The purpose of this study was to analyze imaging mass cytometry data to obtain information about the tumor microenvironment and the pancreatic cancer progression. DBSCAN clustering algorithm was employed to identify and measure the presence of several markers in the pancreatic tumors setting. The results of this study suggest that the presence of cancer cells could inhibit the infiltration of T cells in the tumor microenvironment. This could be interpreted as an inhibition of the immune system which could affect it's ability to prevent tumor progression.
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This work was developed as a final project of CISC372 (Advanced Data Analytics) course from the Computing department of Queen's University.
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