Gene expression of colorectal cancer: preoperative genetic diagnosis using endoscopic biopsies.
Gene expression of colorectal cancer: preoperative genetic diagnosis using endoscopic biopsies.
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DOI：
10.3892/ijo.32.2.367
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发表时间：
2008-02
影响因子：
5.2
通讯作者：
T. Komori;I. Takemasa;M. Yamasaki;M. Motoori;Takeshi Kato;N. Kikkawa;N. Kawaguchi;M. Ikeda;Hirofumi Yamamoto;M. Sekimoto;K. Matsubara;N. Matsuura;M. Monden
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文献类型：
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作者：
T. Komori;I. Takemasa;M. Yamasaki;M. Motoori;Takeshi Kato;N. Kikkawa;N. Kawaguchi;M. Ikeda;Hirofumi Yamamoto;M. Sekimoto;K. Matsubara;N. Matsuura;M. Monden
在结直肠癌中，为了术前预测对化疗和/或放疗的反应或淋巴结转移的存在，除了基于形态学和病理学的常规诊断之外，还需要更有效的诊断系统。使用内窥镜活检将基因表达谱应用于术前癌症诊断可以为患者选择更合适的治疗方法。在本研究中，我们通过研究肿瘤内异质性对基因表达谱的影响并测试肿瘤恶性程度的预测能力，评估了在临床环境中使用结直肠肿瘤术前活检进行基因表达谱分析的可行性。在内窥镜检查下，从10个结直肠癌和10个腺瘤中各取样2个活检样本，并使用cDNA微阵列获得它们的基因表达数据。将图谱的肿瘤内和肿瘤间异质性与无监督聚类分析进行比较。使用监督分类算法对活检进行肿瘤恶性肿瘤的分子预测。在聚类分析中，几乎所有来自同一肿瘤的配对活检样本都相互连接。来自相同肿瘤的活检之间的图谱的皮尔逊相关系数（平均值，0.83）显着大于来自其他癌症的活检组织之间的图谱的相关系数（平均值，0.58）（p<0.0001）。在监督分类方法中，40 个活检中有 39 个具有 8-71 个信息基因，正确预测了恶性肿瘤。使用结直肠肿瘤内镜活检进行的基因表达谱分析显示，肿瘤内异质性小于肿瘤间异质性，并且正确预测了肿瘤的恶性程度。我们的研究结果表明，基因表达谱技术准确地代表了结直肠癌的生物学特性，可以帮助该疾病的术前诊断。
In colorectal cancer, to predict the response to chemo- and/or radio-therapy or the existence of lymph node metastasis preoperatively, a more competent diagnostic system is required, in addition to conventional diagnosis based on morphology and pathology. The application of gene expression profiling to preoperative cancer diagnosis using endoscopic biopsies could enable the selection of a more appropriate therapy for patients. In this study, we evaluated the feasibility of gene expression profiling using preoperative biopsies of colorectal tumors in a clinical setting, by investigating the influence of intra-tumor heterogeneity on the profiles and testing the prediction ability of tumor malignancy. Under endoscopic examination, two biopsies were sampled from each of 10 colorectal cancers and 10 adenomas, and their gene expression data were obtained using cDNA microarrays. The intra- and inter-tumor heterogeneities of the profiles were compared with unsupervised clustering analysis. Molecular prediction of tumor malignancy using biopsies was performed with the supervised classification algorithm. In clustering analysis, almost all paired biopsies from the same tumors joined each other. Pearson's correlation coefficients of the profiles between biopsies from the same tumors (mean, 0.83) were significantly greater than those of the profiles between biopsies from other cancers (mean, 0.58) (p<0.0001). In the supervised classification method, malignancy was correctly predicted in 39 out of 40 biopsies with 8-71 informative genes. Gene expression profiling using endoscopic biopsies of colorectal tumors revealed that the intra-tumor heterogeneity was smaller than the inter-tumor heterogeneity and tumor malignancy was correctly predicted. Our findings suggest that the technique of gene expression profiling accurately represents the biological properties of colorectal cancer and could help the preoperative diagnosis of this disease.