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Studying clonal dynamics in response to cancer therapy using high-complexity barcoding.

Hyo-eun C Bhang1, David A Ruddy2, Viveksagar Krishnamurthy Radhakrishna1

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|April 8, 2015
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Summary
This summary is machine-generated.

Cancer resistance often stems from pre-existing cells, not new mutations. A new barcoding tool, ClonTracer, tracks cancer cells to reveal that resistant clones are usually present before treatment begins.

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Therapeutic resistance in cancer is a major clinical hurdle.
  • Intratumoral heterogeneity is implicated as a driver of resistance.
  • Distinguishing pre-existing versus de novo resistance mechanisms is challenging due to technological limitations.

Purpose of the Study:

  • To develop a high-resolution method for tracking cancer cell populations under drug treatment.
  • To investigate the origin of cancer therapeutic resistance (pre-existing vs. de novo).
  • To quantitatively assess combination therapies for suppressing resistant clones.

Main Methods:

  • Development of a high-complexity barcode library named ClonTracer.
  • High-resolution tracking of over one million cancer cells during drug treatment.
  • Application in two clinically relevant cancer models.

Main Results:

  • The majority of resistant cancer clones originated from small, pre-existing subpopulations.
  • These pre-existing clones selectively survived therapeutic challenges.
  • ClonTracer enabled quantitative evaluation of combination treatments against resistant clones.

Conclusions:

  • Resistant cancer clones are predominantly present before therapy initiation.
  • Up-front combination therapies targeting non-overlapping resistance mechanisms are recommended.
  • ClonTracer is a valuable tool for optimizing cancer treatment strategies and developing curative combination therapies.