Publications
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
Metabolic profiling of serum samples indicated an increase in kynurenine in melanoma and renal cell carcinoma patients treated with immune-checkpoint inhibitor, nivolumab. An increase in kynurenine, a product of tryptophan catabolism, correlates with worse overall survival.
Scientists at the Broad Institute CTD2 Center identified 6-phosphogluconate dehydrogenase, a cytosolic enzyme as a link between carbohydrate metabolism and protein secretion.
A review article on understanding ovarian cancer at the protein-level using large-scale proteomic technologies and proteomic studies.
CTD2 scientists at UCSF showed that neuroepithelial stem cells derived from normal induced pluripotent stem cells could be a powerful experimental resource to evaluate genetic mutations in medulloblastoma.
Scientists at Johns Hopkins University showed that E-cadherin is an essential factor in the seeding phases of metastasis in invasive ductal carcinomas. This is mediated by limiting reactive oxygen-mediated apoptosis.
CTD2 scientists show that metformin suppresses the expression of head and neck squamous cell carcinoma (HNSCC) stem cell programs, causes loss of expression of cancer stem cell markers, and promotes terminal differentiation. This study informs the selection of patients at risk of developing HNSCC.
This study shows that transient overexpression of cyclin E in mammary epithelial cells generated chromosomal copy number alterations (CNAs) signatures. These CNAs can be translated to changes in gene expression patterns that drive tumor growth.
Small-molecule and genome-scale CRISPR knock-out screens revealed that receptor tyrosine kinases and small heterodimer partner2 are vulnerabilities in rhabdoid tumor cell lines.
Scientists at UCSF developed a new analytical framework, GI manifold, for mapping and understanding genetic interactions. This approach describes the transcriptional states that a cell can occupy upon perturbation and could help in identifying synthetic lethal genetic interactions in cancer.
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