SELPLG Expression Was Potentially Correlated With Metastasis and Prognosis of Osteosarcoma

The neutrophil extracellular trap-related gene FPR1 (formyl peptide receptor 1) as a potential prognostic and therapeutic target in osteosarcoma

BACKGROUND

Neutrophil extracellular trap (NET) has been implicated in cancer progression and metastasis. Nevertheless, the role of the NET-related gene, formyl peptide receptor 1 (FPR1), in osteosarcoma (OS) remains largely unexplored. This study aimed to investigate the prognostic significance and biological function of FPR1 in OS.

METHODS

The least absolute shrinkage and selection operator (LASSO) algorithm was employed to construct a NET-related prognostic model utilizing OS datasets from TARGET and GEO (GSE21257) databases. The scRNA-seq dataset GSE162454 was then used for verifying the role of NET-related model in OS at single-cell resolution. Next, survival analysis and multivariate cox regression analysis were performed to evaluate the prognostic value of FPR1 in OS patients. The CIBERSORT algorithm was conducted to evaluate the relationship between FPR1 levels and immune cell abundance. Subsequently, the biological role of FPR1 was explored through CCK-8, and transwell assays in OS cell lines.

RESULTS

A signature NET score, comprising four NET-related genes (TNFRSF10C, FPR1, BST1 and SELPLG), was constructed to predict the prognosis of OS. The survival outcomes for patients in high-NET score group were markedly worse than that in the low-NET score group. Meanwhile, at single cell resolution, OS cells progressively evolved into tumors with elevated NET scores. Furthermore, FPR1 levels were markedly reduced in OS cells when compared to normal osteoblast cells, and the overexpression of FPR1 notably suppressed OS cell viability, migration and invasion. Additionally, OS patients exhibiting high levels of FPR1 demonstrated a favorable overall survival. Moreover, these patients also had a higher proportion of M1 macrophages and a lower proportion of M0 macrophages.

CONCLUSION

Collectively, our study indicates that the NET-related gene FPR1 is closely related to tumor progression, prognosis and immune infiltration in OS.

Distinct Gene Expression and Immune Features Between Different Neutrophil Extracellular Trap-Related Osteosarcoma Subtypes

We sought to determine neutrophil extracellular trap (NET)-related genes' potential value in improving the efficacy of diagnosis and identifying novel therapeutic targets for osteosarcoma. Data were obtained from TARGET, GEO, and CCLE database. Differentially expressed genes were identified between the subtypes based on NET-related genes. PPI network was constructed using STRING, following by ClueGO enrichment analysis. Infiltration of immune cells was calculated by ssGSEA. Risk Score model was built by LASSO Cox regression analysis. Western blot and qRT-PCR were applied to validate the expression of genes used in the model. We identified 19 NET-related genes with prognostic potential in osteosarcoma using univariate Cox regression analysis. Patients from TARGET were clustered into two subtypes with distinct prognosis and immune features. 381 DEGs were identified between the two NET subtypes. Risk Score based on BST1, SELPLG, FPR1 and TNFRSF10C was reliable to predict the prognosis of osteosarcoma patients. The four genes expressed significantly lower in osteosarcoma than normal cells. Low Risk Score individuals only existed in C1 subtype with better prognosis. Osteosarcoma were clustered into two subtypes based on NET-related genes. Risk Score model constructed by four NET-related gene was able to independently predict the prognosis of osteosarcoma.

Identification of UNC5B as a novel aggressive biomarker for osteosarcoma based on basement membrane genes

BACKGROUND

The prognosis of patients with metastatic osteosarcoma is poor, and the variation of basement membrane genes (BMGs) is associated with cancer metastasis. However, the role of BMGs in osteosarcoma has been poorly studied.

METHODS

BMGs were collected and differentially expressed BMGs (DE-BMGs) were found through difference analysis. DE-BMGs were further screened by univariate Cox regression and Lasso regression analyses, and six key BMGs were identified and defined as basement membrane genes signatures (BMGS). Then, BMGS was used to construct the osteosarcoma BMGS risk score system, and the osteosarcoma patients were divided into high- and low-risk groups based on the median risk score. Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE scores were used to investigate the differences in immune infiltration between the two scoring groups. Additionally, we investigated whether UNC5B affects various features in tumors by bioinformatic analysis and whether UNC5B was involved in multiple biological functions of osteosarcoma cells by wound healing assay, transwell assay, and western blot.

RESULTS

The osteosarcoma BMGS risk score reliably predicts the risk of metastasis, patient prognosis, and immunity. UNC5B expression was elevated in osteosarcoma, and correlated with various characteristics such as immune infiltration, prognosis, and drug sensitivity. In vitro assays showed that UNC5B knockdown reduced osteosarcoma cells' capacity for migration and invasion, and EMT process.

CONCLUSION

A novel BMGS risk score system that can effectively predict the prognosis of osteosarcoma was developed and validated. The UNC5B gene in this system is one of the key aggressive biomarkers of osteosarcoma.

Validation of the biological function and prognostic significance of AURKA in neuroblastoma

BACKGROUND

Neuroblastoma (NB) is the most common extracranial solid tumor in children, and the AURKA gene encodes a protein kinase involved in cell cycle regulation that plays an oncogenic role in a variety of human cancers. The aim of this study was to validate the biological function and prognostic significance of AURKA in NB using basic experiments and bioinformatics.

METHODS

Data obtained from Target and GEO databases were analyzed using various bioinformatic techniques. The expression of AURKA in 77 NB samples was detected by immunohistochemistry (IHC) method. The lentiviral RNA interference technique was employed to downregulate AURKA gene expression in NB cell lines. Additionally, cell counting kit-8 and flow cytometry analysis were conducted to investigate the impact of AURKA expression on cell proliferation, cell cycle progression, and apoptosis.

RESULTS

A bioinformatic analysis showed that patients with NB in the AURKA-high-expression group had shorter OS (Overall Survival). Immune cell infiltration analysis showed that only activated CD4 T cell and type 2 T helper cell infiltration levels were higher in the AURKA-high-expression group than in the AURKA-low-expression group, with the infiltration levels of most other immune cells and cytokines lower in the high-expression group. Furthermore, the enhanced infiltration of activated CD4 T cells was associated with worse OS in patients with NB. IHC results showed that the AURKA expression was correlated with MYCN status and INSS stage. Log-rank test showed that pathological type, MYCN status, INSS stage, COG risk group, and AURKA expression was related to PFS (Progression-free survival) of NB patients, but COX regression analysis showed that none of the above factors were independently prognostic for PFS. In vitro, shRNA delivered via an AURKA-specific lentivirus significantly and consistently silenced endogenous AURKA expression in the human NB cell line SK-N-AS. This inhibited tumor cell proliferation, induced apoptosis, and caused G2/M-phase cell cycle arrest. Moreover, western blot assay showed significant reductions in the levels of mTOR, p70S6K, and 4E-BP1 phosphorylation in the AURKA-knockdown group. I found in subsequent experiments that NFYB can bind to the AURKA promoter and thus promote AURKA expression.

CONCLUSIONS

High-level AURKA expression in NB is associated with poor patient prognosis. Silencing AURKA inhibited tumor cell proliferation, induced tumor cell apoptosis, and led to cell cycle arrest in the G2/M phase. Mechanistically, AURKA knockdown inhibited the phosphorylation and the activation of the mTOR1/p70S6K/4E-BP1 signaling pathway. In addition, AURKA was observed to regulate the infiltration levels of various immune cells in the NB tumor microenvironment, resulting in remodeling of the immunosuppressive tumor microenvironment.

Differential Gene Expression of Checkpoint Markers and Cancer Markers in Mouse Models of Spontaneous Chronic Colitis

The presence of checkpoint markers in cancer cells aids in immune escape. The identification of checkpoint markers and early cancer markers is of utmost importance to gain clarity regarding the relationship between colitis and progressive inflammation leading to cancer. Herein, the gene expression levels of checkpoint makers, cancer-related pathways, and cancer genes in colon tissues of mouse models of chronic colitis (Winnie and Winnie-Prolapse mice) using next-generation sequencing are determined. Winnie mice are a result of a Muc2 missense mutation. The identification of such genes and their subsequent expression and role at the protein level would enable novel markers for the early diagnosis of cancer in IBD patients. The differentially expressed genes in the colonic transcriptome were analysed based on the Kyoto Encyclopedia of Genes and Genomes pathway. The expression of several oncogenes is associated with the severity of IBD, with Winnie-Prolapse mice expressing a large number of key genes associated with development of cancer. This research presents a number of new targets to evaluate for the development of biomarkers and therapeutics.

ISG15 is a potential therapeutic target for osteosarcoma: a comprehensive analysis based on bioinformatics and in vitro experiments

BACKGROUND

The expression of aberrant interferon-stimulated gene 15 (ISG15) is connected with various human diseases, including cancer. ISG15 is involved in tumor formation and metastasis. However, its role in osteosarcoma is uncertain.

METHODS

ISG15 expression in pan-cancer from RNA Sequencing data were obtained from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases. The relationship between ISG15 expression and prognosis was assessed through TCGA clinical survival data. Immunohistochemistry (IHC) images of ISG15 were retrieved using the Human Protein Atlas to analyze the differences in selected normal and tumor tissues. Gene enrichment analysis and signaling pathway analysis were used to assess the potential role of ISG15 in sarcoma, and the correlation between ISG15 expressions and immune cell infiltration levels was estimated by immune infiltration analysis. The expression levels of ISG15 were assessed by qRT-PCR and IHC. Colony formation, wound healing assay and transwell assay were used to detect the effects of ISG15 on the biological behaviors of osteosarcoma cells. The correlation between ISG15 levels and CD8+/CD68+ cells was further examined by double-labeled immunofluorescence. The chemotactic effect of ISG15 on CD8+/CD68+ cells was demonstrated by chemotactic experiments and flow cytometry.

RESULTS

ISG15 was highly expressed in most cancers, while high ISG15 expression was significantly correlated with poor overall survival. Gene enrichment analysis in sarcoma suggested that antigen processing and presentation might be involved in the oncogenic mechanism of ISG15. Further immune infiltration analysis showed that high ISG15 expression might reflect the infiltration level of certain immune cells. Additionally, our verification showed that ISG15 was significantly related to the occurrence and metastasis of osteosarcoma, and knockdown of ISG15 significantly altered cell biological behavior, resulting in decreased proliferation, migration and invasion capabilities of osteosarcoma cells. The high expression of ISG15 in osteosarcoma tissue was associated with a high level of CD68+ immune cell infiltration while a low level of CD8+ T cell infiltration. CD68+ immune cells were recruited in vitro by overexpression of ISG15, which on the contrary could weaken the chemotaxis of CD8+ T cells.

CONCLUSION

High ISG15 expression is an inherent feature of osteosarcoma and triggers tumorigenesis and metastasis by regulating tumor immunogenicity. ISG15 is expected to be the target of osteosarcoma treatment.

Construction and validation of a novel prognostic model for thyroid cancer based on N7-methylguanosine modification-related lncRNAs

BACKGROUND

To construct and verify a novel prognostic model for thyroid cancer (THCA) based on N7-methylguanosine modification-related lncRNAs (m7G-lncRNAs) and their association with immune cell infiltration.

METHODS

In this study, we identified m7G-lncRNAs using co-expression analysis and performed differential expression analysis of m7G-lncRNAs between groups. We then constructed a THCA prognostic model, performed survival analysis and risk assessment for the THCA prognostic model, and performed independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, analysis of the regulatory relationship between prognostic differentially expressed m7G-related lncRNAs (PDEm7G-lncRNAs) and mRNAs and correlation analysis of immune cells and risk scores in THCA patients were carried out.

RESULTS

We identified 29 N7-methylguanosine modification-related mRNAs and 116 differentially expressed m7G-related lncRNAs, including 87 downregulated and 29 upregulated lncRNAs. Next, we obtained 8 PDEm7G-lncRNAs. A final optimized model was constructed consisting of 5 PDEm7G-lncRNAs (DOCK9-DT, DPP4-DT, TMEM105, SMG7-AS1 and HMGA2-AS1). Six PDEm7G-lncRNAs (DOCK9-DT, DPP4-DT, HMGA2-AS1, LINC01976, MID1IP1-AS1, and SMG7-AS1) had positive regulatory relationships with 10 PDEm7G-mRNAs, while 2 PDEm7G-lncRNAs (LINC02026 and TMEM105) had negative regulatory relationships with 2 PDEm7G-mRNAs. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with THCA. Forest maps and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Finally, we demonstrated a correlation between different immune cells and risk scores.

CONCLUSION

Our results will help identify high-risk or low-risk patients with THCA and facilitate early prediction and clinical intervention in patients with high risk and poor prognosis.