@article{46ec45d50e414cb8b494d67e6fc438f9,
title = "CCDC167 as a potential therapeutic target and regulator of cell cycle-related networks in breast cancer",
abstract = "According to cancer statistics reported in 2020, breast cancer constitutes 30% of new cancer cases diagnosed in American women. Histological markers of breast cancer are expressions of the estrogen receptor (ER), the progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2. Up to 80% of breast cancers are grouped as ER-positive, which implies a crucial role for estrogen in breast cancer development. Therefore, identifying potential therapeutic targets and investigating their downstream pathways and networks are extremely important for drug development in these patients. Through high-throughput technology and bioinformatics screening, we revealed that coiled-coil domain-containing protein 167 (CCDC167) was upregulated in different types of tumors; however, the role of CCDC167 in the development of breast cancer still remains unclear. Integrating many kinds of databases including ONCOMINE, MetaCore, IPA, and Kaplan-Meier Plotter, we found that high expression levels of CCDC167 predicted poor prognoses of breast cancer patients. Knockdown of CCDC167 attenuated aggressive breast cancer growth and proliferation. We also demonstrated that treatment with fluorouracil, carboplatin, paclitaxel, and doxorubicin resulted in decreased expression of CCDC167 and suppressed growth of MCF-7 cells. Collectively, these findings suggest that CCDC167 has high potential as a therapeutic target for breast cancer.",
keywords = "bioinformatics, breast cancer, cell growth, cell proliferation, coiled-coil domain-containing protein 167",
author = "Chen, {Pin Shern} and Hsu, {Hui Ping} and Phan, {Nam Nhut} and Yen, {Meng Chi} and Chen, {Feng Wei} and Liu, {Yu Wei} and Lin, {Fang Ping} and Feng, {Sheng Yao} and Cheng, {Tsung Lin} and Yeh, {Pei Hsiang} and Omar, {Hany A.} and Zhengda Sun and Jiang, {Jia Zhen} and Chan, {Yi Shin} and Lai, {Ming Derg} and Wang, {Chih Yang} and Hung, {Jui Hsiang}",
note = "Funding Information: Bioinformatics analyses and data mining were conducted at Taipei Medical University. The study was supported by the Ministry of Science and Technology (MOST) of Taiwan (grants MOST105-2325-B-006-003 to M-D.L., and MOST 108-2314-B-006-082 to H-P. H., and MOST109-2320-B-038-009-MY2 to C-Y.W., and MOST108-2320-B-041-002, 109-2320-B-041-001 to J-H.H.), National Cheng Kung University Hospital (grant NCKUH-10601002 to M-D.L.), and Taipei Medical University (grant TMU-108-AE1-B16 to C-Y.W.). This research was supported in part by Higher Education Sprout Project, Ministry of Education to the Headquarters of University Advancement at NCKU. Publisher Copyright: {\textcopyright} 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",
year = "2021",
month = feb,
day = "15",
doi = "10.18632/aging.202382",
language = "English",
volume = "13",
pages = "4157--4181",
journal = "Aging",
issn = "0002-0966",
publisher = "US Administration on Aging",
number = "3",
}
