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February 01, 2013 (Vol. 33, No. 3)

En Bloc Analysis of Epigenetic Publications

New Research Provides Insights into Associations

  • Click Image To Enlarge +
    Figure 1. Epigenetics publication activity. Figures 2 and 3 are available here, below Table 1.

    Epigenetic changes represent a fine-tuning mechanism for gene expression modulation. Epigenetic changes do not involve changes to the DNA sequence, rather chemical modifications of DNA, folding, and complex formation that render genes transcriptionally active or inactive. The existence of epigenetic controls suggests an avenue for therapeutic interventions in various disease states as well as serving as biomarkers. We have applied technology landscaping to better understand the connections between epigenetics and molecular entities.

    To construct the technology landscape, we conducted a broad search in PubMed using the following general keywords: epigenetic, epigenesis, epigenomic, and epigenome. In total, we identified and retrieved 28,574 records from PubMed. The database we constructed using these records means that all conclusions drawn from the analysis incorporate an “epigenetics perspective.”

    Figure 1 presents the growth rate for epigenetic publications. The shape of the curve indicates an area that is exploding onto the scene. With such a rapid growth rate, it may soon be too late for those who have not yet established a presence in the space to enter without considerable effort or an acquisition.

    In order to better understand the connections between epigenetic regulatory components, cytoplasmic control system elements, selected biomarkers, oncogenes, tumor suppressor genes, and disease states, we first divided the database into 537 segments using descriptive keywords. Keywords were chosen using text-clustering results and the scientific literature. A Table lists the keywords chosen for this study.

    After completing the segmentation process, we constructed a hotspot map, an excerpted segment of which is presented in Figure 2. This interesting map illustrates several points:

    • Both text-clustering results and segmentation results show that cancer is a major focus of epigenetics research. Few other diseases have received so much attention in the epigenetics research community. The fact that “other diseases” have received less attention may be a competitive advantage for commercial players to establish unique research and patent positions in a less crowded space.
    • From the area acceleration plots in Figure 3A, we can see that the PIWI, bromodomian, and tudor domain segments are growing even more rapidly than the already fast-moving epigenetics publication rate (Figure 1). It is also clear that karyopherin, a protein involved in transnuclear transport, is a small, but growing segment.

    In addition, Figure 3A shows that certain analytical techniques such as FRET, pyro-sequencing, and Sanger sequencing are growing rapidly. Figure 3B shows most cancer segments are growing at nearly the same rate as the epigenetics database. However, the endothelial-to-mesenchymal transition (EMT) segment is growing faster than might be expected. Figure 3B hints that research focus on other diseases such as hypertension, neurological diseases, obesity, and prognostic or predictive biomarkers may be accelerating.

    • Interestingly, a few cancer biomarkers (RASF1, P16, P14, and IGF2) are fairly strongly connected to cancer even in our epigenetics database. For most other cancer biomarkers, the correlation between biomarker and cancer is weak.
    • Based on our review of the literature, we had expected to find a strong connection between microRNAs and cancer in the epigenetics database. While the idea of the connection is strong for general microRNA keywords, connections between cancer and specific microRNAs are weak, once again indicating that epigenetics is still newly developing (data not shown).
    • Our epigenetics hotspot table does show strong connections between tumor suppressor genes and oncogenes.

    We believe that our epigenetics hotspot analysis is the first to use en bloc technology landscaping methods to understand connections between cancer, putative biomarkers, and epigenetics and can be used to identify niches of opportunity for product vendors and diagnostics/therapeutics developers.

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