摘要
[目的]基于微阵列数据挖掘乳腺癌的生物标志物,筛选其靶向中药。[方法]下载乳腺癌的临床微阵列数据以筛选差异表达基因,构建基因共表达网络,并基于12种算法筛选核心基因。通过卡普兰迈尔(Kaplan-Meier)和比例风险回归模型(Cox proportional hazards model)筛选预后基因,构建预后模型并挖掘相关微RNA(miRNAs)。最后,预测其靶向中药及小分子,并通过分子建模和分子对接验证其结合力。[结果]共获得464个差异表达基因,包括50个核心基因。其中,酰基辅酶A合成酶长链家族成员1(Acyl-CoA Synthetase Long Chain Family Member 1,ACSL1),CD24分子(CD24 Molecule,CD24),谷氨酰氧乙酸转氨酶2(Glutamic-Oxaloacetic Transaminase 2,GOT2)和角蛋白(Keratin 14,KRT14)可被has-miR-373等20个microRNAs调控,是乳腺癌的预后标志物。大青叶、麻黄、雷公藤等35种中药所包含的汉防己甲素等13种成分是上述标志物的靶向药物,且它们的结合能均小于-4.0 kcal/mol。[结论]ACSL1[log-rank P=0.039,风险比=1.4(95%CI,1.02-1.94)],CD24[log-rank P=0,风险比=1.98(95%CI,1.42-2.76)],GOT2[log-rank P=0.046,风险比=1.38(95%CI,1.01-1.91)]和KRT14[log-rank P=0.003,风险比=0.612(95%CI,0.444-0.843)]是乳腺癌的潜在生物标志物,且汉防己甲素等13种成分是其潜在的靶向药物(结合能均小于-4.0 kcal/mol),这为乳腺癌的诊疗提供了新思路。
[Objective]Mining of biomarkers for breast cancer and screening of targeted traditional Chinese medicines based on microarray data.[Method]Clinical microarray data of breast cancer were downloaded to screen differentially expressed genes,construct gene co-expression networks,and screen core genes based on 12 algorithms.Prognostic genes were screened by Kaplan-Meier and Cox proportional hazards model,and prognostic models were constructed and relevant miRNAs were mined.Finally,we predicted their target traditional Chinese medicines and compounds,and verified their binding energies through molecular modeling and molecular docking.[Result]A total of 464 differentially expressed genes were obtained,including 50 core genes.Among them,the expression levels of ACSL1,CD24,GOT2 and KRT14 could be regulated by 20 microRNAs including has-miR-373,which are prognostic markers for breast cancer.Fourteen components,including tetrandrine,contained in 35 traditional Chinese medicines,such as folium isatidis,are the target drugs for the above markers,and binding energies of them were less than-4.0 kcal/mol.[Conclusion]ACSL1(log-rank P=0.039,hazard ratio=1.4(95%CI,1.02-1.94)),CD24(log-rank P=0,hazard ratio=1.98(95%CI,1.42-2.76)),GOT2(log-rank P=0.046,hazard ratio=1.38(95%CI,1.01-1.91))and KRT14(log-rank P=0.003,hazard ratio=0.612(95%CI,0.444-0.843))are potential biomarkers for colon cancer and 13 components such as tetrandrine are their potential target drugs(the binding energies of them were less than-4.0 kcal/mol),which provides a new direction for the diagnosis and treatment of breast cancer.
作者
陈雯雯
张锋
CHEN Wenwen;ZHANG Feng(Wuhan Hospital of Traditional Chinese Medicine,Nanning 530200,China)
出处
《生物技术》
2025年第2期169-176,145,共9页
Biotechnology
基金
武汉市医学科研项目-指导项目(WZ21Z13)
武汉市中医药科研项目-重点项目(WZ22A11)。
关键词
乳腺癌
微阵列数据
生物标志物
分子建模
MICRORNAS
分子对接
中药
靶向药物
methicillin-resistant Staphylococcus aureus
genome sequencing
PutP
gene cloning
plasmid construction
bac-terial double hybridization
target
bioinformatics analysis
