Central Project 2

Central diagnostics, biobanking and genomics: Deciphering clonal evolution as an escape mechanism towards treatment resistance in CLL


 Studies in in-depth characterized primary patient material are needed to discover key driver molecules with significant biological and clinical relevance in CLL. Accordingly, it is indispensable to prove new discoveries being dependent or independent of molecular prognostic parameters, which have been established previously in CLL. In order to provide all scientists of the CRU-286 with well-defined samples of primary human and murine CLL cells, central diagnostics, genomic analyses and biobanking will be performed within this core project 2 (CP2). Furthermore, within CP2 we aim to decipher the clonal evolution to identify escape mechanisms underlying treatment resistance of CLL. Advanced platforms for immunophenotyping, translational genomics, and computational analyses have been established as collaborative structures at the Department I of Internal Medicine  (Hematology/Oncology, K.-A. Kreuzer, C. Herling), the Department of Translational Genomics and the Center of Molecular Medicine (M. Peifer). Peripheral blood, bone marrow and tissue specimens including lymph nodes will be morphologically diagnosed and undergo a systematic diagnostic work-up including immunophenotyping, somatic mutation analyses (i.e., TP53, IGHV), fluorescence-in-situ hybridization, and conventional cytogenetics. Further, appropriate protein and nucleic acid extracts will be stored centrally under appropriate data protection and safety requirements. Using a fully operational genomics unit, on-demand whole-genome-, exome, or target enriched gene extracts will undergo deep sequencing with parallel transcriptome and mutation analyses. The detection of all kinds of genomic alterations and their role in the clonal evolution of CLL will be carried using state-of-the-art computational approaches. The use of patient specimen treated and followed at the University Hospital Cologne (UHC)/Center of Integrated Oncology (CIO) and within clinical trials of the German CLL Study Group (GCLLSG), will provide us with the unique opportunity to study combined clinical and molecular data from CLL patients metachronically over their entire disease course.

Completed projects and work in progress:

Comprehensive analysis of disease-related genes in chronic lymphocytic leukemia by multiplex PCR based next generation sequencing

 High-resolution molecular studies have demonstrated that the clonal acquisition of gene mutations is an important mechanism that may promote rapid disease progression and drug resistance in chronic lymphocytic leukemia (CLL). Therefore, the early and sensitive detection of such mutations is an important prerequisite for future predictive CLL diagnostics in the clinical setting.

 We established a novel, target-specific next generation sequencing (NGS) approach, which combines multiplex PCR-based target enrichment (AmpliSeq, LifeTechnologies) and library generation with ultra-deep high-throughput parallel sequencing using an Illumina MiSeq platform. We designed a CLL specific target panel, covering hotspots or complete coding regions of 15 genes known to be recurrently mutated and/or related to B-cell receptor signaling. High-throughput sequencing was performed using as little as 40 ng of peripheral blood B-cell DNA from 136 CLL patients and a dilution series of two ATM- or TP53-mutated cell lines, the latter of which demonstrated a lower level of mutation detection below 5%. Using a stringent functional assessment algorithm, 102 mutations in 8 genes were identified in CLL patients, including hotspot regions of TP53, SF3B1, NOTCH1, ATM, XPO1, MYD88, DDX3X, and an interesting missense alteration in the phosphatase domain of the B-cell receptor signaling regulator PTPN6. The presence of the suspected mutations was significantly associated with an advanced disease status und molecular markers of an inferior prognosis, such as an unmutated IGHV mutation status or positivity for ZAP70 by flow cytometry.

Computational approaches to reconstruct clonal evolution from genome sequencing data

 Over the past years we have established a computational framework to detect somatic mutational events (point mutations, copy number alterations, and genomic rearrangements) from whole genome or exome sequencing data. By using our recent developments, we can transform the observed allelic fractions of point mutations into cancer cell fractions. These cancer cell fractions are then searched for sub-populations and it is then determined how they change across multiple sample of the same patient. This serves as backbone to determine phylogenetic relationships between the observed clones. In the context of therapy resistance, we envision that this approach will provide us with new insights into the dynamics of molecular events associated with the relapse of the patient.

For further details, please refer to:

 Complex karyotypes and KRAS and POT1 mutations impact outcome in CLL after chlorambucil-based chemotherapy or chemoimmunotherapy. Herling CD, Klaumünzer M, Rocha CK, Altmüller J, Thiele H, Bahlo J, Kluth S, Crispatzu G, Herling M, Schiller J, Engelke A, Tausch E, Döhner H, Fischer K, Goede V, Nürnberg P, Reinhardt HC, Stilgenbauer S, Hallek M, Kreuzer KA. Blood. 2016 Jul 21;128(3):395-404.

 Comprehensive Analysis of Disease-Related Genes in Chronic Lymphocytic Leukemia by Multiplex PCR-Based Next Generation Sequencing. Vollbrecht C, Mairinger FD, Koitzsch U, Peifer M, Koenig K, Heukamp LC, Crispatzu G, Wilden L, Kreuzer KA, Hallek M, Odenthal M, Herling CD, Buettner R. PLoS One. 2015 Jun 8;10(6):e0129544.

 Telomerase activation by genomic rearrangements in high-risk neuroblastoma. Peifer M, Hertwig F, Roels F, Dreidax D, Gartlgruber M, Menon R, Krämer A, Roncaioli JL, Sand F, Heuckmann JM, Ikram F, Schmidt R, Ackermann S, Engesser A, Kahlert Y, Vogel W, Altmüller J, Nürnberg P, Thierry-Mieg J, Thierry-Mieg D, Mariappan A, Heynck S, Mariotti E, Henrich KO, Gloeckner C, Bosco G, Leuschner I, Schweiger MR, Savelyeva L, Watkins SC, Shao C, Bell E, Höfer T, Achter V, Lang U, Theissen J, Volland R, Saadati M, Eggert A, de Wilde B, Berthold F, Peng Z, Zhao C, Shi L, Ortmann M, Büttner R, Perner S, Hero B, Schramm A, Schulte JH, Herrmann C, O'Sullivan RJ, Westermann F, Thomas RK, Fischer M. Nature. 2015 Oct 29;526(7575):700-4.

 Comprehensive genomic profiles of small cell lung cancer. George J, Lim JS, Jang SJ, Cun Y, Ozretić L, Kong G, Leenders F, Lu X, Fernández-Cuesta L, Bosco G, Müller C, Dahmen I, Jahchan NS, Park KS, Yang D, Karnezis AN, Vaka D, Torres A, Wang MS, Korbel JO, Menon R, Chun SM, Kim D, Wilkerson M, Hayes N, Engelmann D, Pützer B, Bos M, Michels S, Vlasic I, Seidel D, Pinther B, Schaub P, Becker C, Altmüller J, Yokota J, Kohno T, Iwakawa R, Tsuta K, Noguchi M, Muley T, Hoffmann H, Schnabel PA, Petersen I, Chen Y, Soltermann A, Tischler V, Choi CM, Kim YH, Massion PP, Zou Y, Jovanovic D, Kontic M, Wright GM, Russell PA, Solomon B, Koch I, Lindner M, Muscarella LA, la Torre A, Field JK, Jakopovic M, Knezevic J, Castaños-Vélez E, Roz L, Pastorino U, Brustugun OT, Lund-Iversen M, Thunnissen E, Köhler J, Schuler M, Botling J, Sandelin M, Sanchez-Cespedes M, Salvesen HB, Achter V, Lang U, Bogus M, Schneider PM, Zander T, Ansén S, Hallek M, Wolf J, Vingron M, Yatabe Y, Travis WD, Nürnberg P, Reinhardt C, Perner S, Heukamp L, Büttner R, Haas SA, Brambilla E, Peifer M, Sage J, Thomas RK. Nature. 2015 Aug 6;524(7563):47-53.