Prognostic and immunological significance of an M1 macrophage-related gene signature in osteosarcoma

Diagnostic value of sphingolipid metabolism-related genes CD37 and CXCL9 in nonalcoholic fatty liver disease

The development of nonalcoholic fatty liver disease (NAFLD) has been reported to be caused by sphingolipid family inducing insulin resistance, mitochondrial dysfunction, and inflammation, which can be regulated by multiple sphingolipid metabolic pathways. This study aimed to explore the molecular mechanism of crucial sphingolipid metabolism related genes (SMRGs) in NAFLD. Firstly, the datasets (GSE48452, GSE126848, and GSE63067) from the Gene Expression Omnibus database and sphingolipid metabolism genes (SMGs) from previous research were collected for this study. The differentially expressed genes (DEGs) between different NAFLD and controls were acquired through "limma," and the SMRGs were authenticated via weighted gene co-expression network analysis (WGCNA). After overlapping the DEGs and SMRGs, the causality between the intersection genes (DE-SMRGs) and NAFLD was explored to sort out the candidate biomarkers by Mendelian randomization (MR) study. The receiver operating characteristic (ROC) curves of candidate biomarkers in GSE48452 and GSE126848 were yielded to determine the biomarkers, followed by the nomogram construction and enrichment analysis. Finally, the immune infiltration analysis, the prediction of transcription factors (TFs) and drugs targeting biomarkers were put into effect. A total of 23 DE-SMRGs were acquired based on the differential analysis and weighted gene co-expression network analysis (WGCNA), of which 3 DE-SMRGs (CD37, CXCL9 and IL7R) were picked out for follow-up analysis through univariate and multivariate MR analysis. The values of area under ROC curve of CD37 and CXCL9 were >0.7 in GSE48452 and GSE126848, thereby being regarded as biomarkers, which were mainly enriched in amino acid metabolism. With respect to the Spearman analysis between immune cells and biomarkers, CD37 and CXCL9 were significantly positively associated with M1 macrophages (P < .001), whose proportion was observably higher in NAFLD patients compared with controls. At last, TFs (ZNF460 and ZNF384) of CD37 and CXCL9 and a total of 79 chemical drugs targeting CD37 and CXCL9 were predicted. This study mined the pivotal SMRGs, CD37 and CXCL9, and systematically explored the mechanism of action of both biomarkers based on the public databases, which could tender a fresh reference for the clinical diagnosis and therapy of NAFLD.

Development and validation of neutrophil extracellular traps-derived signature to predict the prognosis for osteosarcoma patients

Neutrophil extracellular traps (NETs) have been reported to be crucial in tumorigenesis and malignant progression. However, their prognostic significance, association with tumor immune microenvironment (TIME), and therapeutic response in osteosarcoma (OS) stills remain unclear. Hence, TARGET and GSE21257 cohorts were included for analysis. Single-sample gene set enrichment analysis (ssGSEA) and weighted gene co-expression network analysis (WGCNA) were conducted to extract NETs-derived genes. Subsequently, the NETs score (NETScore) model, consisting of 4 signature genes, was established and validated with the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Our results indicated that NETScore has satisfactory predictability of the patient's overall survival, with AUC values at 1-, 3- and 5-year in the training cohort of 0.798, 0.792 and 0.804, respectively; similar prominent prediction performance was obtained in three validation cohorts. Further, real-time quantitative PCR (RT-qPCR) assay was conducted to determine the expression of signature genes in human osteoblasts and OS cells. Besides, NETScore and clinical factors (age, gender, metastatic status) were integrated to construct a nomogram. C-index and AUC values at 1-, 3-, and 5-year were above 0.800, displaying robust predictive performance. Patients with high and low NETScore had different immune statuses and drug sensitivity. Meanwhile, several positive regulatory immune function pathways, including T cell proliferation, activation and migration, were significantly suppressed among patients with high NETScore. Summarily, we established a novel NETScore that can accurately predict OS patients' prognosis, which correlated closely with the immune landscape and therapeutic response and might help to guide clinical decision-making.

Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis

Osteosarcoma (OS) is a heterogeneous, highly metastatic bone malignancy in children and adolescents. Despite advancements in multimodal treatment strategies, the prognosis for patients with metastatic or recurrent disease has not improved significantly in the last four decades. OS is a highly heterogeneous tumor; its genetic background and the mechanism of oncogenesis are not well defined. Unfortunately, no effective molecular targeted therapy is currently available for this disease. Understanding osteosarcoma's tumor microenvironment (TME) has recently gained much interest among scientists hoping to provide valuable insights into tumor heterogeneity, progression, metastasis, and the identification of novel therapeutic avenues. Here, we review the current understanding of the TME of OS, including different cellular and noncellular components, their crosstalk with OS tumor cells, and their involvement in tumor progression and metastasis. We also highlight past/current clinical trials targeting the TME of OS for effective therapies and potential future therapeutic strategies with negligible adverse effects.