Research Paper Volume 14, Issue 7 pp 3030—3048
Skin cutaneous melanoma properties of immune-related lncRNAs identifying potential prognostic biomarkers
- 1 Department of Plastic Surgery, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, P.R. China
- 2 Liaoning Provincial Key Laboratory of Oral Diseases, School of Stomatology, China Medical University, Shenyang 110001, Liaoning Province, P.R. China
- 3 Department of Breast Surgery, The First Hospital of China Medical University, Shenyang 110001, Liaoning Province, P.R. China
Received: December 28, 2021 Accepted: March 9, 2022 Published: March 31, 2022
https://doi.org/10.18632/aging.203982How to Cite
Copyright: © 2022 Ma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Skin cutaneous melanoma (SKCM) is one of the most aggressive and life-threatening cancers with high incidence rate, metastasis rate and mortality. Early detection and stratification of risk assessment are essential to treat SKCM and to improve survival rate. The aim of this study is to construct an immune-related lncRNAs (immlncRNAs) prognosis risk model to identify immune biomarkers for early diagnosis, prognosis assessment and target immunotherapy of SKCM. For this purpose, we identified 46 immlncRNAs significantly correlated with SKCM prognosis to construct the prognostic risk model and patients were stratified into the high- and low-risk subgroups according to the developed model. The predictive efficiency of this model has been proved by K-M survival analysis and receiver operating characteristic curve. Moreover, CIBERSORT algorithms confirmed that there were differences in immune cell infiltration between the high- and low-risk groups. Functional enrichment analysis further indicated that immlncRNAs were related to a variety of immune response process signaling pathways, suggesting that relevant immlncRNAs could play an important role in the immune regulation of SKCM. Finally, subgroup analysis and multiple Cox regression analysis further proved the stability of the model. In summary, we successfully constructed a 46 immlncRNA-related prognostic risk score model with excellent predictive efficacy and provided more possibilities to investigate the immune regulation mechanisms and to develop immunotherapy of SKCM.
Abbreviations
SKCM: skin cutaneous melanoma; immlncRNAs: immune-related lncRNAs; lncRNAs: long non-coding RNAs; SAMMSON: survival-associated mitochondrial melanoma–specific onco-genic non-coding RNA; SLNCR1: SRA-like non-coding RNA; AMKL: acute megakaryocytic leukemia; TAM: tumor- associated macrophages.