Landscapes and predictive markers
To make full use of emerging targeted cancer drugs we need to be able to assess which cellular pathways drive each tumour. To do this, multiple biomarkers associated with the activity of drug targets need to be analysed in parallel. Protein level analysis provides data on how genotype and environmental factors combined drive tumour growth. To generate comprehensive proteome data on tumour samples, we use our high resolution fractionation (HiRIEF) method followed by mass spectrometry (MS) analysis (Branca, Nature methods, 2014). Our cancer proteomics effort is built on translational research from cell lines to clinical cohort analysis. Within our research group, we have basic scientist and clinicians as well as a great collaborative network of researchers in Sweden and worldwide. Today we have vast experience on cancer proteomics on clinical material. Examples of research questions that we are currently focusing on include: How can we improve hormonal breast cancer treatment to reduce relapse risk? How to improve targeted lung cancer therapy by selecting effective drug combinations? How can we improve childhood cancer treatments by adding targeted drugs to minimize the side effects of treatment?
Johansson HJ, Sanchez BC, Forshed J, Stål O, Fohlin H, Lewensohn R, Hall P, Bergh J, Lehtiö J, Linderholm BK. Proteomics profiling identify CAPS as a potential predictive marker of tamoxifen resistance in estrogen receptor positive breast cancer. Clin Proteomics. 2015 Mar 21;12(1):8.
Azimi A, Pernemalm M, Frostvik Stolt M, Hansson J, Lehtiö J, Egyházi Brage S, Hertzman Johansson C. Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance. Br J Cancer. 2014 May 13;110(10):2489-95.
Mundt F, Johansson H, Forshed J, Arslan S, Metintas M, Dobra K, Lehtiö J, Hjerpe A. Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma. Mol Cell Proteomics. 2014 Mar;13(3):701-15
Lazar V, Suo C, Orear C, van den Oord J, Balogh Z, Guegan J, Job B, Meurice G, Ripoche H, Calza S, Hasmats J, Lundeberg J, Lacroix L, Vielh P, Dufour F, Lehtiö J, Napieralski R, Eggermont A, Schmitt M, Cadranel J, Besse B, Girard P, Blackhall F, Validire P, Soria JC, Dessen P, Hansson J, Pawitan Y. Integrated molecular portrait of non-small cell lung cancers. BMC Med Genomics. 2013 Dec 3;6:53
Pernemalm M, De Petris L, Branca RM, Forshed J, Kanter L, Soria JC, Girard P, Validire P, Pawitan Y, van den Oord J, Lazar V, Påhlman S, Lewensohn R, Lehtiö J. Quantitative proteomics profiling of primary lung adenocarcinoma tumours reveals functional perturbations in tumour metabolism. J Proteome Res. 2013 Sep 6;12(9):3934-43..
Johansson H.J, Sanchez B.C., Mundt F., Forshed J., Lundgren B., Martens U., Kovacs A., Máthé G., Yakhini Z., Helou K., Einbeigi Z., Krawiec K., Kanter L., Hjerpe A., Stål O., Linderholm B.K., Lehtiö J. Retinoic acid receptor alpha has potential predictive value in tamoxifen treated breast cancer patients. Nature Commun. 2013. Jul 19;4:2175.
Zirath H.,Frenzel A., Oliynyk G., Segerström L., Westermark U.K., Larsson K., Munksgaard Persson M.,Hultenby K., Lehtiö J., Einvik C.,Påhlman S.,Kogner P., Jakobsson P.J., Arsenian Henriksson M., MYC-Inhibition Induces Metabolic Changes Leading to Accumulation of Lipid Droplets in Tumor Cells. Proc Natl Acad Sci U S A., 2013 Jun 18;110(25):10258-63.
Orre L.M., Panizza E., Kaminskyy V., Vernet E., Gräslund T.B., Zhivotovsky B., Lehtiö J. S100A4 interacts with p53 in the nucleus and promotes p53 degradation. Oncogene, 2013 Dec 5;32(49):5531-40.
Figure from Johansson H., et al., Nature Communications. High tumoral protein levels of retinoic acid receptor alpha indicates poor prognosis in tamoxifen treated hormone receptor positive breast cancer. In this publication we also demonstrate that cell line model representing high RARA tumors responds well on fulvestand (another estrogen receptor blocking drug).