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Updated: Aug 2, 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
Evolution of resistance during clonal expansion
Yoh Iwasa1, Martin A Nowak, Franziska Michor
1Department of Biology, Faculty of Sciences, Kyushu University, Fukuoka, Japan. yiwasscb@mbox.nc.kyushu-u.ac.jp
Abstract:
Acquired drug resistance is a major limitation for cancer therapy. Often, one genetic alteration suffices to confer resistance to an otherwise successful therapy. However, little is known about the dynamics of the emergence of resistant tumor cells. In this article, we consider an exponentially growing population starting from one cancer cell that is sensitive to therapy. Sensitive cancer cells can mutate into resistant ones, which have relative fitness alpha prior to therapy. In the special case of no cell death, our model converges to the one investigated by Luria and Delbrück. We calculate the probability of resistance and the mean number of resistant cells once the cancer has reached detection size M. The probability of resistance is an increasing function of the detection size M times the mutation rate u. If Mu << 1, then the expected number of resistant cells in cancers with resistance is independent of the mutation rate u and increases with M in proportion to M(1-1/alpha) for advantageous mutants with relative fitness alpha>1, to l nM for neutral mutants (alpha = 1), but converges to an upper limit for deleterious mutants (alpha<1). Further, the probability of resistance and the average number of resistant cells increase with the number of cell divisions in the history of the tumor. Hence a tumor subject to high rates of apoptosis will show a higher incidence of resistance than expected on its detection size only.
Insights
Acquired drug resistance in cancer therapy is a significant challenge. This study models how resistant cells emerge, finding resistance probability increases with tumor size and cell division rates.
Area of Science:
- Oncology
- Mathematical Biology
- Genetics
Background:
- Acquired drug resistance limits cancer therapy effectiveness.
- The emergence dynamics of resistant tumor cells are not well understood.
- One genetic alteration can confer resistance to therapy.
Purpose of the Study:
- To model the emergence of drug-resistant cancer cells.
- To calculate the probability and number of resistant cells at detection size.
- To investigate the influence of mutation rate and cell division on resistance.
Main Methods:
- An exponentially growing cancer cell population model was used.
- The model considers sensitive cells mutating to resistant ones with relative fitness alpha.
- Calculations for resistance probability and mean resistant cell number were performed.
Main Results:
- Resistance probability increases with detection size (M) and mutation rate (u).
- For advantageous mutants (alpha>1), expected resistant cells increase with M.
- Apoptosis rates correlate with higher resistance incidence.
Conclusions:
- Tumor size and cell division are key factors in the emergence of drug resistance.
- Understanding these dynamics can inform cancer therapy strategies.
- Therapeutic interventions may need to account for tumor growth and mutation rates.
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