Publications

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November 09, 2017
Nature

CTD2 scientists at UCSF (1), Broad Institute, and TGen have identified that drug-tolerant persister cancer cells from multiple tumor types that survive chemotherapy were found to be vulnerable to chemical inhibition or genetic loss of function of GPX4.

September 25, 2017
Oncogenesis

Scientists found that overexpression of PRAS40 in lung adenocarcinoma and cutaneous melanoma was associated with poor prognosis. This study describes a novel protein interaction signaling node where PRAS40 can increase NF-κB transcriptional activity through physical association with P65.

September 22, 2017
Nature Communications

Scientists use hydrocarbon peptide stapling to develop cell permeable and stabile peptides capable of blocking RAB25-FIP complex formation. These peptides inhibit RAB25-depenent (pro- and anti-tumorigenic) phenotypes in cancer cells.

August 24, 2017
Database

The CTD2  Dashboard is an interactive web interface which compiles conclusions with associated supporting evidence. This open access resource makes the data findable, accessible, interoperable and reusable to both computational and non-computational experts. 

August 23, 2017
Cell Systems

CTD2 scientists developed an Onco-GPS tool—a data-driven approach useful in establishing relationships—to explore cancers with altered RAS/MAPK. These components help to map individual samples onto a novel visual paradigm and strategize therapy against cancers with well-defined oncogenic lesions.

August 03, 2017
BioRxiv

CTD2 researchers at UCSF-1 present a quantitative map linking the influence of chemotherapeutic agents to tumor genetics. This chemical-genetic interaction map can aid in identifying new factors that dictate responses to chemotherapy and prioritize drug combinations.

July 27, 2017
Cell

Scientists have developed a cancer dependency map by combining off-target effects of RNAi and genomic characterization information across 501 cancer cell lines. The map facilitates identification and prioritization of therapeutic targets by predicting the genes essential for cell viability.

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