Successful identification of a predictive biomarker for lymph node metastasis in colorectal cancer using a proteomic approach

Koichiro Mori, Yuji Toiyama, Kohei Otake, Shozo Ide, Hiroki Imaoka, Masato Okigami, Yoshinaga Okugawa, Hiroyuki Fujikawa, Susumu Saigusa, Junichiro Hiro, Minako Kobayashi, Masaki Ohi, Koji Tanaka, Yasuhiro Inoue, Yuhko Kobayashi, Yasuhiko Mohri, Issei Kobayashi, Ajay Goel, Masato Kusunoki

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


Colorectal cancer (CRC)-associated mortality is primarily caused by lymph node (LN) and distant metastasis, highlighting the need for biomarkers that predict LN metastasis and facilitate better therapeutic strategies. We used an Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-based comparative proteomics approach to identify novel biomarkers for predicting LN metastasis in CRC patients. We analyzed five paired samples of CRC with or without LN metastasis, adjacent normal mucosa, and normal colon mucosa, and differentially expressed proteins were identified and subsequently validated at the protein and/or mRNA levels by immunohistochemistry and qRT-PCR, respectively. We identified 55 proteins specifically associated with LN metastasis, from which we selected ezrin for further analysis and functional assessment. Expression of ezrin at both the protein and mRNA levels was significantly higher in CRC tissues than in adjacent normal colonic mucosa. In univariate analysis, high ezrin expression was significantly associated with tumor progression and poor prognosis, which was consistent with our in vitro findings that ezrin promotes the metastatic capacity of CRC cells by enabling cell invasion and migration. In multivariate analysis, high levels of ezrin protein and mRNA in CRC samples were independent predictors of LN metastasis. Our data thus identify ezrin as a novel protein and mRNA biomarker for predicting LN metastasis in CRC patients.

Original languageEnglish
Pages (from-to)106935-106947
Number of pages13
Issue number63
Publication statusPublished - 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Oncology


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