Department of Medical Sciences

Research and development

Our aim is to develop and apply bioinformatic tools to describe and understand biological processes involved in human disease so that improved treatments can be developed. We focus on how to use large-scale molecular data including microarray data to obtain these goals. In practice it means that we are involved in two types of research acivities.

1) BIOINFORMATIC TOOLS

We develop improved bioinformatic tools that can provide better answers to relevant research questions.

Our efforts to develop new bioinformatic tools have been focused on three major areas over the last few years: genomic aberrations in tumor cells, non-coding RNAs from RNAseq data and improved performance estimation.

Identification of genomic aberrations in tumor cells

The goal is to identify copy number aberrations in tumor cells in clinical tumor samples. However there are a number of issues that makes this task difficult. Often large proportions of non-tumor cells are present in the sample. Tumor cells are often aneuploid complicating normalization. Different tumor cells may also have different aberrations.

Whole genome sequencing data

We have developed a bioinformatic tool called Patchwork that uses whole-genome sequencing data from cancer samples to obtain segments with allele-specific copy numbers.

Mayrhofer M, DiLorenzo S, Isaksson A. 2013. Patchwork: allele-specific copy number analysis of whole genome sequenced tumor tissue. Genome Biol. Mar 25;14(3):R24

SNP array data

We have also developed one bioinformatic tool called Tumor Aberration Prediction Suite (TAPS) identifies allele-specific copy numbers and loss-of heteozygosity from SNP array data, even in the presence of large proportions of non-tumor cells and aneuploidy.

2) DATA ANALYSIS

We apply publically available tools or those we have developed ourselves to perform data analysis for particular biomedical applications.

Our efforts to analyze data in biomedical applications fall into two broad categories: Analysis of genomic DNA, mRNA expression and/or methylation in tumor samples and Identification of mRNA biomarkers in various types of samples

Analysis of genomic DNA, mRNA expression and/or methylation in tumor samples

Kanduri M, Marincevic M, Halldórsdóttir AM, Mansouri L, Juvenik K, Ntoufa S, Göransson Kultima H, Isaksson A, Juliusson G, Andersson P-O, Ehrencrona H, Stamatopoulos K, Rosenquist R. 2012. Distinct transcriptional control in major immunogenetic subsets of chronic lymphocytic leukemia exhibiting subset-biased global DNA methylation profiles. Epigenetics Dec 1; 7(12):1435-42

Sooman, L.; Ekman, S.; Andersson, C.; Johansson, F.; Goransson-Kultima, H.; Isaksson, A.; Bergqvist, M.; Blomquist, E.; Lennartsson, J.; Gullbo, J. 2012. 1012 Synergistic Effects of PI3K or P38 MAPK Inhibition in Combination With Vandetanib Treatment in Glioblastoma Cells. European Journal of Cancer vol. 48 July, 2012. p. S244

Skirnisdottir I, Mayrhofer M, Rydåker M, Åkerud H and Isaksson A. 2012.Loss-of-heterozygosity on chromosome 19q in early-stage serous ovarian cancer is associated with recurrent disease. BMC Cancer2012, 12:407doi:10.1186/1471-2407-12-407

Cahill N, Bergh AC, Kanduri M, Göransson-Kultima H, Mansouri L, Isaksson A, Ryan F, Smedby KE, Juliusson G, Sundström C, Rosén A, Rosenquist R. 2012. 450K-array analysis of chronic lymphocytic leukemia cells reveals global DNA methylation to be relatively stable over time and similar in resting and proliferative compartments. Leukemia. 2013 Jan;27(1):150-8. doi: 10.1038/leu.2012.245. Epub 2012 Aug 27

Mansouri L, Gunnarsson R, Sutton LA, Ameur A, Hooper SD, Mayrhofer M, Juliusson G, Isaksson A, Gyllensten U, Rosenquist R. 2012. Next generation RNA-sequencing in prognostic subsets of chronic lymphocytic leukemia. Am J Hematol. 2012 Jul;87(7):737-40.

Edlund K, Lindskog C, Saito A, Berglund A, Pontén F, Göransson-Kultima H, Isaksson A, Jirström K, Planck M, Johansson L, Lambe M, Holmberg L, Nyberg F, Ekman S, Bergqvist M, Landelius P, Lamberg K, Botling J, Ostman A, Micke P. 2012. CD99 is a novel prognostic stromal marker in non-small cell lung cancer. Int J Cancer. 2012 131(10):2264-73

Halldórsdóttir AM, Kanduri M, Marincevic M, Mansouri L, Isaksson A, Göransson H, Axelsson T, Agarwal P, Jernberg-Wiklund H, Stamatopoulos K, Sander B, Ehrencrona H, Rosenquist R. 2012. Mantle cell lymphoma displays a homogenous methylation profile: A comparative analysis with chronic lymphocytic leukemia. Am J Hematol 2012 Apr;87(4):361-7. doi: 10.1002/ajh.23115. Epub 2012 Feb 28.

Schmidt M, Hellwig B, Hammad S, Othman A, Lohr M, Chen Z, Böhm D, Gebhard S, Petry IB, Lebrecht A, Cadenas C, Marchan R, Stewart J, Solbach C, Holmberg L, Edlund K, Kultima HG, Rody A, Berglund A, Lambe M, Isaksson A, Botling J, Karn T, Müller V, Gerhold-Ay A, Cotarelo C, Sebastian M, Kronenwett R, Bojar H, Lehr HA, Sahin U, Koelbl H, Gehrmann M, Micke P, Rahnenführer J, Hengstler JG. 2012. A comprehensive analysis of human gene expression profiles identifies stromal immunoglobulin kappa C as a compatible prognostic marker in human solid tumors. Clin Cancer Res. 2012 May 1;18(9):2695-703. doi: 10.1158/1078-0432.CCR-11-2210. Epub 2012 Feb 20.

Micke P, Edlund K, Holmberg L, Kultima HG, Mansouri L, Ekman S, Bergqvist M, Scheibenflug L, Lamberg K, Myrdal G, Berglund A, Andersson A, Lambe M, Nyberg F, Thomas A, Isaksson A, Botling J. Gene copy number aberrations are associated with survival in histologic subgroups of non-small cell lung cancer. J Thorac Oncol. 2011 Nov;6(11):1833-40.

Gunnarsson R, Mansouri L, Isaksson A, Göransson H, Cahill N, Jansson M, Rasmussen M, Lundin J, Norin S, Buhl AM, Smedby KE, Hjalgrim H, Karlsson K, Jurlander J, Geisler C, Juliusson G, Rosenquist R. Array-based genomic screening at diagnosis and during follow-up in chronic lymphocytic leukemia. Haematologica. 2011 Aug;96(8):1161-9. Epub 2011 May 5.

Halldórsdóttir AM, Sander B, Göransson H, Isaksson A, Kimby E, Mansouri M, Rosenquist R, Ehrencrona H. (2011) High-resolution genomic screening in mantle cell lymphoma-specific changes correlates with genoic complexity, the proliferative signature and survival. Genes Chromosomes Cancer. 2011 Feb;50(2):113-21.

Marincevic M, Mansouri M, Kanduri M, Isaksson A, Goransson H, Ekstrom Smedby K, Jurlander J, Juliusson G, Davi F, Stamatopoulos K, Rosenquist R. 2010. Distinct gene expression profiles in subsets of chronic lymphocytic leukemia expressing stereotyped IGHV4-34 B cell receptors. Haematologica. 2010 Aug 26.

Marincevic M, Cahill M, Gunnarsson R, Isaksson A, Mansouri M, Göransson H, Rasmussen M, Jansson M, Ryan F, Karlsson K, Adami HO, Davi F, Jurlander J, Juliusson G, Stamatopoulos K and Rosenquist R. 2010. High-density screening reveals diferent sepctra of genomic aberrations in chronic lymphosytic leukemia patients with “stereotyped” IGHV3-21 or IGHV4-34 B-cell receptors. Haematologica. Apr 26.

Kanduri M, Cahill N, Göransson H, Enström C, Ryan F, Isaksson A and Rosenquist R. 2010. Differential genome-wide methylation profiles in prognostic subsets of chronic lymphocytic leukemia. Blood. Jan 14;115(2):296-305

Gunnarsson R, Isaksson A, Mansouri M, Göransson H, Jansson M, Cahill N, Rasmussen M, Staaf J, Lundin J, Norin, Buhl AM, Ekström Smedby K, Hjalgrim H, Karlsson K, Jurlander J, Juliusson G and Rosenquist R. 2010. Large but not small copy-number alterations correlate to high-risk genomic aberrations and survival in chronic lymphocytic leukemia: A high-resolution genomic screening of newly diagnosed patients. Leukemia. Jan;24(1):211-5

Gunnarsson R, Staaf J, Jansson M, Ottesen AM, Göransson H, Liljedahl U, Ralfkiaer U, Mansouri M, Buhl AM, Ekström Smedby K, Hjalgrim H, Syvänen A-C, Borg Å, Isaksson A, Jurlander J, Juliusson G and Rosenquist R. 2008. Screening for copy number alterations and loss-of-heterozygosity in Chronic Lymphocytic Leukemia -A comparative study of four differently designed high-resolution microarray platforms. Genes Chromosomes and Cancer 2008 Aug;47(8):697-711

Fryknäs M, Dhar S, Öberg F, Rickardson L, Rydåker M, Göransson H, Gustafsson MG, Pettersson U, Nygren P, Larsson R and Isaksson A. 2007. STAT1 signaling is associated with acquired cross-resistance to doxorubicin and radiation in myeloma cell lines. Int J Cancer. Jan 1;120(1):189-95.
 

Identification of mRNA biomarkers in various types of samples

Brunberg E, Jensen P,Isaksson A, Keeling L. 2012. Brain gene expression differences are associated with abnormal tail biting behavior in pigs. Genes Brain Behav. 2012 Nov 12. doi: 10.1111/gbb.12002.

Zhao H, Dahlö M, Isaksson A, Syvänen AC, Pettersson U. The transcriptome of the adenovirus infected cell. Virology. 2012 Jan 9.

Ronquist GK, Larsson A, Ronquist G, Isaksson A, Hreinsson J, Carlsson L, Stavreus-Evers A. Prostasomal DNA characterization and transfer into human sperm. Mol Reprod Dev. 2011 Jul;78(7):467-76. doi: 10.1002/mrd.21327. Epub 2011 Jun 2.

Brunberg E, Jensen P, Isaksson A, Keeling L. Feather pecking behavior in laying hens: hypothalamic gene expression in birds performing and receiving pecks.Poult Sci. 2011 Jun;90(6):1145-52.

Laryea D, Gullbo J, Isaksson A, Larsson R, Nygren P. 2010. Characterization of the cytotoxic properties of the benzimidazole fungicides, benomyl and carbendazim in human tumor cell lines and primary cultures of patient tumor cells. Anticancer Drugs. 2010 Jan;21(1):33-42