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
CTD2 scientists at Stanford University developed SCIMET, an analytical framework that provides quantitative measurement of dynamics of metastasis in a patient-specific manner; indicates early dissemination of colorectal cancer in the majority of the patients.
CTD2 scientists at OHSU demonstrated that sequential therapy with PARP and either WEE1 or ATR inhibitors is effective and potentially less toxic in multiple relevant cancer models.
Integrative genomic analyses of expression profiling, CRISPR-Cas9 and ORF/cDNA, identifies cell-essential genes suppressed by BET-bromodomain inhibition. The study suggests the use of cell-cycle inhibitors in combination with BET-bromodomain inhibitors to treat MYC-amplified medulloblastoma.
Columbia CTD2 researchers developed ADVOCATE, a computational model to analyze gene expression data of epithelial and stromal pancreatic ductal adenocarcinoma samples. These studies indicated a novel classification signature which could facilitate the development of precision oncology approaches.
Scientists at the UCSD CTD2 Center showed that epigenetic dysregulation and silencing are associated with chromatin repression and aberrant hypermethylation at the transcription start site in HPV-related oral cancers; independent of CpG island and is associated with MYC pathway activation.
CTD2 researchers showed that ovarian cancer patients with CD3+ tumor infiltrating lymphocytes and homologous recombination deficiency have improved survival.
Researchers profiled 225 metabolites in 928 cell lines from more than 20 cancer types in the cancer cell line encyclopedia using liquid chromatography – mass spectrometry.
Cancer Cell Line Encyclopedia, provides a detailed genetic characterization of human cancer cell lines from gene to transcript to protein. Integration of this data with chemical and genetic perturbation data reveals potential therapeutic targets and biomarkers for cancer.
Perspective on the role of tumor immune compartment, microenvironment, heterogeneity, and epigenetics during cancer pathogenesis and development of treatment resistance.
Texomer, a statistical approach, improves molecular characterization of cancer samples by integrating cancer genome and transcriptome sequencing data obtained from patient tissue samples.