Included here is a list of publications from OCG programs. All published data are available to the research community through the program-specific data matrices.
* denotes publications from the CTD2 initiative that are results of intra-Network collaborations
Researchers developed a platform that integrates whole exome sequencing with high throughput drug screening in patient-derived tumor organoids. This platform has the potential to identify effective therapeutic strategies for patients where standard treatment options have been exhausted.
CTD2 scientists at Emory University have identified Aurora Kinase A as a novel H-Ras binding partner in enhancing MAPK signaling. This novel protein-protein interaction is a potential therapeutic target in cancer.
Scientists at Dana Farber have performed CRISPR-Cas9 drug resistance screens and identified that loss of KEAP1 expression negates inhibitors targeting RTK/MAPK pathways in Lung cancer. This finding may assist with treatment decisions in managing lung cancer.
CTD2 researchers at Dana Farber have identified the transcription factor ATXN1-CIC-ETS as a mediator of resistance to MAPK inhibitors in KRAS mutant pancreatic cancer cell lines using genome-scale CRISPR-Cas9 loss-Of-function screens.
CTD2 scientists at Dana Farber have identified the serine/threonine kinase family member NEK6 as a central mediator in restoring sensitivity to hormone ablation in prostate cancer xenograft models.
The OncoPPi network is a resource of experimentally determined physical protein-protein interactions that builds on cancer genomics for discovery and exploitation of cancer vulnerabilities.
MEDICI is a new computational method to predict the protein-protein interaction (PPI) essentiality which helps to prioritize PPIs for drug discovery.
Scientists at UTSW Medical Center identified Aurora Kinase A as a potential therapeutic target in NSCLCs with SMARCA4/BRG1 mutations
Emory researchers developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions.
FHCRC developed a tool which models gene centric dependencies across multiple genomic platforms. They demonstrated that this method could be used to identify genes essential to tumorigenesis in the pancreatic and lung adenocarcinoma patient cohorts from The Cancer Genome Atlas.