Recent work

Philip Gerlee, Linnéa Schmidt, Naser Monsefi, Teresia Kling, Rebecka Jörnsten, Sven Nelander "Searching for synergies: matrix algebraic approaches for efficient pair screening " Submitted 2012

Philip Gerlee and Sven Nelander "The impact of phenotypic switching on glioma growth and progression" PLoS Computational Biology 2012, Accepted for publication

Marta Persson, Ywonne Andren, Christopher Moskaluk, Henry Frierson, Susanna Cooke, Andrew Futreal, Teresia Kling, Sven Nelander, Anders Nordkvist, Fredrik Persson, and Goran Stenman "Clinically Significant Copy Number Alterations and Complex Rearrangements of MYB and NFIB in Head and Neck Adenoid Cystic Carcinoma" Genes, Chromosomes and Cancer 2012, Accepted for publication

Abenius T, Jörnsten R, Kling T, Schmidt L, Sánchez J, Nelander S. "System-Scale Network Modeling of Cancer Using EPoC". Adv Exp Med Biol. 2012;736:617-43."

Rebecka Jörnsten,  Tobias Abenius, Teresia Kling, Linnea Schmidt, Erik Johansson,  Torbjörn Nordling, Bodil Nordlander, Chris Sander, Peter Gennemark, Keiko Funa, Björn Nilsson, Linda Lindahl, Sven Nelander "Network modeling of the transcriptional effects of copy number aberrations in glioblastoma" Molecular Systems Biology 2011; 7:486

Nikolaus Schultz, Dina R Marenstein, Dino A De Angelis, Wei-Qing Wang, Sven Nelander, Anders Jacobsen, Debora S Marks, Joan Massague and Chris Sander: "Off-target effects dominate a large-scale RNAi screen for modulators of the TGF-beta pathway and reveal microRNA regulation of TGFBR2" Silence 2011 , 2:3 

Barretina J, Taylor BS, Banerji S, Ramos AH, Lagos-Quintana M, Decarolis PL, Shah K, Socci ND, Weir BA, Ho A, Chiang DY, Reva B, Mermel CH, Getz G, Antipin Y, Beroukhim R, Major JE, Hatton C, Nicoletti R, Hanna M, Sharpe T, Fennell TJ, Cibulskis K, Onofrio RC, Saito T, Shukla N, Lau C, Nelander S, Silver SJ, Sougnez C, Viale A, Winckler W, Maki RG, Garraway LA, Lash A, Greulich H, Root DE, Sellers WR, Schwartz GK, Antonescu CR, Lander ES, Varmus HE, Ladanyi M, Sander C, Meyerson M, Singer S. “Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy” Nature Genetics. 2010 Aug;42(8):715-21. 

Nelander S, Wang W, Nilsson B, She QB, Pratilas C, Rosen N, Gennemark P, Sander C. “Models from experiments: combinatorial drug perturbations of cancer cells” Molecular Systems Biology 2008;4:216. Epub 2008 Sep 2.

Nilsson B, Johansson M, Heyden A, Nelander S, Fioretos T. “An improved method for detecting and delineating genomic regions with altered gene expression in cancer” Genome Biology 2008 Jan 21;9(1):R13.

The best way to obtain EPoC is through CRAN as an R library. Find our more on http://sysbio.med.gu.se/epoc.html

Glioblastoma is a highly invasive tumor of the brain that affects 13,000 Europeans per year. Recently, glioblastoma has emerged as an important model problem in medical systems biology. Large scale molecular mapping efforts have enabled very ambitious integrative data analytical studies of the biology of this tumor. Furthermore, the study of glioblastoma is facilitated by a reliable range of model systems from mouse models and newly extracted cancer stem cell lines. The fact that glioblastoma tumors form naturally occurring molecular subgroups, indicate a potential for patient-selective targeting based on systems biology techniques.

Large scale network modeling of cancer Our goal is to develop high resolution, data-derived models of the glioblastoma subtypes. The models aim to define important biological differences between subtypes, define candidate disease driving genes and identify drug targets. We construct the models using (a generalization of) our method EPoC, which we introduced in a recent MSB paper (Jörnsten et al 2011).

Systematic testing and follow-up of model predictions We test the identified targets and genes in panels of patient-specific glioblastoma-derived cells. This work is done in collaboration with neurooncologists at IGP, Uppsala University and the screening facility at Science for Life Laboratory at the Karolinska Institute (KI).

Our projects aim to accelerate the identification of therapeutic targets for neural tumors, and define new principles by which systems biology is used to for patient-selective therapy. Key challenges ahead include extending the computational methodology, validating new targets and understanding principles that make drug combinations robust with respect to genotype. We expect that our work can generalize to a wider set of tumors in the future.

Are you interested in opportunities in cancer systems biology? Do you want to conduct a challenging project in state-of-the-art computational biology? Do not hesitate to contact us. Drop an email to: sven.nelander[nospam]igp.uu.se

Two new PhD positions with last application date April 30th 2012: systems-scale modeling of cancer and optimal targeting of glioma-derived stem cells .