Division of Experimental Therapy, Department of Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066CX Amsterdam, The Netherlands.
BMC Cancer. 2010 Dec 2;10:662. doi: 10.1186/1471-2407-10-662.
Accurate staging of colorectal cancer (CRC) with clinicopathological parameters is important for predicting prognosis and guiding treatment but provides no information about organ site of metastases. Patterns of genomic aberrations in primary colorectal tumors may reveal a chromosomal signature for organ specific metastases.
Array Comparative Genomic Hybridization (aCGH) was employed to asses DNA copy number changes in primary colorectal tumors of three distinctive patient groups. This included formalin-fixed, paraffin-embedded tissue of patients who developed liver metastases (LM; n = 36), metastases (PM; n = 37) and a group that remained metastases-free (M0; n = 25).A novel statistical method for identifying recurrent copy number changes, KC-SMART, was used to find specific locations of genomic aberrations specific for various groups. We created a classifier for organ specific metastases based on the aCGH data using Prediction Analysis for Microarrays (PAM).
Specifically in the tumors of primary CRC patients who subsequently developed liver metastasis, KC-SMART analysis identified genomic aberrations on chromosome 20q. LM-PAM, a shrunken centroids classifier for liver metastases occurrence, was able to distinguish the LM group from the other groups (M0&PM) with 80% accuracy (78% sensitivity and 86% specificity). The classification is predominantly based on chromosome 20q aberrations.
Liver specific CRC metastases may be predicted with a high accuracy based on specific genomic aberrations in the primary CRC tumor. The ability to predict the site of metastases is important for improvement of personalized patient management.
通过临床病理参数准确分期结直肠癌（CRC）对于预测预后和指导治疗很重要，但不能提供转移器官部位的信息。原发性结直肠肿瘤中基因组畸变的模式可能揭示了器官特异性转移的染色体特征。
采用阵列比较基因组杂交（aCGH）评估三组不同患者的原发性结直肠肿瘤中的 DNA 拷贝数变化。这包括发生肝转移（LM；n = 36）、转移（PM；n = 37）的福尔马林固定、石蜡包埋组织的患者，以及未发生转移的患者（M0；n = 25）。使用 KC-SMART 这一新颖的统计方法来识别复发性拷贝数变化，以找到针对各种组的特定基因组异常位置。我们使用预测分析微阵列（PAM）基于 aCGH 数据创建了用于器官特异性转移的分类器。
在随后发生肝转移的原发性 CRC 患者的肿瘤中，KC-SMART 分析确定了 20 号染色体上的基因组异常。LM-PAM 是一种用于肝转移发生的缩小质心分类器，能够以 80%的准确率（78%的敏感性和 86%的特异性）将 LM 组与其他组（M0&PM）区分开来。分类主要基于 20 号染色体异常。
基于原发性 CRC 肿瘤中的特定基因组异常，可以高精度预测肝特异性 CRC 转移。预测转移部位的能力对于改善个性化患者管理很重要。
