Accumulation of aberrant proteins and inclusion bodies are hallmarks in most neurodegenerative diseases. Consequently, these aggregates within neurons lead to toxic effects, overproduction of reactive oxygen species a...Accumulation of aberrant proteins and inclusion bodies are hallmarks in most neurodegenerative diseases. Consequently, these aggregates within neurons lead to toxic effects, overproduction of reactive oxygen species and oxidative stress. Autophagy is a significant intracellular mechanism that removes damaged organelles and misfolded proteins in order to maintain cell homeostasis. Excessive or insufficient autophagic activity in neurons leads to altered homeostasis and influences their survival rate, causing neurodegeneration. The review article provides an update of the role of autophagic process in representative chronic and acute neurodegenerative disorders.展开更多
目的构建并验证一种头颈鳞状细胞癌(head and neck squamous cell carcinoma,HNSCC)自噬相关基因预后风险评分模型。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库下载全部HNSCC转录组表达数据(RNA sequencing,RNA-seq)及...目的构建并验证一种头颈鳞状细胞癌(head and neck squamous cell carcinoma,HNSCC)自噬相关基因预后风险评分模型。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库下载全部HNSCC转录组表达数据(RNA sequencing,RNA-seq)及临床信息,筛选出差异表达基因,与GeneCards数据库检索的自噬相关基因(autophagy related genes,ARGs)取交集,得到差异表达的ARGs,整合临床信息后经预后分析获得预后相关的ARGs,再对其富集分析。应用套索(the least absolute shrinkage and selection operator,LASSO)回归和Cox回归模型构建一种用于预测HNSCC预后及生存情况的风险评分模型;绘制受试者工作特征(receiver operating characteristic,ROC)曲线,计算曲线下面积(area under the curve,AUC)及最佳截断(cut-off)值,并以最佳cut-off值将患者分为高、低风险评分组;绘制Kaplan-Meier生存曲线评价该模型的预测性能;将临床信息与风险评分对应整合,再次利用Cox回归分析评价风险评分的独立预后价值。结果通过对差异表达的ARGs进行预后分析初筛出20个与预后相关的ARGs,再应用LASSO回归和Cox回归分析获得9个与预后显著相关的ARGs,以此构建HNSCC的预后风险评分模型。ROC曲线及Kaplan-Meier生存曲线分析显示,低风险评分组生存时间优于高风险评分组,两组生存时间差异有统计学意义(P<0.001),且该模型在训练集(AUC最大值为0.69)与外部验证集(AUC最大值为0.822)中均展现出良好的预测性能。纳入临床信息后,对风险评分进行Cox回归分析,提示其与HNSCC患者预后显著相关(P<0.001),表明风险评分对HNSCC具有独立预后价值。结论由9个ARGs组成的HNSCC风险评分模型,可有效预测HNSCC患者的预后情况。展开更多
文摘Accumulation of aberrant proteins and inclusion bodies are hallmarks in most neurodegenerative diseases. Consequently, these aggregates within neurons lead to toxic effects, overproduction of reactive oxygen species and oxidative stress. Autophagy is a significant intracellular mechanism that removes damaged organelles and misfolded proteins in order to maintain cell homeostasis. Excessive or insufficient autophagic activity in neurons leads to altered homeostasis and influences their survival rate, causing neurodegeneration. The review article provides an update of the role of autophagic process in representative chronic and acute neurodegenerative disorders.
文摘目的构建并验证一种头颈鳞状细胞癌(head and neck squamous cell carcinoma,HNSCC)自噬相关基因预后风险评分模型。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库下载全部HNSCC转录组表达数据(RNA sequencing,RNA-seq)及临床信息,筛选出差异表达基因,与GeneCards数据库检索的自噬相关基因(autophagy related genes,ARGs)取交集,得到差异表达的ARGs,整合临床信息后经预后分析获得预后相关的ARGs,再对其富集分析。应用套索(the least absolute shrinkage and selection operator,LASSO)回归和Cox回归模型构建一种用于预测HNSCC预后及生存情况的风险评分模型;绘制受试者工作特征(receiver operating characteristic,ROC)曲线,计算曲线下面积(area under the curve,AUC)及最佳截断(cut-off)值,并以最佳cut-off值将患者分为高、低风险评分组;绘制Kaplan-Meier生存曲线评价该模型的预测性能;将临床信息与风险评分对应整合,再次利用Cox回归分析评价风险评分的独立预后价值。结果通过对差异表达的ARGs进行预后分析初筛出20个与预后相关的ARGs,再应用LASSO回归和Cox回归分析获得9个与预后显著相关的ARGs,以此构建HNSCC的预后风险评分模型。ROC曲线及Kaplan-Meier生存曲线分析显示,低风险评分组生存时间优于高风险评分组,两组生存时间差异有统计学意义(P<0.001),且该模型在训练集(AUC最大值为0.69)与外部验证集(AUC最大值为0.822)中均展现出良好的预测性能。纳入临床信息后,对风险评分进行Cox回归分析,提示其与HNSCC患者预后显著相关(P<0.001),表明风险评分对HNSCC具有独立预后价值。结论由9个ARGs组成的HNSCC风险评分模型,可有效预测HNSCC患者的预后情况。
