Advancing systems medicine with mass spectrometry


Current cancer classification is based on the idea of cell of origin and histopathological attributes of cancer biopsies. However, cancer patients with the same histopathological diagnosis still experience diverse disease outcome. Therefore, interrogating an extended panel of proteins, beyond the rather few antigens currently used in immunohistochemistry, as well as additional biomolecules such as metabolites would be highly relevant to predict disease progression in a variety of cancers, and to guide therapy based on a patient’s individual risk profile. Discovery and implementation of clinically useful multi-omics molecular profiles requires a systems medicine approach that can only be achieved by tight integration of clinical, technological and computational expertise and resources. This is technically and logistically highly challenging, since it requires various criteria that need to be met simultaneously:

  • availability of a significant number of well-annotated clinical samples that adhere to defined clinical inclusion criteria and that are collected by standardized procedures;
  • standardized procedures for sample preparation and mass spectrometry for robust proteome and metabolome analysis;
  • advanced IT infrastructure, data integration and mathematical modeling
  • appropriate means for clinical validation and implementation (e.g. trials, multidisciplinary teams for personalized medicine)
  • a scientific environment that facilitates coordinated integration of the above preconditions.

SMART-CARE aims to tackle these challenges by posing the following specific aims:

  1. Establish a pipeline for systems medicine that seamlessly combines clinical sample collection, proteomic and metabolomic analysis, and data integration to produce informative molecular profiles and models.
  2. Use the established pipeline to address the systems medicine question to derive predictive models for tumor recurrence from integrated clinical, proteomic and metabolomic data.

We aim to establish a systems medicine program that integrates proteomic and metabolomic analysis of patient cancer samples, multi-omic profiling, bioinformatic analysis, mathematical modeling and setup towards a clinical exploitation. By comparing proteomic and metabolomic profiles of cancer patients with detailed molecular characterization (e.g. whole exome- and RNA-sequencing) and the clinical parameters, we will obtain “big data” of associations of metabolomic and proteomic profiles with outcome. To achieve this, SMART-CARE brings together a consortium of internationally recognized clinicians, mass spectrometrists, theoreticians and data scientists at the Heidelberg medical campus to address the requirements for effective systems medicine, and to collectively move the field beyond the “cell of origin” paradigm for prognosis prediction and therapy assignment. Artificial intelligence approaches such as pattern recognition by machine learning will lead to next generation diagnostics.