Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine.

Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.

A Mass Spectrometry Imaging Based Approach for Prognosis Prediction in UICC Stage I/II Colon Cancer.

Currently, pathological evaluation of stage I/II colon cancer, following the Union Internationale Contre Le Cancer (UICC) guidelines, is insufficient to identify patients that would benefit from adjuvant treatment. In our study, we analyzed tissue samples from 276 patients with colon cancer utilizing mass spectrometry imaging. Two distinct approaches are herein presented for data processing and analysis. In one approach, four different machine learning algorithms were applied to predict the tendency to develop metastasis, which yielded accuracies over 90% for three of the models. In the other approach, 1007 m/z features were evaluated with regards to their prognostic capabilities, yielding two m/z features as promising prognostic markers. One feature was identified as a fragment from collagen (collagen 3A1), hinting that a higher collagen content within the tumor is associated with poorer outcomes. Identification of proteins that reflect changes in the tumor and its microenvironment could give a very much-needed prediction of a patient's prognosis, and subsequently assist in the choice of a more adequate treatment.

Click-Chemistry-Mediated Synthesis of Selective Melanocortin Receptor 4 Agonists.

The melanocortin receptor 4 (MC4R) subtype of the melanocortin receptor family is a target for therapeutics to ameliorate metabolic dysfunction. Endogenous MC4R agonists possess a critical pharmacophore (HFRW), and cyclization of peptide agonists often enhances potency. Thus, 17 cyclized peptides were synthesized by solid phase click chemistry to develop novel, potent, selective MC4R agonists. Using cAMP measurements and a transcriptional reporter assay, we observed that several constrained agonists generated by a cycloaddition reaction displayed high selectivity (223- to 467-fold) toward MC4R over MC3R and MC5R receptor subtypes without compromising agonist potency. Significant variation was also observed between the EC50 values for the two assays, with robust levels of reporter expression measured at lower concentrations than those effecting appreciable increases in cAMP levels for the majority of the compounds tested. Collectively, we characterized significant elements that modulate the activity of the core pharmacophore for MC4R and provide a rationale for careful assay selection for agonist screening.