COL1A2 is a Novel Biomarker to Improve Clinical Prediction in Human Gastric Cancer: Integrating Bioinformatics and Meta-Analysis
COL1A2 is a Novel Biomarker to Improve Clinical Prediction in Human Gastric Cancer: Integrating Bioinformatics and Meta-Analysis
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DOI：
10.1007/s12253-017-0223-5
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发表时间：
2018-01-01
影响因子：
2.8
通讯作者：
Liu, Fengfeng
中科院分区：
文献类型：
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作者：
Rong, Li;Huang, Wei;Liu, Fengfeng
胃癌是全球癌症相关死亡的第三大常见原因。在胃癌早期靶向控制发病机制的关键基因至关重要。本研究描述了一种集成的生物信息学方法来识别胃癌患者癌组织中的分子生物标志物。我们报告了基因表达表（GEO）在大型胃癌队列中的不同表达基因。结果显示，433个基因在人胃癌中表达有显著差异。通过生物信息学分析、共表达网络构建等进一步验证胃癌中不同表达基因谱。基于共表达网络和排名靠前的基因，我们发现编码I型胶原蛋白的前α 2链的COL1A2 （COL1A2）是37个基因网络中通过与细胞骨架相互作用调节细胞运动的关键基因。此外，利用免疫组织化学方法确定COL1A2在人胃癌组织中的预后作用。与正常胃组织相比，COL1A2在人胃癌中高表达。统计分析显示COL1A2表达水平与组织类型和淋巴结状态有显著相关性。然而，COL1A2的表达与年龄、淋巴结数量、肿瘤大小或临床分期没有相关性。总之，本研究中使用的新型生物信息学方法鉴定了改善人类胃癌诊断的生物标志物，并有助于进一步分析其进展过程中的关键改变。
Gastric cancer is the third most common cause of cancer-related death in worldwide. It is crucial to target the key genes controlling pathogenesis in the early stage of gastric cancer. This study describes an integrated bioinformatics to identify molecular biomarkers for gastric cancer in patients' cancer tissues. We reports differently expression genes in large gastric cancer cohorts from Gene Expression Ominus (GEO). Our findings revealed that 433 genes were significantly different expressed in human gastric cancer. Differently expression gene profile in gastric cancer was further validated by bioinformatic analyses, co-expression network construction. Based on the co-expression network and top-ranked genes, we identified collagen type I alpha 2 (COL1A2) which encodes the pro-alpha2 chain of type I collagen whose triple helix comprises two alpha1 chains and one alpha2 chain, was the key gene in a 37-gene network that modulates cell motility by interacting with the cytoskeleton. Furthermore, the prognostic role of COL1A2 was determined by use of immunohistochemistry on human gastric cancer tissue. COL1A2 was highly expressed in human gastric cancer as compared with normal gastric tissues. Statistical analysis showed COL1A2 expression level was significantly associated with histological type and lymph node status. However, there were no correlations between COL1A2 expression and age, lymph node numbers, tumor size, or clinical stage. In conclusion, the novel bioinformatics used in this study has led to identification of improving diagnostic biomarkers for human gastric cancer and could benefit further analyses of the key alteration during its progression.