• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2022 Fiscal Year Final Research Report

Immunostaining of SLC transporters for predicting the effect of preoperative chemotherapy in esophageal cancer

Research Project

  • PDF
Project/Area Number 20K07391
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 49020:Human pathology-related
Research InstitutionKobe University

Principal Investigator

Kamoshida Shingo  神戸大学, 保健学研究科, 教授 (70351020)

Co-Investigator(Kenkyū-buntansha) 松岡 宏  藤田医科大学, 医学部, 教授 (40367719)
大崎 博之  神戸大学, 保健学研究科, 准教授 (80438291)
Project Period (FY) 2020-04-01 – 2023-03-31
Keywords食道癌 / 術前薬物療法 / 効果予測 / SLCトランスポーター / p53 / 免疫組織化学染色
Outline of Final Research Achievements

We assessed the predictive value of immunostaining of organic cation transporter 1 (OCT1) and p53 for the effect of preoperative chemotherapy with cisplatin/5-FU (CF) or docetaxel/CF in esophageal cancer. Mutant-type expression of p53 (p53MT-ex) in pretreatment biopsies was significantly correlated with poor histopathological response. In combined analysis, tumors with either p53MT-ex or low expression of OCT1 (OCT1Low) showed a significant correlation with poor response compared with tumors with the opposite pattern. Combined p53/OCT1 was the only independent predictor of histopathological response. When stratified by chemotherapy regimen, combined p53/OCT1 was a significant predictor of response in the CF group in univariate and multivariate analyses. These results suggest that either p53MT-ex or OCT1Low expression may be a potential predictor of poor response to preoperative chemotherapy with the CF regimen in esophageal cancer.

Free Research Field

腫瘍病理学、免疫組織化学

Academic Significance and Societal Importance of the Research Achievements

術前薬物療法を施行した進行食道癌患者の治療前生検材料を対象として、薬物療法の効果予測因子の発現を明らかにすることは、進行食道癌の治療戦略の構築、薬物療法の個別化を実現する手掛かりとなる可能性がある。

URL: 

Published: 2024-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi