Abstract
New integrative approaches are needed to harness the potential of rapidly growing datasets of protein expression and microbial community composition in colorectal cancer. Chemical and thermodynamic models offer theoretical tools to describe populations of biomacromolecules and their relative potential for formation in different microenvironmental conditions. The average oxidation state of carbon (ZC) can be calculated as an elemental ratio from the chemical formulas of proteins, and water demand per residue (n}{}{overline{n}}_{{mathrm{H}}_{2}mathrm{O}}) is computed by writing the overall formation reactions of proteins from basis species. Using results reported in proteomic studies of clinical samples, many datasets exhibit higher mean ZC or n}{}{overline{n}}_{{mathrm{H}}_{2}mathrm{O}} of proteins in carcinoma or adenoma compared to normal tissue. In contrast, average protein compositions in bacterial genomes often have lower ZC for bacteria enriched in fecal samples from cancer patients compared to healthy donors. In thermodynamic calculations, the potential for formation of the cancer-related proteins is energetically favored by changes in the chemical activity of H2O and fugacity of O2 that reflect the compositional differences. The compositional analysis suggests that a systematic change in chemical composition is an essential feature of cancer proteomes, and the thermodynamic descriptions show that the observed proteomic transformations in host tissue could be promoted by relatively high microenvironmental oxidation and hydration states.
Highlights
Datasets for differentially expressed proteins in cancer are often interpreted from a mechanistic perspective that emphasizes molecular interactions
This approach reveals common patterns of chemical changes among many proteomic datasets, and the possibility that proteomic transformations may be shaped by energetic constraints associated with the changing tumor microenvironment
This study has identified a strong shift toward higher average oxidation state of carbon in proteins that are more highly expressed in colorectal cancer
Summary
Datasets for differentially expressed proteins in cancer are often interpreted from a mechanistic perspective that emphasizes molecular interactions. Alternative approaches exemplified by recent models that use information theory demonstrate the possibility of interpreting proteomic expression data in a high-level conceptual framework (Rietman et al, 2016) These approaches may combine concepts from dynamical systems theory and thermodynamics, such as the correspondence of “attractor states” in landscape models with low-energy states of a system (Enver et al, 2009; Davies et al, 2011). Despite these advances, energetic functions for differential protein expression have not previously been formulated in terms of physicochemical variables that reflect the conditions of tumor microenvironments. This approach reveals common patterns of chemical changes among many proteomic datasets, and the possibility that proteomic transformations may be shaped by energetic constraints associated with the changing tumor microenvironment
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