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 at DFCI analyzed genome-scale loss-of-function datasets and identified adenosine deaminase acting on RNA as a gene dependency in subsets of lung cancer.
Scientists report that two myeloid leukemia cases with FMS-like tyrosine kinase (FLT3) fusions demonstrate mixed features of myelodysplastic and myeloproliferative syndromes; showed sensitivity to FLT3 inhibitors in ex vivo drug screening assays.
CTD2 scientists at Stanford University demonstrated that air-liquid interface patient-derived tumor organoid models retain the original tumor immune cells, enabling testing for personalized immunotherapy in cancer.
CTD2 researchers at Emory University identify novel role for large tumor suppressor 2, LATS2, as a regulator of the ASK1-mediated stress response pathway which may lead to new strategies to control cellular response to stress in normal cells and diseases.
UCSF scientists developed a bioinformatic approach, MAGNETIC, which integrates multi-omic data from cancer patients with pharmacogenomic data from cell lines into a small set of pathway-enriched gene modules. These modules connect tumor and cell line biomarkers and may inform therapeutic targets.
TARGET study associated RNA signatures of cytotoxic tumor-infiltrating lymphocytes with the presence of activated NK-/T-cells and suggested improved outcomes in newly diagnosed high-risk neuroblastoma patients with MYCN-NA tumor.
CTD2 scientists at Oregon Health and Science University performed genetic and small-molecule screens and identified CSF1R as a novel therapeutic target of acute myeloid leukemia.
Study demonstrates that EGFR and EGFRvIII cooperate through KRAS, to upregulate chemokine CCL2 and promote infiltration of macrophages in glioblastoma.
CTD2 scientists studied the functional consequences of missense mutations of cell surface protein kinase receptor, PDGFRA, identified from different tumor types. These studies identified a driver mutation in the extracellular domain of PDFRA that are resistant to PDFR inhibitors.