AUTHOR=Wang Guowei , Zhang Xiaobo , Feng Wanjiang , Wang Jianlong 

TITLE=Prediction of Prognosis and Immunotherapy of Osteosarcoma Based on Necroptosis-Related lncRNAs

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.917935

DOI=10.3389/fgene.2022.917935

ISSN=1664-8021

ABSTRACT=BACKGROUND: Osteosarcoma (OS) is the most common primary tumour of bone in adolescents and its survival rate is generally less than 20% when metastases occur. Necroptosis, a novel form of programmed necrotic cell death distinct from apoptosis, has been increasingly recognized as a promising therapeutic strategy. This study sought to identify long non-coding RNAs (lncRNAs) associated with necrotizing apoptosis to predict prognosis and target drug use to improve patient survival.

METHODS: Transcriptomic data and clinical data from 85 OS patients with survival time data and expression profiles from 85 random normal adipose tissue samples were extracted from the UCSC Xena website	(http://xena.ucsc.edu/).	Nine necroptosis-associated differential prognostic lncRNAs were then identified by analysis of variance, correlation analysis, univariate Cox (uni-Cox) regression and Kaplan-Meier analysis. Then, patients were randomised into train or text groups. According to uni-Cox, we obtained prognostic lncRNAs in the train group and intersected them with the above 9 lncRNAs to obtain the final necrotizing apoptosis-related differential prognostic lncRNAs (NRlncRNAs).

Next, we performed the least absolute shrinkage and selection operator (LASSO) to construct a risk model of NRlncRNAs. Kaplan-Meier analysis, ROC curves, nomograms, calibration curves and PCA were used to validate and evaluate the models and grouping. We also analysed the differences in tumour immunity and drugs between risk groups.

RESULTS: We constructed a model containing 3 NRlncRNAs (AL391121.1, AL354919.2 and AP000851.2) and validated its prognostic predictive power. The value of AUC curve of 1-, 3- and 5-year survival probability was 0.806, 0.728 and 0.731. Meantime, we found that the overall survival time of patients in the high-risk group was shorter than that in the low-risk group. GSEA and ssGSEA showed that immune related pathways were mainly abundant in the low-risk group. We also validated the differential prediction of immune checkpoint expression, tumour immunity and therapeutic compounds in the two risk groups.

Conclusion: Overall, NRlncRNAs have important functions in OS, and these three NRlncRNAs can predict the prognosis of OS and provide guidance for immunotherapy in OS.