Abstract
Purpose
Emerging evidence demonstrates the vital role of aging and long non-coding RNAs (lncRNAs) in breast cancer (BC) progression. Our study intended to develop a prognostic risk model based on aging-related lncRNAs (AG-lncs) to foresee BC patients’ outcomes.
Patients and Methods
307 aging-related genes (AGs) were sequenced from the TCGA project. Then, 697 AG-lncs were identified by the co-expression analysis with AGs. Using multivariate and univariate Cox regression analysis, and LASSO, 6 AG-lncs, including al136531.1, mapt-as1, al451085.2, otud6b-as1, tnfrsf14-as1, and linc01871, were validated to compute the risk score and establish a risk signature. Expression levels of al136531.1, mapt-as1, al451085.2, tnfrsf14-as1, and linc01871 were higher in low-risk BC patients, whereas otud6b-as1 expression was higher in high-risk BC patients. In the training and testing set, high-risk patients performed shorter PFI, OS, and DFS than low-risk patients.
Results
Our risk signature had the highest concordance index among other established prognostic signatures and displayed ideal predictive ability for 1-, 3- and 5-year patient OS in the nomogram. Additionally, BC patients with different risk score levels showed different immune statuses and responses to immunotherapy via GSEA, ssGSEA, ESTIMATE algorithm, and TIDE algorithm analysis. Of note, the qRT-PCR analysis validated that these 6 AG-lncs expressed quite differentially in BC tissues at various clinical stages.
Conclusion
The risk signature of 6 AG-lncs might offer a novel prognostic biomarker and promisingly enhance BC immunotherapy’s effectiveness.
Keywords:
Abbreviations
AG, aging-related gene; AG-lncs, aging-related lncRNAs; AUC, area under curve; BC, breast cancer; CBC, contralateral breast cancer; cDNA, complementary DNA; DEAGs, differentially expressed AGs; DSS, disease-specific survival; ECM, extracellular matrix; GO, Gene Ontology; GSEA, gene set enrichment analysis; HNSCC, head and neck squamous cell carcinoma; HAGR, human aging genome resource; ICI, immune checkpoint inhibitor; KEGG, Kyoto Encyclopedia of Genes and Genomes; lncRNAs, long non-coding RNAs; ncRNAs, non-coding RNAs; OS, overall survival; PCA, Principle Component Analysis; PFI, progression-free interval; PPI, protein-protein interaction; ROC, receiver operating characteristic; ssGSEA, single-sample gene set enrichment analysis; TCGA, The Cancer Genome Atlas; TNBC, triple-negative breast cancer; TIDE, tumor immune dysfunction and exclusion.
Data Sharing Statement
All the datasets displayed in this study can be obtained in the online database. Further questions can be directed to the corresponding author.
Ethics Approval and Informed Consent
The study was performed after agreement from the ethics committee of Tongji Hospital of Huazhong University of Science and Technology the patients’ informed consent. The clinical samples in the study comply with the Declaration of Helsinki.
Consent for Publication
All authors have provided their consent for publication.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis, and interpretation, or in all these areas; have drafted or written, or substantially revised or critically reviewed the article; have agreed on the journal to which the article will be submitted; reviewed and agreed on all versions of the article before submission, during revision, the final version accepted for publication, and any significant changes introduced at the proofing stage; and agree to take responsibility and be accountable for the contents of the article. Zi-Hui Yang and Hong Zeng are co-correspondence authors for this study.
Disclosure
The authors declare that they have no conflicts of interest to report regarding the present study.