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 language | English |
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| Qualification | Doctor of Philosophy |
| Awarding Institution |
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| Supervisors/Advisors |
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| Award date | 10 Apr 2026 |
| Place of Publication | Maastricht |
| Publisher | |
| Print ISBNs | 9789465342993 |
| DOIs | |
| Publication status | Published - 10 Apr 2026 |
Keywords
- Lung cancer
- Personal care
- Immunity regulation
- Prediction model
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