A risk assessment model of acute liver allograft rejection by genetic polymorphism of CD276
MOLECULAR GENETICS & GENOMIC MEDICINE
Authors: Yu, Xiaobo; Wei, Bajin; Su, Rong; Yao, Jia; Feng, Xiaowen; Jiang, Guoping; Xie, Haiyang; Wu, Jian; Xu, Xiao; Zhang, Min; Zheng, Shusen; Zhou, Lin
BackgroundLiver transplantation is an effective therapy for end-stage liver diseases and acute liver failure. After the operation, however, recipients may suffer grafts loss induced by alloimmune reaction, which is termed as acute allograft rejection. The interaction between costimulatory molecules, CD276, and its ligand, TREML2, promotes T cell-mediated immune response, as well as acute or chronic allograft rejection. Our research aimed at correlating genetic polymorphisms of CD276/TREML2 with acute rejection, and evaluating its prognostic value of acute rejection after liver transplantation. MethodsThe study enrolled a total of 388 recipients. Among them, acute allograft rejection was observed in 54 cases. We performed single nucleotide polymorphism genotyping of CD276, including rs11072431, rs11574495, rs12593558, rs12594627, rs2127015, rs3816661 and rs7176654, and TREML2, including rs4714431, rs6915083, rs7754593, and rs9394767 from preoperative peripheral blood genome DNA. ResultsWe found rs2127015 of CD276, rs6915083 and rs7754593 of TREML2, and HBV infection as well were associated with acute rejection. And, rs2127015 influences CD276 expression. Moreover, we established a risk assessment model, composited by statistically proved risk factors. ConclusionBy integrating both clinical and genetic variables, liver transplant recipients can be categorized into different risk groups, and might benefit from individualized therapies.
Genomic analysis of biomarkers related to the prognosis of acute myeloid leukemia
Authors: Li, Guilan; Gao, Yang; Li, Kun; Lin, Anqi; Jiang, Zujun
Acute myeloid leukemia (AML) is the most common childhood cancer and is a major cause of morbidity among adults with hematologic malignancies. Several novel genetic alterations, which target critical cellular pathways, including alterations in lymphoid development-regulating genes, tumor suppressors and oncogenes that contribute to leukemogenesis, have been identified. The present study aimed to identify molecular markers associated with the occurrence and poor prognosis of AML. Information on these molecular markers may facilitate prediction of clinical outcomes. Clinical data and RNA expression profiles of AML specimens from The Cancer Genome Atlas database were assessed. Mutation data were analyzed and mapped using the maftools package in R software. Kyoto Encyclopedia of Genes and Genomes, Reactome and Gene Ontology analyses were performed using the clusterProfiler package in R software. Furthermore, Kaplan-Meier survival analysis was performed using the survminer package in R software. The expression data of RNAs were subjected to univariate Cox regression analysis, which demonstrated that the mutation loads varied considerably among patients with AML. Subsequently, the expression data of mRNAs, microRNAs (miRNAs/miR) and long non-coding RNAs (lncRNAs) were subjected to univariate Cox regression analysis to determine the the 100 genes most associated with the survival of patients with AML, which revealed 48 mRNAs and 52 miRNAs. The top 1,900 mRNAs (P<0.05) were selected through enrichment analysis to determine their functional role in AML prognosis. The results demonstrated that these molecules were involved in the transforming growth factor-beta, SMAD and fibroblast growth factor receptor-1 fusion mutant signaling pathways. Survival analysis indicated that patients with AML, with high MYH15, TREML2, ATP13A2, MMP7, hsa-let-7a-2-3p, hsa-miR-362-3p, hsa-miR-500a-5p, hsa-miR-500b-5p, hsa-miR-362-5p, LINC00987, LACAT143, THCAT393, THCAT531 and KHCAT230 expression levels had a shorter survival time compared with those without these factors. Conversely, a high KANSL1L expression level in patients was associated with a longer survival time. The present study determined genetic mutations, mRNAs, miRNAs, lncRNAs and signaling pathways involved in AML, in order to elucidate the underlying molecular mechanisms of the development and recurrence of this disease.