Pivotal regulatory network and genes in osteosarcoma

A novel stratification framework based on anoikis-related genes for predicting the prognosis in patients with osteosarcoma

Background

Anoikis resistance is a prerequisite for the successful development of osteosarcoma (OS) metastases, whether the expression of anoikis-related genes (ARGs) correlates with OS prognosis remains unclear. This study aimed to investigate the feasibility of using ARGs as prognostic tools for the risk stratification of OS.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided transcriptome information relevant to OS. The GeneCards database was used to identify ARGs. Differentially expressed ARGs (DEARGs) were identified by overlapping ARGs with common differentially expressed genes (DEGs) between OS and normal samples from the GSE16088, GSE19276, and GSE99671 datasets. Anoikis-related clusters of patients were obtained by consistent clustering, and gene set variation analysis (GSVA) of the different clusters was completed. Next, a risk model was created using Cox regression analyses. Risk scores and clinical features were assessed for independent prognostic values, and a nomogram model was constructed. Subsequently, a functional enrichment analysis of the high- and low-risk groups was performed. In addition, the immunological characteristics of OS samples were compared between the high- and low-risk groups, and their sensitivity to therapeutic agents was explored.

Results

Seven DEARGs between OS and normal samples were obtained by intersecting 501 ARGs with 68 common DEGs. BNIP3 and CXCL12 were significantly differentially expressed between both clusters (P<0.05) and were identified as prognosis-related genes. The risk model showed that the risk score and tumor metastasis were independent prognostic factors of patients with OS. A nomogram combining risk score and tumor metastasis effectively predicted the prognosis. In addition, patients in the high-risk group had low immune scores and high tumor purity. The levels of immune cell infiltration, expression of human leukocyte antigen (HLA) genes, immune response gene sets, and immune checkpoints were lower in the high-risk group than those in the low-risk group. The low-risk group was sensitive to the immune checkpoint PD-1 inhibitor, and the high-risk group exhibited lower inhibitory concentration values by 50% for 24 drugs, including AG.014699, AMG.706, and AZD6482.

Conclusion

The prognostic stratification framework of patients with OS based on ARGs, such as BNIP3 and CXCL12, may lead to more efficient clinical management.

miR‑181b‑p53 negative feedback axis regulates osteosarcoma cell proliferation and invasion

Osteosarcoma (OS) is one of the most common malignant tumors in young adults and as a high distant metastasis rate. The p53 protein, a potent prognostic biomarker for patients with OS, is altered in ~50% of OS cases. p53 was reported to exert its effects through regulating the transcription of microRNAs (miRNAs/miRs) and other genes. In the present study, the expression of miR-181b, a critical OS oncomiR, was shown to be significantly upregulated whereas p53 expression was downregulated within OS tissues and cells; in tissue samples, miR-181b and p53 were negatively correlated. p53 inhibited the transcription of miR-181b via targeting its promoter region, whereas miR-181b bound the TP53 3′-untranslated region (UTR) to inhibit p53 expression. miR-181b silencing considerably increased p53, p21, and epithelial-Cadherin protein levels but decreased Cyclin D1 protein levels in OS cells. In addition, miR-181b inhibition reduced OS cell proliferation and invasion. In contrast, p53 knockdown had the opposite effects on these proteins and OS cell proliferation and invasion. Above all, p53 knockdown significantly attenuated the effects of miR-181b inhibition. Moreover, OS cell xenograft assays further confirmed the roles of the miR-181b/p53 axis in OS growth. In conclusion, miR-181b and p53 are negatively regulated by one another and therefore form a negative feedback axis that regulates the proliferation and invasion abilities of OS cells. Targeting miR-181b to inhibit its abnormal upregulation might be a potent strategy for OS treatment.

Identification of Differentially Expressed Genes under the Regulation of Transcription Factors in Osteosarcoma

The present study was to investigate and identify the differentially expressed genes (DEGs) in the transcriptional regulatory network of osteosarcoma (OS). The gene expression dataset from Gene Expression Omnibus (GEO) datasets was downloaded. DEGs were identified and their functional annotation was also conducted. In addition, differentially expressed transcription factors (TFs) and the regulatory genes were identified. The electronic validation was used to verify the expression of selected genes. The integrated analysis led to 932 DEGs. The results of functional annotation indicated that these DEGs significantly enriched in the p53 signaling pathway, Jak-STAT signaling pathway and Wnt signaling pathway. ZNF354C, NFIC, NFATC2, SP2, FOXO3, EGR1, ZEB1, RREB1, EGR2 and SRF were covered by most TFs. The expression levels of NFIC and EGR2 in electronic validation were compatible with our bio-informatics result. In conclusion, the deregulation of these genes may provide valuable information in understanding the underlying molecular mechanism in the OS.

Integrated analysis of gene expression and copy number variations in MET proto‑oncogene‑transformed human primary osteoblasts

The aim of the present study was to screen the potential osteosarcoma (OS)‑associated genes and to obtain additional insight into the pathogenesis of OS. Transcriptional profile (ID: GSE28256) and copy number variations (CNV) profile were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between MET proto‑oncogene‑transformed human primary osteoblast (MET‑HOB) samples and the control samples were identified using the Linear Models for Microarray Data package. Subsequently, CNV areas and CNVs were identified using cut‑off criterion of >30%‑overlap within the cases using detect_cnv.pl in PennCNV. Genes shared in DEGs and CNVs were obtained and discussed. Additionally, the Database for Annotation, Visualization and Integrated Discovery was used to identify significant Gene Ontology (GO) functions and pathways in DEGs with P<0.05. A total of 1,601 DEGs were screened out in MET‑HOBs and compared with control samples, including 784 upregulated genes, such as E2F transcription factor 1 (E2F1) and 2 (E2F2) and 817 downregulated genes, such as retinoblastoma 1 (RB1) and cyclin D1 (CCND1). DEGs were enriched in 344 GO terms, such as extracellular region part and extracellular matrix and 14 pathways, including pathways in cancer and extracellular matrix‑receptor interaction. Additionally, 239 duplications and 439 deletions in 678 genes from 1,313 chromosome regions were detected. A total of 12 genes were identified to be CNV‑driven genes, including cadherin 18, laminin subunit α 1, spectrin β, erythrocytic, ciliary rootlet coiled‑coil, rootletin pseudogene 2, β‑1,4-N-acetyl-galactosaminyltransferase 1, G protein regulated inducer of neurite outgrowth 1, EH domain binding protein 1‑like 1, growth factor independent 1, cathepsin Z, WNK lysine deficient protein kinase 1, glutathione S‑transferase mu 2 and microsomal glutathione S‑transferase 1. Therefore, cell cycle‑associated genes including E2F1, E2F2, RB1 and CCND1, and cell adhesion‑associated genes, such as CDH18 and LAMA1 may be used as diagnosis and/or therapeutic markers for patients with OS.

Wilms' tumor gene 1 silencing inhibits proliferation of human osteosarcoma MG-63 cell line by cell cycle arrest and apoptosis activation

Wilms’ tumor gene 1 (WT1) plays complex roles in tumorigenesis, acting as tumor suppressor gene or an oncogene depending on the cellular context. A high WT1 expression level was described in various types of human bone and soft-tissue sarcomas, including osteosarcoma (OS), but its function in carcinogenesis is not yet well understood. This study investigated WT1 both in human OS tissues and in human OS MG-63 cell line in which WT1 gene is up-regulated. The results demonstrated that WT1 is expressed in 50% of human OS cases. WT1-silenced MG-63 cells showed deregulation of proteins of cell cycle and down-regulation of PI3K/AKT pathway. Induction of apoptotic programme was also established by activation of caspase-3 and increase of Bax/Bcl2 ratio and p53 protein. This study provided new findings on role of WT1 and indicated an association between WT1 expression, cell cycle and apoptotic machinery. In conclusion, WT1 acts as a tumour promoter in osteosarcoma and it could be a potential therapeutic target.

Investigation of crucial genes and microRNAs in conventional osteosarcoma using gene expression profiling analysis

The present study aimed to screen potential genes associated with conventional osteosarcoma (OS) and obtain further information on the pathogenesis of this disease. The microarray dataset GSE14359 was downloaded from the Gene Expression Omnibus. A total of 10 conventional OS samples and two non‑neoplastic primary osteoblast samples in the dataset were selected to identify the differentially expressed genes (DEGs) using the Linear Models for Microarray Data package. The potential functions of the DEGs were predicted using Gene Ontology (GO) and pathway enrichment analyses. Protein‑protein interaction (PPI) data were also obtained using the Search Tool for the Retrieval of Interacting Genes database, and the PPI network was visualized using Cytoscape. Module analysis was then performed using the Molecular Complex Detection module. Additionally, the potential microRNAs (miRNAs) for the upregulated DEGs in the most significant pathway were predicted using the miRDB database, and the regulatory network for the miRNAs‑DEGs was visualized in Cytoscape. In total, 317 upregulated and 670 downregulated DEGs were screened. Certain DEGs, including cyclin‑dependent kinase 1 (CDK1), mitotic arrest deficient 2 like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine‑protein kinase (BUB1), were significantly enriched in the cell cycle phase and oocyte meiosis pathway. DEGs, including replication factor C subunit 2 (RFC2), RFC3, RFC4 and RFC5, were significantly enriched in DNA replication and interacted with each other. RFC4 also interacted with other DEGs, including CDK1, MAD2L1, NDC80 kinetochore complex and BUB1. In addition, RFC4, RFC3 and RFC5 were targeted by miRNA (miR)‑802, miR‑224‑3p and miR‑522‑3p. The DEGs encoding RFC may be important for the development of conventional OS, and their expression may be regulated by a number of miRNAs, including miR‑802, miR‑224‑3p and miR‑522‑3p.

Effects of distinct drugs on gene transcription in an osteosarcoma cell line

Osteosarcoma (OS) is a common cancerous bone tumor which has a detrimental impact on the lives of patients and their families. The present study aimed at investigating the underlying molecular mechanism of various drug treatments pertaining to OS, including dimethyl sulfoxide (DMSO), doxorubicin (DXP), Nutlin-3, actinomycin D (ActD) and etoposide (Eto). Microarray and p53 chromatin immunoprecipitation combined with sequencing (ChIP-seq) datasets of the OS cell line U2OS treated with distinct drugs were acquired from the Gene Expression Omnibus and differentially-expressed genes (DEGs) were screened for alignment analysis. The p53-binding target genes were identified and ChIP-seq and microarray gene expression data were combined to identify directly and indirectly targeted genes. A regulatory network of p53 was constructed with the acquired data. Finally, the Database for Annotation, Visualization and Integrated Discovery was interrogated for annotation of target genes. A total of 212 p53-binding peaks were obtained in the untreated group, whereas thousands of peaks were obtained in the treated groups. In total, ~1,000 target genes were identified in each of DXP, DMSO, Eto and ActD treatment groups, whereas the Nutlin-3 treatment group identified an increased number, with 5,458 target genes obtained. Several common DEGs including MDM2, TP53I3, RRM2B, FAS and SESN1 were targeted by all the drugs with the exception of DMSO. p53 regulated various genes including EHF, HOXA10 and BHLHE40 in the Nutlin-3 treatment group, whereas p53 regulated EHF, RFX3, TRAF40 and TCF7L2 in the DXR treatment group. The results of the present study indicate that p53 was able to directly regulate target genes including MDM2, TP53I3 and RRM2B or indirectly regulate numerous further genes through several hub genes including EHF and RFX through various drug treatments in U2OS cells. Furthermore, p53 regulated distinct molecular processes in various drug treatments.

Screening of candidate key genes associated with human osteosarcoma using bioinformatics analysis

The aim of the present study was to identify the key genes associated with osteosarcoma (OS) using a bioinformatics approach. Microarray data (GSE36004) was downloaded from the Gene Expression Omnibus database, including 19 OS cell lines and 6 normal controls. Differentially expressed genes (DEGs) in the OS cell lines were identified using the Limma package, and differentially methylated regions were screened with methyAnalysis in R. Copy number analysis was performed and genes with copy number gains/losses were further screened using DNAcopy and cghMCR packages. Functional enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery online tool, and protein-protein interactions were identified based on information obtained from the Search Tool for the Retrieval of Interacting Genes database. A total of 47 downregulated genes were screened in hyper-methylated regions, including the fragment crystallizable (Fc) region of immunoglobulin E, high affinity I, receptor for; γ polypeptide (FCER1G), leptin (LEP) and feline Gardner-Rasheed sarcoma viral oncogene homolog (FGR). In addition, a total of 17 upregulated genes, including the TPase family, AAA domain containing 2 (ATAD2) and cyclin-dependent kinase 4 (CDK4), exhibited copy number gains, while 5 downregulated genes, including Rho GTPase activating protein 9 (ARHGAP9) and major histocompatibility complex, class II, DO α (HLA-DOA), exhibited copy number losses. These results indicate that hyper-methylation of FCER1G, LEP, and FGR may serve a crucial function in the development of OS. In addition, copy number alterations of these DEGs, including ATAD2, CDK4, ARHGAP9 and HLA-DOA, may also contribute to OS progression. These DEGs may be candidate targets for the diagnosis and treatment of this disease.

Analysis of the molecular mechanism of osteosarcoma using a bioinformatics approach

The aim of this study was to explore the underlying molecular mechanism related to the process and progression of osteosarcoma (OS). The differentially expressed genes (DEGs) were downloaded from the Gene Expression Omnibus database. The pathway and gene ontology (GO) enrichment analysis, as well as transcription factor, tumor-associated gene and tumor suppressor gene analyses were performed to investigate the functions of DEGs. Next, the protein-protein interaction (PPI) network was constructed and module analysis was further assessed by cluster analysis with the overlapping neighborhood expansion (Cluster ONE) cytoscape plug-in. A total of 359 upregulated and 614 downregulated DEGs were identified to be differentially expressed between OS samples and normal controls. Pathways significantly enriched by DEGs included the focal adhesion and chromosome maintenance pathways. Significant GO terms were cell adhesion, cell cycle and nucleic acid metabolic processes. The upregulated PPI network was constructed with 170 nodes and the downregulated PPI network was constructed with 332 nodes. Breast-ovarian cancer gene 1 (BRCA1), melanocyte-stimulating hormone 2 (MSH2), cyclin D1 (CCND1) and integrin α5 (ITGA5) were identified to be hub proteins in PPI. In conclusion, the dysregulated genes played key roles in the progression of OS. Cell adhesion is a significant biological process in OS development, and the genes BRCA1, MSH2, CCND1 and ITGA5 may be potential targets in the therapy of OS.

Interleukin-1β (3953/4) C→T polymorphism increases the risk of chronic periodontitis in Asians: evidence from a meta-analysis of 20 case-control studies

INTRODUCTION

To investigate the association of the interleukin-1β (IL-1β) (3953/4) C→T polymorphism with chronic periodontitis (CP) in Asians.

MATERIAL AND METHODS

Systematic searches of electronic databases and hand searching of references were performed, including PubMed, Embase, the Cochrane Library, and the Chinese National Knowledge Infrastructure (CNKI). Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the strength of the associations. Publication bias was tested by Egger's test. Sensitivity analysis was conducted by limiting the meta-analysis studies conforming to Hardy-Weinberg equilibrium (HWE). Data analyses were carried out using RevMan 6.0.

RESULTS

A meta-analysis was performed on 20 published case-control studies, including 1,656 CP cases and 1,498 healthy controls. The pooled OR was 1.60 (95% CI = 1.02-2.52, p = 0.04) for the T allele carriers (TT + CT) compared with CC and 1.60 (95% CI = 1.06-2.42, p = 0.02) for T vs. C. Subgroup analysis by country revealed significant risks of CP among Indians carrying the T allele (TT vs. CC: OR = 3.88, 95% CI = 1.77-8.50, p = 0.0007).

CONCLUSIONS

The analysis showed that IL-1β (3953/4) C→T polymorphism probably increases the risk of CP in Asians, and the IL-1β+3954 TT genotype may be associated with a strongly increased risk of CP in Indians, but not in Chinese.

Genomic heterogeneity of osteosarcoma - shift from single candidates to functional modules

Osteosarcoma (OS), a bone tumor, exhibit a complex karyotype. On the genomic level a highly variable degree of alterations in nearly all chromosomal regions and between individual tumors is observable. This hampers the identification of common drivers in OS biology. To identify the common molecular mechanisms involved in the maintenance of OS, we follow the hypothesis that all the copy number-associated differences between the patients are intercepted on the level of the functional modules. The implementation is based on a network approach utilizing copy number associated genes in OS, paired expression data and protein interaction data. The resulting functional modules of tightly connected genes were interpreted regarding their biological functions in OS and their potential prognostic significance. We identified an osteosarcoma network assembling well-known and lesser-known candidates. The derived network shows a significant connectivity and modularity suggesting that the genes affected by the heterogeneous genetic alterations share the same biological context. The network modules participate in several critical aspects of cancer biology like DNA damage response, cell growth, and cell motility which is in line with the hypothesis of specifically deregulated but functional modules in cancer. Further, we could deduce genes with possible prognostic significance in OS for further investigation (e.g. EZR, CDKN2A, MAP3K5). Several of those module genes were located on chromosome 6q. The given systems biological approach provides evidence that heterogeneity on the genomic and expression level is ordered by the biological system on the level of the functional modules. Different genomic aberrations are pointing to the same cellular network vicinity to form vital, but already neoplastically altered, functional modules maintaining OS. This observation, exemplarily now shown for OS, has been under discussion already for a longer time, but often in a hypothetical manner, and can here be exemplified for OS.