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Updated: Jul 26, 2025

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Clinical trial designs for evaluating and exploiting cancer evolution
Alvaro H Ingles Garces1, Nuria Porta2, Trevor A Graham3
1Drug Development Unit, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, UK.
Abstract:
The evolution of drug-resistant cell subpopulations causes cancer treatment failure. Current preclinical evidence shows that it is possible to model herding of clonal evolution and collateral sensitivity where an initial treatment could favourably influence the response to a subsequent one. Novel therapy strategies exploiting this understanding are being considered, and clinical trial designs for steering cancer evolution are needed. Furthermore, preclinical evidence suggests that different subsets of drug-sensitive and resistant clones could compete between themselves for nutrients/blood supply, and clones that populate a tumour do so at the expense of other clones. Treatment paradigms based on this clinical application of exploiting cell-cell competition include intermittent dosing regimens or cycling different treatments before progression. This will require clinical trial designs different from the conventional practice of evaluating responses to individual therapy regimens. Next-generation sequencing to assess clonal dynamics longitudinally will improve current radiological assessment of clinical response/resistance and be incorporated into trials exploiting evolution. Furthermore, if understood, clonal evolution can be used to therapeutic advantage, improving patient outcomes based on a new generation of clinical trials.
Insights
Understanding cancer
Area of Science:
- Oncology
- Cancer Biology
- Evolutionary Medicine
Background:
- Drug resistance in cancer leads to treatment failure.
- Clonal evolution and collateral sensitivity can be modeled.
- Cell-cell competition influences tumor population dynamics.
Purpose of the Study:
- To explore novel therapeutic strategies for cancer treatment.
- To propose new clinical trial designs for steering cancer evolution.
- To leverage understanding of clonal dynamics for improved patient outcomes.
Main Methods:
- Modeling clonal evolution and collateral sensitivity.
- Investigating cell-cell competition for nutrients/blood supply.
- Utilizing next-generation sequencing for longitudinal clonal dynamics assessment.
Main Results:
- Preclinical evidence supports modeling herding of clonal evolution.
- Initial treatments can favorably influence subsequent responses.
- Exploiting cell-cell competition suggests intermittent dosing or treatment cycling.
Conclusions:
- Cancer evolution can be therapeutically exploited.
- New clinical trial designs are needed to incorporate evolutionary principles.
- Longitudinal assessment of clonal dynamics will enhance response/resistance evaluation.
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