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Related Concept Videos

Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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Gene expression profiling of diffuse large B-cell lymphoma.

Andreas Rosenwald1, Louis M Staudt

  • 1Metabolism Branch, Center for Cancer Research, National Cancer Institute, Building 10, 4N114, 9000 Rockville Pike, Bethesda, MD, USA. aroswald@mail.nih.gov

Leukemia & Lymphoma
|June 19, 2004
PubMed
Summary

Gene expression profiling reveals distinct subtypes of diffuse large B-cell lymphoma (DLBCL), including germinal center B-cell-like (GCB) and activated B-cell-like (ABC) DLBCL. These subtypes have different prognoses and underlying molecular mechanisms, guiding personalized treatment strategies.

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Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Diffuse large B-cell lymphoma (DLBCL) was initially considered a single entity.
  • Gene expression profiling identified distinct molecular subtypes within DLBCL.
  • These subtypes, GCB-DLBCL and ABC-DLBCL, exhibit different clinical outcomes and cellular origins.

Purpose of the Study:

  • To further characterize DLBCL heterogeneity using gene expression profiling.
  • To identify distinct molecular subgroups and their associated oncogenic events.
  • To develop a gene expression-based model for predicting patient survival in DLBCL.

Main Methods:

  • Gene expression profiling of DLBCL patient samples.
  • Analysis of 274 DLBCL cases to confirm and expand subgroup identification.
  • Identification of recurrent oncogenic events and their association with specific subgroups.
  • Development of a multivariate gene expression model to predict survival.

Main Results:

  • Confirmed the existence of GCB-DLBCL and ABC-DLBCL subtypes, with additional subgroups identified.
  • GCB-DLBCL showed specific oncogenic events (t(14;18), c-rel amplification), while ABC-DLBCL exhibited constitutive NF-kappaB activation.
  • A 17-gene multivariate model stratified DLBCL patients into quartiles with significantly different 5-year survival rates (73% to 15%).

Conclusions:

  • DLBCL comprises pathogenetically distinct molecular subtypes.
  • Gene expression signatures reflect key biological features like cell of origin, proliferation, and immune response.
  • Molecular subtyping and gene expression profiling hold promise for integrating diagnosis and guiding personalized treatment selection in DLBCL.