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Related Concept Videos

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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Molecular pathways: extracting medical knowledge from high-throughput genomic data.

Theodore C Goldstein1, Evan O Paull, Matthew J Ellis

  • 1Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA.

Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
|February 23, 2013
PubMed
Summary
This summary is machine-generated.

Cancer molecular pathway analysis reveals that pathway activity signatures, not just gene expression, can predict patient outcomes. This "activitome" approach connects genomic events to clinical factors for better cancer prognostics.

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Area of Science:

  • Oncology
  • Genomics
  • Systems Biology

Background:

  • High-throughput genomic data (RNA expression, DNA copy number, mutation status, protein levels) offer insights into cancer's molecular pathways.
  • Genomic lesions and epigenetic modifications disrupt cellular pathways, leading to common tumor subtypes with similar phenotypes despite diverse alterations.

Purpose of the Study:

  • To explore how high-throughput genomic data can be translated into medical knowledge for prognostic and predictive cancer information.
  • To investigate the utility of pathway-based signatures over gene expression signatures for improved cancer diagnostics and prognostics.

Main Methods:

  • Analysis of high-throughput genomic data to understand molecular pathway structure in cancer.
  • Prediction of molecular entity activities using pathway analysis.
  • Development of the "activitome" concept, a composite of molecular activities, to link genomic events with clinical factors.

Main Results:

  • Genomic alterations can lead to concordant pathway activities and common tumor subtypes.
  • Pathway activity signatures show potential for providing prognostic and diagnostic cues.
  • The "activitome" framework connects genomic events to clinical factors to identify drivers of poor outcomes.

Conclusions:

  • Pathway-based signatures, or the "activitome," offer a promising approach for cancer prognostics and therapeutics.
  • This approach moves beyond traditional gene expression signatures to leverage higher-level biological information.
  • Translating genomic insights into clinical knowledge through pathway analysis can improve patient care for high-risk individuals.