Molecular-pathological prognostic factors of gastric cancer: a review.
Molecular-pathological prognostic factors of gastric cancer: a review.
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DOI：
10.1007/s10120-005-0320-0
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发表时间：
2005-01-01
期刊：
影响因子：
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通讯作者：
Nakayama, Hirofumi
中科院分区：
文献类型：
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作者：
Yasui, Wataru;Oue, Naohide;Nakayama, Hirofumi
侵袭和转移是癌症发病率的关键决定因素。参与这些步骤的基因和分子必须被视为潜在的预后因素。生长因子及其受体、细胞周期调节剂、细胞粘附分子和基质降解酶是用作预后因子的那些，包括表皮生长因子（EGF）、EGF受体、K-sam、HER-2、白细胞介素（IL）-8、血管内皮生长因子（VEGF）、细胞周期蛋白E、p27、E-钙粘蛋白、CD 44 v6、基质金属蛋白酶-1（MMP-1）、和基质金属蛋白酶组织抑制剂-1（TIMP-1）。表观遗传学的改变，如异常DNA甲基化和组蛋白修饰，部分与胃癌的肿瘤进展相关，可以是候选的预后因素。甲基化基因的数量可以作为肿瘤进展的标志。遗传多态性不仅影响癌症易感性，而且影响恶性表型;实例包括HER-2和MMP-9基因中的单核苷酸多态性。全面的基因表达分析有助于寻找与侵袭转移相关的新基因和潜在的预后因素。基因表达系列分析（SAGE）已经鉴定出几个这样的基因，如CDH 17、APOE、FUS、COL 1A 1、COL 1A 2、GW 112和MIA。发现MIA的过表达与不良预后相关。从基因表达谱的角度来看，微阵列分析在识别个体癌症特征方面具有很大的潜力。这些检查的组合不仅可以预测患者的预后，还可以提供与个性化癌症医学和预防直接相关的信息。
Invasion and metastasis are critical determinants of cancer morbidity. Genes and molecules participating in these steps must be regarded as potential prognostic factors. Growth factors and their receptors, cell-cycle regulators, cell-adhesion molecules and matrix-degrading enzymes are those to be used as prognostic factors, including epidermal growth factor (EGF), EGF receptor, K-sam, HER-2, interleukin (IL)-8, vascular endothelial growth factor (VEGF), cyclin E, p27, E-cadherin, CD44v6, matrix metalloproteinase-1 (MMP-1), and tissue inhibitor of matrix metalloproteinase-1 (TIMP-1). Alterations in epigenetics, such as aberrant DNA methylation and histone modification that are, in part, associated with the tumor progression of gastric cancer, can be candidate prognostic factors. The number of methylated genes may serve as a marker of tumor progression. Genetic polymorphism not only affects cancer susceptibility but also influences malignant phenotype; examples include single-nucleotide polymorphism in the HER-2 and MMP-9 genes. Comprehensive gene expression analyses are useful to search for novel genes related to invasion and metastasis and potential prognostic factors. Serial analysis of gene expression (SAGE) has identified several these genes, such as CDH17, APOE, FUS, COL1A1, COL1A2, GW112, and MIA. Overexpression of MIA is found to be associated with poor prognosis. Microarray analysis has great potential for identifying the characteristics of individual cancers, from the view point of gene expression profiles. A combination of these examinations can not only foretell a patient's prognosis but can also give information directly connected with personalized cancer medicine and prevention.