基于生物信息学方法的儿童急性不明确谱系白血病的潜在治疗靶基因筛选

doi:10.3969/j.issn.1674-8115.2021.03.006

摘要/Abstract

摘要：

目的·利用生物信息学分析方法探索儿童急性不明确谱系白血病（acute leukemia of ambiguous lineage，ALAL）致病通路、生存相关的独特基因表达谱及枢纽基因。方法·从TARGET （Therapeutically Applicable Research to Generate Effective Treatment）和GEO （Gene Expression Omnibus）数据库下载患者和健康人的表达数据，利用limma、clusterProfiler、survival等生信工具对基因表达量进行差异分析、功能分析及生存分析，最后通过构建蛋白-蛋白相互作用网络筛选得到与ALAL发病及生存相关的枢纽基因。结果·将ALAL组和健康对照组进行比较，共筛选得到4 053个显著差异基因（均P<0.05），其中表达上调基因1 844个，表达下调基因2 209个。利用GO（Gene Ontology）和KEGG（Kyoto Encyclopedia of Genes and Genomes）富集分析发现，上调基因参与细胞周期及剪接，下调基因参与免疫调节。通过与其他类型白血病的表达谱进行比较，发现ALAL中生存相关基因呈现独特的表达模式。蛋白质-蛋白质相互作网络显示生存基因网络的核心基因为CXCL8（C-X-C motif chemokine ligand 8）和LMNA（lamin A/C）。结论·ALAL的发病机制与细胞周期以及免疫相关，ALAL预后不良可能与其生存基因的独特表达谱有关；CXCL8和LMNA在ALAL中发挥重要作用，可能作为潜在的治疗靶点；这些结果对ALAL的机制研究和临床治疗具有提示作用。

关键词: 生物信息学, 数据挖掘, 白血病, 生存分析

Abstract:

Objective·To explore the pathogenetic pathways, unique gene expression profiles related to survival and hub genes in children with acute leukemia of ambiguous lineage (ALAL) by bioinformatics analysis.

Methods·From TARGET (Therapeutically Applicable Research to Generate Effective Treatment) and GEO (Gene Expression Omnibus), the expression data of patients and healthy individuals were downloaded. The differential analysis of gene expression, as well as its function and survival analysis, were performed by bioinformatics tools, such as limma, clusterProfiler and survival. Finally, the hub genes of ALAL were screened by constructing protein-protein interaction network (PPI).

Results·Four thousand and fifty-three significant differentially expressed genes were identified in the differential analysis between ALAL group and control group (all P<0.05), of which 1 844 were up-regulated genes and 2 209 were down-regulated genes. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis indicated that up-regulated genes were related to cell cycle and splicing, while the down-regulated genes were associated with immunity. By comparing the expression profiles with those of other types of leukemia, a unique expression pattern of survival-related genes in ALAL were found. Finally, PPI showed that CXCL8 (C-X-C motif chemokine ligand 8) and LMNA (lamin A/C) were the hub genes of the survival gene network.

Conclusion·The pathogenesis of ALAL is related to cell cycle and immunity. The poor prognosis of ALAL may be related to the unique expression profile of survival-related genes. CXCL8 and LMNA play an important role in ALAL, and may act as potential therapeutic targets. These results have implications for the mechanism research and clinical treatment of ALAL.

Key words: bioinformatics, data mining, leukemia, survival analysis

中图分类号:

R733.73

吴任燕, 郭晓琳, 洪登礼, 陈磊. 基于生物信息学方法的儿童急性不明确谱系白血病的潜在治疗靶基因筛选[J]. 上海交通大学学报(医学版), 2021, 41(3): 320-327.

Ren-yan WU, Xiao-lin GUO, Deng-li HONG, Lei CHEN. Identification of potential therapeutic target genes in pediatric acute leukemia of ambiguous lineage based on bioinformatics analysis[J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2021, 41(3): 320-327.

图/表 4

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Gene	Control group (N=21)	ALAL complete group (N=136)	AML group (N=187)	ALL group (N=532)
CXCL8	1.356±0.574	4.054±1.972^①⑧?	6.265±1.578^④	2.935±1.578^⑥
SCHIP1	0.092±0.138	1.606±1.312^①⑧?	0.912±0.939^④	1.175±1.288^⑥
SLC1A2	0.145±0.180	1.525±0.917^①⑧?	0.459±0.445^④	1.017±0.810^⑥
CYGB	0.269±0.253	1.566±1.370^①?	0.946±0.916^④	2.144±2.090^⑥
GREM1	0.158±0.269	1.154±1.434^①?	0.579±0.622^④	1.046±1.200^⑥
PER1	3.024±0.237	4.868±1.143^①?	5.807±0.697^④	5.075±0.985^⑥
SMARCA5-AS1	0.591±0.519	1.522±0.501^①⑨?	0.331±0.251	1.277±0.818^⑥
LMNA	2.208±0.444	3.760±1.355^①⑧?	4.993±1.025^④	3.225±1.196^⑥
TMEM52B	0.062±0.124	0.760±0.848^①⑧?	1.043±0.734^④	0.185±0.274^⑥
RNU6-1208P	0	0.581±0.408^①⑩?	0.153±0.187^④	0.495±0.416^⑥
RPL23AP23	0.643±0.416	1.987±0.924^①??	0.293±0.277^④	1.700±1.086^⑥
PDE6H	0.073±0.120	0.678±0.669^①⑧?	0.472±0.538^④	0.172±0.225^⑥
CCNL1	5.680±0.177	6.811±0.683^①?	6.358±0.964^④	6.764±0.776^⑥
LILRA4	2.196±0.528	0.743±0.621^①⑧?	0.489±0.526^④	0.603±0.644^⑥
BACH2	5.090±0.433	3.240±1.276^①⑧?	2.044±1.017^④	4.010±1.469^⑥
RHOXF2B	0.573±0.491	0.075±0.052^②⑧?	0.049±0.172^⑤	0.010±0.031^⑥
LEF1	5.597±0.503	3.692±1.471^①⑧?	2.627±1.312^④	5.798±0.902^⑦
SLC7A8	1.664±0.440	0.729±0.521^①⑧?	1.128±0.818^④	0.505±0.506^⑥
ABCA11P	1.756±0.450	0.698±0.477^①??	0.163±0.166^④	0.533±0.361^⑥
AMIGO3	1.116±0.721	0.364±0.186^①⑧?	0.108±0.083^④	0.262±0.175^⑥
RPSAP41	0.495±0.376	0.188±0.135^①⑧?	0.046±0.050^④	0.144±0.151^⑥
ZNF853	2.311±0.355	1.074±0.597^①⑧?	0.923±0.623^④	1.541±0.638^⑥
LMOD1	0.737±0.640	0.378±0.409^②⑧?	0.105±0.227^④	0.294±0.372^⑥
BTN1A1	0.781±0.358	0.349±0.251^①⑧?	0.087±0.175^④	0.322±0.418^⑥
LINC01355	3.194±0.326	1.946±1.140^①⑧?	0.393±0.396^④	1.099±0.791^⑥
ZNF135	2.485±0.434	1.566±1.173^①⑧?	0.559±0.524^④	2.008±1.203
ST6GALNAC4P1	0.780±0.471	0.397±0.257^①⑩?	0.169±0.159^④	0.349±0.279^⑥
ZNF582-AS1	1.500±0.319	0.723±0.351^①?	0.554±0.311^④	0.688±0.356^⑥
PABPC1P7	0.863±0.308	0.503±0.336^①⑧?	0.089±0.093^④	0.338±0.267^⑥
GBP6	0.573±0.394	0.347±0.299^③⑧?	0.060±0.094^④	0.153±0.188^⑥
GOLGA6L9	2.353±0.300	1.310±0.630^①?	0.791±0.544^④	1.400±0.736^⑥

Gene	Control group (N=21)	ALAL complete group (N=136)	AML group (N=187)	ALL group (N=532)
CXCL8	1.356±0.574	4.054±1.972^①⑧?	6.265±1.578^④	2.935±1.578^⑥
SCHIP1	0.092±0.138	1.606±1.312^①⑧?	0.912±0.939^④	1.175±1.288^⑥
SLC1A2	0.145±0.180	1.525±0.917^①⑧?	0.459±0.445^④	1.017±0.810^⑥
CYGB	0.269±0.253	1.566±1.370^①?	0.946±0.916^④	2.144±2.090^⑥
GREM1	0.158±0.269	1.154±1.434^①?	0.579±0.622^④	1.046±1.200^⑥
PER1	3.024±0.237	4.868±1.143^①?	5.807±0.697^④	5.075±0.985^⑥
SMARCA5-AS1	0.591±0.519	1.522±0.501^①⑨?	0.331±0.251	1.277±0.818^⑥
LMNA	2.208±0.444	3.760±1.355^①⑧?	4.993±1.025^④	3.225±1.196^⑥
TMEM52B	0.062±0.124	0.760±0.848^①⑧?	1.043±0.734^④	0.185±0.274^⑥
RNU6-1208P	0	0.581±0.408^①⑩?	0.153±0.187^④	0.495±0.416^⑥
RPL23AP23	0.643±0.416	1.987±0.924^①??	0.293±0.277^④	1.700±1.086^⑥
PDE6H	0.073±0.120	0.678±0.669^①⑧?	0.472±0.538^④	0.172±0.225^⑥
CCNL1	5.680±0.177	6.811±0.683^①?	6.358±0.964^④	6.764±0.776^⑥
LILRA4	2.196±0.528	0.743±0.621^①⑧?	0.489±0.526^④	0.603±0.644^⑥
BACH2	5.090±0.433	3.240±1.276^①⑧?	2.044±1.017^④	4.010±1.469^⑥
RHOXF2B	0.573±0.491	0.075±0.052^②⑧?	0.049±0.172^⑤	0.010±0.031^⑥
LEF1	5.597±0.503	3.692±1.471^①⑧?	2.627±1.312^④	5.798±0.902^⑦
SLC7A8	1.664±0.440	0.729±0.521^①⑧?	1.128±0.818^④	0.505±0.506^⑥
ABCA11P	1.756±0.450	0.698±0.477^①??	0.163±0.166^④	0.533±0.361^⑥
AMIGO3	1.116±0.721	0.364±0.186^①⑧?	0.108±0.083^④	0.262±0.175^⑥
RPSAP41	0.495±0.376	0.188±0.135^①⑧?	0.046±0.050^④	0.144±0.151^⑥
ZNF853	2.311±0.355	1.074±0.597^①⑧?	0.923±0.623^④	1.541±0.638^⑥
LMOD1	0.737±0.640	0.378±0.409^②⑧?	0.105±0.227^④	0.294±0.372^⑥
BTN1A1	0.781±0.358	0.349±0.251^①⑧?	0.087±0.175^④	0.322±0.418^⑥
LINC01355	3.194±0.326	1.946±1.140^①⑧?	0.393±0.396^④	1.099±0.791^⑥
ZNF135	2.485±0.434	1.566±1.173^①⑧?	0.559±0.524^④	2.008±1.203
ST6GALNAC4P1	0.780±0.471	0.397±0.257^①⑩?	0.169±0.159^④	0.349±0.279^⑥
ZNF582-AS1	1.500±0.319	0.723±0.351^①?	0.554±0.311^④	0.688±0.356^⑥
PABPC1P7	0.863±0.308	0.503±0.336^①⑧?	0.089±0.093^④	0.338±0.267^⑥
GBP6	0.573±0.394	0.347±0.299^③⑧?	0.060±0.094^④	0.153±0.188^⑥
GOLGA6L9	2.353±0.300	1.310±0.630^①?	0.791±0.544^④	1.400±0.736^⑥

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