Keloid is a disease difficult to heal due to its tumor-like characters including rapid growth and invasion to normal skin and resistance to therapy with high recurrence rate. Keloid patients are also characterized by their specific diathesis including genetic predisposition and familial aggregation, gene mutation, abnormal production of growth factor, cytokine and inflammatory factors as well as abnormal hormonal levels. In addition, significant individual variation was also observed among different patients. In the past, keloid research was conducted within limited scope due to the shortcomings of available technology. In this study, we hypothesized that keloid genetic and protein markers are likely to defined by the application of whole-genome sequencing, transcriptome and epigenic sequencing to the best tissue samples of clinical cases, and these defined markers are likely to be manufactured as a special chip for keloid diagnosis and prognosis prediction. Meanwhile, the functions of defined genetic markers will also be verified with gene-editing technology. Furthermore, based on the individual variation of defined gene targets, individualized targeted drug therapy will also be experimented via available cancer target therapy drugs in an in vitro cell experimental model.
瘢痕疙瘩具有高度增长、侵袭、抵抗放化疗和高复发率等肿瘤特点,其“瘢痕体质”特征包括遗传倾向、基因突变、生长因子、细胞和炎症因子过度表达及内分泌激素异常等,且不同患者间的临床症状和预后存在巨大差异。以往瘢痕疙瘩研究多以“碎片化”和“盲人模象”模式进行。我们假设采用全基因组、转录组和表观遗传测序加上高通量蛋白芯片等技术,对最典型的临床病例的血样和组织标本开展宏观和多层次立体筛查,有望获得瘢痕疙瘩患者共有的易感基因和血清蛋白标志物以及不同以及个体间差异基因,作为瘢痕疙瘩患者诊断和预后判断和个体化治疗的基础。利用本单位的临床资源优势与国内顶级超高通量基因测序研究机构开展合作,以期将筛选出的基因和蛋白标志物制备成瘢痕疙瘩特异的诊断芯片,用于后续的大规模筛查和验证。同时,也将采用基因编辑手段来验证易感基因的功能。基于测序所发现的个体化差异,将初步开展体外细胞培养模型的个性化药物靶向治疗实验研究。
瘢痕疙瘩是一种浸润性生长、复发率高的肿瘤样疾病。常染色体显性遗传可能是其致病机制之一。然而,GWAS未能发现外显子区域的功能变异,而在非编码区发现了单核苷酸多态性,提示有必要进行创新性的遗传学研究。本研究采用GWAS、RNA-Sequence和Hi-C分析方法,以配对瘢痕疙瘩和正常皮肤为研究对象,对瘢痕疙瘩的遗传机制进行了剖析。利用RNA测序挖掘出的差异表达基因、miRNAs和lncRNAs构建网络。在此基础上,富集和验证了瘢痕疙瘩发病机制中的6条重要信号通路。此外,通过Hi-C数据定位了敏感位点上的拓扑相关结构域,并鉴定了6个差异表达的RNA。通过过表达和基因敲除实验证实它们在细胞周期和凋亡中的作用。本研究首次利用RNA序列和已报道的位点变异揭示了关键的生物标志物和信号通路,为揭示瘢痕疙瘩和其他通过GWAS未能成功找寻发病机制的疾病机制研究提供了一种可行的途径。
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数据更新时间:2023-05-31
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