Identification of LTF as a Prognostic Biomarker for Osteosarcoma.
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ABSTRACT:
SUBMITTER: Liu X
PROVIDER: S-EPMC8799371 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundOsteosarcoma (OS) is a type of primary malignant tumor, and increasing evidence shows the clinical benefits of immunotherapy in treating OS. However, the lack of comprehensive studies on the complex OS immune microenvironment hinders the application of immunotherapy. Thus, this study aimed to systematically explore the immune characteristics of OS and identify novel biomarkers for OS treatment.MethodsWe systematically studied the immune score and proportions of infiltrating immune cells in OS in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases using the ESTIMATE and CIBERSORT algorithms. Differential expression and functional analyses were used to identify dysregulated genes and explore their functions. Survival and Cox regression analyses were applied to establish an immune-related prognostic signature. Additionally, qPCR and immunohistochemistry were performed to validate the results.ResultsA total of 103 differentially expressed immune genes (DEIGs) were found in the TARGET-OS and GSE39058 databases, and these DEIGs were mainly enriched in leukocyte proliferation, leukocyte differentiation, osteoclast differentiation, natural killer (NK) cell-mediated cytotoxicity, and the adaptive immune system. A predictive signature was constructed based on the survival analysis, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.65. Moreover, we found that mitogen-activated protein kinase kinase kinase 15 (MAP3K15) can predict the prognosis of patients with OS and is closely related to CD4+ T cells and macrophages. The OS patients with high MAP3K15 expression had a significantly poorer prognosis.ConclusionsOur study found that MAP3K15, whose expression level is closely related to immune activity in tumors, is a critical immune-related biomarker, and our findings may provide a basis for OS immunotherapy.
| S-EPMC8350644 | biostudies-literature
Project description:Osteosarcoma often occurs in children and adolescents and causes poor prognosis. The role of RNA-binding proteins (RBPs) in malignant tumors has been elucidated in recent years. Our study aims to identify key RBPs in osteosarcoma that could be prognostic factors and treatment targets. GSE33382 dataset was downloaded from Gene Expression Omnibus (GEO) database. RBPs extraction and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological function of differential expression RBPs. Moreover, we constructed Protein-protein interaction (PPI) network and obtained key modules. Key RBPs were identified by univariate Cox regression analysis and multiple stepwise Cox regression analysis combined with the clinical information from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Risk score model was generated and validated by GSE16091 dataset. A total of 38 differential expression RBPs was identified. Go and KEGG results indicated these RBPs were significantly involved in ribosome biogenesis and mRNA surveillance pathway. COX regression analysis showed DDX24, DDX21, WARS and IGF2BP2 could be prognostic factors in osteosarcoma. Spearman's correlation analysis suggested that WARS might be important in osteosarcoma immune infiltration. In conclusion, DDX24, DDX21, WARS and IGF2BP2 might play key role in osteosarcoma, which could be therapuetic targets for osteosarcoma treatment.
| S-EPMC8120427 | biostudies-literature
Project description:The tumor microenvironment (TME) acts as a crucial role in the occurrence and development of osteosarcoma (OS). Despite this, the mechanism controlling the components of immunity and stroma in the tumor microenvironment remains a mystery. To conduct this study, we download and collate transcriptome data from the TARGET database, whose full name is Therapeutically Applicable Research to Generate Effective Treatments, as well as available clinical information of OS. The CIBERSORT and ESTIMATE methodology are used to acquire the proportions of components of immunity and stroma and tumor-infiltrating immune cells (TICs). Protein-protein interaction (PPI) networks and Cox regression analysis are used to select differentially expressed genes (DEGs). A prognostic biomarker is determined by intersecting univariate COX and PPI results, which lead to the finding of Triggering receptor expressed on myeloid cells-2 (TREM2). Based on the next analysis, TREM2 expression is positively correlated with OS survival time. Immune function-related genes have enrichment in the group with high expression of TREM2, according to gene set enrichment analysis (GSEA). The percentage of TICs by CIBERSORT methodology revealed that the expression of TREM2 is positively associated with follicular helper T cells, CD8-positive T cells, and M2 macrophages and negatively correlated with plasma cells, M0 macrophages, and naive CD4-positive T cells. All results suggest a possible integral role of TREM2 in the immune-related events of TME. Therefore, TREM2 may be a potential indicator of remodeling of TME in osteosarcoma, which is useful and helpful in predicting the clinical prognostic outcome of OS patients and provide a unique perspective for immunotherapy for OS.
| S-EPMC9957636 | biostudies-literature
Project description:MicroRNAs (miRNAs/miRs) are a class of small noncoding RNA molecules that have important roles in regulating the expression of target genes associated with the development and progression of cancer. The majority of miRNAs are expressed in a highly tissue- and region-specific manner, and released into the bloodstream as a consequences of different diseases. Furthermore, altered levels of miRNAs have been observed in several diseases, including cancer. In the present study, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) demonstrated that circulating miR-17 levels were significantly upregulated in patients with osteosarcoma (OS) compared with healthy subjects. RT-qPCR also revealed that high levels of circulating miR-17 expression were inversely correlated with phosphatase and tensin homolog expression, which was identified as a target gene of miR-17 in OS tissues. Furthermore, the overall survival of patients with OS was shorter in those with high miR-17 expression compared with moderate and low expression. Taken together, these findings indicate that miR-17 may function as a useful diagnostic and prognosis biomarker or therapeutic target of OS.
| S-EPMC5228414 | biostudies-literature
Project description:Metastatic progression is the major cause of death in osteosarcoma, the most common bone malignancy in children and young adults. However, prognostic biomarkers and efficacious targeted treatments for metastatic disease remain lacking. Using an immunoproteomic approach, we discovered that autoantibodies against the cell-cycle kinase inhibitor p27 (KIP1, CDKN1B) were elevated in plasma of high-risk osteosarcoma patients. Using a large cohort of serum samples from osteosarcoma patients (n = 233), we validated that a higher level of the p27 autoantibody significantly correlated with poor overall and event-free survival (P < 0.05). Immunohistochemical analysis also showed that p27 was mislocalized to the cytoplasm in the majority of osteosarcoma cases and in highly metastatic osteosarcoma cell lines. We demonstrated that ectopic expression of cytoplasmic p27 promoted migration and invasion of osteosarcoma cells, whereas shRNA-mediated gene silencing suppressed these effects. In addition, mutations at the p27 phosphorylation sites S10 or T198, but not T157, abolished the migratory and invasive phenotypes. Furthermore, the development of pulmonary metastases increased in mice injected with cells expressing cytoplasmic p27 compared with an empty vector control. Collectively, our findings support further investigation of p27 as a potential prognostic biomarker and therapeutic target in osteosarcoma cases exhibiting aberrant p27 subcellular localization. Cancer Res; 76(13); 4002-11. ©2016 AACR.
| S-EPMC4930684 | biostudies-literature
Project description:BackgroundOver the past four decades, outcomes for osteosarcoma patients have plateaued as there have been few emerging therapies showing clinical results. Thus, the identification of novel biomarkers and therapeutic strategies are urgently needed to address these primary obstacles in patient care. Although the Myc-oncogene has known roles in oncogenesis and cancer cell growth, its expression and function in osteosarcoma are largely unknown.MethodsExpression of Myc was determined by Western blotting of osteosarcoma cell lines and patient tissues, and by immunohistochemistry of a unique osteosarcoma tissue microarray (TMA) constructed from 70 patient samples with extensive follow-up data. Myc specific siRNA and inhibitor 10058-F4 were applied to examine the effect of Myc inhibition on osteosarcoma cell proliferation. The clonogenicity and migration activity was determined by clonogenic and wound-healing assays. A mimic in vivo assay, three-dimensional (3D) cell culture model, was performed to further validate the effect of Myc inhibition on osteosarcoma cell tumorigenic markers.ResultsMyc was significantly overexpressed in human osteosarcoma cell lines compared with normal human osteoblasts, and also highly expressed in fresh osteosarcoma tissues. Higher Myc expression correlated significantly with metastasis and poor prognosis. Through the addition of Myc specific siRNA and inhibitor, we significantly reduced Myc protein expression, resulting in decreased osteosarcoma cell proliferation. Inhibition of Myc also suppressed the migration, clonogenicity, and spheroid growth of osteosarcoma cells.ConclusionOur results support Myc as an emerging prognostic biomarker and therapeutic target in osteosarcoma therapy.
| S-EPMC7222246 | biostudies-literature
Project description:Receptor activity modifying protein 1 (RAMP1) facilitates the localization of the calcitonin-like receptor (CLR) to the plasma membrane, but its role in osteosarcoma (OS) remains unclear. We evaluated the RAMP1 expression and prognostic value across different cancers, studying tumor immune infiltration. The prognostic value was analyzed using the GSE39058 and TARGET datasets. Differential gene expression was evaluated. a protein-protein interaction network was constructed, and gene set enrichment analysis was performed. The function of RAMP1 in the tumor microenvironment was analyzed, and its expression in OS cell lines was validated using quantitative real-time PCR. High RAMP1 expression correlated with poor prognosis relative to low RAMP1 expression (p < 0.05). Low RAMP1 expression correlated with an abundance of CD4+ memory-activated T cells. whereas a high expression level correlated with a high proportion of gamma-delta T cells (γδ T cells). Differentially expressed genes from TARGET was enriched in olfactory transduction pathways (normalized enrichment scores [NES] = 1.6998, p < 0.0001). RAMP1 expression negatively correlated with CD44 expression but positively correlated with TNFSF9 expression. The RAMP1 gene is substantially expressed in OS cells compared to the normal osteoblast cell line hFOB1.19. Thus, RAMP1 may be a prognostic biomarker and potential therapeutic target in OS.
| S-EPMC10553254 | biostudies-literature
Project description:BackgroundOsteosarcoma was the most common primary bone malignancy in children and adolescents. It was imperative to identify effective prognostic biomarkers for this cancer. This study was aimed to identify potential crucial genes of osteosarcoma by integrated bioinformatics analysis.MethodsIdentification of differentially expressed genes from public data gene expression profiles (GSE42352), functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction and module analysis, Cox regression and survival analysis was conducted.ResultsTotally 17 co-differential genes were found to be differentially expressed. These genes were enriched in biological processes, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) pathway of inflammatory immune response. PPI network was constructed with 63 differentially expressed genes that co-existed between the test set and the validation set. The area under the receiver operating characteristic curve (AUC value) was 0.855, which indicated that the expression of PODN had a good diagnostic value for osteosarcoma. Furthermore, Cox regression and survival analysis revealed 5 genes were statistically significant.ConclusionsPODN was regarded as a potential biomarker for the diagnosis and prognosis of osteosarcoma, ACTA2, COL6A1, FAP, OLFML2B and COL6A3, can be used as potential prognostic indicators for osteosarcoma.
| S-EPMC8285818 | biostudies-literature
Project description:BackgroundCopper is an indispensably mineral element involved in various metabolic processes and functions in the active sites of many metalloproteins. Copper dysregulation is associated with cancers such as osteosarcoma (OS), the most common primary bone malignancy with invasiveness and metastasis. However, the causality between cuproptosis and OS remains elusive. We aim to identify cuproptosis-related long non-coding RNAs (lncRNAs) for osteosarcomatous prognosis, immune microenvironment response, and immunotherapy.MethodsThe Person correlation and differential expression analysis were used to identify differentially expressed cuproptosis-related lncRNAs (CRLs). The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct the CRL signature. The Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curve, internal validation, independent prognostic analysis, and nomograph were used to evaluate the prognostic value. The functional enrichment, tumor microenvironment, immunotherapy and chemotherapy response between the two distinct groups were further explored using a series of algorithms. The expression of signature CRLs was verified by real-time quantitative polymerase chain reaction (RT-qPCR) in OS cell lines.ResultsA novel CRL signature consisting of four CRLs were successfully identified. The K-M survival analysis indicated that the OS patients in the low-risk groups had a better prognosis than that in the high-risk group. Then, the ROC curve and subgroup survival analysis confirmed the prognostic evaluation performance of the signature. Equally, the independent prognostic analysis demonstrated that the CRL signature was an independently predicted factor for OS. Friends analysis determined the hub genes that played a critical role in differentially expressed genes between two distinct risk groups. In addition, the risk score was related to immunity status, immunotherapy response, and chemotherapeutic drug sensitivity. Finally, the expression of these signature CRLs detected by RT-qPCR was consistent with the bioinformatic analysis results.ConclusionIn summary, our study confirmed that the novel CRL signature could effectively evaluate prognosis, tumor immune microenvironment, and immunotherapy response in OS. It may benefit for clinical decision-making and provide new insights for personalized therapeutics.
| S-EPMC9606239 | biostudies-literature
Project description:BackgroundCancer is a disease of abnormal cell proliferation caused by abnormal expression of cancer-related genes. However, it is still difficult to distinguish benign and malignant lesions in many cases. KIF4A has been reported to be associated with a variety of cancer lesions. We aimed to explore whether KIF4A could be used as a biomarker of pan-cancer diagnostic.MethodsWe identified twenty-eight cell cycle-related genes that were overexpressed in no less than ten types of cancer. We determined KIF4A mRNA and protein expression in osteosarcoma (OS) cells. Furthermore, to determine the effect of KIF4A in OS, we silenced KIF4A in OS cells and detected cell viability, colony formation, invasion, migration, apoptosis and cell cycle parameters.ResultsKIF4A exhibited upregulated expression in eleven types of cancer. Cell cycle-related genes are extensively overexpressed in various types of cancers. KIF4A overexpression can serve as a diagnostic and prognostic marker in various cancers. Silencing KIF4A inhibited the viability, colony formation, invasion and migration and induced apoptosis and cell cycle arrest of OS cells. Our findings revealed that high expression of KIF4A could serve as a diagnostic and prognostic marker in OS cancers.ConclusionKIF4A could serve as a pan-cancer diagnostic and prognostic marker. KIF4A could be used as a novel therapeutic target for OS.
| S-EPMC8142929 | biostudies-literature