Center for Stem Cell Research and Application, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Biomed Res Int. 2022 Apr 29;2022:4010786. doi: 10.1155/2022/4010786. eCollection 2022.
Tumor microenvironment (TME) has been revealed as an important determinant of diagnosis and treatment response in AML patients. The scores of immune and stromal cell scores of AML in the intermediate-risk group from The Cancer Genome Atlas (TCGA) database were calculated using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Differentially expressed genes were identified between high and low scores. Gene set enrichment and pathway analyses were performed. A risk score model based on TME for six immune-related genes was established and validated. Patients with a lower immune score had a longer overall survival than those with a higher score ( = 0.044). A total of 805 intersected genes as differentially expressed genes were identified and selected according to the comparison of both immune and stromal scores. The functional enrichment analysis shows that these genes are mainly associated with the immune/inflammatory response. The risk score model based on TME for six immune-related genes (including MEF2C, ENPP2, FAM107A, CD37, TNFAIP8L2, and CASS4) was established and validated in the TCGA database and well validated in the TARGET database ( = 0.005). A key microenvironment-related gene signature was identified that affects the outcomes of AML patients in the intermediate-risk group and might serve as therapeutic targets.
肿瘤微环境（TME）已被揭示为 AML 患者诊断和治疗反应的重要决定因素。使用基于表达数据算法估计恶性肿瘤组织中基质和免疫细胞的算法，计算了来自癌症基因组图谱（TCGA）数据库中中等风险组 AML 的免疫和基质细胞评分。鉴定了高低评分之间差异表达的基因。进行了基因集富集和通路分析。基于 TME 的六个免疫相关基因的风险评分模型建立并验证。免疫评分较低的患者总生存期长于评分较高的患者（=0.044）。根据免疫和基质评分的比较，共鉴定出 805 个差异表达基因，并进行了选择。功能富集分析表明，这些基因主要与免疫/炎症反应有关。基于 TME 的六个免疫相关基因（包括 MEF2C、ENPP2、FAM107A、CD37、TNFAIP8L2 和 CASS4）的风险评分模型在 TCGA 数据库中建立并验证，并在 TARGET 数据库中得到很好的验证（=0.005）。确定了一个关键的与微环境相关的基因特征，该特征影响中等风险组 AML 患者的预后，并可能作为治疗靶点。
