Team

Prof. Peter J. Wild

 

Principal Investigator
peter.wild {at} usz.ch
List of Publication
Curriculum Vitae
Scopus Author Identifier
Read More

 

Peter Wild is Full Professor for Systems Pathology and Senior Consultant Pathologist at the University of Zurich (UZH) and University Hospital of Zurich (USZ). Since 2017 he is also Chief Scientific Officer (CSO) of the Foundation Medicine Lab at the University Hospital Zurich.

 

Among the main achievements of Peter Wild are that he has established and validated next-generation-sequencing technologies including whole exome sequencing for diagnostic molecular pathology, established the Molecular Tumorboard Zurich (MTBZ), characterized the first mouse model of type II endometrial carcinomas, generated a seven-marker signature for clinical outcome in malignant melanoma, screened a library of small interfering RNAs for glycoproteome genes whose inhibition causes synthetic lethality with the PTEN gene in prostate cancer cells in vitro, and generated comprehensive cancer tissue microarrays of large patient cohorts (prostate, breast, bladder, skin cancer).

 

He is a graduate of the University of Regensburg Medical School in Germany, and has completed a postdoctoral training in Medical Biometrics at the University of Heidelberg, Germany. In 2002, he has finished his doctoral thesis in pathology (summa cum laude) in the laboratory of Ferdinand Hofstädter and Arndt Hartmann on predictive biomarkers of patients with advanced breast cancer at the University Hospital Regensburg. For his residency training in pathology, he went to the Institutes of Pathology at the University Hospitals in Regensburg, Hamburg-Eppendorf, and Zurich. In 2008 and 2010, he received the German and the Swiss Board Certification in Pathology, respectively. For a two year postdoctoral research training, he joined the laboratory of Wilhelm Krek at ETH Zurich to investigate the role of the PI3K-AKT-mTOR signalling pathway in cancer and its use for diagnostic serum signatures and functional studies. In April 2010 he also received his Venia Legendi in Pathology from the University of Zurich for his work on molecular biomarkers of bladder cancer. In September 2012, Peter Wild was appointed Assistant Professor (tenure track) for Systems Pathology, leading the High-Throughput Genomics Laboratory at the USZ.

 

Peter Wild has received several awards, including the Rudolf-Virchow-Preis (2013) of the German Society of Pathology, the Young Investigator Award for Cancer Research of the Charles Rodolphe Brupbacher Foundation (2007), and the Research Award of the Novartis Foundation for Therapeutical Research (2004).

 

Dr. Markus Rechsteiner

 

Resident Scientist
markus.rechsteiner {at} usz.ch
List of Publication
Curriculum Vitae
Read More

 

Current Research Projects

Evaluation of next-generation sequencing for diagnostic applications.

 

Research Interests

Identification of biomarkers on genomic level for prognosis and prediction.

 

Dr. Qing Zhong

 

Data Scientist
qing.zhong {at} usz.ch
List of Publication: ORCID
Read More

 

Current Research Projects

Application of machine learning algorithms on a plethora of heterogeneous data for biomedical knowledge discovery and patient stratification.

 

fig2

Research Interests

Mathematical modelling of biological system. Bioinformatic algorithm design and computational biology. Machine learning and computer vision.

 

Curriculum Vitae 

 

2013 Data scientist in the Wild Lab, Institute of Surgical Pathology, University Hospital Zurich
2013 Dr. sc. ETHZ in the Gerlich Lab, Institute of Biochemistry and Department of Computer Science, Prof. Buhmann, ETH Zurich
2010 MSc. CS, Department of Computer Science, Prof. Buhmann, ETH Zurich

 

Dr. Christine Fritz

 

Postdoctoral Research Fellow
christine.fritz {at} usz.ch
Read More

 

Current Research Projects

Next-generation sequencing and functional genomics of prostate cancer.

 

Research Interests

Prostate cancer and next-generation sequencing as a diagnostic tool.

 

Selected Publications

Wong C. E., Yu J. S., Quigley D. A., To M. D., Jen KY., Huang P. Y., Del Rosario R., and Balmain A. Inflammation and Hras signaling control epithelial-mesenchymal transition during skin tumor progression. Genes Dev. 2013 Mar 15;27(6):670-82.

 

Adorno M., Cordenonsi M., Montagner M., Dupont S., Wong C., Hann B., Solari A., Bobisse S., Rondina M. B., Guzzardo V., Parenti A. R., Rosato A., Bicciato S., Balmain A., Piccolo S. A mutant p53/Smad complex opposes p63 to empower TGF-beta-induced metastasis. Cell. 2009 Apr 3;137(1):87-98.

 

To M. D., Wong C. E., Karnezis A. N., Del Rosario R., Di Lauro R., and Balmain A. Kras regulatory elements and exon4A determine mutation specificity in lung cancer. Nat Genet. 2008 Oct;40(10).

 

Wong C. E.*, Paratore C.*, Rochat A., Suter U., Meijer D., Beermann F., Barrandon Y., and Sommer L. Neural crest-derived cells with stem cell features can be traced back to multiple lineages in the adult skin. J Cell Biol. 2006 Dec 18;175(6):1005-15. * equal contribution.

 

Curriculum Vitae

 

2013 Postdoctoral fellow in the Wild Lab, Institute of Surgical Pathology, University Hospital Zurich
2007 – 2012 Postdoctoral Fellow at the CRI, University of California San Francisco (UCSF), in the lab of Prof. Allan Balmain
2002 – 2006 Ph.D at the Institute of Cell Biology, ETH Zurich, in the lab of Prof. Lukas Sommer
1997 – 2002 Bachelor and Master of Science in Biology, Biocenter, University of Basel, Switzerland

 

Dr. Nadejda Valtcheva

 

Nadejda Postdoctoral Research Fellow
nadejda.valtcheva {at} usz.ch
Read More

p53mice_histo

p53mice_IGV

Genetic fingerprinting of uterine cancer

Uterine cancer (endometrial carcinoma) is the most common malignancy of the female genital tract. Two broad categories of uterine cancer are recognised; type I tumours (endometrioid) are the most frequent form in 80% of cases, while the more aggressive type II tumours (serous, clear cell and undifferentiated) occur more rarely but account for about half of the cases of endometrial cancer-related death. In comparison to other common types of human tumours, very few molecular studies of uterine cancer have been undertaken to date.

 

In order to understand uterine cancer development and to improve therapy in the future we are employing a novel mouse model based on the deletion of a tumour suppressor gene (p53) in the endometrium. This mouse model recapitulates the development of human endometrial cancer from normal tissue over precursor lesions to carcinoma. We screen the DNA isolated from these samples with high-throughput sequencing technologies to systematically identify the alterations that accompany and/or underlie the morphological changes during uterine cancer formation. Eventually, we will investigate if similar DNA alterations are detected in human patient samples.

 

Current Research Project 

Next generation sequencing and functional genomics of endometrial cancer

 

Research Interests

Identification of the driver mutations in endometrial cancer for diagnostic and therapeutic applications. Oncogene addiction and signalling pathways in endometrial cancer.

 

Selected Publications

Feil S, Valtcheva N, Feil R (2009) Inducible Cre mice. Methods Mol Biol 530:343-63

 

Valtcheva N, Nestorov P, Beck A, Russwurm M, Hillenbrand M, Weinmeister P, Feil R (2009) The commonly used cGMP-dependent protein kinase type I (cGKI) inhibitor Rp-8-Br-PET-cGMPS can activate cGKI in vitro and in intact cells. J Biol Chem 284:556-62

 

Curriculum Vitae

 

2013 Postdoctoral fellow in the Wild Lab, Institute of Surgical Pathology, University Hospital Zurich
2009 – 2012 Postdoctoral fellow at the Institute of Pharmaceutical Sciences, ETHZ, Group of Prof. Michael Detmar
2005 – 2009 PhD studies at the Institute of Biochemistry, University of Tübingen, Germany, Group of Prof. Robert Feil
1999 – 2004 Diploma in Biology (Cell biology, Genetics and Biochemistry), University of Tübingen, Germany

 

Dr. Ulrich Wagner

 

Bioinformatician
ulrich.wagner {at} usz.ch
Read More

 

Current Research Projects

Implementation of robust next-generation sequencing data analysis workflows in the framework of diagnostic applications.

 

Research Interests

All flavors of next-generation sequencing data analysis, in particular in the fields of genomics, transcriptomics and methylomics.

 

Selected Publication

Leung D. *, Du T. *, Wagner U. *, Xie W., Lee A.Y., Goyal P., Li Y., Szulwach K.E., Jin P., Lorincz M.C., Ren B. (2014), Regulation of DNA methylation turnover at LTR retrotransposons and imprinted loci by the histone methyltransferase Setdb1, PNAS 111:6690-6695, * equal contribution.

 

Hawkins R.D. *, Larjo A. *, Tripathi S.K. *, Wagner U., Luu Y., Lönnberg T., Raghav S.K., Lee L.K., Lund R., Ren B., Lähdesmäki H., Lahesmaa R. (2013), Global chromatin state analysis reveals lineage-­-specific enhancers during the initiation of human T helper 1 and T helper 2 cell polarization. Immunity 38:1271-84, * equal contribution.

 

Jishage M., Malik S., Wagner U., Uberheide B., Ishihama Y., Hu X., Chait B.T., Gnatt A., Ren B., Roeder R.G. (2012), Transcriptional regulation by Pol II(G) involving mediator and competitive interactions of Gdown1 and TFIIF with Pol II. Mol. Cell. 45:51-63.

 

Nègre N.*, Brown C.D.*, Ma L.*, Bristow C.A.*, Miller S.W.*, Wagner U.*, Kheradpour P., Eaton M.L., Loriaux P., Sealfon R., Li Z., et al. (2011), A cis-regulatory map of the Drosophila genome. Nature 471:527-531, * equal contribution.

 

Gyenesei A.*, Wagner, U.*#, Stolte E., Schlapbach R. (2007) Mining attribute profiles for the detection of functional associations in gene expression data. Bioinformatics. 23; 1927-­-1935, * equal contribution, # corresponding author.

 

Wagner U., Edwards R., Dixon D.P., Mauch F. (2002), Probing the diversity of the Arabidopsis glutathione S-transferase gene family. Plant Mol. Biol. 49: 515-32.

 

Curriculum Vitae 

 

2014 Bioinformatician in the Wild Lab, Institute of Surgical Pathology, University Hospital Zurich
2013 Bioinformatics Project Scientist, University of Bern, Interfaculty Bioinformatics Unit
2008-2013 Bioinformatics Research Scientist, Ludwig Institute for Cancer Research, San Diego, Gene Regulation Unit, Group of Prof. Bing Ren
2002-2008 Bioinformatics Research Scientist, University/ETH Zurich, Functional Genomics Center Zurich, Transcriptome Analysis Group
2002 Masters in Bioinformatics, Swiss Institute of Bioinformatics, University of Geneva and University of Lausanne, Switzerland
2001 PhD in Natural Sciences, Dept. of Biology, University of Fribourg, Switzerland, Group of Prof. Dr. Felix Mauch
1995 Diploma in Biological Sciences, Department of Plant Physiology, University of Kaiserslautern, Germany, Group of Prof. Dr. Heinrich Kauss

 

Dr. Nadezda Velizheva

 

Postdoctoral Research Fellow
nadezda.velizheva {at} usz.ch
Read More

 

Current Research Projects

Amplicon-based next-generation sequencing of lung adenocarcinomas on clinical specimens: FFPE samples, cytological cell blocks and stained cytological smears

Velizheva_Project

 

Research Interests

Molecular pathology of malignancies, predictive and prognostic markers of lung cancer

 

Selected Publication

Nadezhda Velizheva, Maria Dardyk, Tatiana Kondratieva. Subtyping diagnosis of lung carcinomas on small materials (cytological, histological and immunohistochemical correlations): is it a chance or reality? Acta Cytologica 57 (suppl 1) (2013).

 

Irina Shubina, Nadezhda Velizheva, Mikhail Kiselevsky. CD4+/CD25+ T regulatory cells. Atlas Effectors of Anti-Tumor Immunity. Mikhail V. Kiselevsky (ed.) Springer Science+Business Media B. V. (2008).

 

Curriculum Vitae 

 

2014 Postdoctoral Fellow in the Wild Lab, Institute of Surgical Pathology, University Hospital Zurich, Switzerland
2012 -2014 Scientist, N.N. Blokhin Russian Cancer Research Center, Moscow, Russia
2006-2012 PhD in Oncology, N.N. Blokhin Russian Cancer Research Center, Moscow, Russia
2000-2006 Diploma in Medicine, 1st Moscow Medical University, Moscow, Russia

 

Dr. Dorothea Rutishauser

 

Postdoctoral Research Fellow​
dorothea.rutishauser {at} usz.ch
Read More

 

Current Research Projects

Proteomics
 

Selected Publication

https://www.ncbi.nlm.nih.gov/pubmed/?term=rutishauser+d
 

Curriculum Vitae 

 

2016 Postdoctoral Fellow in the Wild Lab, Proteomics Coordination, Institute of Surgical Pathology, University Hospital Zurich, Switzerland
2010-2016 Project Leader PK/KI, Proteomics Karolinska, Department of Medical Biochemistry and Biophysics; Core Facility Manager of Advanced Proteomics at SciLifeLab Stockholm, Sweden
2007-2010 Senior Scientist, Functional Genomics Center Zurich, ETH Zurich, Switzerland
2007 PhD, Institute of Neuropathology, University Hospital of Zurich, Switzerland

 

Dr. Laura De Vargas Roditi

 

Laura Postdoctoral Research Fellow
laura.deVargas {at} usz.ch
Read More

li

Computational analysis of single-cell resolved prostate cancer data

Prostate cancer is the most commonly diagnosed cancer amongst males. Castration-resistant prostate cancer is the second most common cause of cancer-related deaths in men. Typically, prostate cells, including cancerous ones, depend on androgens, such as testosterone, which are normally produced in the testicles; therefore the first line of treatment for prostate cancer patients consists of androgen ablation through surgical or chemical castration. This treatment leads to temporary disease regression but often fails after development of castration-resistant prostate cancer.

 

Prostate cancer is characterized by multiple genomic alterations leading to the complex nature and heterogeneity of the disease. Intra-tumor heterogeneity can impair precise molecular analysis of tumors and interferes with biomarker qualification, treatment personalization as well as drives therapy resistance, highlighting the importance of characterizing tumor heterogeneity.
 

Current Research Projects 

Single cell analysis of prostate cancer tissue using mass cytometry.

 

Research Interests

Using mathematical and computational modeling to analyze high-dimensional single-cell data with the goal of characterizing cancer heterogeneity, describing the cancers’ evolutionary trajectory, and to help develop new therapeutic approaches for the treatment of cancer.

 

Dr. Sandra Freiberger

 

Sandra Scientist
sandra.freiberger {at} usz.ch
Read More

Current Research Projects 

Establishing sequencing applications for diagnostics and development of a melanoma-specific gene panel for diagnostics (in collaboration with USZ Dermatology)

 
Selected Publication

Kulig P, Musiol S, Freiberger SN, Schreiner B, Russo G, Pantelyushin S, Hishihara K, Alessandrini F, Sallusto F, Hofbauer GFL, Gyülveszi G, Haak S, Kündig T, Becher B: IL-12 protects from psoriasiform skin inflammation. (Nat. Commun. 2016)

 

Frauenfelder SR, Freiberger SN, Bouwes Bavinck JN, Quint KD, Genders R, Serra AL, Hofbauer GFL: Prostaglandin E2, Tumor Necrosis Factor α, and Pro-opiomelanocortin Genes as Potential Mediators of Cancer Pain in Cutaneous Squamous Cell Carcinoma of Organ Transplant Recipients. (JAMA Dermatol. 2016 Dec 7)

 

Raaijmakers MI, Widmer DS, Narechania A, Eichhoff O, Freiberger SN, Wenzina J, Cheng PF, Mihic-Probst D, Desalle R, Dummer R, Levesque MP: Co-existence of BRAF and NRAS driver mutations in the same melanoma cells results in heterogeneity of targeted therapy resistance. (Oncotarget. 2016 Oct 24)

 

Freiberger SN, Zehnder M, Gafvelin G, Grönlund H, Kündig TM, Johansen P: IgG4 but no IgG1 antibody production after intralymphatic immunotherapy with recombinant MAT-Feld1 in human. (Allergy. 2016 Jun 2)

 

Freiberger SN, Cheng PF, Iotzova-Weiss G, Neu J, Liu Q, Dziunycz P, Zibert JR, Dummer R, Skak K, Levesque MP, Hofbauer GF: Ingenol Mebutate Signals via PKC/MEK/ERK in Keratinocytes and Induces Interleukin Decoy Receptors IL1R2 and IL13RA2. (Mol Cancer Ther. 2015 Sep;14(9):2132-42.)

 

Iotzova-Weiss G, Dziunycz PJ, Freiberger SN, Läuchli S, Hafner J, Vogl T, French LE, Hofbauer GF: S100A8/A9 stimulates keratinocyte proliferation in the development of squamous cell carcinoma of the skin via the receptor for advanced glycation-end products. (PLoS One. 2015 Mar 26;10(3):e0120971.)

 

Dziunycz PJ, Lefort K, Wu X, Freiberger SN, Neu J, Djerbi N, Iotzowa-Weiss G, French LE, Dotto GP, Hofbauer GF: The oncogene ATF3 is potentiated by cyclosporin A and ultraviolet light A (J Invest Dermatol. 2014 Jul;134(7): 1998-2004. Epub 2014 Feb 7)

 

Hofbauer GF, Freiberger SN, Iotzova-Weiss G, Shafaeddin B, Dziunycz PJ: Organ transplantation and skin – principles and concepts (Curr Probl Dermatol. 2012;41:1-8; Epub 2012 Feb 17)

 

Mauthe M, Jacob A, Freiberger SN, Hentschel K, Stierhof Y, Codogno P, Proikas-Cezanne T: Resveratrol mediated autophagy requires WIPI-1 regulated LC3 lipidation in the absence of induced phagophore formation (Autophagy, 2011 Dec1; 7 (12).)

 
Curriculum Vitae 

 

2016 Scientist, Institute of Pathology and Molecular Pathology, University Hospital Zurich, Switzerland
2015-2016 Postdoctoral Researcher, Department of Dermatology, University Hospital Zurich, Switzerland
2011-2015 PhD student, Cancer Biology PhD Program, Department of Dermatology, University Hospital and University of Zurich, Switzerland
2010 PhD student, Department of Molecular Biology, Interfaculty Institute for Cell Biology, University of Tuebingen, Germany

 

Dr. Ana Filipa Goncalves

 

Postdoctoral Research Fellow, Cancer Cell Biology
anaFilipa.goncalves {at} usz.ch

 

 

Dr. Ailsa Christiansen

 

Scientist
ails.christiansen {at} usz.ch

 

 

Dr. med. Jan Hendrik Rüschoff

 

jan Resident
jan.rueschoff {at} usz.ch

 

Dr. med. Kristian Ikenberg

 

kristian Attending Physician
kristian.ikenberg {at} usz.ch

 

Dr. med. Niels Rupp

 

kristian Resident
niels.rupp {at} usz.ch

 

Dr. med. Kim Fricker

 

kristian Resident
kim.fricker {at} usz.ch

 

Dr. med. Christian D. Fankhauser

 

christian Resident, Guest Scientist
christian.fankhauser {at} usz.ch

 

Karim Saba

 

saba Resident, Guest Scientist
karim.saba {at} usz.ch

 

Annette Bohnert von Rotz

 

Annette Technician
Dipl. biomedizinisch Analytikerin HF
annette.bohnert {at} usz.ch

 

Jelena Ljubicic

 

Jelena Praktikantin
jelena.ljubicic {at} usz.ch

 

Kathrin Oehl

 

Kathrin PhD Student
kathrin.oehl {at} usz.ch

 

Elisa Bellini

 

Elisa PhD Student
elisa.bellini {at} usz.ch
Read More

 

Identification of the molecular drivers of Endometrial Cancer progression

Endometrial carcinoma is the most common malignancy of the female genital tract. Although PI3K-mTOR pathway activation and TP53 inactivation play different roles in the initiation of different endometrial cancer subtypes, co-occurring alterations in both signaling pathways represent a frequent unifying pathogenic feature of late stage tumors of all subtypes.
Our aim is to identify and functionally assess the role of the proteins crucial for the survival of endometrial cancer cells with the aforementioned molecular signature. For this purpose, we designed a PI3K pathway-dependent synthetic lethality screen using RNAi technology and used TALEN (TAL-effector nuclease) genome editing tool to knock-out PTEN (an important inhibitor of the PI3K pathway) in TP53-/- endometrial carcinoma cell lines.
To confirm the aberrations critical for disease progression and assign them to each step of endometrial cancer development, we will further investigate the obtained results using the tissue microarrays (TMAs), containing a very large cohort of human endometrial cancer tissues, available at the Tissue-Biobank of our Institute.
Ultimately, this approach aims at using the knowledge gained from the cell culture model to decipher mechanisms commonly involved in the progression of the endometrial cancer of patients. The final goal is to characterize new prognostic and potentially predictive markers for improving personalised molecular diagnosis and treatment.
EB_Fig1

Figure. Synthetic lethality is a type of genetic interaction where the co-occurrence of two genetic events results in organismal or cellular death.

 

Malamati (Elina) Koletou

 

Elisa PhD Student
malamati.koletou {at} usz.ch
Read More

fig1_TCGA
Figure 1. Data from TCGA (The Cancer Genome Atlas).
We aim to search for prostate cancer specific genomic alterations and infer patterns across different types of omics datasets in order to improve the stratification of prostate cancer in two classes, significant and insignificant disease.

fig2_Pattern
Figure 2. Pattern detection via dictionary learning.
We are developing a novel computational framework that offers a novel perspective into analysing genomic data from relatively very small number of samples and that can integrate multiple omics datasets.