BACKGROUND: It has been proven that ornithine aminotransferase (OAT) might play an important role in the oncogenesis and progression of numerous malignant tumors. The aim of this study is to detect the mRNA and protein expression of OAT in non-small cell lung cancer (NSCLC), as well as to analyze the bioinformatic features and binary interactions. METHODS: OAT mRNA expression was detected in A549 and 16HBE cell lines by reverse transcription-polymerase chain reaction. OAT protein expression was determined in 55 cases of NSCLC and 17 cases of adjacent non-tumor lung tissues by immunohistochemical staining. The bioinformatic features and binary interactions of OAT were analyzed. Gene ontology annotation and signal pathway analysis were performed. RESULTS: OAT mRNA expression in A549 cells was 2.85-fold lower than that in 16HBE cells. OAT protein expression was significantly higher in NSCLC tissues than that in adjacent non-tumor lung tissues. A significant difference of OAT protein expression was existed between squamous cell lung cancer and adenocarcinoma (P < 0.05), but was not correlated with the gender, age, lymph node metastasis, tumor size, and TNM stages. Bioinformatic analysis suggested that OAT was a highly homologous and stable protein located in the mitochondria. An aminotran-3 domain and several sites of phosphorylation, which may function in signal transduction, gene transcription, and molecular transit, were found. In the 54 selected binary interactions of OAT, TNF and TRAF6 play roles in the NF-κB pathway. CONCLUSIONS: OAT may play an important role in the oncogenesis and progression of NSCLC. Thus, OAT may be a novel biomarker for the diagnosis of NSCLC or a new target for its treatment.
BACKGROUND: It has been proven that ornithine aminotransferase (OAT) might play an important role in the oncogenesis and progression of numerous malignant tumors. The aim of this study is to detect the mRNA and protein expression of OAT in non-small cell lung cancer (NSCLC), as well as to analyze the bioinformatic features and binary interactions. METHODS:OAT mRNA expression was detected in A549 and 16HBE cell lines by reverse transcription-polymerase chain reaction. OAT protein expression was determined in 55 cases of NSCLC and 17 cases of adjacent non-tumor lung tissues by immunohistochemical staining. The bioinformatic features and binary interactions of OAT were analyzed. Gene ontology annotation and signal pathway analysis were performed. RESULTS:OAT mRNA expression in A549 cells was 2.85-fold lower than that in 16HBE cells. OAT protein expression was significantly higher in NSCLC tissues than that in adjacent non-tumor lung tissues. A significant difference of OAT protein expression was existed between squamous cell lung cancer and adenocarcinoma (P < 0.05), but was not correlated with the gender, age, lymph node metastasis, tumor size, and TNM stages. Bioinformatic analysis suggested that OAT was a highly homologous and stable protein located in the mitochondria. An aminotran-3 domain and several sites of phosphorylation, which may function in signal transduction, gene transcription, and molecular transit, were found. In the 54 selected binary interactions of OAT, TNF and TRAF6 play roles in the NF-κB pathway. CONCLUSIONS:OAT may play an important role in the oncogenesis and progression of NSCLC. Thus, OAT may be a novel biomarker for the diagnosis of NSCLC or a new target for its treatment.
OAT基因PCR电泳结果Electrophoresis of OAT gene PCR product
免疫组化结果
OAT蛋白以棕黄色颗粒表达于胞浆,在NSCLC组织中表达阳性率为81.82%(45/55),而在癌旁肺组织中均无阳性表达(χ2=39.080, P < 0.001),差异有统计学意义(图 3)。OAT表达为“-”、“+”、“++”和“+++”的分别有10例、27例、10例和8例(图 4)。按性别、年龄、组织病理学类型、有无淋巴结转移、肿瘤直径及TNM分期对NSCLC进行分组分析,结果显示OAT蛋白在腺癌和鳞癌组间的表达差异有统计学意义(χ2=5.169, P=0.023)。OAT蛋白在肺腺癌组中的阳性率(100%)高于其在肺鳞癌组中的阳性率(71.43%)。而OAT蛋白的表达和患者性别、年龄、有无淋巴结转移、肿瘤直径及TNM分期无关。
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OAT蛋白在肺鳞癌(A)、肺腺癌(B)和癌旁肺组织(C)中的表达(IHC,×400)
The expression of OAT in squamous lung cancer (A), adenocarcinoma (B) and adjacent non-tumor lung tissue (C) (IHC, ×400)
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OAT蛋白在肺癌组织中的表达情况示意图
The expression of OAT in lung cancer tissues
OAT蛋白在肺鳞癌(A)、肺腺癌(B)和癌旁肺组织(C)中的表达(IHC,×400)The expression of OAT in squamous lung cancer (A), adenocarcinoma (B) and adjacent non-tumor lung tissue (C) (IHC, ×400)OAT蛋白在肺癌组织中的表达情况示意图The expression of OAT in lung cancer tissues
The secondary structure prediction result of OAT by SOPMA
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OAT蛋白质的磷酸化位点预测结果
The result of phosphorylation sites prediction of OAT
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OAT蛋白质三维结构图
The three-demensional structure of OAT protein
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OAT基因功能初步分析结果
The functional prediction of OAT Gene
OAT Gene Ontology category
Prob
Odds
Signal_transducer
0.096
0.447
Receptor
0.007
0.041
Hormone
0.001
0.206
Structural_protein
0.002
0.073
Transporter
0.025
0.227
Ion_channel
0.010
0.168
Voltage-gated_ion_channel
0.004
0.170
Cation_channel
0.010
0.215
Transcription
0.027
0.215
Transcription_regulation
0.018
0.144
Stress_response
0.013
0.144
Immune_response
0.013
0.151
Growth_factor
0.006
0.421
Metal_ion_transport
0.009
0.020
SOPMA软件对OAT二级结构预测图The secondary structure prediction result of OAT by SOPMAOAT蛋白质的磷酸化位点预测结果The result of phosphorylation sites prediction of OATOAT蛋白质三维结构图The three-demensional structure of OAT proteinOAT基因功能初步分析结果The functional prediction of OAT Gene通过搜索IntAct、MINT、DIP、InteroPorc和STRING等在线数据库,发现存在重复和冗余数据,为了获得相对可靠的相互作用蛋白,进一步将具有文献依据的相互作用蛋白总结如下(表 2),表中蛋白质相互作用关系的获取方式有:免疫共沉淀、串联亲和纯化和酵母双杂交等。
具有文献依据的OAT相互作用蛋白及相关信息The binary interactions of OAT in literatureSTRING数据库的结果(图 8,图中着色节点表示和OAT可能直接相关的分子,白色节点代表可能存在更深层次关系的分子,节点间连线以不同的颜色分别代表不同的依据来源,下方表中详细罗列了各着色节点的相关信息及综合评分)则进一步扩大了相互作用的预测范围,该数据库包含了直接(物理上)和间接(功能上)的各种相互作用关系,数据结果综合了基因背景、高通量实验、共表达和已知信息等,并对每一个相互作用关系进行评分,该数据库目前涵盖了来自1133个物种的5, 214, 234种蛋白质的相互作用信息。STRING数据库预测所得与OAT相互作用蛋白中评分最高的20种蛋白依次为:OTC、ARG1、ARG2、ALDH18A1、ODC1、ALDH4A1、ASS1、ASL、ACY1、TBC1D25、TNF、TLR4、SLC22A6、SLC22A8、IL2、SLC22A7、B3GAT1、GLUD2、GLUL、SCL22A20。
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STRING数据库:OAT相互作用蛋白预测结果
Predicted functional partners of OAT in STRING database
STRING数据库:OAT相互作用蛋白预测结果Predicted functional partners of OAT in STRING database综合各数据库信息,筛选出54种可能和OAT存在相互作用的蛋白质并提交至DAVID在线平台,其中52种蛋白质在DAVID中查找到对应的ID,通过Gene Ontology对这52种蛋白质进行本体论注释,在相应参数设置条件下,发现共有35种蛋白质参与了73种不同的生物学途径(biological process),20种蛋白质参与了14种不同的细胞组件(cellular component),27种蛋白质参与了18种不同的分子功能(molecular function)。分子信号通路分析结果(图 9)显示有17种蛋白质参与了包括:NF-κB信号通路、NOD样受体信号通路及精氨酸和脯氨酸代谢等在内的8个重要的信号转导通路。
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17种蛋白质基于KEGG和BIOCARTA数据库的信号转导通路分析结果
The signal pathway analysis of 17 proteins based on KEGG and BIOCARTA databases
17种蛋白质基于KEGG和BIOCARTA数据库的信号转导通路分析结果The signal pathway analysis of 17 proteins based on KEGG and BIOCARTA databases
Authors: Sarah Tonack; Sabina Patel; Mehdi Jalali; Taoufik Nedjadi; Rosalind E Jenkins; Christopher Goldring; John Neoptolemos; Eithne Costello Journal: World J Gastroenterol Date: 2011-04-21 Impact factor: 5.742
Authors: Guoan Chen; Tarek G Gharib; Chiang-Ching Huang; Jeremy M G Taylor; David E Misek; Sharon L R Kardia; Thomas J Giordano; Mark D Iannettoni; Mark B Orringer; Samir M Hanash; David G Beer Journal: Mol Cell Proteomics Date: 2002-04 Impact factor: 5.911