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Improvement of personalized lung cancer care: integrating immunological insights and precision medicine

Research output: ThesisDoctoral ThesisInternal

31 Downloads (Pure)

Abstract

Lung cancer is difficult to treat because every patient's tumor is unique. A common test that doctors use to decide on immunotherapy can be misleading, as it only looks at a tiny part of the tumor and may not tell the whole story. This thesis also compared two types of radiation and found that proton therapy did not trigger stronger immune responses than standard radiation. To improve treatment selection, miniature replica tumors were developed in the lab from patient samples. These replicas successfully predicted how individual patients would respond to chemotherapy. Additionally, clues in the blood might help forecast patient outcomes, though this approach is not yet ready for routine use. Ultimately, this research aims to move away from one-size-fits-all treatments and toward matching each patient with the therapy most likely to work for their specific type of cancer.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Maastricht University
Supervisors/Advisors
  • de Ruysscher, Dirk, Supervisor
  • Vooijs, Marc, Supervisor
  • Vaes, Rianne D.W., Co-Supervisor
Award date10 Apr 2026
Place of PublicationMaastricht
Publisher
Print ISBNs9789465342993
DOIs
Publication statusPublished - 10 Apr 2026

Keywords

  • Lung cancer
  • Personal care
  • Immunity regulation
  • Prediction model

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