1,1′-binaphthyl-2,2′-diamine as a novel MALDI matrix to enhance the in situ imaging of metabolic heterogeneity in lung cancer

Profile the spatial distributions of endogenous metabolites in heterogeneous tissues is critical to elucidate the complex metabolic mechanisms during pathological progression. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a label-free technique for tissue imaging that allows simultaneous localisation and quantification of metabolites in different histological regions of interest. In the present study, 1,1′-binaphthyl-2,2′-diamine (BNDM) was developed as a novel MALDI matrix for the detection and imaging of metabolites because of its low background interference, high sensitivity, and applicability in both positive and negative ion modes. 301 negative metabolite ions and 175 positive metabolite ions, including amino acids, organic acids, nucleosides, nucleotides, nitrogenous bases, cholesterols, peptides, fatty acids, cholines, carnitines, polyamines, creatine, phospholipids, etc., were imaged in rat brain when BDMN was used as matrix. Furthermore, BNDM-assisted MALDI-MSI of mouse lung cancer tissue successfully characterized the spatial features of numerous metabolites in viable, necrotic, and connective tissue areas. Importantly, our results demonstrate that the viable area of lung cancer tissue contained a higher abundance of K+ adducts, while the necrotic area showed a stronger Na+ adducts intensity. Data-driven segmentation analysis based on the in situ tissue metabolic fingerprints clearly visualized the underlying metabolic heterogeneity of lung cancer, which may provide new insights into the profiling of tumor microenvironment. All these results suggest that the newly developed matrix has great potential application in the field of biomedical research. [Display omitted] •1,1′-Binaphthyl-2,2′-diamine (BNDM) was developed as a novel MALDI matrix for the imaging of metabolites.•The spatial distributions 301 negative metabolite ions and 175 positive metabolite ions in rat brain were imaged.•We characterized the spatial features of numerous metabolites in heterogeneous lung cancer tissue.•Data-driven cancer segmentation analysis clearly visualizes the underlying metabolic heterogeneity of lung cancer.