Biomedical Informatic and Bioinformatic Platform, Biomedical Research Institute of Murcia (IMIB-Arrixaca-UMU), University Clinical Hospital "Virgen de la Arrixaca," University of Murcia, Murcia, Spain.
Experimental Gastroenterology and Solid Organ Transplantation Lab, Biomedical Research Institute of Murcia (IMIB-Arrixaca-UMU), University Clinical Hospital "Virgen de la Arrixaca," University of Murcia, Murcia, Spain.
Transplantation. 2019 Sep;103(9):1887-1892. doi: 10.1097/TP.0000000000002587.
Numerous studies have emphasized the genetic and phenotypic profiles of tolerant transplant patients. Moreover, different groups have defined several biomarkers, trying to distinguish patients who are going to be tolerant from those who are going to reject. However, most of these biomarkers have not been validated by other groups or even established for clinical practice.
We reanalyzed and stratified the predictive capacity of 20 previously described biomarkers for liver transplantation tolerance in a cohort of 17 liver transplant patients subjected to an independent, nonrandomized, prospective study of immunosuppression drug withdrawal.
Only 4 of the 20 studied biomarkers (expression of SENP6, FEM1C, miR31, and miR95) showed a strong predictive capacity in the present study. miR31 and FEM1C presented an area under the ROC curve of 96.7%, followed by SENP1 with 93.3%. Finally, miR95 had an area under the ROC curve value <86.7%.
Even though this independent analysis seems to confirm the predictive strength of SENP6 and FEM1C in liver transplantation tolerance, there are also risks in establishing biomarkers for clinical phenotypes without an understanding of how they are biologically relevant. Future collaborations between groups should be promoted so that the most promising biomarkers can be validated and implemented in daily clinical practice.
许多研究强调了耐受移植患者的遗传和表型特征。此外，不同的研究小组已经定义了几种生物标志物，试图区分将要耐受的患者和将要排斥的患者。然而，这些生物标志物中的大多数尚未被其他小组验证，甚至尚未确立用于临床实践。
我们在 17 例接受免疫抑制剂停药的独立、非随机、前瞻性研究的肝移植患者队列中重新分析和分层了 20 个先前描述的肝移植耐受生物标志物的预测能力。
在本研究中，仅 20 个研究的生物标志物中的 4 个（SENP6、FEM1C、miR31 和 miR95 的表达）显示出较强的预测能力。miR31 和 FEM1C 的 ROC 曲线下面积为 96.7%，其次是 SENP1 的 93.3%。最后，miR95 的 ROC 曲线下面积值<86.7%。
尽管这种独立分析似乎证实了 SENP6 和 FEM1C 在肝移植耐受中的预测强度，但在不了解其生物学相关性的情况下，为临床表型建立生物标志物也存在风险。应该促进小组之间的未来合作，以便能够验证和实施最有前途的生物标志物，并将其纳入日常临床实践。
