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Updated: Apr 15, 2026
VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
Published on: December 28, 2015
Studying clonal dynamics in response to cancer therapy using high-complexity barcoding
Hyo-eun C Bhang1, David A Ruddy2, Viveksagar Krishnamurthy Radhakrishna1
1Oncology Disease Area, Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.
Abstract:
Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.
Insights
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.
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.
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