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Tracking Cancer Evolution through the Disease Course.

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Cancer evolution involves tumor cells adapting to pressures like treatment. TRACERx studies track this adaptation in lung and kidney cancers, revealing new ways to detect minimal residual disease.

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Area of Science:

  • Oncology
  • Cancer Genomics
  • Evolutionary Biology

Background:

  • Cancer is characterized by intratumor heterogeneity, driven by genomic instability and epigenetic changes.
  • Tumor cells compete under dynamic selection pressures, adapting to challenges like immune surveillance and therapy.
  • Understanding cancer evolution is crucial for improving patient outcomes and developing effective treatments.

Purpose of the Study:

  • To investigate the relationship between intratumor heterogeneity and patient outcomes in cancer.
  • To track cancer evolution from early to late stages and through therapy using longitudinal sampling.
  • To detail evolutionary processes in the tumor and immune microenvironment of specific cancer types.

Main Methods:

  • Integrating multiregion sequencing of primary tumors.
  • Longitudinal sampling of a prospectively recruited patient cohort.
  • Tracking cancer evolution from early- to late-stage disease and through therapy.

Main Results:

  • Detailed evolutionary processes in non-small cell lung cancer and clear-cell renal cell carcinoma.
  • Demonstrated the potential therapeutic utility of targeting clonal neoantigens.
  • Highlighted ctDNA detection as a tool for minimal residual disease detection.

Conclusions:

  • Cancer evolution is a dynamic process influenced by selection pressures.
  • TRACERx studies provide insights into tumor evolution and immune microenvironment interactions.
  • Targeting clonal neoantigens and using ctDNA hold promise for future cancer therapies and early detection.