Molecular Precision Oncology Program

Single cell sequencing technologies become more and more important for many research groups at the DKFZ. To address this need, the DKFZ founded the Single Cell Open Lab (scOpen Lab), which started operation in January 2018. The Molecular Precision Oncology Program supports the scOpen Lab by providing funding for the scOpen Lab staff. The scOpen Lab offers assisted access to instrumentation for processing cells and preparing the libraries for sequencing to all DKFZ groups.

Currently, commercial drop-seq workflows as well as tailored plate-based protocols are available to profile the genome, epigenome and transcriptome.
Contact: Dr. Jan-Philipp Mallm, j.mallm@Dkfz-Heidelberg.de

» DKFZ scOpenLab Homepage

The Genomics and Proteomics Core Facility (GPCF) at the DKFZ is a central research infrastructure providing access to sophisticated and expensive key technologies that are of critical relevance in biomedical science and which would otherwise not be accessible to the center’s research groups. Our services are open to external users subject to available capacities. Dedicated and trained personnel ascertain fast turnaround times of high-quality data and information. Quality standards have been developed to keep tight quality control during all processes. The table below presents all workflows currently established in the Sequencing Unit and the Microarray Unit.

Sequencing Unit

• Exome Sequencing
• Amplicon Sequencing
• Whole Genome Sequencing
• Whole Genome Bisulfite Sequencing
• RNA Sequencing
• Small RNA Sequencing
• Low Amount RNA Sequencing
• ChIP Sequencing
• Sequencing of Custom Libraries/Multiplexes

Microarray Unit

• Methylation Analysis (incl. FFPE)
• Hydroxymethylation Profiling
• mRNA Expression Profiling (incl. low quantity and FFPE)
• microRNA Profiling
• Genotyping (incl. FFPE)
• Kinase Activity Profiling

Contact
Dr. Stephan Wolf: s.wolf@dkfz-heidelberg.de
Dr. Melanie Bewerunge-Hudler: m.hudler@dkfz-heidelberg.de
» DKFZ GPCF Homepage

The availability and usage of large scale, high-throughput technologies such as next generation sequencing (NGS) has exploded in recent years. At the same time these technologies have found their way into direct patient care. All of these technologies generate large amounts of data that need to be managed and analyzed. The Omics IT and Data Management Core Facility (ODCF) at DKFZ supports scientists and physicians to securely store and analyze these data in a structured and efficient manner. On the one hand, we import, structure, store and analyze (alignment, variant calling) NGS data directly using our software OTP (www.otp.dkfz.de). On the other hand, in cooperation with the DKFZ IT-Core Facility, we operate a compute cluster with a large stack of pre-installed scientific software for scientists to perform custom analyses.

OTP is equipped with a graphical user interface allowing the scientist to keep an easy overview of their sequencing projects. Here we provide basic information about the samples (metadata) as well as quality measures concerning the data and results. In addition, the user interface displays all project members and allows the responsible PI to manage access rights and roles in a transparent manner.

All sequencing data produced by the Molecular Precision Oncology Program is automatically imported and managed by ODCF.

Contact: odcf-service@dkfz.de or i.buchhalter@dkfz.de

The application of next generation sequencing and other high-throughput screening techniques for precision oncology requires advanced bioinformatics methods for data analysis and the generation of interpretable results. Computational Oncology (CO, headed by D. Hübschmann) is a research group in the Molecular Precision Oncology Program (headed by S. Fröhling and P. Lichter) of the National Center for Tumor diseases (NCT) Heidelberg and the German Cancer Research Center (DKFZ). CO is responsible for (a) the bioinformatic analyses behind the Molecular Tumor Boards (MTBs) in several precision oncology programs as well as for (b) cohort analyses and unsupervised discovery projects.

a) MTBs and precision oncology programs: CO provides data analysis for DKTK/NCT-MASTER (Molecularly Aided Stratification for Tumor Eradication Research) as well as CATCH (Comprehensive Assessment of Clinical Features and Biomarkers To Identify Patients with Advanced or Metastatic Breast Cancer for Marker Driven Trials in Humans) and COGNITION (Comprehensive assessment of clinical features, genomics and further molecular markers to identify patients with early breast cancer for enrolment on marker driven trials). This involves basic steps of NGS data analysis including alignment and quality control (QC), as well as variant calling and pre-filtering of clinically interesting and/or targetable mutations. Starting from sets of somatic variants for each tumor, extensive annotation will cover matches in databases of drug targets, known cancer driver mutations and germline predisposition variants. Interpretation of variant sets will rank those that are potentially therapeutically relevant and associate them to systemic cancer treatments. Incorporating oncological expertise, the evidence level for each candidate mutation will then be determined from literature and clinical trial information.

b) Cohort analyses: CO is in charge of NGS analyses for projects covering a wide range of cancer entities as well as different data types. A major goal is the provision of standardized, state-of-the-art data processing and analysis workflows. Currently, CO is involved in the application and development of the following workflows for central and standardized data processing:
a. alignment of whole genome, whole genome bisulphite, exome, ChIP and RNA sequencing data (and variants of these technologies)
b. somatic variant calling of single nucleotide variants (SNVs) insertions and deletions (indels), structural variation (SVs), and copy number abberations (CNAs)
c. methylation calling

c) Furthermore, CO focuses on the development of resources to facilitate the exploration of high dimensional data sets, self learning cohort analysis tools, adoption of responsible and reproducible bioinformatics practices, and organizing training for clinical bioinformatics analysis together with the clinical bioinformatics team.

CO develops and maintains its code base in close collaboration with the Omics IT and Data Management Core Facility (ODCF, headed by I. Buchhalter) and the Applied Bioinformatics division (ABI, headed by B.Brors). In the framework of the MTBs, CO is intimately linked to the respective clinical divisions Translational Medical Oncology (TMO, headed by S. Fröhling) and Gynecologic Cancers / Breast Cancer (headed by A. Schneeweis).

 

Projects within the Molecular Precision Oncology Program were established to enable prospective multi-omic analyses, including, e.g., whole-genome and transcriptome sequencing, for individualized patient care. Following molecular profiling and the processing of the data using various bioinformatics pipelines, it is the task of a specialized molecular tumor board (MTB), held three times a week, to evaluate the results concerning their clinical relevance. For this purpose, all acquired molecular alterations are assessed employing various databases regarding their possible function as cancer drivers and their suitability as targets for therapeutic intervention. Besides, genes associated with a predisposition to cancer are evaluated for the presence of hereditary alterations, which may necessitate genetic counseling or also be suitable as therapeutic targets. The MTB members include clinicians, particularly medical and translational oncologists, bioinformaticians, molecular biologists, pathologists, and human geneticists. The final result of all discussions in the MTB is a standardized report that is made available to the treating physician of the respective patient. This report describes all relevant molecular changes and concludes with one or more evidence-based recommendations for clinical management, which can mainly be assigned to three areas, diagnostic re-evaluation, genetic counseling, and – in the majority of cases – personalized therapy, wherever possible within the framework of a molecularly stratified clinical trial.

• MASTER - Molecularly Aided Stratification for Tumor Eradication
   
• CATCH - Comprehensive Assessment of Clinical Features and Biomarkers To Identify Patients with Advanced or Metastatic Breast Cancer for Marker Driven Trials in Humans
   
• COGNITION - Comprehensive assessment of clinical features, genomics and further molecular marker to identify patients with early breast cancer for enrolment on marker driven trials
   
• NCT Neuro Master Match (N2M2)
   
• INdividualized Therapy FOr Relapsed Malignancies in Childhood (INFORM)
   
• Personalizing Refractory Myeloma Therapy (PeRMyT)
  Contact: Myelom.Studien@med.uni-heidelberg.de