Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling

Abstract

Osteosarcoma is the most common type of malignant bone cancer, which often affects teenagers and young adults. The present study aimed to screen for critical genes and microRNAs (miRNAs/miRs) involved in osteosarcoma. A total of four microarray datasets (accession numbers GSE32981, GSE21257, GSE14827 and GSE14359) were downloaded from the Gene Expression Omnibus database. Following data preprocessing, module analysis was performed to identify the stable modules using the weighted gene co-expression network analysis (WGCNA) package. The differentially expressed genes (DEGs) between metastatic samples and non-metastatic samples were screened, followed by gene co-expression network construction, and Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Subsequently, prognosis-associated genes were screened and a miRNA-target gene regulatory network was constructed. Finally, the data for critical genes were validated. WGCNA analysis identified six modules; blue and yellow modules were significantly positively associated with osteosarcoma metastasis. A total of 1,613 DEGs were screened between primary tissue samples and metastatic samples. Following comparison of the genes in the two (blue and yellow) modules, a total of 166 DEGs were identified (metastatic samples vs. non-metastatic samples). Functional enrichment analysis demonstrated that these DEGs were mainly involved in ‘defense response’, ‘p53 signaling pathway’ and ‘lysosome’. By utilizing the clinical information in GSE21257, 10 critical genes associated with osteosarcoma prognosis were obtained, including CTP synthase 2 ( CTPS2 ), tumor protein p53 inducible protein 3 ( TP53I3 ) and solute carrier family 1 member 1 ( SLC1A1 ). In addition, hsa-miR-422a and hsa-miR-194 were highlighted in the miRNA-target gene network. Finally, matrix metallopeptidase 3 ( MMP3 ) and vascular endothelial growth factor B ( VEGFB ) were predicted as critical genes in osteosarcoma metastasis. CTPS2, TP53I3 and SLC1A1 may serve major roles in osteosarcoma development, and hsa-miR-422a, hsa-miR-194, MMP3 and VEGFB may be associated with osteosarcoma metastasis.

A model of twenty-three metabolic-related genes predicting overall survival for lung adenocarcinoma

“…CHPT1 mediates metabolic changes in breast cancer cells, and silencing CHPT1 can inhibit breast cancer cell proliferation and early metastasis of tamoxifen-resistant breast cancer cells, suggesting that CHPT1 is a treatment target for cancers (Fedorova et al, 2019;Jia et al, 2016). CTPS2 had a profound effect on osteosarcoma metastasis (Fan et al, 2019) and also participated in the primary immunodeficiency of herpes virus susceptible populations (Verzegnassi et al, 2018). Low CTPS2 expression may be the underlying determinant of 5FU resistance (Tan et al, 2011).…”

Identification of potential prognostic markers for osteosarcoma by integrated analysis

“…The analysis of WGCNA allows for identi cation of biological-relevant modules and hub genes, which may eventually serve as biomarkers for detection or treatment [9]. By constructing WGCNA to detect gene expression of OS, Fan et al identi ed matrix metallopeptidase 3 (MMP3) and vascular endothelial growth factor B (VEGFB) as critical genes for OS development [25].…”

Peer Review #1 of "A model of twenty-three metabolic-related genes predicting overall survival for lung adenocarcinoma (v0.1)"

“…CHPT1 mediates metabolic changes in breast cancer cells, and silencing CHPT1 can inhibit breast cancer cell proliferation and early metastasis of tamoxifen-resistant breast cancer cells, suggesting that CHPT1 is a treatment target for cancers (Fedorova et al,2019;Jia et al,2016). CTPS2 had a profound effect on osteosarcoma metastasis (Fan et al,2019) and also participated in the primary immunodeficiency of herpes virus susceptible populations (Verzegnassi et al,2018). Low CTPS2 expression may be the underlying determinant of 5FU resistance (Tan et al,2011).…”