In the post-genome area, Proteomics has become a major tool for qualitative and quantitative analysis of complex biological systems and to understand the background of cellular functions and malfunctions. While mass spectrometric methods have reached the required level of sensitivity to identify proteins in biological systems, the vast complexity of protein modifications, isoforms, truncations or splice variants cannot be covered by today approaches. Recent publications have shown that each gene results in many different active forms of the protein are present in a cellular system. Protein-biomarker discovery is mainly based on the search for up- or down-regulated proteins, either by quantitative mass spectrometry comparing samples from healthy and diseased individuals or on extracting potential candidates from orthogonal data sets, as from Transcriptomics. This approach only takes increased or decreased levels of proteins into account, not looking at possible different post-translational modifications that affect the function of the protein and lead to diseases. Also gene-related modifications, as mutations, truncations, splice-variant, RNA-edited amino acid exchanges are not considered. Taking all the possible modifications into account, each protein covers a wide space in a three dimensional room with the dimensions: concentration, gene-related modifications and post-translational modifications. In this room some of the combinations will not affect the protein function in the cellular system, while others lead to malfunction and diseases. These would serve as an biomarker for diagnostics and to stratifying personalized medical treatment. The full analysis of each protein covering all of these dimensions is still not possible today.
A reverse Omics’ approach may help to overcome these limitations. Most of the biological pathways are either directly or indirectly connected to metabolic processes, to the synthesis or conversion of small molecules. Even these are representing a vast complexity of different molecules, each of them represents a unique structure accessible by mass spectrometric techniques in combination with targeted sample preparation and extraction procedures. These metabolomic data enable the conclusion back to the disturbed pathway and a targeted analysis of the proteins and their mutations and modifications involved this pathway. Beside the potential use of the identified Metabolites as biomarkers, proteins of the disturbed pathway can be taken into account as biomarker candidates and submitted to verification using targeted mass spectrometry. A general approach for the combination of Proteomics and Metabolomics to detect potential biomarkers will be discussed.