Keiko Sato1, Kazunori Akimoto2. 1. Department of Information Sciences, Faculty of Science and Technology, Tokyo University of Science, Chiba, Japan. Electronic address: keiko@is.noda.tus.ac.jp. 2. Department of Medicinal and Life Sciences, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Chiba, Japan.
Abstract
INTRODUCTION: In general, it has been considered that estrogen receptor-positive (ER+) breast cancer has a good prognosis and is responsive to endocrine therapy. However, one third of patients with ER+ breast cancer exhibit endocrine therapy resistance, and many patients develop recurrence and die 5 to 10 years after diagnosis. In ER+ breast cancer, a major problem is to distinguish those patients most likely to develop recurrence or metastatic disease within 10 years after diagnosis from those with a sufficiently good prognosis. MATERIALS AND METHODS: We downloaded the messenger RNA expression data and the clinical information for 401 patients with ER+ breast cancer from the cBioPortal for Cancer Genomics. An information-theoretical approach was used to identify the prognostic factors for survival in patients with ER+ breast cancer and to classify those patients according to the prognostic factors. RESULTS: The information-theoretical approach contributed to the identification of KMT2C and SLC20A1 as prognostic biomarkers in ER+ breast cancer. We found that low KMT2C expression was associated with a poor outcome and high SLC20A1 expression was associated with a poor outcome. Both levels of KMT2C and SLC20A1 expression were significantly and strongly associated with the differentiation of survival. The 10-year survival rate for ER+ patients with low KMT2C and high SLC20A1 expression was 0%. In contrast, for ER+ patients with high KMT2C and low SLC20A1 expression, the 10-year survival rate was 86.78%. CONCLUSION: Our results strongly suggest that clinical examination of the expression of both KMT2C and SLC20A1 in ER+ breast cancer will be very useful for the determination of prognosis and therapy.
INTRODUCTION: In general, it has been considered that estrogen receptor-positive (ER+) breast cancer has a good prognosis and is responsive to endocrine therapy. However, one third of patients with ER+ breast cancer exhibit endocrine therapy resistance, and many patients develop recurrence and die 5 to 10 years after diagnosis. In ER+ breast cancer, a major problem is to distinguish those patients most likely to develop recurrence or metastatic disease within 10 years after diagnosis from those with a sufficiently good prognosis. MATERIALS AND METHODS: We downloaded the messenger RNA expression data and the clinical information for 401 patients with ER+ breast cancer from the cBioPortal for Cancer Genomics. An information-theoretical approach was used to identify the prognostic factors for survival in patients with ER+ breast cancer and to classify those patients according to the prognostic factors. RESULTS: The information-theoretical approach contributed to the identification of KMT2C and SLC20A1 as prognostic biomarkers in ER+ breast cancer. We found that low KMT2C expression was associated with a poor outcome and high SLC20A1 expression was associated with a poor outcome. Both levels of KMT2C and SLC20A1 expression were significantly and strongly associated with the differentiation of survival. The 10-year survival rate for ER+ patients with low KMT2C and high SLC20A1 expression was 0%. In contrast, for ER+ patients with high KMT2C and low SLC20A1 expression, the 10-year survival rate was 86.78%. CONCLUSION: Our results strongly suggest that clinical examination of the expression of both KMT2C and SLC20A1 in ER+ breast cancer will be very useful for the determination of prognosis and therapy.
Authors: Kathryn J Ruddy; Daniel J Schaid; Ann H Partridge; Nicholas B Larson; Anthony Batzler; Lothar Häberle; Ralf Dittrich; Peter Widschwendter; Visnja Fink; Emanuel Bauer; Judith Schwitulla; Matthias Rübner; Arif B Ekici; Viktoria Aivazova-Fuchs; Elizabeth A Stewart; Matthias W Beckmann; Elizabeth Ginsburg; Liewei Wang; Richard M Weinshilboum; Fergus J Couch; Wolfgang Janni; Brigitte Rack; Celine Vachon; Peter A Fasching Journal: Fertil Steril Date: 2019-07-29 Impact factor: 7.329
Authors: Xinhua Liu; Rongfang Qiu; Min Xu; Miaomiao Meng; Siyu Zhao; Jiansong Ji; Yang Yang Journal: Breast Cancer Res Treat Date: 2021-07-08 Impact factor: 4.872