Open Access Research article

LRpath analysis reveals common pathways dysregulated via DNA methylation across cancer types

Jung H Kim12, Alla Karnovsky1, Vasudeva Mahavisno1, Terry Weymouth1, Manjusha Pande3, Dana C Dolinoy2, Laura S Rozek24 and Maureen A Sartor1*

Author Affiliations

1 Department of Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA

2 Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA

3 Neurology Department, Medical School, University of Michigan, Ann Arbor, MI, USA

4 Department of Otolaryngology, Medical School, University of Michigan, Ann Arbor, Mi, USA

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BMC Genomics 2012, 13:526  doi:10.1186/1471-2164-13-526

Published: 4 October 2012

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Additional file 1:

Table S1. Significance of overlap in the specific differentially methylated genes in significant GO terms between pairs of studies using Fisher’s exact test (p-value<0.05 is indicated with red text)GO term - Immune Response GO term - Epidermis Development GO term – Neurogenesis.

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Additional file 2:

Figure S1. Waterfall plots showing the methylation change in significant genes between normal and tumor samples involved in neurogenesis and epidermis development (GO terms). Positive values indicate hypermethylation in cancer, while negative values indicate hypomethylation in cancer. A. Neurogenesis. B. Epidermis Development. Figure S2. Change in average percent methylation of HOX gene family, PAX gene family, and WT1 involved in Transcription Factor Activity. Figure S3. Unsupervised clustering of probes involved in Sequence-specific Transcription Factor Activity. Figure S4. The status of PRC2 targets and CpG islands for those probes involved in the specified GO terms. Figure S5. The proportion of differentially methylated genes among the PRC2 targets and non-PRC2 targets (those probes with the p-value<0.05 and the minimum difference between the average methylation percentage of tumor vs. normal greater than 5% are graphed) A. Ectoderm Development. B. Epidermis Development. C. Embryo Development. D. Neurogenesis. Figure S6. Clustering of metabolite, drug target, and transcription factor concepts. Hypomethylated concepts are shown in red and hypermethylated concepts are shown in green. A. Metabolite concepts. B. Drug concepts. C. Transcription Factor concepts. Figure S7. Change in average percent methylation of the probes for TP73, CDKN1A, 1B, 1C, 2A and 2B, 2C, 2D, and APC. Figure S8. Cancer-specific enriched concepts in LRpath directional analysis. Biological concepts enriched with a significant p-value < 1e-4 in one tumor type are listed in the table below. In myeloma, kinase activities are enriched among hypermethylated genes, and muscle-related processes and components are enriched among hypomethylated genes. In breast cancer, several circadian processes are shown up to be enriched among hypomethylated genes. Figure S9. Bar graphs showing the methylation change in genes involved in circadian rhythm process in breast cancer. In tumor samples, the increase in the level of methylation in DRD1, PTGDS, CASP1, and PGLYRP1 genes are observed.

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