@article {ABRAMOWSKI179, author = {PIERRE ABRAMOWSKI and OLGA KRAUS and SASCHA ROHN and KRISTOFFER RIECKEN and BORIS FEHSE and HARTMUT SCHL{\"U}TER}, title = {Combined Application of RGB Marking and Mass Spectrometric Imaging Facilitates Detection of Tumor Heterogeneity}, volume = {12}, number = {4}, pages = {179--187}, year = {2015}, publisher = {International Institute of Anticancer Research}, abstract = {Cancer-cell heterogeneity dramatically influences treatment success, but escapes detection by classical histology. Mass-spectrometric imaging (MSI) represents a powerful method for visualizing the spatial distribution of proteins in tissue sections. Herein we asked whether MSI also facilitates detection of tumor heterogeneity. We first transduced the human neuroendocrine-carcinoma BON cell line following the red-green-blue (RGB) marking principle. RGB marking allows for specific color-coding of individual clones. Mice transplanted with RGB-marked BON cells developed liver tumors. We identified 16 primary tumors clearly distinguishable by histology and fluorescence imaging, but also based on a common tumor-specific signal pattern detected by MSI. Importantly, this pattern was clearly confined to tumor tissue while was absent from surrounding liver tissue. At the same time, we observed protein signals differentially present in a few or even single tumors. Since these signals were independent of RGB marking, they apparently reflected unique intrinsic protein-signal patterns of individual tumors. Thus, our data propose MSI as a tool for identifying divergent tissue by {\textquoteleft}fingerprints{\textquoteright} of protein signals, allowing not only for differentiation of tumor from healthy tissue but also detection of tumor heterogeneity. In conclusion, by visualizing tumor heterogeneity, MSI ideally complements microscopy-based methods. This might help to better understand tumor biology and develop future treatment strategies.}, issn = {1109-6535}, URL = {https://cgp.iiarjournals.org/content/12/4/179}, eprint = {https://cgp.iiarjournals.org/content/12/4/179.full.pdf}, journal = {Cancer Genomics \& Proteomics} }