A Novel Necroptosis-Related lncRNA Signature for Osteosarcoma

Abstract

Backgrounds: Osteosarcoma (OS) is easy to metastasis. Necroptosis-related long noncoding RNA (lncRNA) (NRlncRNA) plays a vital role in the tumorigenesis of many malignant tumors. Nonetheless, there have been few studies investigating the relations between NRlncRNA and OS. During the investigation, NRlncRNAs in OS were confirmed and characterized and their relationships with prognoses were investigated.

Methods: NRlncRNAs were downloaded from The Cancer Genome Atlas (TCGA) OS expression data and clinical-pathological information. First, univariate Cox regression and LASSO regression analyses were used to screen for prognostic-related NRlncRNAs. Second, multivariate regression analyses were used to establish a prognostic nomogram for predicting individual survival probability. Survival analyses demonstrated that high-risk patients (HRPs) had a poor prognosis. In addition, gene set enrichment analyses (GSEA) were used to identify gene function in high- and low-risk groups based on the survival mode.

Results: The 7 NRlncRNAs (AC004812.2, AC022915.1, AC073073.2, AC090559.1, AL512330.1, DDN-AS1, and SENCR) were shown to have a distinct difference and were used to construct an NRlncRNA signature. Using the signature as a risk score was an independent factor for OS patients. The signature divided OS patients into the high- and low-risk groups. Furthermore, the seven lncRNAs were significantly enriched in cell migration and metabolism.

Conclusions: The 7 NRlncRNA survival models have the potential to serve as therapeutic targets and molecular biomarkers for patients with OS, as well as to precisely predict OS prognoses.

Figure 1

NRlncRNA selection using Lasso mode. (a) Lasso coefficient values for 13 NRlncRNAs in osteosarcoma. The dashed vertical lines represent the optimal log (lambda) value. (b) Lasso coefficient profiles.

Figure 2

Screening of prognostic NRlncRNA in OS. (a) Network of lncRNAs and NRlncRNAs coexpressed in OS. (b) An illustration of the association between NRlncRNA, mRNA, and risk types.

Figure 3

The KM survival curve. (a) Based on seven NRlncRNAs, the KM survival curve of risk score. (b‑h) The KM survival curves for osteosarcoma patients in various groups.

Figure 4

Evaluation of the predictive survival mode of the 7 NRlncRNAs in OS. (a) The UCRA risk score (RS) and clinical factors. (b) MCRA outcomes for RS and CFs. (c) The AUC for RS and CFs, as well as the ROC plots. CFs include gender, M (metastatic), metastasis site, primary tumor site, and specific tumor site.

Figure 5

The nomogram of RS and CFs.

Figure 6

(a) One-, three-, and five-year ROC plots. (b) An assessment of the association between the predicted and actual OS for the prognostic model using calibration plots. It indicates excellent calibration because the predictive probabilities match the actual probabilities.

Figure 7

The outcomes of functional analyses based on NRlncRNAs. (a) GO enrichment analyses. (b) KEGG enrichment analyses.