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Development of a Ten-lncRNA Signature Prognostic Model for Breast Cancer Survival: A Study with the TCGA Database
Joint Authors
Zhou, Wenqing
Pang, Yongkui
Yao, Yunmin
Qiao, Huiying
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Long noncoding RNA (lncRNA) plays a critical role in the development of tumors.
The aim of our study was construction of a lncRNA signature model to predict breast cancer (BRCA) patient survival.
We downloaded RNA-seq data and relevant clinical information from the Cancer Genome Atlas (TCGA) database.
Differentially expressed lncRNA were computed using the “edgeR” package and subjected to the univariate and multivariate Cox regression analysis.
Corresponding protein-coding genes were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis.
Finally, 521 differentially expression lncRNA were obtained.
We constructed a ten-lncRNA signature model (LINC01208, RP5-1011O1.3, LINC01234, LINC00989, RP11-696F12.1, RP11-909N17.2, CTC-297N7.9, CTA-384D8.34, CTC-276P9.4, and MAPT-IT1) to predict BRCA patient survival using the multivariate Cox proportional hazard regression model.
The C-index was 0.712, and AUC scores of training, test, and entire sets were 0.746, 0.717, and 0.732, respectively.
Univariate Cox regression analysis indicated that age, tumor status, N status, M status, and risk score were significantly related to overall survival in patients with BRCA.
Further, the multivariate analysis showed that risk score and M status had outstanding independent prognostic values, both with p<0.001.
The Gene Ontology (GO) function and KEEG pathway analysis was primarily enriched in immune response, receptor binding, external surface of plasma membrane, signal transduction, cytokine-cytokine receptor interaction, and cell adhesion molecules (CAMs).
Finally, we constructed a ten-lncRNA signature model that can serve as an independent prognostic model to predict BRCA patient survival.
American Psychological Association (APA)
Zhou, Wenqing& Pang, Yongkui& Yao, Yunmin& Qiao, Huiying. 2020. Development of a Ten-lncRNA Signature Prognostic Model for Breast Cancer Survival: A Study with the TCGA Database. Analytical Cellular Pathology،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1126196
Modern Language Association (MLA)
Zhou, Wenqing…[et al.]. Development of a Ten-lncRNA Signature Prognostic Model for Breast Cancer Survival: A Study with the TCGA Database. Analytical Cellular Pathology No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1126196
American Medical Association (AMA)
Zhou, Wenqing& Pang, Yongkui& Yao, Yunmin& Qiao, Huiying. Development of a Ten-lncRNA Signature Prognostic Model for Breast Cancer Survival: A Study with the TCGA Database. Analytical Cellular Pathology. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1126196
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1126196