TEAM lEADER Dr. Henrik Johansson
Our overall aim in the BC team is to use MS based proteomics tools to increase our biological understanding of breast cancer, define clinical subtypes, and identify biomarkers for personalized therapy.
The estrogen and progesterone receptors are routinely used together with the tyrosine kinase receptor HER2 to stratify breast cancer patients into different clinical treatment regimes. Genomics efforts have further divided breast cancer, so called PAM50 subtypes, into Luminal A, B, HER2, Basal and normal-like subtypes based on mRNA expression, with refinement based on mutational patterns.
The drug tamoxifen has been one of the cornerstones of treatment of estrogen receptor positive breast cancer for nearly 4 decades. Tamoxifen treatment has reduced the recurrence rate by 50%, but about one-third of these patients still relapse. 80% of all breast cancer patients are eligible for tamoxifen, which highlights the need to find biomarkers to guide treatment. In our efforts to address this question, we have identified a 13 protein panel and the nuclear receptor, RARA, as potential predictive markers of tamoxifen resistance (Johansson, Nature Communications 2013; Johansson, Clinical Proteomics 2015).
We use so called mass spectrometry (MS) based proteomics methods to characterize the proteome. Our method is based on isoelectric focusing of peptides followed by MS analysis that provide in-depth quantification of the proteome (Branca et al Nature Methods 2014). We use proteome information from breast tumors together with other levels of data as copy number, mRNA to gain novel understanding of BC biology. mRNA measurements is frequently used as surrogate measurements for protein and using our in-depth proteomics data we can elucidate the link between mRNA and protein. Since there is not always a direct correlation between mRNA and protein, the proteome provide a new avenue to identify biomarkers for personalized therapy. In addition to using protein levels as biomarkers, we are also investigating the use of protein interactions, as representing a functional unit, as biomarkers.
We are also interested in how the mutational landscapes affect the proteome and whether this information can be used as tumor specific antigens in immunotherapy.
Henrik Johansson – PhD, Team Leader http://lehtiolab.se/about/34-team/104-henrik-johansson-researcher
Fabio Socciarelli – MD, Pathologist, PhD Candidate http://lehtiolab.se/about/34-team/122-fabio-socciarelli-phd-student
Nathaniel Vacanti – PhD, Bioengineer specializing in metabolic function, Postdoc http://lehtiolab.se/about/34-team/107-nathaniel-vacanti-post-doc
Ioannis Siavelis – MD, Bioinformatician, PhD student http://lehtiolab.se/about/34-team/121-john-siavelis-phd-student
Johansson HJ, Sanchez BC, Mundt F, Forshed J, Kovacs A, Panizza E, Hultin-Rosenberg L, Lundgren B, Martens U, Máthé G, Yakhini Z, Helou K, Krawiec K, Kanter L, Hjerpe A, Stål O, Linderholm BK, Lehtiö J. Retinoic acid receptor alpha is associated with tamoxifen resistance in breast cancer. Nature Communications. (2013) 4:2175. doi:10.1038/ncomms3175. https://www.ncbi.nlm.nih.gov/pubmed/23868472
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. Clinical Proteomics. 2015 Mar 21;12(1):8. https://www.ncbi.nlm.nih.gov/pubmed/25878567
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