Introduction to proteomics

Clinical proteomics of breast cancer

Clinical proteomics aims to find protein biomarkers and drug targets in patient-derived samples. In cancer research, clinical proteomics analyzes tumor tissues and body fluids. In our laboratory we concentrate on the analysis of breast cancer clinical samples and examine fundamental questions in cancer biology. We study differences between distinct breast cancer subtypes, stages and examine the internal tumor heterogeneity.  For relative quantification of tumor samples we use the super-SILAC technology [1,2]. In this method cancer cell lines are SILAC-labeled and these serve as a reference for the clinical- non-labeled samples. quantification of each of the samples relative to the same standard enables accurate comparison between them. Following cell and tissue lysis, proteins are digested to peptides and these are then separated by reverse-phase liquid chromatography (LC) coupled to high-resolution mass spectrometry (MS). Each LC-MS run eventually leads to the identification and quantification of thousands of proteins, which can be compared between the clinical samples. Advanced computational tools are then used to extract the significant proteins. These serve as the basis for further bioinformatic and biological research.

Cancer metabolism

Metabolic remodeling has been recently recognized as a novel cancer hallmark. It was first recognized in 1924 by Otto Warburg who identified high rates of glycolysis and lactate production in cancer cells even under aerobic conditions. The interest in the connection between cancer and metabolism dramatically increased in recent years with the identification of oncogenes and tumor suppressors that directly affect metabolism, and with identification of cancer mutations in metabolic enzymes. The human metabolic network consists of approximately 2000 enzymes. The proteomic profiles that we obtain from cancer cells and tumor tissues provide a global view of the network and computational analysis translates the protein-level information to pathways and processes. In the next step we examine how these metabolic alterations affect the cellular proteome, the phosphoproteome as well as the tumorigenic capabilities of the cells.

 Our Funding

 

 References

  1. Geiger T, Cox J, Ostasiewicz P, Wisniewski JR, Mann M: Super-SILAC mix for quantitative proteomics of human tumor tissueNature methods 2010, 7(5):383-385.
  2. Geiger T, Wisniewski JR, Cox J, Zanivan S, Kruger M, Ishihama Y, Mann M: Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomicsNature protocols 2011, 6(2):147-157.