Group "Clinical bioinformatics"

Group "Clinical bioinformatics"

Our group "Clinical Bioinformatics" which is also part of the DKFZ division of Pediatric Neurooncology works on the identification and classification of genetic and epigenetic changes in childhood tumors using computational methods. This work enables us to generate personalized molecular tumor profiles that allow physicians to design a tailored therapy approach for each individual patient. In addition, we focus on bioinformatics method development for optimized diagnosis and prognosis of pediatric cancer based on molecular data from high-throughput sequencing, as well as the analysis of possible mechanisms of tumorigenesis.

The genetic and epigenetic analysis generates enormous amounts of data.
The molecular data we work with are mainly based on high-throughput sequencing and includes (I) genome- and exome-wide DNA sequencing, which allows us to identify small mutations as well as structural variants such as translocations and (II) RNA sequencing to identify changes in gene expression and gene fusions. We analyze epigenetic changes such as aberrant DNA methylation of the tumor using genome-wide bisulfite sequencing and methylation arrays. In addition, we investigate various histone modifications by means of ChIP sequencing, since these play an important role in the regulation of gene activity and are often altered in cancer cells.

In order to interpret, integrate and visualize the vast amount of molecular biological data, we use state-of-the-art computer-assisted methods to understand the genetic and epigenetic diversity of childhood cancer and to provide accurate molecular diagnosis and personalized therapies.

Main research aspects

With our analyses, we significantly support the INFORM program, an international project to create personalized molecular tumor profiles for children with recurrent or refractory tumors. By analyzing the tumor data, we identify molecular changes that may represent potential targets for a given drug and therefore may help treating physicians to find tailored therapies for the young patient.



As part of a European initiative (ITCC-P4), which aims at developing a preclinical platform for solid pediatric cancer types, our group is involved in the bioinformatic analysis and research. To better predict therapeutic efficacy in vivo, patient-derived xenograft models (PDXs), organoids, and mouse models for preclinical testing are being developed and utilized. Using molecular data based on high-throughput sequencing, we create molecular profiles and comparisons of the (epi-)genetic changes in patient material and the different models. Additionally, we are interested in uncovering the molecular mechanisms and biomarkers that enable response to therapy. Furthermore, we are interested in the question of how tumor cells can adapt to therapy and thereby become resistant.


  • Dr. Natalie Jäger (group leader)
  • Dr. Prakash Balasubramanian, PhD (Senior Scientist)
  • Rolf Kabbe (IT-Koordinator & Cluster Admin)
  • Dr. Martin Sill (Biostatistician, Senior Scientist)
  • Dr. Robert Autry (Postdoc)
  • Dr. Konstantin Okonechnikov, PhD (Postdoc)
  • Pengbo Beck (PhD student)
  • Enrique Blanco Carmona (PhD student)
  • Dina ElHarouni (PhD student)
  • Apurva Gopisetty (PhD student)
  • Lukas Madenach (PhD student)
  • Elias Ulrich (MD student)


  • Mischan Vali Pour-Jamnani (Master student)
  • Tanvi Sharma (PhD student)
  • Venu Thatikonda (PhD student)

Dr. Natalie Jäger

Group leader "Clinical bioinformatics"

Postal address:
Hopp Children's Cancer Center Heidelberg
Im Neuenheimer Feld 280
D-69120 Heidelberg




1. Kool M, Jones DT, Jäger N, Northcott PA, Pugh TJ, Hovestadt V, Piro RM, Esparza LA, Markant SL, Remke M, Milde T, Bourdeaut F, Ryzhova M, Sturm D, Pfaff E, Stark S, Hutter S, Seker-Cin H, Johann P, Bender S, Schmidt C, Rausch T, Shih D, Reimand J, Sieber L, Wittmann A, Linke L, Witt H, Weber UD, Zapatka M, König R, Beroukhim R, Bergthold G, van Sluis P, Volckmann R, Koster J, Versteeg R, Schmidt S, Wolf S, Lawerenz C, Bartholomae CC, von Kalle C, Unterberg A, Herold-Mende C, Hofer S, Kulozik AE, von Deimling A, Scheurlen W, Felsberg J, Reifenberger G, Hasselblatt M, Crawford JR, Grant GA, Jabado N, Perry A, Cowdrey C, Croul S, Zadeh G, Korbel JO, Doz F, Delattre O, Bader GD, McCabe MG, Collins VP, Kieran MW, Cho YJ, Pomeroy SL, Witt O, Brors B, Taylor MD, Schüller U, Korshunov A, Eils R, Wechsler-Reya RJ, Lichter P, Pfister SM, Genome Sequencing of SHH Medulloblastoma Predicts Genotype-Related Response to Smoothened Inhibition. Cancer Cell 2014 Mar 17;25(3):393-405

2. Jäger N, Schlesner M, Jones DT, Raffel S, Mallm JP, Junge KM, Weichenhan D, Bauer T, Ishaque N, Kool M, Northcott PA, Korshunov A, Drews RM, Koster J, Versteeg R, Richter J, Hummel M, Mack SC, Taylor MD, Witt H, Swartman B, Schulte-Bockholt D, Sultan M, Yaspo ML, Lehrach H, Hutter B, Brors B, Wolf S, Plass C, Siebert R, Trumpp A, Rippe K, Lehmann I, Lichter P, Pfister SM, Eils R. Hypermutation of the inactive X chromosome is a frequent event in cancer. Cell. 2013 Oct 24;155(3):567-81

3. Jones DT*, Jäger N*, Kool M, Zichner T, Hutter B, Sultan M, Cho YJ, Pugh TJ, Hovestadt V, Stütz AM, Rausch T, Warnatz HJ, Ryzhova M, Bender S, Sturm D, Pleier S, Cin H, Pfaff E, Sieber L, Wittmann A, Remke M, Witt H, Hutter S, Tzaridis T, Weischenfeldt J, Raeder B, Avci M, Amstislavskiy V, Zapatka M, Weber UD, Wang Q, Lasitschka B, Bartholomae CC, Schmidt M, von Kalle C, Ast V, Lawerenz C, Eils J, Kabbe R, Benes V, van Sluis P, Koster J, Volckmann R, Shih D, Betts MJ, Russell RB, Coco S, Tonini GP, Schüller U, Hans V, Graf N, Kim YJ, Monoranu C, Roggendorf W, Unterberg A, Herold-Mende C, Milde T, Kulozik AE, von Deimling A, Witt O, Maass E, Rössler J, Ebinger M, Schuhmann MU, Frühwald MC, Hasselblatt M, Jabado N, Rutkowski S, von Bueren AO, Williamson D, Clifford SC, McCabe MG, Collins VP, Wolf S, Wiemann S, Lehrach H, Brors B, Scheurlen W, Felsberg J, Reifenberger G, Northcott PA, Taylor MD, Meyerson M, Pomeroy SL, Yaspo ML, Korbel JO, Korshunov A, Eils R, Pfister SM, Lichter P. Dissecting the genomic complexity underlying medulloblastoma. Nature. 2012 Aug 2;488(7409):100-5

4. Jones, DTW., Banito, A., Grünewald, TGP., Haber, M., Jäger, N., et al., and Pfister SM. (2019) Molecular Characteristics and Therapeutic Vulnerabilities Across Pediatric Solid Tumors. Nature Reviews Cancer, 19, p420–438 (2019)

5. Begemann, M., Waszak, SM., Robinson, GW., Jäger, N., Sharma, T., et al. Germline GPR161 Mutations Predispose to Pediatric Medulloblastoma. J. Clin. Oncol. JCO.19.00577 (2019). doi:10.1200/JCO.19.00577

6. Johann PD, Jäger N, Pfister SM, Sill M. (2019) RF_Purify: a novel tool for comprehensive analysis of tumor-purity in methylation array data based on random forest regression. BMC Bioinformatics. 20(1):428.

7. Sharma, T., Schwalbe, E.C., Williamson, D. et al. Second-generation molecular subgrouping of medulloblastoma: an international meta-analysis of Group 3 and Group 4 subtypes. Acta Neuropathol 138, 309–326 (2019).

8. Jonas Ecker, Venu Thatikonda,  et al. Reduced chromatin binding of MYC is a key effect of HDAC inhibition in MYC amplified medulloblastoma, Neuro-Oncology, noaa191,