Integrative analysis of gene expression and promoter methylation during reprogramming of a non-small-cell lung cancer cell line using principal component analysis-based unsupervised feature extraction

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Abstract

Cancer cells are to some extent regarded as similar to undifferentiated cells, such as embryonic stem cells and induced pluripotent cells. However, cancer cells can be reprogrammed using standard reprogramming procedures. Thus, it would be interesting to observe the result of cancer cell reprogramming. In this paper, we reanalyzed publically available mRNA expression and promoter methylation profiles during reprogramming of non-small-cell lung cancer cell lines, using the recently proposed principal component analysis-based unsupervised feature extraction. Six genes, TGFBI, S100A6, CSRP1, CLDN11, PRKCDBP, and CRIP1, were commonly found (P = 0.003) in the 100 top-ranked genes with aberrant expression or aberrant promoter methylation. Because all six genes were related to cancer in the literature, they might be new therapeutic targets for treatment of non-small-cell lung cancer. © 2014 Springer International Publishing Switzerland.

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Taguchi, Y. H. (2014). Integrative analysis of gene expression and promoter methylation during reprogramming of a non-small-cell lung cancer cell line using principal component analysis-based unsupervised feature extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8590 LNBI, pp. 445–455). Springer Verlag. https://doi.org/10.1007/978-3-319-09330-7_52

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