The CTD² Network sponsored Dialogue on Reverse Engineering and Assessment Methods (DREAM) Challenges powered by Sage Bionetworks; invites the community to develop predictive bioinformatics models. Visit the CTD² Pancancer Chemosensitivity DREAM Challenge registration site for details.
Publications
556 Publications Available
March 04, 2019
Journal for ImmunoTherapy of Cancer
CTD2 scientists at the University of California, San Francisco showed that α-PD-1/α-TGFβ combinatorial therapy could be a potential treatment option for squamous cell carcinomas with high mutational load and form the basis for the clinical trial NCT02947165.
March 04, 2019
Current Opinion in Genetics & Development
March 01, 2019
Molecular & Cellular Proteomics
Researchers developed PTMsigDB, a database of post-translational modifications, such as site-specific phosphorylation signatures of kinases, perturbations, and signaling pathways, curated from more than 2,500 publications.
March 01, 2019
Experimental Hematology
Review on using human pluripotent stem cells derived natural killer cells and macrophages as a novel cell-based approach for cancer immunotherapy.
March 01, 2019
Trends in Molecular Medicine
March 01, 2019
Trends in Cancer
Review article discusses the mechanisms of resistance developed to cancer therapy and advantages of using intermittent therapies to maintain a balance between therapy-sensitive and therapy-resistant populations.
February 18, 2019
Molecular Cancer Research
Scientists at DFCI identified that genes MCL1 and DEDD contribute to aggressive urothelial carcinoma.
February 13, 2019
Cell Metabolism
Systematic analyses of genetic and pharmacologic screening revealed that inhibition of deubiquitinases and glutathione synthesis blocks tumor growth.
February 12, 2019
Nature Communications
Scientists show that loss of PIK3R1 in ovarian cancers activates AKT and JAK2/STAT3 signaling. These studies provide a rationale for mechanism-based combinatorial therapy with AKT and STAT3 inhibitors.
February 12, 2019
Cancer Research
DFCI scientists integrated data from large-scale RNAi, CRSIPR-Cas9, and small-molecule screens of malignant rhabdoid tumor cell lines and identified MDM2 and MDM4 as actionable targets.
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