Automatic Tumor-Stroma Separation in Fluorescence TMAs Enables the Quantitative High-Throughput Analysis of Multiple Cancer Biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry

Formation of ArF from LPdAr(F): Catalytic Conversion of Aryl Triflates to Aryl Fluorides

Despite increasing pharmaceutical importance, fluorinated aromatic organic molecules remain difficult to synthesize. Present methods require either harsh reaction conditions or highly specialized reagents, making the preparation of complex fluoroarenes challenging. Thus, the development of general methods for their preparation that overcome the limitations of those techniques currently in use is of great interest. We have prepared [LPd(II)Ar(F)] complexes, where L is a biaryl monophosphine ligand and Ar is an aryl group, and identified conditions under which reductive elimination occurs to form an Ar-F bond. On the basis of these results, we have developed a catalytic process that converts aryl bromides and aryl triflates into the corresponding fluorinated arenes by using simple fluoride salts. We expect this method to allow the introduction of fluorine atoms into advanced, highly functionalized intermediates.National Institutes of Health (U.S.) (Grant GM46059)Merck & Co., Inc.Boehringer Ingelheim PharmaceuticalsBASFNational Science Foundation (U.S.) (Grant CHE 9808061)National Institutes of Health (U.S.) (Grant DBI 9729592

Copper-catalyzed trifluoromethylselenolation of aryl and alkyl halides: The silver effect in transmetalation

10.1021/ol403406yOrganic Letters162524-527ORLE