The CTD2 initiative seeks novel insights into cancer etiology that can be developed and in the future applied to improve therapeutic strategies. To achieve this goal, each center utilizes a distinct array of advanced computational and functional systems biology approaches. These methods allow reconstruction of cell-context specific gene networks that underlie each cancer subtype. The CTD2 Centers gain power from having both complementary and reinforcing expertise. Highlighted below are a few of the methodologies used by CTD2 members:

  • Bioinformatics – Computational analysis is applied to large genomic datasets to make predictions and hypotheses about biologically relevant phenotypes that can be tested experimentally.
  • Chemical genetics –Small-molecules are used to probe biological pathways and discover possible therapeutic targets. This approach may also yield small-molecule compounds with therapeutic potential. Small-molecules perturb cellular pathways in real time, providing experimental data that cannot be gathered from traditional genetics means.
  • Genome-wide gain-of-function – Gain-of-function technologies, including cDNA expression libraries and CRISPRa, are useful for identifying oncogenes and/or genes whose overexpression either initiates or suppresses cancerous transformation.
  • Genome-wide loss-of-function – Loss-of-function experimental approaches, including RNAi and CRISPR/cas9 or CRISPRi, are used to find genes upon which tumors are dependent for survival.
  • Protein-protein interactions – Perturbation of protein networks is used to map critical cellular pathways and helps inform therapeutic strategies.
  • In vivo gain- and loss-of-function models – Expansion of cell culture findings into animal models is important for determining which genes and genetic alterations are relevant in an organism.

Data generated by CTD2 Network members can be found on the CTD2 Data Portal.Opens in a New Tab

Last updated: May 05, 2016