Objectives: Genes
involved in different biological processes form complex interaction networks. However,
only few have a high number of interactions with the other genes in the network
and therefore might have an important role. In previous bioinformatics and
experimental studies concerning human
T lymphocytes cell cycle, osteogenesis and periodontitis, these genes were
identified and termed as "leader genes". In this theoretical
work, genes involved in human oral lichen planus (OLP) are identified and
ranked according to their number of interactions, to preliminarily obtain a
broader view of molecular mechanisms of OLP and plan targeted experimentations.
Methods: Genes
involved or potentially involved in OLP were identified with systematic interrelated
queries of several databases until identification of a final set. Interactions among
genes were mapped and given a significance score using web-available STRING
database. Weighted number of links (i.e. weighed sum of scores for every
interactions in which each gene is involved) were calculated for each gene.
Genes were clustered according to this parameter. The genes in the highest
cluster were termed as leader genes. Results: In
total, 41 genes involved or potentially involved in OLP were identified. Only 7
of them were identified as leader genes. For 5 leader genes there is an
already-established strong evidence of involvement in OLP; 2 new genes potentially
playing an important role in this disease were identified. Six leader genes are
also involved in oral carcinoma, which is a well-known complication of OLP. Conclusions:
A bioinformatic algorithm is applied to increase our knowledge of molecular
mechanisms of OLP. Even with the limitations of any ab-initio analysis, this study can suggest
targeted experimentation, focused on leader genes and therefore simpler than
mass scale molecular genomics. The identification of leader genes might suggest
new potential risk factor and therapeutic targets.
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