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. 2020 Dec 3;13(1):1212-1235.
doi: 10.18632/aging.202258. Epub 2020 Dec 3.

Therapeutic potential of targeting HSPA5 through dual regulation of two candidate prognostic biomarkers ANXA1 and PSAT1 in osteosarcoma

Xiaojun Tang  1   2 , Lingli Luo  3 , Yukun Li  4 , Hailong Wu  5 , Qing Hu  6 , Haiyan Yue  7 , Xiao He  8 , Juan Zou  4 , Shaoxiong Min  1   5
Affiliations

Therapeutic potential of targeting HSPA5 through dual regulation of two candidate prognostic biomarkers ANXA1 and PSAT1 in osteosarcoma

Xiaojun Tang et al. Aging (Albany NY). .

Abstract

Osteosarcoma is the most common primary malignant bone tumor that mostly affects young people's health. The prognosis of patients with unresectable or recurrent osteosarcoma still remains dismal. Based on gene integration analysis from GEO and TARGET databases by R language, the differentially expressed genes of osteosarcoma patients were identified. Biological molecular function analysis indicated that these genes were importantly enriched in the process of cell adhesion molecule binding. Gene significance highly-related to clinical traits of osteosarcoma was found by weighted gene co-expression network analysis. Additionally, receiver operating characteristic curve analysis was conducted to find prognostic markers in LASSO Cox regression model. Two candidate biomarkers, ANXA1 and PSAT1, for the prognosis of osteosarcoma were detected separately on the basis of WGCNA and LASSO model. Of note, their expression profiles were interrelated with an important therapeutic target HSPA5. In vitro pharmaceutical experiments were performed to explore the biological role and prognostic benefit of candidates. Suppression of HSPA5 effectively upregulated ANXA1 and inhibited PSAT1, resulting in osteosarcoma cell proliferation arrest and apoptosis. These findings suggest that HSPA5 serves as a core molecule for osteosarcoma therapy due to its bidirectional regulation of candidate prognostic biomarkers ANXA1 and PSAT1.

Keywords: ANXA1; HSPA5; PSAT1; osteosarcoma; prognosis.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Identification of DEGs in OS. (A) Heatmap shows differential expression profiles in normal tissues and tumor tissues from the GSE16087 and GSE16088 datasets. DEGs were defined with |log2FC| > 1 and adjusted P-value < 0.05. (B) Genome-wide gene expression profiles of OS tumor and normal tissues from two GSE datasets were shown with volcano plots. Black symbols represent normally expressed genes. Red and blue symbols represent the aberrantly expressed genes with |log2FC| > 1 and adjusted P-value < 0.05. (C) Hierarchical clustering analysis of differential expression profiles of 515 common DEGs in OS tumor and normal tissues from the two GSE datasets. Blue and red blockages respectively indicate the expression level of genes lower or higher than the median expression value across all samples.
Figure 2
Figure 2
Significantly enriched pathways of DEGs in OS. (A, B) Representative GSEA of KEGG pathway gene set has04141 among DEGs from GSE16087 and GSE16088 datasets. (C, D) Heatmap analysis of shared DEGs enriched in KEGG pathway hsa04141 from the two GSE datasets. DEGs were defined with |log2FC| > 1 and adjusted P-value < 0.05.
Figure 3
Figure 3
Significantly enriched molecular function of DEGs in OS. (A, B) The top 10 significantly enriched molecular function terms of DEGs in OS are shown using GSEA.
Figure 4
Figure 4
WGCNA discoveries the key ANXA1-entered module. (A) Hierarchical clustering dendrogram of tumor samples from TARGET_OS with the indicated clinical traits. (B–C) Scale independence and mean connectivity analyses of OS samples. Soft-thresholding power β = 3 fits the scale-free topology. (D) Clustering tree of genes with divergence. The branches of tree represent different modules. (E) Heatmap of TOM among 1000 genes which were selected randomly in WGCNA. Dark/light color corresponds to the degree of overlap. (F) Relevance of module eigengenes with traits. Based on the correlation and P-value in each cell, the magenta module containing ANXA1 is selected.
Figure 5
Figure 5
The potential association between ANXA1 and HSPA5. (A) Genes involved in magenta module shown in scatter plot. Cut-off of module membership = 0.8 and gene significances for survival time = 0.2 as the criteria for the hub genes where ANXA1 included. (B) Gene ontology analysis of genes linked to ANXA1 expression based on the topological overlap. (C) The positive correlation between ANXA1 and HSPA5 mRNA expression levels (log2) in TARGET_OS dataset. Statistical P-value was obtained by Pearson correlation analysis. (D) ANXA1 and HSPA5 expression levels in bone marrow cancer and normal tissues through GENT2 online analysis.
Figure 6
Figure 6
High ANXA1 expression and low HSPA5 expression are involved in good outcomes of OS patients. (A–C) Box plots showing differential mRNA levels of ANXA1 and HSPA5 between sarcoma and normal tissues from ONCOMINE database. (D) The correlation of HSAP5 expression with the overall survival of sarcoma patients shown in Kaplan-Meier curve from KM plotter database. (E, F) The correlation of HSAP5 expression with the overall survival (69 cases) and progression free survival (63 cases) of OS patients shown in Kaplan-Meier curves from TARGET_OS dataset. (G, H) Kaplan-Meier analyses of overall survival (in 81 cases) and progression free survival (in 77 cases) were conducted to show OS patients with lower ANXA1 mRNA level live shorter from TARGET_OS dataset.
Figure 7
Figure 7
Integrated gene signature for OS prognosis prediction. (A, B) Univariable Cox regression analysis to find prognosis-associated genes from GSE16091 and TARGET_OS. (C, D) Kaplan-Meier curves showing the overall survival according to risk score of the set of prognosis-related signature OS patients in the two datasets. (E, F) ROC analysis of the cluster of prognostic biomarkers for OS in TARGET database and GSE16091 dataset.
Figure 8
Figure 8
Cross-talk between HSPA5 and the leading OS prognosis-associated predictor PSAT1. (A) The distribution of risk scores is shown for the cohorts from the dataset GSE16091 (upper panel). The alive are shown in green, while the dead are shown in red. And the heatmap of expression profiles of prognostic gene signature. PSAT1 ranks first where high expression indicates poor prognosis of OS patients. (B) Box plot to show differential mRNA level of PSAT1 in sarcoma tumor and normal tissues from ONCOMINE database. (C) PSAT1 expression levels in bone cancer and normal tissues through GENT2 online analysis. (D) Kaplan-Meier curves to show the overall survival of sarcoma patients about PSAT1 gene expression from online KM plotter database. (E, F) The positive correlation between PSAT1 and HSPA5 mRNA expression levels (log2) in GSE16091 and TARGET_OS datasets. Statistical P-value was obtained by Pearson correlation analysis.
Figure 9
Figure 9
A dual role of HSPA5 in transcriptional mediation of ANXA1 and PSAT1 and its correlation with the clinicopathological features of OS. (A) PPI network of proteins GRP78 (HSPA5), Annexin A1 and PSAT1. (B) The gene regulation of ANXA1 and PSAT1 in stable HSPA5-expressing U-2 OS cells. (C) The expression of the indicated genes in HSPA5-siRNAs and HSPA5-rescued plasmid-transfected U-2 OS cells. (D) Stable HSPA5-expressing or the empty U-2 OS cells were subjected to immunoblotting analysis of PSAT1 and GRP78 levels. *P < 0.05 and **P < 0.01 compared to the control. (E, F) The expression levels of (E) Annexin A1 and PSAT1 and (F) molecules involved in AKT pathway and apoptotic pathway in HSPA5 siRNAs-transfected U-2 OS cells. (G) Expression of GRP78 and PCNA were detected by immunohistochemical staining in indicated adjacent normal tissues and tumors from OS patients. (H) Images of immunohistochemical staining for protein GRP78 in OS tissues of representative patients. (I) GRP78 expression increased progressively with aggressive progression of OS tissues with P-value less than 0.05. (J, K) IHC staining quantification of GRP78 and PCNA in the matched OS and adjacent normal tissues (n = 11 and 15, respectively). (L) The correlation of GRP78 and PCNA staining in OS tissues (n = 12). All data are shown with mean ± SD.*or #P < 0.05, **or ##P < 0.01 and ***or ###P < 0.001 in comparison with the indicated group; ns, no significant difference.
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