From biomarkers to clinical practice The value of consensus molecular subtypes in the management of non-metastatic colon cancer

Open Access
Authors
  • S. van de Weerd
Supervisors
  • J.P. Medema
  • J.H.J.M. van Krieken
Cosupervisors
  • J.M.L. Roodhart
  • E. Dekker
Award date 04-03-2025
ISBN
  • 9789464963236
Number of pages 223
Organisations
  • Faculty of Medicine (AMC-UvA)
Abstract
This thesis, From Biomarkers to Clinical Practice: the Value of Consensus Molecular Subtypes in the Management of non-Metastatic Colon Cancer, explores ways to improve treatment strategies for colon cancer by focusing on tumour biology, biomarkers, and patient stratification methods.
Although surgical resection followed by adjuvant chemotherapy is the standard treatment for stage II and III colon cancer, many patients face either overtreatment or inadequate treatment, leading to recurrence or metastasis. Existing biomarkers are limited in predicting chemotherapy responses. This thesis evaluates the potential of the Consensus Molecular Subtypes (CMS) classification, which divides CC into four subtypes based on gene expression, to refine clinical decision-making.
This thesis investigates histological markers, such as tumour-infiltrating lymphocytes and the tumour-stroma ratio, and their association with CMS subtypes, uncovering important genotype-phenotype correlations that could inform personalized treatment approaches. Furthermore, this thesis demonstrates that CMS classification is dynamic and can shift during tumour progression, highlighting its evolving nature in early-stage lesions.
Further analysis suggests that CMS subtypes could predict chemotherapy response, with CMS3 showing limited benefit from adjuvant chemotherapy. Additionally, the thesis explores the potential of neoadjuvant chemotherapy to provide earlier intervention and adequate response assessment, proposing that CMS classification could guide treatment decisions in this setting. However, challenges in molecular subtyping and radiologic staging present obstacles to widespread clinical application. The thesis calls for refining both techniques to improve treatment outcome predictions and advance personalized therapy for colon cancer.
Document type PhD thesis
Language English
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