High accuracy classification of developmental toxicants by in vitro tests of human neuroepithelial and cardiomyoblast differentiation. High accuracy classification of developmental toxicants by in vitro tests of human neuroepithelial and cardiomyoblast differentiation

Stem cell-based tests for developmental toxicity are currently intensively studied. Here, we used a protocol that differentiates human induced pluripotent stem cells (hiPSCs) to neural ectodermal progenitor cells (UKN1) and exposed them to 23 teratogens and 16 non-teratogens at human relevant concentrations. Substance-induced, genome-wide expression profiles were analyzed by two procedures that classified the compounds either based on the number of significantly deregulated genes or on a classification technique with cross-validation. Both procedures demonstrated a high performance with accuracy, sensitivity and specificity of 0.90, 0.83 and 1.0, as well as 0.87, 0.92 and 0.80, respectively. Comparing the present findings with the UKN1 test to those from our recently published UKK2 test that instead recapitulates cardiomyogenic differentiation showed a high congruence in compound classification. This may be explained by the fact that the same pathways, such as PI3K-Akt, P53, TGF-beta, MAPK, EGFR and Hippo were overrepresented among the differentially expressed genes for both tests. However, for some teratogens discrepant results were obtained, such as atorvastatin and thalidomide. In conclusion, UKN1 identifies teratogens with high sensitivity and specificity, and combined interpretation analysis with other tests that differentiate hiPSCs into otherdifferent cell types may further improve the results in the future. Overall design: Human iPSCs were differentiated for 6 days according to a neuroepithelial protocol (UKN1) and incubated with compounds at the same time. RNA was isolated from these cells and a whole transcritpome analysis was performed with Affymetrix HG-U133 Plus 2.0 arrays. Compound-induced gene expression changes were determined with statistical models.

基于干细胞的发育毒性检测方法目前正得到广泛深入的研究。本研究采用一套可将人类诱导多能干细胞（human induced pluripotent stem cells, hiPSCs）诱导分化为神经外胚层祖细胞（UKN1）的实验方案，以人类相关暴露浓度下的23种致畸物与16种非致畸物处理该细胞模型。我们通过两种分析流程对物质诱导的全基因组表达谱展开分析：其一基于显著失调基因的数量对受试化合物进行分类，其二采用带交叉验证的分类技术完成分类。两种分析流程均展现出优异的分类性能：第一种流程的准确率、灵敏度与特异度分别为0.90、0.83与1.0，第二种流程则分别为0.87、0.92与0.80。将本研究中UKN1检测模型的结果与我们近期发表的UKK2检测模型（该模型可重现心肌细胞分化过程）的结果进行对比后发现，二者在化合物分类结果上具有高度一致性。这一结果可通过以下事实得到解释：两种检测模型的差异表达基因中均富集了相同的信号通路，例如PI3K-Akt、P53、TGF-beta、MAPK、EGFR以及Hippo通路。不过，部分致畸物的检测结果存在不一致，例如阿托伐他汀与沙利度胺。综上，UKN1检测模型可高灵敏度、高特异度地识别致畸物；未来若将其与其他将hiPSCs诱导分化为不同细胞类型的检测模型开展联合解读分析，可进一步提升检测效果。实验整体设计：按照神经上皮细胞诱导方案（UKN1）将人类诱导多能干细胞（hiPSCs）诱导分化6天，同时加入受试化合物进行孵育。从上述细胞中提取总RNA，采用Affymetrix HG-U133 Plus 2.0基因芯片开展全转录组分析。通过统计模型分析受试化合物诱导产生的基因表达变化。