Comprehensive transcriptome mining of the direct conversion of mesodermal cells.

The direct reprogramming of somatic cells is a promising approach for regenerative medicine, especially in the production of mesoderm layer-derived cells. Meta-analysis studies provide precise insight into the undergoing processes and help increase the efficiency of reprogramming. Here, using 27 high-throughput expression data sets, we analyzed the direct reprogramming of mesodermal cells in humans and mice. Fibroblast-derived cells showed a common expression pattern of up- and down-regulated genes that were mainly involved in the suppression of the fibroblast-specific gene expression program, and may be used as markers of the initiation of reprogramming. Furthermore, we found a specific gene expression profile for each fibroblast-derived cell studied, and each gene set appeared to play specific functional roles in its cell type, suggesting their use as markers for their mature state. Furthermore, using data from protein-DNA interactions, we identified the main transcription factors (TFs) involved in the conversion process and ranked them based on their importance in their gene regulatory networks. In summary, our meta-analysis approach provides new insights on the direct conversion of mesodermal somatic cells, introduces a list of genes as markers for initiation and maturation, and identifies TFs for which manipulating their expression may increase the efficiency of direct conversion.

Comprehensive Dissection of Transcriptome Data and Regulatory Factors in Pancreatic Cancer Cells.

Features of pancreatic cancers include high mortality rates caused by rapid tumor progression and a lack of effective therapy. Underpinning the molecular mechanisms involved in the alteration of the gene expression program in the pancreatic cancer remains to be understood. In the current study, we performed a comprehensive analysis using 282 pancreatic tumor and normal samples from seven independent expression data sets to provide a better view on the interactions between different transcription factors (TFs) and the most affected biological pathways in pancreatic cancer. We highlighted common differentially expressed genes (DEGs) and common affected processes within pancreatic cancer samples. We revealed 16 main DE-TFs that regulated gene expression alterations as well as the most significant processes in pancreatic cancer compared to normal cells. For example, we found the upregulated FOXM1 to be a top regulator of pancreatic cellular transformation based on results from different analyses, including from its regulation of gene regulatory networks, its presence in protein complex, its significant regulation of genes related to cancer pathways, and its regulation of most of the identified DE-TFs. Furthermore, we provided a model and assessed the role of different DE-TFs in the regulation of the most affected pancreatic- and cancer-specific processes. In conclusion, our bioinformatics meta-analysis of high throughput expression data sets, besides clarifying common affected genes and pathways, also showed the mechanisms involved in regulating these common profiles. Our results, especially for DE-TFs, could potentially be useful for screening for pancreatic cancer, and for confirming or determining novel pharmacological targets. J. Cell. Biochem. 118: 3976-3985, 2017. © 2017 Wiley Periodicals, Inc.