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. 2020 Mar 16:26:e920803.
doi: 10.12659/MSM.920803.

Identification of Biomarkers for Osteosarcoma Based on Integration Strategy

Junjie Bao  1 , Zhaona Song  2 , Chunyu Song  1 , Yahui Wang  2 , Wan Li  2 , Wei Mai  1 , Qingyu Shi  1 , Hongwei Yu  1 , Linying Ni  1 , Yishu Liu  1 , Xiaolin Lu  1 , Chuan He  1 , Lina Chen  2 , Guofan Qu  1
Affiliations

Identification of Biomarkers for Osteosarcoma Based on Integration Strategy

Junjie Bao et al. Med Sci Monit. .

Abstract

BACKGROUND Osteosarcoma (OS) is the most common primary malignant tumor of bone. The identification of novel biomarkers is necessary for the diagnosis and treatment of osteosarcoma. MATERIAL AND METHODS We obtained 11 paired fresh-frozen OS samples and normal controls from patients between September 2015 and February 2017. We used an integration strategy that analyzes next-generation sequencing data by bioinformatics methods based on the pathogenesis of osteosarcoma. RESULTS One susceptibility lncRNA and 7 susceptibility genes regulated by the lncRNA for osteosarcoma were effectively identified, and real-time PCR and clinical index ALP data were used to test their effectiveness. CONCLUSIONS The results showed that the expression levels of the 7 genes were highly consistent in the training and test sample sets, especially between the expression value of the gene ALPL and the plasma detection value of its encoded protein ALP. In particular, both the expression of gene ALPL and the plasma detection values of protein ALP encoded by gene ALPL showed a high degree of consistency among different data types. The identified lncRNA and genes effectively classified the samples proved so that they could be used as potential biomarkers of osteosarcoma. Our strategy may also be helpful for the identification of biomarkers for other diseases.

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Figures

Figure 1
Figure 1
ROC Curves of 7 susceptibility genes. (A) ROC curves of ALPL, ATP1B3, FAM20C, and MYDGF. (B) ROC curves of RGS3, STT3A, and CTPS1.
Figure 2
Figure 2
ROC Curves of the susceptibility lncRNA. (A) ROC curves of 2 transcripts of lncRNA (SNHG3). (B) ROC curve of the mean values of 2 transcripts
Figure 3
Figure 3
ROC Curves of 4 OS-driving genes.
Figure 4
Figure 4
ROC curves of 7 susceptibility genes sequentially corresponding to the ROC curves of the following genes: ALPL (A), ATP1B3 (B), CTPS1 (C), FAM20C (D), MYDGF (E), RGS3 (F), and STT3A (G). The red line is the ROC curve of each gene for samples with RNA_seq data, and the black line is the ROC curve of each gene for samples with real-time PCR data.
Figure 5
Figure 5
Sample consistency test of 2 sample sets.
See this image and copyright information in PMC

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