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. 2022 Jul 29:13:919231.
doi: 10.3389/fimmu.2022.919231. eCollection 2022.

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Mingyi Yang  1 , Haishi Zheng  1 , Ke Xu  1 , Qiling Yuan  1 , Yirixaiti Aihaiti  1 , Yongsong Cai  1 , Peng Xu  1
Affiliations

A novel signature to guide osteosarcoma prognosis and immune microenvironment: Cuproptosis-related lncRNA

Mingyi Yang et al. Front Immunol. .

Abstract

Objective: Osteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS.

Methods: Transcriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in Science. Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS.

Results: Six CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS.

Conclusion: CRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

Keywords: LncRNA; cuproptosis; immunity; osteosarcoma; prognosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The differential analysis of the GSE16088 dataset. (A) Volcano plot of DEGs, red for high expression and blue for low expression. (B) Heatmap of DEGs, with high expression in red and low expression in green.
Figure 2
Figure 2
Differentially CRGs and CRLncs related to OS. (A) The intersection of DEGs and OS-related CRGs obtained OS-related differentially CRGs. (B) Pathway enrichment analysis of OS-related differentially CRGs. (C) By co-expression analysis, OS-related differentially CRGs yielded a total of 118 OS-related CRLncs.
Figure 3
Figure 3
Construction of risk prognostic model. (A) Univariate Cox regression analysis obtained 14 candidate prognostic CRLncs for OS, including 11 high-risk CRLncs and three low-risk CRLncs. (B) LASSO regression analysis. (C) Selection of the optimal penalty parameter for LASSO regression.
Figure 4
Figure 4
Total sample group. (A) Survival status map. (B) Risk heatmap. (C) Survival curve. (D) ROC curve. (E) Univariate COX regression analysis. (F) Multivariate COX regression analysis.
Figure 5
Figure 5
Training group. (A) Survival status map. (B) Risk heatmap. (C) Survival curve. (D) ROC curve. (E) Univariate COX regression analysis. (F) Multivariate COX regression analysis.
Figure 6
Figure 6
Test group. (A) Survival status map. (B) Risk heatmap. (C) Survival curve. (D) ROC curve. (E) Univariate COX regression analysis. (F) Multivariate COX regression analysis.
Figure 7
Figure 7
Total sample group. (A) Principal component analysis. (B) t-Distributed stochastic neighbor embedding analysis. (C) Differential analysis of tumor microenvironment.
Figure 8
Figure 8
Total sample group. (A) Immune cell differential analysis for single sample gene set enrichment analysis. (B) Immune function differential analysis for single sample gene set enrichment analysis. (C) Drug sensitivity analysis.
Figure 9
Figure 9
Validation of the mRNA expression level of CRGs and CRLncs in OS cell lines. (A) The mRNA expression level of CRGs. (B) The mRNA expression level of CRLncs. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 each experiment was repeated three times.
Figure 10
Figure 10
Validation of the protein expression levels of CRGs in OS cell lines. Representative protein grayscale bands. Statistical histogram of grayscale quantification of protein bands. *p < 0.05, ***p < 0.001, each experiment was repeated three times.
Figure 11
Figure 11
Immunohistochemistry (IHC) staining of OS and normal osteogenic tissue using anti-CRGs antibody and hematoxylin and eosin (HE) staining. Scale bar, 200 μm (left panel) and 100 μm (right panel).
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