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Gastric Cancer 2016-Apr

Lectin microarray technology identifies specific lectins related to lymph node metastasis of advanced gastric cancer.

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Keishi Yamashita
Atsushi Kuno
Atsushi Matsuda
Yuzuru Ikehata
Natsuya Katada
Jun Hirabayashi
Hisashi Narimatsu
Masahiko Watanabe

Keywords

Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

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