A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer
المؤلفون المشاركون
Sun, Yuan-Lin
Zhang, Yang
Guo, Yu-Chen
Yang, Zi-Hao
Xu, Yue-Chao
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-01
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
An increasing number of studies have shown that abnormal metabolism processes are closely correlated with the genesis and progression of colorectal cancer (CRC).
In this study, we systematically explored the prognostic value of metabolism-related genes (MRGs) for CRC patients.
A total of 289 differentially expressed MRGs were screened based on The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB), and 72 differentially expressed transcription factors (TFs) were obtained from TCGA and the Cistrome Project database.
The clinical samples obtained from TCGA were randomly divided at a ratio of 7 : 3 to obtain the training group (n=306) and the test group (n=128).
After univariate and multivariate Cox regression analyses, we constructed a prognostic model based on 6 MRGs (AOC2, ENPP2, ADA, GPD1L, ACADL, and CPT2).
Kaplan–Meier survival analysis of the training group, validation group, and overall samples proved that the model had statistical significance in predicting the outcomes of patients.
Independent prognosis analysis suggested that this risk score might serve as an independent prognosis factor for CRC patients.
Moreover, we combined the prognostic model and the clinical characteristics in a nomogram to predict the overall survival of CRC patients.
Furthermore, gene set enrichment analysis (GSEA) was conducted to identify the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in the high- and low-risk groups, which might provide novel therapeutic targets for CRC patients.
We discovered through the protein-protein interaction (PPI) network and TF-MRG regulatory network that 7 hub genes were retrieved from the PPI network and 4 kinds of differentially expressed TFs (NR3C1, MYH11, MAF, and CBX7) positively regulated 4 prognosis-associated MRGs (GSTM5, PTGIS, ENPP2, and P4HA3).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sun, Yuan-Lin& Zhang, Yang& Guo, Yu-Chen& Yang, Zi-Hao& Xu, Yue-Chao. 2020. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sun, Yuan-Lin…[et al.]. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sun, Yuan-Lin& Zhang, Yang& Guo, Yu-Chen& Yang, Zi-Hao& Xu, Yue-Chao. A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1135401
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1135401
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر