دورية أكاديمية

Development and validation of metabolism-related gene signature in prognostic prediction of gastric cancer

التفاصيل البيبلوغرافية
العنوان: Development and validation of metabolism-related gene signature in prognostic prediction of gastric cancer
المؤلفون: Tianqi Luo, Yuanfang Li, Runcong Nie, Chengcai Liang, Zekun Liu, Zhicheng Xue, Guoming Chen, Kaiming Jiang, Ze-Xian Liu, Huan Lin, Cong Li, Yingbo Chen
المصدر: Computational and Structural Biotechnology Journal, Vol 18, Iss , Pp 3217-3229 (2020)
بيانات النشر: Elsevier, 2020.
سنة النشر: 2020
المجموعة: LCC:Biotechnology
مصطلحات موضوعية: Gastric cancer, Metabolic studies, Nomogram, Prognosis, Biotechnology, TP248.13-248.65
الوصف: Gastric cancer is one of the most common malignant tumours in the world. As one of the crucial hallmarks of cancer reprogramming of metabolism and the relevant researches have a promising application in the diagnosis treatment and prognostic prediction of malignant tumours. This study aims to identify a group of metabolism-related genes to construct a prediction model for the prognosis of gastric cancer.A large cohort of gastric cancer cases (1121 cases) from public database was included in our analysis and classified patients into training and testing cohorts at a ratio of 7: 3. After identifying a list of metabolism-related genes having prognostic value, we constructed a risk score based on metabolism-related genes using LASSO-COX method. According to the risk score, patients were divided into high- and low-risk groups. Our results revealed that high-risk patients had a significantly worse prognosis than low-risk patients in both the training (high-risk vs low-risk patients; five years overall survival: 37.2% vs 72.2%; p
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2001-0370
Relation: http://www.sciencedirect.com/science/article/pii/S2001037020304219; https://doaj.org/toc/2001-0370
DOI: 10.1016/j.csbj.2020.09.037
URL الوصول: https://doaj.org/article/341a17ce9e0b4ba685e1c1b36488ea5b
رقم الأكسشن: edsdoj.341a17ce9e0b4ba685e1c1b36488ea5b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20010370
DOI:10.1016/j.csbj.2020.09.037