Skip to main content
An official website of the United States government

About The Center for Cancer Genomics (CCG)

Mission Statement

CCG supports the development and application of genomic science to improve cancer diagnosis, treatments, and outcomes by bringing data and resources to the research community, investigating the molecular underpinnings of the disease, and identifying targets and strategies for precision medicine.

Recognizing the power of cancer genomics, NCI established the Center for Cancer Genomics (CCG) to develop and apply molecular characterization technologies to better understand cancer and diagnose and treat cancer patients. The scope of CCG’s research has since grown alongside the rapidly developing fields of large-scale molecular characterization technologies and computational analyses. Each CCG resource is developed with the research community in mind and serves as a springboard to further cancer knowledge.

CCG’s work in genomics may be categorized as:

  • Structural—characterizing mutations and other molecular features of cancers
  • Functional—elucidating the biological pathways underlying disease and informing precision medicine
  • Computational—improving data accessibility and analyses

Throughout these efforts, CCG strives to balance the protection of patients’ privacy with the need to access data for treatment or research.

CCG collaborates with other agencies, institutes, and investigators in the United States and around the world, seeking to answer important questions, such as:

  • What genomic profiling methodologies are able to resolve cancer into subtypes that are biologically distinct and respond differentially to therapy?
  • What new technologies for molecular profiling of tumors can add to our understanding of cancer biology?
  • Given the heterogeneity of cancer between patients and the heterogeneity of cell types within individual tumors, what type and scale of molecular profiling is needed to improve the diagnosis and treatment of cancer?
  • What recurrent genetic alterations and oncogenic mechanisms remain to be discovered in pediatric cancers, recalcitrant cancers and rare cancer subtypes?
  • What high-throughput methods can functionally characterize a myriad of genetic driver alterations, each which may be acting in nuanced ways upon different pathways?
  • What novel targets for cancer therapy will emerge from functional screens of cancer models using genetic and chemical perturbations?
  • Can new cell culture technologies such as organoids more accurately model complex diseases and provide actionable insights into genetic subtypes of cancer, rare and aggressive cancers, and cancers from understudied ethnic populations?
  • What analytical and visualization tools are needed to derive new knowledge from complex cancer datasets?
  • How can we democratize access and utilization of molecular and clinical data by the research community to help advance cancer research as a whole?

Center for Cancer Genomics Fact Sheet

Past Press Coverage on the Center for Cancer Genomics


CCG is comprised of two program offices:

The Office of Cancer Genomics (OCG)

OCG aims to advance the molecular understanding of cancers with the goal to improve patient outcomes. OCG supports multidisciplinary genomic research programs, as well as the development of next-generation cancer models and tools, to accelerate the translation of findings into the clinic and contribute to precision oncology. Data, analytical tools, and resources generated by OCG initiatives are made publicly available to further the collaborative goal of enabling precision oncology to improve patient care. OCG shares data through the Genomic Data Commons and various program databases (data matrices, data portal and dashboard) with the public.

The CCG Programs Office

Overseeing the genome characterization pipeline, the office partners with clinical trials and community oncology groups to collect tissue samples and clinical data, applies large-scale characterization technologies, performs integrative analyses on the resulting data by utilizing computational knowledge assembled by the Genomic Data Analysis Network, and shares the data with the research community and facilitates further analyses through the Genomic Data Commons.

  • Updated: