Profiling protein expression and interactions: proximity ligation as a tool for personalized medicine

Authors


Ulf Landegren, Department of Genetics & Pathology, Rudbeck Laboratory, SE-75185 Uppsala, Sweden.
(fax: +4618 4714808; e-mail: ulf.landegren@genpat.uu.se).

Abstract

Abstract.  Blokzijl A, Friedman M, Pontén F, Landegren U (From the Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden). Profiling protein expression and interactions: proximity ligation as a tool for personalized medicine. (Review) J Intern Med 2010; 268: 232–245.

The ability to detect very low levels of expressed proteins has enormous potential for early diagnostics and intervention at curable stages of disease. An extended range of targets such as interacting or post-translationally modified proteins can further improve the potential for diagnostics and patient stratification, and for monitoring response to treatment. These are critical building blocks for personalized treatment strategies to manage disease. The past few decades have seen a remarkably improved understanding of the molecular basis of disease in general, and of tumour formation and progression in particular. This accumulated knowledge creates opportunities to develop drugs that specifically target molecules or molecular complexes critical for survival and expansion of tumour cells. However, tumours are highly variable between patients, necessitating the development of diagnostic tools to individualize treatment through parallel analysis of sets of biomarkers.

The proximity ligation assay (PLA) can address many of the requirements for advanced molecular analysis. The method builds on the principle that recognition of target proteins by two, three or more antibodies can bring in proximity DNA strands attached to the antibodies. The DNA strands can then participate in ligation reactions, giving rise to molecules that are amplified for highly sensitive detection. PLA is particularly well suited for sensitive, specific and multiplexed analysis of protein expression, post-translational modifications and protein–protein interactions. The analysis of this extended range of biomarkers will prove critical for the development and implementation of personalized medicine.

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