| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Kesmir, Can | |
| dc.contributor.author | Groeneveld, Reinier | |
| dc.date.accessioned | 2023-11-16T00:00:47Z | |
| dc.date.available | 2023-11-16T00:00:47Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/45534 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | Melanoma is one of the most immunogenic tumours and has the greatest potential to be treated by immune
checkpoint blockade (immunotherapy). Tumour mutational burden (TMB, expressed as somatic mutations per
MB coding DNA) is suggested as a good marker for prognosis of immunotheraphy. Still, it is not enough to explain
why less than half of all patients respond to immunotherapy. We focussed on getting better insight into other factors that shape
the outcome of an immunotherapy. | |
| dc.title | A computational approach to identify biomarkers for lack of
response to immunotherapies. | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Molecular and Cellular Life Sciences | |
| dc.thesis.id | 986 | |
