COLORECTAL CANCER

Tumour matrilysin expression predicts metastatic potential of stage I (pT1) colon and rectal cancers

S Kurokawa¹, Y Arimura², H Yamamoto², Y Adachi², T Endo², T Sato⁴, T Suga³, M Hosokawa⁵, Y Shinomura², K Imai²

¹ First Department of Internal Medicine, Sapporo Medical University, Sapporo, Japan, and Department of Gastroenterology, Sapporo Kosei General Hospital, Sapporo, Japan
² First Department of Internal Medicine, Sapporo Medical University, Sapporo, Japan
³ Department of Gastroenterology, Sapporo Kosei General Hospital, Sapporo, Japan
⁴ Department of Pathology, Sapporo Kosei General Hospital, Sapporo, Japan
⁵ Department of Surgery, Keiyukai Sapporo Hospital, Sapporo, Japan

Correspondence to:
Correspondence to:
Dr Y Arimura
First Department of Internal Medicine, Sapporo Medical University, S-1, W-16, Chuo-ku, Sapporo 060-8543, Japan; arimura{at}sapmed.ac.jp

Background and aims: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Abbreviations: ARD, automatic relevance determination; ANN, artificial neural network; CRC, colon and rectal cancer; EMR, endoscopic mucosal resection; MMP, matrix metalloproteinase; MMP-7, matrilysin; SAM, significance analysis of microarray; SEM, structural equation modelling

Keywords: matrilysin; Bayesian neural network; structural equation modelling; nodal metastasis; colon and rectal cancer

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