Original Research ARTICLE
LncRNA OSTN-AS1 may represent a novel immune related prognostic marker for triple-negative breast cancer based on integrated analysis of a ceRNA network
- 1Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China
The competing endogenous RNA (ceRNA) networks are an effective method for investigating cancer; however, construction of ceRNA networks among different subtypes of breast cancer has not been previously performed. Based on analysis of differentially expressed RNAs between 150 triple-negative breast cancer (TNBC) tissues and 823 non-triple-negative breast cancer (nTNBC) tissues downloaded from TCGA database, a ceRNA network was constructed based on database comparisons using Cytoscape. Survival analysis and receiver operating characteristic (ROC) curve data were combined to screen out prognostic candidate genes, which were subsequently analyzed using co-expressed functionally related analysis, Gene Set Variation Analysis (GSVA) pathway-related analysis, and immune infiltration and tumor mutational burden (TMB) immune related analysis. A total of 190 DElncRNAs, 48 DEmRNAs and 13 DEmiRNAs were differentially expressed in the ceRNA network between TNBC and nTNBC subtypes. Gene ontology (GO) analysis of mRNAs co-expressed with prognostic candidate lncRNAs (AC104472.1, PSORS1C3, DSCR9, OSTN−AS1, AC012074.1, AC005035.1, SIAH2−AS1 and ERVMER61−1) were utilized for functional prediction. Consequently, OSTN-AS1 was primarily related to immunologic function, for instance, immune cell infiltration and TMB levels, and GSVA deviation degree was increased with its increased expression. In addition, many important immune molecules, such as PDCD1 and CTLA-4, were strongly correlated in terms of their quantitative expression. ceRNA networks may identify candidate therapeutic targets and potential prognostic biomarkers in breast cancer. In particular, OSTN-AS1 serves as a novel immune related molecule and could be involved in immunotherapy efforts in the future.
Keywords: bioinformatics, Survival, gene set variation analysis, Immune infiltration, ceRNA network, breast cancer, Tumor mutational burden (TMB)
Received: 15 May 2019;
Accepted: 14 Aug 2019.
Edited by:Seyed Javad Mowla, Tarbiat Modares University, Iran
Reviewed by:Yvonne Tay, National University of Singapore, Singapore
Haruko Watanabe-Takano, National Cerebral and Cardiovascular Center (Japan), Japan
Copyright: © 2019 Liu, Mi, Li, Zheng, Wu and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Liling Zhang, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, Hubei Province, China, firstname.lastname@example.org