Norihisa Uemura Yukihiro Nakanishi Hoichi Kato Shigeru Saito Masato Nagino Setsuo Hirohashi and Tadashi Kondo.

Abstract

Esophageal cancer is one of the most deadly malignancies. The response to treatment modalities such as surgery or chemotradiotherapy is variable even when the patients are at the same clinical stage, and is not predicted by the existing diagnostic modalities. Novel predictive clinical tools have long been desired to optimize the therapeutic strategies and improve clinical outcomes. To develop such diagnostic tools, we aimed to discover biomarker candidates by examining tumor tissues analyzed by 2D DIGE and their corresponding clinical data. Laser microdissection was used to recover tumor cells from 58 matched cased. The patients did not receive anticancer treatment prior to surgery, and their prognosis was monitored for at least five years after surgery. The proteins in the recovered cells were labeled with CyDye DIGE Fluor saturation dye and separated by a large format 2D gel apparatus with the internal control sample labeled with a different fluorescent dye. Bioinformatics was employed to determine the protein spots that are most informative for clinicl-patholiogocal data. Mass spectrometric analysis identified the proteins corresponding to these protein spots. 2D-DIGE generated quantitative expression profiles with 3623 protein spots from approximately 3000 cells. Based on the intensity of the protein spots, unsupervised classification distinguished the tumor tissues from their normal counterparts. The intensity of 22 protein spots showed statistical difference (FDR<0.05) between patient groups with different prognosis. Mass spectrometric analysis revealed that the identified proteins are involved in important biological processes such as signal transduction, cytiskeletal/structural organization and transportation. They have been individually implicated in a range of cancer types, and our study observed them collectively in a single type of malignancy, esophageal cancer. These proteins are h2 candidates for biomarkers to establish novel therapeutic strategies.

関連論文

1. Norihisa Uemura, Yukihiro Nakanishi, Hoichi Kato, Shigeru Saito, Masato Nagino, Setsuo Hirohashi and Tadashi Kondo. Transglutaminase 3 as a prognostic biomarker in esophageal cancer revealed by proteomics. Int J Cancer, 124, 2106-2115. 2009. [PubMed]（外部リンク）