Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, MCMR-TT, 504 Scott Street, Ft. Detrick, MD, 21702, USA.
Center for Wound Healing and Tissue Regeneration, College of Dentistry, University of Illinois, Chicago, 801 S. Paulina Street, Chicago, IL, 60612, USA.
J Transl Med. 2018 Feb 20;16(1):32. doi: 10.1186/s12967-018-1406-x.
Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds.
We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers.
We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy.
Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.
病理性瘢痕是一种常见的临床结局，其预后选择有限。本研究旨在探讨细胞信号蛋白是否可作为创伤性皮肤伤口病理性瘢痕的预后生物标志物。
我们使用之前开发和验证的损伤起始伤口愈合的计算模型来模拟血小板、6 种细胞类型和 21 种参与伤口愈合炎症和增殖阶段的蛋白的时间过程。接下来，我们分析了数千种模拟的伤口愈合情况，以确定那些导致病理性（即过度）瘢痕形成的情况。然后，我们确定了在这些模拟中在伤口愈合的早期阶段升高（或降低）的候选蛋白，因此可以作为病理性瘢痕结局的预测生物标志物。最后，我们进行了逻辑回归分析，并计算了接收器操作特征曲线下的面积，以定量评估模型确定的潜在生物标志物的预测准确性。
我们确定了三种蛋白（白细胞介素 10、基质金属蛋白酶 1 的组织抑制剂和纤维连接蛋白），它们在受伤后 2 周内病理性瘢痕中升高，并且可以预测 40 天后发生病理性瘢痕形成的结果，准确率为 80%。
我们预测潜在预后性伤口生物标志物的方法可能是指导鉴定预测病理性瘢痕形成的蛋白的有效手段。
