Molecular Stratification of Somatic and Hereditary Cancers

A central goal of NCT is molecularly guided patient stratification as the basis for individualized treatment decisions in somatic and hereditary cancers. By leveraging the expertise of NCT, DKFZ and DKTK in multidimensional tumor characterization and molecular mechanism-based therapy, NCT has developed a standard for (1) comprehensive molecular profiling, (2) clinical interpretation of molecular data, (3) functional analysis of primary patient samples, (4) treatment decision making in molecular tumor boards, (5) longitudinal clinical data collection and (6) clinical trial design and conduct. This pipeline provides a framework for multiple clinical programs and is intertwined with translational research projects centered on understanding the functional consequences of molecular alterations, with the ultimate goal to incorporate functional genomic profiling and ex vivo treatment testing in the precision oncology workflow.

Research Profile Dresden

Personalized oncology through molecular stratification at NCT/UCC Dresden combines in-depth genomic characterization with additional layers of clinical specimen characterization. Broad subgenomic sequencing at the Core Unit for Molecular Tumor Diagnostics (CMTD) and comprehensive profiling within MASTER are provided and tailored to the specific needs in surgical, radiological and medical oncology. The newly established Preclinical Model Unit systematically develops and generates organoid and spheroid models for the functionalization of genomic alterations, drug testing, and functional screening supported by extensive expertise in Dresden. Exosomes and circulating tumor cells are explored as biomarkers for drug response and resistance in glioblastoma, gastrointestinal, and gynecological cancers.

Example from research

Seeking new therapies by tackling signaling pathways in melanoma

Evaluation of genetic cancer predisposition variants Classification of germline variants is of utmost importance for hereditary cancer, allowing for surveillance, treatment decisions, as well as for prevention. So far, approximately 30% of patients at risk have been identified and most variants identified are of unknown significance. The aims are as follows: (1) to participate and evaluate germline data in MASTER, INFORM, nNGM and others. (2) To study (a) acute leukemia of childhood, (b) pheochromocytomas and paragangliomas, (c) pancreatic cancer and other cohorts. (3) To perform functional validation of variants of uncertain significance (VUS) using model systems combining genetics, metabolomics and exposure to infection. (4) To perform in vitro assessment of targeted therapies for pathogenic germline variants. The aim is to improve health care for patients with a genetic disposition to cancer. A nationwide consortium named “Digital Network for Genetic Tumor Risk (DNGT)” has been started.

Chudasama et al., Nat Commun 2018; Richter et al., Genet Med 2019