Biological significance of genome-wide DNA methylation profiles in keloids.

2017 
Objectives/Hypothesis To obtain biological insight into keloid pathogenesis and treatment using pathway analysis of genome-wide differentially methylated gene profiles between keloid and normal skin. Study Design Prospective cohort. Methods Genome-wide profiling was previously done, with institutional review board approval, on six fresh keloid and six fresh normal skin tissue samples, using the Infinium HumanMethylation450 BeadChip kit. Statistically significant differentially methylated cytosine-phosphodiester bond-guanines (CpGs, n = 197) between keloid and normal tissue mapped to 152 genes. These genes were uploaded into Ingenuity Pathway Analysis (IPA) software to identify biological functions or regulatory networks interacting. The pathways (or “network”) with an enrichment probability value ≤ .01 were subjected to a heuristic filter of keywords associated with keloid pathogenesis. Results Of the 197 CpGs, 191 were found in the IPA database and mapped to 152 unique genes. The top 10 hypermethylated genes were ACTR3C, LRRC61, PAQR4, C1orf109, SLCO2B1, CMKLR1, AHDC1, FYCO1, CCDC34, and CACNB2. The top 10 hypomethylated genes were GALNT3, SCML4, PPP1R13L, ANKRD11, WIPF1, MX2, IFFO1, DENND1C, CFH, and GHDC. IPA identified nine pathways with enrichment probability values ≤ .01, of which five (histidine degradation V1, phospholipase C signaling, colorectal cancer metastasis signaling, P2Y purinergic receptor signaling, and Gαi signaling) were associated with keloid keywords and contained “keloid genes” (P < .05). Conclusions Genes differentially methylated between keloid and normal skin reside in known bionetwork pathways involved in critical biological functioning and signaling events in the cell. This information could be used to refine screening processes for biological significance to better understand keloid pathogenesis and to develop molecular-targeted therapy. Level of Evidence NA Laryngoscope, 2016
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    42
    References
    15
    Citations
    NaN
    KQI
    []