This thesis sprang from an interdisciplinary collaboration between the European Organisation for Research and Treatment of Cancer (EORTC), the Mathematical Institute of Leiden University, and the... Show moreThis thesis sprang from an interdisciplinary collaboration between the European Organisation for Research and Treatment of Cancer (EORTC), the Mathematical Institute of Leiden University, and the Leiden University Medical Center (LUMC) Department of Medical Oncology. Research was split into two separate parts. In Part I, the main goal was to provide modern efficacy thresholds for designing new phase II clinical trials for common histotypes of locally advanced or metastatic soft-tissue sarcoma patients. An update was necessary as well-established values were reported back in 2002 by the EORTC – Soft Tissue and Bone Sarcoma Group.Nowadays, there is a growing interest by the medical community in applying machine learning to predict clinical outcomes. In Part II, the main goal was to investigate the potential of existing and novel machine learning techniques compared with traditional statistical benchmarks for real-life clinical data (small/medium or large sample sizes, low- or high-dimensional settings) with time-to-event endpoints. Findings indicate an urgent need to pay closer attention to calibration (absolute predictive accuracy) of machine learning techniques to achieve a complete comparison with statistical models. Show less
This thesis contributes to understanding vascular tumors and other soft-tissue sarcomas. For epithelioid hemangioma a new translocation is described leading to truncation of the FOS protein. It was... Show moreThis thesis contributes to understanding vascular tumors and other soft-tissue sarcomas. For epithelioid hemangioma a new translocation is described leading to truncation of the FOS protein. It was found that this truncation leads to a longer half-life of the FOS protein, which could explain the tumorigenesis of epithelioid hemangioma. For patients with pseudomyogenic hemangioendothelioma the mechanism of action for treatment with telatinib is elucidated. For pseudomyogenic hemangioendothelioma a new cell-line based model was developed. With CRISPR/Cas9 the characterizing translocation could be inserted into the DNA of endothelial cells, thereby recapitulating multiple characteristics of pseudomyogenic hemangioendothelioma. Throughout this thesis computational biology was used to study vascular tumors and other soft-tissue sarcomas to gain new insights and find potential new treatment options. Show less
