Job description:
The specific project that you would be mainly working on is related to BAP1 specific cancers (i.e. uveal melanoma, cholangiocarcinoma, renal cell carcinoma) and seeks to develop specific therapies for the treatment of tumors with BAP1 loss in an interdisciplinary consortium where we are responsible for the bioinformatics / data science tasks mainly focusing on digital pathology (i.e. analyzing histologic slides via convolutional neural networks). Renal cell carcinoma, uveal melanoma, cholangiocarcinoma and malignant mesothelioma are cancer entities with frequent mutations in the tumor suppressor gene BAP1 and associated with tumor aggressiveness, metastasis and poor patient prognosis. Unfortunately, there are currently no specific therapies for the treatment of tumors with BAP1 loss. We have strong evidence that inactivating mutations in BAP1 are involved in new signaling pathways. Thus, we will evaluate targeting vulnerabilities of these signaling pathways in vitro using cell lines, in vivo using mouse models and ex vivo using patient-derived organoids as pre-clinical models.
Furthermore, we will evaluate whether BAP1 loss correlates with specific biomarkers by immunohistochemistry (IHC) in human tumor samples and develop predictive digital biomarkers via multimodal data integration. This would facilitate identifying patients who could potentially benefit from these novel therapies and provide evidence for the use of BAP1 as a biomarker of response in precision medicine. In this project, where we are responsible for the bioinformatics / data science, tasks mainly focusing on digital pathology (i.e. analyzing histologic slides via convolutional neural networks). You would work into an interdisciplinary consortium of renowned partners and help to detect signatures / develop digital biomarkers in whole slide images that support the stratification of patients.