Affiliation:
1. School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310027, China
Abstract
Background:
Bone fracture healing is a time-consuming and high-priority orthopedic
problem worldwide.
Objectives:
Discovering the potential mechanism of bone healing at a time course and transcriptional
level may better help manage bone fracture.
Methods:
In this study, we analyze a time-course bone fracture healing transcriptional dataset in a
rat model (GSE592, GSE594, and GSE1371) of Gene Expression Omnibus (GEO). RNA was obtained
from female Sprague-Dawley rats with a femoral fracture at the initial time (day 3) as well
as early (week 1), middle (week 2), and late (week 4) time periods, with nonfracture rats used as
control. Gene Ontology (GO) functional analysis and pathway examinations were performed for
further measurements of GSEA and hub genes.
Results:
Results indicated that the four stages of bone fracture healing at the initial, early, middle,
and late time periods represent the phases of hematoma formation, callus formation, callus molding,
and mature lamellar bone formation, respectively. Extracellular organization was positively
employed throughout the four stages. At the hematoma formation phase, the muscle contraction
process was downregulated. Antibacterial peptide pathway was downregulated at all phases. The
upregulation of Fn1 (initial, early, middle, and late time periods), Col3a1 (initial, early, and middle
time periods), Col11a1 (initial and early time periods), Mmp9 (middle and late time periods),
Mmp13 (early, middle, and late time periods) and the downregulation of RatNP-3b (initial, early,
middle, and late time periods) were possible symbols for bone fracture healing and may be used as
therapeutic targets.
Conclusion:
These findings suggest some new potential pathways and genes in the process of bone
fracture healing and further provide insights that can be used in targeted molecular therapy for
bone fracture healing.
Publisher
Bentham Science Publishers Ltd.
Subject
Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine
Cited by
3 articles.
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