where m1= intensity of m/z in FFPE, ma= mean intensity of M/z in FFPE; n1=intensity of m/z in FF, na= mean intensity of m/z in FF. The scale used for analysis uses a scale from -1 to 1, where 1 is perfect correlation, 0 is no correlation, and -1 is anti-correlation. For comprehensive statistical analysis, the Costes analysis will tell us if the Pearson Correlation Coefficient and the Manders’ analysis coefficients are better than pure chance or not. This is done by shuffling the pixels in one of the images, and then reperforming the Manders and Pearson Correlation Analysis. A P-value of 1.00 means that none of the randomized images had better correlation. Any m/z values that do not meet this requirement will be discarded as noise. Following analysis, each m/z value will have a value for both spatial and intensity for both FFPE and FF conditions. Expected Results: We believe that lipids, amino acids, and carbohydrates will also remain conserved, as in mass spectrometry studies previously done. Criteria for conservation of a m/z value for mass spectrometry: Pearson’s R value greater than or equal to .5, a Manders coefficient greater than or equal to .85, and a Costes p-value of 1.0. Following characterization in spheroid analysis, this study will be used to generate a conserved list of metabolites to perform biomarker analysis using FFPE tissue microarrays. Mass spectrometry imaging may be able to provide new metabolite biomarkers that are able to distinguish normal tissue, chronic pancreatitis, and PDAC grade. Tissue microarrays will be similarly prepared, and receiver operator curve analysis and pathology annotation will be able to calculate biomarkers from FFPE tissues. By creating a list of conserved metabolites, the mass spectrometry imaging community and cancer research community can further probe many different FFPE for metabolite markers of chemoresistance and metastatic markers. Pitfalls or alternative methods: Matrix application and mass spectrometry parameters may need to be optimized to successfully extract various classes of metabolites for analysis.