Title |
Troponin I2 as a Specific Biomarker for Prediction of Peritoneal Metastasis in Gastric Cancer
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Published in |
Annals of Surgical Oncology, April 2018
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DOI | 10.1245/s10434-018-6480-z |
Pubmed ID | |
Authors |
Koichi Sawaki, Mitsuro Kanda, Takashi Miwa, Shinichi Umeda, Haruyoshi Tanaka, Chie Tanaka, Daisuke Kobayashi, Masaya Suenaga, Norifumi Hattori, Masamichi Hayashi, Suguru Yamada, Goro Nakayama, Michitaka Fujiwara, Yasuhiro Kodera |
Abstract |
Although peritoneal metastasis is a serious concern in patients with gastric cancer, no acceptable and specific biomarker is available. We aimed to identify a candidate biomarker to predict peritoneal metastasis of gastric cancer. Metastatic pathway-specific transcriptome analysis was conducted by comparison of patient groups with no recurrence and with peritoneal, hepatic, and nodal recurrence. Fifteen cell lines and 262 pairs of surgically resected gastric tissues were subjected to messenger RNA (mRNA) expression analysis. Polymerase chain reaction array analysis was performed to explore coordinately expressed cancer-related genes. To evaluate the in situ protein localization and expression patterns, immunohistochemical staining was performed. From transcriptome data, troponin I2 (TNNI2) was identified as a candidate molecule specifically overexpressed in gastric cancer prone to peritoneal metastasis. TNNI2 mRNA was expressed at differential levels, independent of differentiated phenotype of cell lines. Epithelial to mesenchymal transition-related genes, tumor inhibitor of metalloproteinase 1 (TIMP1), and vacuolar protein sorting 13 homolog A (VPS13A) were expressed with TNNI2 at correlation coefficient > 0.7. The optimal cutoff of TNNI2 expression was determined as 0.00017. High TNNI2 expression was significantly and specifically associated with peritoneal metastasis and served as an independent risk marker for peritoneal recurrence after curative gastrectomy. Prevalence of peritoneal recurrence increased in parallel with staining intensity of TNNI2. TNNI2 expression in gastric tissues may serve as a specific biomarker for prediction of peritoneal metastasis of gastric cancer and contribute to improvement of patient management. |
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