Computational approaches to dissect immunotherapy response in breast cancer
O. Isaeva (TU Delft - Pattern Recognition and Bioinformatics)
Lodewyk Wessels – Promotor (TU Delft - Pattern Recognition and Bioinformatics)
Marleen Kok – Copromotor (Nederlands Kanker Instituut - Antoni van Leeuwenhoek ziekenhuis)
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Abstract
This thesis is dedicated to applications of high-throughput sequencing data analysis in immunology. Initially, the project included the part focusing on the T cell biology in the context of cancer, supervised by Dr. Pia Kvistborg, and the part focusing on the translational analysis of the breast cancer clinical trials, supervised by Dr. Marleen Kok, both under the general supervision of Dr. Lodewyk Wessels. Because of the COVID- 19 pandemic, Part 1 of this work focused instead on the T cell functionality in the context of COVID-19. As Dr. Kvistborg resigned in 2022, the larger part of the thesis, Part 2, was completed under the supervision of Dr. Kok and Dr. Wessels, the copromotor and promotor of this work.
Thus, this thesis describes bioinformatics approaches to the translational studies in immunology in the context of COVID-19 disease and breast cancer. We demonstrate that the use of genomic and transcriptomic data, including whole-exome and shallow whole-genome DNA sequencing and single-cell and bulk RNA sequencing, allows us to make conclusions about the underlying biology of the disease and identify biomarkers related to disease outcomes and response to treatment...