1. Computational integration of homolog and pathway gene module expression reveals general stemness signatures
- Author
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Martina Koeva, E. Camilla Forsberg, and Joshua M. Stuart
- Subjects
DNA Repair ,Microarrays ,Cellular differentiation ,Induced Pluripotent Stem Cells ,Gene Expression ,lcsh:Medicine ,Computational biology ,Biology ,Stem cell marker ,Models, Biological ,Molecular Genetics ,Mice ,Neural Stem Cells ,Cancer stem cell ,Neoplasms ,Animals ,Humans ,lcsh:Science ,Genome Evolution ,Embryonic Stem Cells ,Oligonucleotide Array Sequence Analysis ,Regulation of gene expression ,Genetics ,Multidisciplinary ,Models, Statistical ,Systems Biology ,Stem Cells ,Gene Expression Profiling ,lcsh:R ,Computational Biology ,Genomics ,Hematopoietic Stem Cells ,Embryonic stem cell ,Neural stem cell ,Chromatin ,Gene expression profiling ,Wnt Proteins ,Adult Stem Cells ,Gene Expression Regulation ,lcsh:Q ,Stem cell ,Genome Expression Analysis ,Algorithms ,Research Article ,Developmental Biology - Abstract
The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.
- Published
- 2011