Differential array sensing for cancer cell classification and novelty detection
| Autor: | Eric V. Anslyn, Margaret K. Meadows, Andrew D. Ellington, Alexandra M. Gade |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Cell
Analytical chemistry Tissue Array Analysis Computational biology 010402 general chemistry 01 natural sciences Biochemistry Novelty detection Epitope chemistry.chemical_compound Cell Line Tumor Neoplasms medicine Humans A-DNA Benzothiazoles Physical and Theoretical Chemistry Fluorescent Dyes 010405 organic chemistry Chemistry Organic Chemistry Linear discriminant analysis 0104 chemical sciences medicine.anatomical_structure Cancer cell Quinolines Peptides DNA |
| Zdroj: | Organicbiomolecular chemistry. 15(46) |
| ISSN: | 1477-0539 |
| Popis: | A series of semi-specific peptides reported in the literature to bind various epitopes on cell surfaces were used in a differential sensing array to pattern cell line identity. The peptides were conjugated to thiazole orange to act as both a fluorescence reporter and a DNA intercalator. Fluorescence data for the peptides exposed to cells, with and without exogenous double stranded DNA (dsDNA), led to chemometric fingerprints for eight cancer cell lines. In contrast to the use of structures meant to act in completely non-specific ways, the use of a limited level of specificity generated linear discriminant score plots with high dimensionality, i.e. several principle components carrying significant variance. The arrays were found to correctly classify the cell lines from 60% to 100% depending upon the cell line. Due to the high dimensionality score plots, the identification of cell lines that were not part of the training set was examined. Support vector machines were used as a novelty detection routine and showed that a cancer line not part of the original training set could be correctly identified as being novel. |
| Databáze: | OpenAIRE |
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