domingo, 9 de julio de 2017

Divide and Conquer: The Molecular Diagnosis of Cancer - National Cancer Institute

Divide and Conquer: The Molecular Diagnosis of Cancer - National Cancer Institute

National Cancer Institute

Divide and Conquer: The Molecular Diagnosis of Cancer

April 13, 2015, by Louis M. Staudt, M.D., Ph.D.
Louis M. Staudt, M.D., Ph.D.
Dr. Louis Staudt
NCI Center for Cancer Genomics
Owing to advances in our ability to sequence and understand the human genome, traditional descriptions of cancer are being superseded by a new classification framework that focuses on the genetic abnormalities and molecular derangements of malignant tumors. This conceptual transformation has the potential to alter diagnostic categories, enhance treatment strategies, enable early detection and prevention, and improve outcomes for cancer patients. This precision medicine approach to cancer has already led to new treatments that are tailored to the particular molecular abnormalities that cause cancer in individual patients.
NCI's Center for Cancer Genomics (CCG) was constituted in 2012 to promote this transformation in cancer diagnosis and treatment through the application of genomics. By coordinating the efforts of many committed investigators, CCG hopes to provide data and resources that will enable cancer researchers worldwide.
Key to our mission is the identification of projects that address specific current needs in cancer research that are optimally achieved by a concerted “team science” approach. Recent examples include The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research to Generate Effective Treatments (TARGET), which aim to derive a catalog of recurrent genetic and epigenetic alterations in adult and pediatric cancers, respectively.
Cancer genomics can be conceptually divided into three sub-disciplines – structural genomics, functional genomics, and computational genomics – and CCG fosters research in each of these areas.
Structural genomics – the “parts list” of genetic abnormalities in cancer – has been placed on a solid footing by TCGA and TARGET. However, many of the genetic aberrations that drive cancer are only present in a small percentage of individuals, and the efforts to date have not revealed all of these. Most importantly, we have yet to adequately address the relationship between genetic changes in cancer cells and the clinical behavior of the disease. By deploying genomic methodologies in the context of clinical trials supported by the NCI, CCG seeks to answer such questions as:
  • Will the cancer progress slowly or aggressively?
  • Will it respond to particular treatments?
  • Will it metastasize?
Functional genomics refers to genome-wide methods to manipulate the expression or activity of genes in cancer cells and then observe the consequence on cancer cell phenotypes such as proliferation, viability, and metastatic spread. One method uses RNA interference to reduce the expression levels of individual genes but newer methods use the bacterial CRISPR-Cas9 system to achieve the same end. Broad interrogation of cancer biology can also be achieved using libraries of small drug-like molecules that inhibit important signaling and regulatory pathways in the cancer cell. CCG promotes the application of these methods in a systematic, genome-wide fashion through the Cancer Target and Driver Discovery Network (CTD2) .
Computational genomics has emerged as a discipline to integrate the massive genomic data generated by current high-throughput technologies so as to derive new insights into the cancer process. Mathematicians, computer scientists, and statisticians bring new tools and techniques to bear on these datasets in order to relate the molecular features of cancer to biological and clinical features of the disease. Advanced analytical methods are necessary to appropriately merge data derived from different genomic technologies, ultimately leading to the new molecular taxonomy of cancer envisioned above.
A core principle of computational genomics is data sharing, since data from one research project can be reused and combined with new data in another project to gain additional knowledge. CCG fosters data sharing by creating a cancer genomics data system termed the NCI Genomics Data Commons (GDC) GDC will integrate both molecular and clinical data from thousands of cancer patients, allowing researchers to derive new hypotheses to guide their research.
CCG's mission is to synthesize research in different fields of cancer genomics—structural, functional, and computational—with the goal of improving patient outcomes. As a resource for cancer genomics researchers around the world, CCG will help usher in a new age of precision medicine.

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