Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis
المؤلفون المشاركون
Yi, Ming
Li, Tianye
Qin, Shuang
Yu, Shengnan
Chu, Qian
Li, Anping
Wu, Kongming
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-10
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer.
The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined.
This study aimed to screen genes related to the progression of lung adenocarcinoma.
By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients’ clinical traits, then further identify predictive biomarkers.
GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients.
Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort.
After the average linkage hierarchical clustering, a total of 9 modules were generated.
In the clinical significant module (R = 0.44, P<0.0001), we identified 29 network hub genes.
Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas.
Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues.
Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues.
In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yi, Ming& Li, Tianye& Qin, Shuang& Yu, Shengnan& Chu, Qian& Li, Anping…[et al.]. 2020. Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis. BioMed Research International،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1133748
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yi, Ming…[et al.]. Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis. BioMed Research International No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1133748
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yi, Ming& Li, Tianye& Qin, Shuang& Yu, Shengnan& Chu, Qian& Li, Anping…[et al.]. Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1133748
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1133748
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