AUTHOR=Qian Da , Qian Cheng , Ye Buyun , Xu Ming , Wu Danping , Li Jialu , Li Dong , Yu Bin , Tao Yijing 

TITLE=Development and Validation of a Novel Stemness-Index-Related Long Noncoding RNA Signature for Breast Cancer Based on Weighted Gene Co-Expression Network Analysis

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.760514

DOI=10.3389/fgene.2022.760514

ISSN=1664-8021

ABSTRACT=Background: Breast cancer (BC) is a major leading cause of woman deaths around the world. Increasing evidence has revealed that stemness features are related to prognosis and progression of tumors. Nevertheless, the roles of stemness-index related lncRNAs in BC remain unclear. 
Methods: Differentially expressed stemness-index related lncRNAs between BC and normal samples in the Cancer Genome Atlas (TCGA) database were screened based on weighted gene co-expression network analysis (WGCNA) and differential analysis. Univariate Cox and absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify prognostic lncRNAs and construct a stemness-index related lncRNAs signature. Time-dependent receiver operating characteristic (ROC) curves were plotted to evaluate the predictive capability of the stemness-index related lncRNAs signature. Moreover, functional enrichment analysis was conducted to investigated the stemness-index related lncRNAs signature related biological function. 
Finally, quantitative real time PCR was used to detect the expression levels of lncRNAs.
Results: A total of 73 differentially expressed stemness-index related lncRNAs were identified. Next, FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 were used to construct a stemness-index related lncRNAs signature, and ROC curves indicated that stemness-index related lncRNAs signature can predict the prognosis of BC well. Moreover, functional enrichment analysis suggested that DEGs between the high-risk group and low-risk group were mainly involved in immune related biological processes and pathways. Furthermore, functional enrichment analysis of lncRNAs related protein coding genes revealed that FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 were associated with neuroactive ligand-receptor interaction, AMPK signaling pathway, PPAR signaling pathway, and cGMP-PKG signaling pathway. Finally, quantitative real time PCR revealed that FAM83H-AS1, HID1-AS1, RP11-1100L3.8, and RP11-696F12.1 may be used as the potential diagnostic biomarkers of BC.
Conclusion: The stemness-index related lncRNAs signature based on FAM83H-AS1, HID1-AS1, HOXB-AS1, RP11-1070N10.3, RP11-1100L3.8, and RP11-696F12.1 could be used as an independent predictor for the survival of BC, and FAM83H-AS1, HID1-AS1, RP11-1100L3.8, and RP11-696F12.1 might be used as the diagnostic markers of BC.