Development of prediction system of recurrence for endometrial cancer

2014 Fiscal Year Final Research Report

• Project/Area Number: 24592531
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Obstetrics and gynecology
• Research Institution: Keio University
• Principal Investigator: KATAOKA Fumio 慶應義塾大学, 医学部, 助教 (40306824)
• Co-Investigator(Kenkyū-buntansha): TSUDA Hiroshi 慶應義塾大学, 医学部, 講師 (00434880)
• Project Period (FY): 2012-04-01 – 2015-03-31
• Keywords: 子宮体癌 / マイクロアレイ解析 / 再発予測

Outline of Final Research Achievements

We analyzed the relationship between the expression profile pattern and prognosis of endometrial cancer, simultaneously in both cancer cells and associated stroma. We established a formula based on the gene expression profile of cancer and stroma to predict the recurrence using a logistic regression model. We estimated the accuracy of the formula using the 0.632 method. The estimated areas under the curve (AUC) of ROC in cancer and stroma, which were used to predict recurrence, were 0.800 and 0.758, respectively. The moderate accuracies to predict recurrence were achieved by the formula based on the gene expression profile of cancer and stroma. The established formula may predict the risk of recurrence more efficiently than conventional pathological diagnosis.

Free Research Field

婦人科腫瘍学