bioRxiv ScienceSearch

Biology subjects

Mock, A.

Publications and source records attributed to Mock, A..

2 recordsLinked to original sources

Primary and recurrent glioma patient-derived orthotopic xenografts (PDOX) represent relevant patient avatars for precision medicine

Patient-derived cancer models are essential tools for studying tumor biology and preclinical interventions. Here, we show that glioma patient-derived orthotopic xenografts (PDOXs) enable long-term propagation of patient tumors and represent clinically relevant patient avatars. We created a large collection of PDOXs from primary and recurrent gliomas with and without mutations in IDH1, which retained histopathological, genetic, epigenetic and transcriptomic features of patient tumors with no mouse-specific clonal evolution. Longitudinal PDOX models recapitulate the limited genetic evolution of gliomas observed in patient tumors following treatment. PDOX-derived standardized tumor organoid cultures enabled assessment of drug responses, which were validated in mice. PDOXs showed clinically relevant responses to Temozolomide and to targeted treatments such as EGFR and CDK4/6 inhibitors in (epi)genetically defined groups, according to MGMT promoter and EGFR/CDK status respectively. Dianhydrogalactitol, a bifunctional alkylating agent, showed promising potential against glioblastoma. Our study underlines the clinical relevance of glioma PDOX models for translational research and personalized treatment studies.

cancer biology

Integrative kinomics reveals kinase-driven subtypes of gastric adenocarcinomas with sunitinib as a potential common inhibitor

Molecular subtyping of tumors promises a personalized stratification into different treatment regimens. In gastric adenocarcinoma, the four molecularly defined subtypes chromosomal instable (CIN), microsatellite unstable (MSI), genomically stable (GS) and EBV-positive subtype have been proposed. Following an integrative kinomics approach this computational analysis aimed to predict the best kinase inhibitor for every molecular subtype of gastric adenocarcinomas using publicly available TCGA data (n=404). Intriguingly, using the regulatory network of gastric cancer to estimate protein activity, 43% of all samples could be identified to be kinase-driven. These samples were divided into three clusters with mutually exclusive kinase activities that were independent of the established molecular subtypes. Integrating the pattern of kinase overexpression with an unsupervised target landscape of 37 approved clinical kinase drugs revealed that sunitinib had the best target spectrum across the activated kinases in all three sample clusters. Future work is warranted to validate the kinase-driven subsets of gastric cancer and sunitinib as a potential common inhibitor.

cancer biology