【摘要】 目的基于数据挖掘技术,对肺癌晚期患者不同基因突变、融合或扩增相关性进行探讨。方法收集我院630份病例,利用Excel 2016建立药物数据库。采用频数分析与关联规则进行统计分析,统计分析在SPSS 22.0和SPSS Moder统计软件上进行。结果高频率基因有26位,EGFR-19突变、ALK融合、RET突变、EGFR-L858R-21突变、ALK突变、T790M突变位列前6;前26位中NRAS-G12D突变与BRAF-G466V突变、MYC-R450W突变与CYP2D6突变、GATA3M423fs突变与ESR1突变、SRC突变与GATA3M423fs突变、SRC突变与ESR1突变分类值之间相关联。基因关联分析最小值50%,支持度10%,经Apriori模块分析,EGFR-19突变与14基因未见(置信度46.667%)、EGFR-19突变与T790M突变(置信度40.000%)、EGFR-19突变与TP53突变(置信度13.333%)、ROS1融合与MET扩增(置信度47.619%)、MET扩增与ROS1融合(置信度50.000%)、T790M突变与EGFR扩增(置信度57.895%)、EGFR-19突变与EGFR扩增(置信度42.105%)。聚类分析BRAF-G466V与NRAS-G12D,MYC-R450W与CYP2D6,GATA3M423fs与SRC,PIK3CA扩增与PIK3CA,Pten与EGFE-L861Q-21,KRAS G12A与KRAS G12D,MET扩增与ROS1融合,EGFR扩增与BRAF-G466V,ERBB2 S310F与BRAFG464V。结论肺癌晚期不同基因之间以及基因的突变、融合、缺少与扩增等具有关联性。更多还原

【Abstract】 Objective Based on data mining technology, we discussed the correlation of different gene mutation, fusion or amplification in advanced lung cancer patients. Methods 630 cases in our hospital were collected and the drug database was established by Excel 2016. Frequency analysis and association rules were used for statistical analysis, and statistical analysis was performed on SPSS22.0 and SPSSModerler statistical software.Results There were 26 high frequency genes, such as EGFR-19 mutation, ALK fusion, RET mutation, EGFRL858 R-21 mutation, ALK mutation, and the first 6 cases of T790M mutation. The first 26 were NRAS-G12 D mutation and BRAF-G466 V mutation, MYC-R450 W mutation and CYP2D6 mutation, GATA3 M423 fs mutation and ESR1 mutation, abrupt mutation, mutation and sudden process. The variable classification values are associated with each other. The minimum value of gene association analysis was 50% and support was 10%. After Apriori module analysis, EGFR-19 mutation and 14 genes were not found(confidence degree 46.667%), EGFR-19 mutation and T790 M mutation(confidence degree 40%), EGFR-19 mutation and TP53 mutation(confidence degree 13.333%), ROS1 fusion and MET amplification(confidence 47.619%), MET amplification and ROS1 melting(confidence level 50%), T790 M mutation and EGFR amplification(confidence level 57.895%), EGFR-19 mutation and EGFR amplification(confidence 42.105%). Cluster analysis BRAF-G466 V and NRAS-G12D,MYC-R450 W and CYP2 D6, GATA3 M423 fs and SRC, PIK3 CA amplification and PIK3CA, Pten and EGFEL861 Q-21, KRAS G12A and blending. Conclusion There are correlations between different genes and mutation,fusion, lack and amplification of lung cancer.更多还原