functional relevance of newly characterized PPIs. The Functional Genomics and Proteomics Core (Core 1) will provide the infrastructure and technical expertise essential to the completion of the overall CCMI objectives. With support of two Core facilities, the Functional Genomics and Proteomics Core will provide its expertise in CRISPR genetic screens (Institute for Genomic Medicine (IGM) Genomics Center, UCSD) and proteomic technologies (Thermo Fisher Scientific Proteomics Facility for Disease Target Discovery, UCSF, Quantitative Biosciences Institute (QBI), Gladstone Institute) for the generation of high-quality protein-protein (Aim 2; in support of Project 1) and genetic (Aim 1; in support of Project 2) interaction data, which will be integrated using systems biology approaches in Project 3 and Core 2. Our goal is to provide functional and structural characterization of cancer driver networks, model their functional interactions in three different cancers (breast, head and neck, lung cancer), and determine consequences of introducing point mutations. Finally, we will use a unique platform for Endogenous Network/Dynamic Structure (EN/DS) determination (Aim 3) that will use CRISPR-based genetics to introduce point mutations and FLAG-affinity tags into the endogenous loci of selected genes to study endogenous protein complex stoichiometry and structure using mass spectrometry and cryo-EM (in support of Project 1).

NATIONAL CANCER INSTITUTEU54ZCA1-RTRB-Fsystemsscientificselectedidentificationtargetbiosciencesbreasttailoredinstitutefishercompletionsummarysfdcharacterizationgeneticdiseasedeterminecomplexthermostructural

Are you the primary organization running this research?

The two tools below are built for the principal investigator & host institution behind this project.