Yamashita Keishi, Kuno Atsushi, Matsuda Atsushi, Ikehata Yuzuru, Katada Natsuya, Hirabayashi Jun, Narimatsu Hisashi, Watanabe Masahiko
Department of Surgery, Kitasato University School of Medicine, Asamizodai 2-1-1, Minami-ku, Sagamihara, Kanagawa, 252-0380, Japan.
Research Center for Medical Glycoscience, National Institute of Advanced Industrial Science and Technology, AIST Tsukuba Central 2, Tsukuba, Ibaraki, 305-8568, Japan.
Gastric Cancer. 2016 Apr;19(2):531-542. doi: 10.1007/s10120-015-0491-2. Epub 2015 Apr 4.
Although various molecular profiling technologies have the potential to predict specific tumor phenotypes, the comprehensive profiling of lectin-bound glycans in human cancer tissues has not yet been achieved.
We examined 242 advanced gastric cancer (AGC) patients without or with lymph node metastasis-N0 (n = 62) or N+ (n = 180)-by lectin microarray, and identified the specific lectins highly associated with AGC phenotypes.
In seven gastric cancer cell lines, in contrast to expressed-in-cancer lectins, not-expressed-in-cancer (NEC) lectins were tentatively designated by lectin microarray. Binding signals of the specific lectins were robustly reduced in AGC patients with N+ status as compared with those with N0 status. The receiver operating characteristic curve determined the optimal cutoff value to differentiate N0 status from N+ status, and subsequent profiling of NEC lectins identified Vicia villosa agglutinin (VVA) association with the significant other lectins involved in lymph node metastasis. VVA reaction was clearly found on cancer cells, suggesting that it may result from carcinoma-stroma interaction in primary AGC, because VVA is an NEC lectin. Most intriguingly, VVA reaction was remarkably attenuated in the tumor cells of the metastatic lymph nodes, even if it was recognized in primary AGC. In AGC, histological type was strongly associated with soybean agglutinin and Bauhinia purpurea lectin, whereas p53 mutation was the best correlated with Griffonia simplicifolia lectin II.
Lectin microarrays can be used to very accurately quantify the reaction of glycans with tumor tissues, and such profiles may represent the specific phenotypes, including N+ status, histological type, or p53 mutation of AGC.
尽管各种分子谱分析技术有预测特定肿瘤表型的潜力，但尚未实现对人类癌组织中凝集素结合聚糖的全面分析。
我们通过凝集素微阵列检测了242例无淋巴结转移（N0，n = 62）或有淋巴结转移（N+，n = 180）的进展期胃癌（AGC）患者，并鉴定了与AGC表型高度相关的特定凝集素。
在7种胃癌细胞系中，与癌组织中表达的凝集素相反，凝集素微阵列初步鉴定出癌组织中未表达的（NEC）凝集素。与N0状态的AGC患者相比，N+状态的AGC患者中特定凝集素的结合信号显著降低。通过绘制受试者工作特征曲线确定了区分N0状态和N+状态的最佳临界值，随后对NEC凝集素进行分析，发现绒毛野豌豆凝集素（VVA）与参与淋巴结转移的其他重要凝集素有关。在癌细胞上明显发现了VVA反应，这可能是由于原发性AGC中的癌-基质相互作用所致，因为VVA是一种NEC凝集素。最有趣的是，即使在原发性AGC中可检测到VVA反应，但在转移性淋巴结的肿瘤细胞中VVA反应明显减弱。在AGC中，组织学类型与大豆凝集素和紫羊蹄甲凝集素密切相关，而p53突变与简叶豆凝集素II相关性最好。
凝集素微阵列可用于非常准确地定量聚糖与肿瘤组织的反应，这些图谱可能代表AGC的特定表型，包括N+状态、组织学类型或p53突变。
