The CTD² Network and Cancer Systems Biology Consortium organized a virtual symposium series titled “Multidisciplinary Approaches to Understand Cancer Treatment Resistance”. Please join us on 11/16, 11/17, 12/2, 12/16, and 12/17. Click here to view the registration website.
Publications
CTD2 scientists initiated MD Anderson Cell Lines Project (MCLP) and characterized the expression of ~ 230 proteins in >650 cell lines using reverse-phase protein arrays (RPPA). The data is available through an interactive web platform MCLP Data Portal.
Scientists validate the pre-mRNA splicing factor SF3B1 as a Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS (CYCLOPS) gene and SF3B1 can be exploited as a therapeutic target for cancer.
Researchers characterize the T-cell receptor for Merkel Cell Polyomavirus (MCPyV) and determine infiltration of MCPyV-specific T-cells leads to superior tumor control. This study supports inquiry of agents to improve T-cell homing and infiltration in Merkel cell cancer.
Scientists characterize the immune cell landscape of non-small cell lung cancer (NSCLC) and identify immune suppressive factors are frequently present in NSCLC. Identifying the dominant suppressive factors within a tumor subtype may improve immune-based therapeutics for patients.
Researchers find a novel role for the transcription factor ZEB2 in regulating proliferation and differentiation of acute myeloid leukemia using in vitro genome-scale shRNA and in vivo murine studies.
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.