Sascha Dietrich and Wolfgang Huber
Wolfgang Huber and Sascha Dietrich
Our research interest
We aim to understand intra- and inter-patient heterogeneity of response to anti-cancer drugs, a major clinical and scientific challenge. Our focus is to study the interaction tumour cells with their microenvironment and consequences for drug response. We employ a tightly integrated combination of experimental and computational approaches, which include
- ex-vivo drug perturbation assays of patient derived leukaemia and lymphoma cells,
- culture models of niche compartments and their cross talk with tumour cells,
- imaging based quantitative phenotyping,
- multi-omic molecular profiling,
- statistical analysis and
- mathematical modelling of dynamical response patterns and resistance mechanisms.
Background and overall Goals
Response to anti-cancer agents is often restricted to subsets of patients, and even within patients, to subfractions of the tumour. In addition, signals provided by the tumour microenvironment modify pathway-activities, including those targeted by drugs. Our knowledge of such complex interactions of different factors underlying drug response is incomplete. Our goal is to increase the understanding of drug response heterogeneity and to provide the scientific basis for biology-based individualized treatment of lymphoma and leukaemia.
We pursue a systems medicine approach that integrates systematic modelling of niche compartments and their cross talk with tumour cells subsets with drug perturbation assays of primary cancer cells, multi-omic molecular profiling, cutting-edge statistical data analysis, mathematical modelling and a setup towards a clinical exploitation.
Approach and foci
Ex-vivo drug testing platform to map the biological complexity and inter- and intra-patient heterogeneity of blood tumours in the context of their interaction with the microenvironment.
Niche models. We isolate tumour cells from surgically extracted lymph-nodes and bone marrow aspirates and characterize their functional states and pathway activities by phospho-proteomics and phospho-specific antibodies. These results serve as a reference for in-vitro models that aim to resemble the niche specific context.
Further dimensions of drug sensitivity and resistance: 3D space, timing, and dynamics of clonal composition.
Cancer cell phenotyping using an automated microscopy platform and computational image analysis of cellular morphology (mitochondria, nuclei, microtubules) for dynamic understanding of cell fate in time.
Statistical multivariate modelling to explain and predict the heterogeneity of drug response by integration of cancer cell phenotypes and multi-omics data types.
Clinical applications. This includes assessment of our ex-vivo tumour models for clinical outcome prediction and preparation for prospective clinical studies.
Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.
Argelaguet R, Velten B, Arnol D, Dietrich S, Zenz T, Marioni JC, Buettner F, Huber W, Stegle O.
Mol Syst Biol. 2018 Jun 20;14(6):e8124. doi: 10.15252/msb.20178124. PMID:29925568
Drug-perturbation-based stratification of blood cancer.
Dietrich S, Oleś M, Lu J, Sellner L, Anders S, Velten B, Wu B, Hüllein J, da Silva Liberio M, Walther T, Wagner L, Rabe S, Ghidelli-Disse S, Bantscheff M, Oleś AK, Słabicki M, Mock A, Oakes CC, Wang S, Oppermann S, Lukas M, Kim V, Sill M, Benner A, Jauch A, Sutton LA, Young E, Rosenquist R, Liu X, Jethwa A, Lee KS, Lewis J, Putzker K, Lutz C, Rossi D, Mokhir A, Oellerich T, Zirlik K, Herling M, Nguyen-Khac F, Plass C, Andersson E, Mustjoki S, von Kalle C, Ho AD, Hensel M, Dürig J, Ringshausen I, Zapatka M, Huber W, Zenz T.
J Clin Invest. 2018 Jan 2;128(1):427-445. doi: 10.1172/JCI93801. Epub 2017 Dec 11.PMID:29227286
Data-driven hypothesis weighting increases detection power in genome-scale multiple testing.
Ignatiadis N, Klaus B, Zaugg JB, Huber W.
Nat Methods. 2016 Jul;13(7):577-80. doi: 10.1038/nmeth.3885.
BRAF inhibition in hairy cell leukemia with low-dose vemurafenib.
Dietrich S, Pircher A, Endris V, Peyrade F, Wendtner CM, Follows GA, Hüllein J, Jethwa A, Ellert E, Walther T, Liu X, Dyer MJ, Elter T, Brummer T, Zeiser R, Hermann M, Herold M, Weichert W, Dearden C, Haferlach T, Seiffert M, Hallek M, von Kalle C, Ho AD, Gaehler A, Andrulis M, Steurer M, Zenz T.
Blood. 2016 Jun 9;127(23):2847-55. doi: 10.1182/blood-2015-11-680074.
A chemical-genetic interaction map of small molecules using high-throughput imaging in cancer cells.
Breinig M, Klein FA, Huber W, Boutros M.
Mol Syst Biol. 2015 Dec 23;11(12):846. doi: 10.15252/msb.20156400.
Single-cell transcriptome analysis reveals coordinated ectopic gene-expression patterns in medullary thymic epithelial cells.
Brennecke P, Reyes A, Pinto S, Rattay K, Nguyen M, Küchler R, Huber W, Kyewski B, Steinmetz LM. Nat Immunol. 2015 Sep;16(9):933-41. doi: 10.1038/ni.3246.
Recurrent CDKN1B (p27) mutations in hairy cell leukemia.
Dietrich S, Hüllein J, Lee SC, Hutter B, Gonzalez D, Jayne S, Dyer MJ, Oleś M, Else M, Liu X, Słabicki M, Wu B, Troussard X, Dürig J, Andrulis M, Dearden C, von Kalle C, Granzow M, Jauch A, Fröhling S, Huber W, Meggendorfer M, Haferlach T, Ho AD, Richter D, Brors B, Glimm H, Matutes E, Abdel Wahab O, Zenz T.
Blood. 2015 Aug 20;126(8):1005-8. doi: 10.1182/blood-2015-04-643361.
Improved binding site assignment by high-resolution mapping of RNA-protein interactions using iCLIP.
Hauer C, Curk T, Anders S, Schwarzl T, Alleaume AM, Sieber J, Hollerer I, Bhuvanagiri M, Huber W, Hentze MW, Kulozik AE.
Nat Commun. 2015 Aug 11;6:7921. doi: 10.1038/ncomms8921.
A map of directional genetic interactions in a metazoan cell.
Fischer B, Sandmann T, Horn T, Billmann M, Chaudhary V, Huber W, Boutros M.
Elife. 2015 Mar 6;4. doi: 10.7554/eLife.05464.
Orchestrating high-throughput genomic analysis with Bioconductor.
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M.
Nat Methods. 2015 Feb;12(2):115-21. doi: 10.1038/nmeth.3252. Review.
Continued response off treatment after BRAF inhibition in refractory hairy cell leukemia.
Dietrich S, Hüllein J, Hundemer M, Lehners N, Jethwa A, Capper D, Acker T, Garvalov BK, Andrulis M, Blume C, Schulte C, Mandel T, Meissner J, Fröhling S, von Kalle C, Glimm H, Ho AD, Zenz T.
J Clin Oncol. 2013 Jul 1;31(19):e300-3. doi: 10.1200/JCO.2012.45.9495. No abstract available.
Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping.
Laufer C, Fischer B, Billmann M, Huber W, Boutros M.
Nat Methods. 2013 May;10(5):427-31. doi: 10.1038/nmeth.2436.
BRAF inhibition in refractory hairy-cell leukemia.
Dietrich S, Glimm H, Andrulis M, von Kalle C, Ho AD, Zenz T.
N Engl J Med. 2012 May 24;366(21):2038-40. doi: 10.1056/NEJMc1202124.