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Related Experiment Video

Updated: May 11, 2026

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening
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Improved risk stratification in myeloma using a microRNA-based classifier.

Ping Wu1, Luca Agnelli, Brian A Walker

  • 1Section of Haemato-Oncology, Institute of Cancer Research, Sutton, Surrey, UK.

British Journal of Haematology
|May 31, 2013
PubMed
Summary

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New microRNA (miRNA) profiling identifies distinct expression patterns in multiple myeloma (MM) molecular subgroups. A novel miRNA-based classifier improves risk stratification beyond current methods for MM patients.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Multiple myeloma (MM) is a complex blood cancer with varied patient outcomes.
  • Current staging systems like ISS/FISH and gene expression profiles (GEP) aid prognosis but require enhancement.
  • MicroRNAs (miRNAs) represent a newly discovered layer of gene regulation with potential diagnostic value.

Purpose of the Study:

  • To investigate miRNA expression profiles in MM patients.
  • To identify specific miRNA signatures associated with known MM molecular subgroups.
  • To develop and validate a novel miRNA-based classifier for MM patient risk stratification.

Main Methods:

  • Global miRNA profiling of 163 newly diagnosed MM patient samples.
  • Analysis of miRNA expression in relation to established MM molecular subgroups (4p16, MAF, 11q13 translocations).
Keywords:
genomic profilingmicroRNAmyelomaoutcome classifierrisk stratification

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  • Development of a two-miRNA (MIR17 and MIR886-5p) outcome classifier and validation against ISS/FISH and GEP data.

    • Main Results:

    • Distinct miRNA expression patterns were identified in specific MM molecular subgroups.
    • The developed miRNA classifier stratified patients into three distinct risk groups with significantly different overall survival (OS).
    • The miRNA classifier demonstrated improved prognostic power compared to ISS/FISH and was independent of GEP signatures.

    Conclusions:

    • MicroRNAs can be effectively integrated into molecular diagnostic strategies for multiple myeloma.
    • A novel miRNA-based classifier offers a powerful tool for improved risk stratification in MM patients.
    • This study highlights the potential of miRNAs in understanding MM biology and guiding clinical decisions.