Kurokawa S, Arimura Y, Yamamoto H, Adachi Y, Endo T, Sato T, Suga T, Hosokawa M, Shinomura Y, Imai K
First Department of Internal Medicine, Sapporo Medical University, S-1, W-16, Chuo-ku, Sapporo 060-8543, Japan.
Gut. 2005 Dec;54(12):1751-8. doi: 10.1136/gut.2005.071035.
Nodal metastases are indisputable determinants of prognosis for colon and rectal cancer. Using classical histological criteria, many attempts to predict nodal metastasis have failed, preventing the adequate management of stage I (pT1) cancer. We investigated the role of tumour matrilysin in predicting metastatic potential, and discuss its potential use in individualising treatment of pT1 colon and rectal cancer.
The gene signature associated with nodal metastasis was investigated by cDNA array in 24 colon and rectal cancers. We studied 494 colon and rectal cancer patients to identify risk factors for nodal metastasis and evaluated the potential to predict nodal metastasis by either the logistic regression model or the Bayesian neural network model with built-in matrilysin. We then inferred possible causality of nodal metastasis from structural equation modelling.
cDNA array revealed that matrilysin was maximally upregulated in the metastasis signature identified. Tumour matrilysin expression emerged as a stage independent risk factor for nodal metastasis, resulting in a similar predictive performance in receiver operating characteristic curve analysis in the two models. A Bayesian approach called automatic relevance determination identified matrilysin as one of the most relevant predictors examined. Structural equation modelling suggested possible direct causality between matrilysin and nodal metastasis.
We have provided evidence that tumour matrilysin expression is a promising biomarker predicting nodal metastasis of colon and rectal cancer. Analysis of tumour matrilysin expression would help clinicians achieve the goal of individualised cancer treatment based on the metastatic potential of pT1 colon and rectal cancer.
淋巴结转移是结肠癌和直肠癌预后的决定性因素。采用经典组织学标准，许多预测淋巴结转移的尝试均告失败，这使得I期（pT1）癌症无法得到充分治疗。我们研究了肿瘤基质溶解素在预测转移潜能中的作用，并讨论其在pT1结肠癌和直肠癌个体化治疗中的潜在用途。
通过cDNA阵列研究了24例结肠癌和直肠癌中与淋巴结转移相关的基因特征。我们研究了494例结肠癌和直肠癌患者，以确定淋巴结转移的危险因素，并通过逻辑回归模型或内置基质溶解素的贝叶斯神经网络模型评估预测淋巴结转移的潜力。然后通过结构方程模型推断淋巴结转移的可能因果关系。
cDNA阵列显示，基质溶解素在鉴定出的转移特征中上调最为明显。肿瘤基质溶解素表达成为淋巴结转移的一个与分期无关的危险因素，在两种模型的受试者工作特征曲线分析中具有相似的预测性能。一种称为自动相关性确定的贝叶斯方法将基质溶解素确定为所检测的最相关预测因子之一。结构方程模型表明基质溶解素与淋巴结转移之间可能存在直接因果关系。
我们提供的证据表明，肿瘤基质溶解素表达是预测结肠癌和直肠癌淋巴结转移的一个有前景的生物标志物。分析肿瘤基质溶解素表达将有助于临床医生根据pT1结肠癌和直肠癌的转移潜能实现个体化癌症治疗的目标。
