Interpretable clinical visualization model for prediction of prognosis in osteosarcoma: a large cohort data study

Serum glutathione peroxidase 4 as a novel biomarker for nontraumatic osteonecrosis of the femoral head: A retrospective case-control study

There are no serum biomarkers available in nontraumatic osteonecrosis of the femoral head in clinical practice. This study aimed to evaluate the clinical value of serum glutathione peroxidase 4 in nontraumatic osteonecrosis of the femoral head. This retrospective study analyzed serum glutathione peroxidase 4 levels and clinical data of 80 patients with nontraumatic osteonecrosis of the femoral head and 80 healthy controls between August 2021 and May 2022. Serum glutathione peroxidase 4 levels were analyzed using an enzyme-linked immunosorbent assay. The Association Research Circulation Osseous classification system determined disease progression. Clinical severity was assessed by Harris hip score and visual analogue scale. Correlations between serum glutathione peroxidase 4 and disease progression as well as clinical severity were evaluated statistically. The diagnostic accuracy of serum glutathione peroxidase 4 in nontraumatic osteonecrosis of the femoral head was determined using receiver operating characteristic analysis. The baseline characteristics of participants between 2 groups were comparable. Patients with nontraumatic osteonecrosis of the femoral head displayed a decreased glutathione peroxidase 4 level compared with healthy controls (11.87 ± 2.76 μU/mL vs 16.54 ± 4.89 μU/mL, P < .01). The levels of glutathione peroxidase 4 were inversely correlated with Association Research Circulation Osseous stage (P < .01) and visual analogue scale scores (P < .01), and positively correlated with Harris score (P < .01). Receiver operating characteristic analyses showed that area under curves of glutathione peroxidase 4 was 0.808 (95% CI 0.721-0.858) and 0.847 (95% CI 0.743-0.951) with regard to diagnosis and collapse prediction in nontraumatic osteonecrosis of the femoral head, respectively. Serum glutathione peroxidase 4 could serve as a novel biomarker for diagnosing nontraumatic osteonecrosis of the femoral head and predicting collapse of the femoral head.

Downregulated annexin A1 expression correlates with poor prognosis, metastasis, and immunosuppressive microenvironment in Ewing's sarcoma

OBJECTIVE

Ewing's sarcoma (ES) is a common bone malignancy in children and adolescents that severely affects the prognosis of patients. The aim of this study was to identify novel biomarkers and potential therapeutic targets for ES.

METHODS

Highly prognosis-related hub genes were identified by independent prognostic analysis in the GSE17679 dataset. We then performed survival analysis, Cox regression analysis and clinical correlation analysis on the key gene and validated them with the GSE63157, GSE45544 and GSE73166 datasets. Differentially expressed genes (DEGs) were screened based on the high and low expression of key gene, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were performed to explore the underlying mechanisms of ES, and significant module genes were established based on protein-protein interaction (PPI) networks. Furthermore, the correlations between module genes and the immune microenvironment were analyzed and the correlations between the key gene and immune infiltration levels in sarcoma were investigated using TIMER and TISIDB. Finally, the expression levels of these key genes in ES cell lines (RD-ES and A673 cells) were further validated by real-time quantitative PCR (RT-qPCR). CCK-8 and EdU assays were performed to assess the effect of ANXA1 knockdown on RD-ES cell proliferation.

RESULTS

ANXA1 was identified as a key gene for ES prognosis. The overall survival (OS) time of patients with low ANXA1 expression was shorter, and the expression level of ANXA1 in the metastatic group was significantly lower than that in the primary group (P<0.01). Additionally, the abundance of 12 immune cells in the ANXA1 low-expression group was significantly lower than that in the high-expression group (all P<0.05), which may be related to the inhibition of the immune microenvironment. A PPI network was constructed based on 96 DEGs to further identify the five ANXA1-related module genes (COL1A2, MMP9, VIM, S100A11 and S100A4). The expression levels of ANXA1, COL1A2, MMP9, VIM, S100A11 and S100A4 were significantly different between ES cell lines and mesenchymal stem cells after validation in two ES cell lines (all P<0.01). Among these genes, ANXA1, COL1A2, MMP9, VIM and S100A4 were significantly associated with the prognosis of ES patients (all P<0.05). Importantly, ANXA1 knockdown significantly promoted the proliferation of RD-ES cells, which may explain the susceptibility to ES metastasis in the ANXA1 low-expression group.

CONCLUSIONS

ANXA1 may serve as an independent prognostic biomarker for ES patients and is associated with metastasis and the immunosuppressive microenvironment in ES, which needs to be validated in further studies.

Association between aspartate aminotransferase to alanine aminotransferase ratio and the risk of diabetes in Chinese prediabetic population: A retrospective cohort study

Background

Accumulating evidence has revealed that the aspartate aminotransferase to alanine aminotransferase (AST/ALT) ratio is a promising novel biomarker for insulin resistance (IR) and metabolic diseases. However, research on the association between the AST/ALT ratio and the incidence of diabetes progressing from prediabetes remains lacking. Herein, this study aimed to evaluate the relationship between the baseline AST/ALT ratio and risks of diabetes in patients with prediabetes.

Methods

This was a retrospective cohort study involving a total of 82,683 participants across 32 regions and 11 cities in China from 2010 to 2016. Data was obtained based on the DATADRYAD database from the health check screening program. Participants were stratified according to the interquartile range of the AST/ALT ratio (groups Q1 to Q4). The Cox proportional hazard model and smooth curve fitting were used to explore the relationship between the baseline AST/ALT ratio and the risk of diabetes in prediabetic patients. In addition, subgroup analysis was used to further validate the stability of the results.

Results

The mean age of the selected participants was 49.9 ± 14.0 years, with 66.8% of them being male. During the follow-up period 1,273 participants (11.3%) developed diabetes progressing from prediabetes during the follow-up period. Participants who developed diabetes were older and were more likely to be male. The fully-adjusted Cox proportional hazard model revealed that the AST/ALT ratio was negatively associated with the risk of diabetes in prediabetic patients (HR = 0.40, 95% CI: 0.33 to 0.48, P < 0.001). Higher AST/ALT ratio groups (Q4) also presented with a lower risk of progressing into diabetes (HR = 0.35, 95% CI: 0.29 to 0.43, P < 0.001, respectively) compared with the lowest quintile group (Q1). Through subgroup analysis and interaction tests, it was found that the association stably existed in all subgroup variables, and there were a stronger interactive effects in people with age < 45 years, and TG ≤ 1.7 mmol/L in the association between AST/ALT ratio and diabetes incidences in patients with prediabetes (P for interaction < 0.05).

Conclusion

According to our study, a higher AST/ALT ratio is associated with a lower risk of progressing into diabetes from prediabetes. Regular monitoring of AST/ALT ratio dynamics and corresponding interventions can help prevent or slow prediabetes progression for diabetes.

DJ-1 promotes osteosarcoma progression through activating CDK4/RB/E2F1 signaling pathway

Osteosarcoma (OS) is a primary malignant tumor of the bone characterized by poor prognosis due to chemotherapy resistance and high recurrence rates. DJ-1 (PARK7) is known as an oncogene and its abnormal expression is related to the poor prognosis of various types of malignant tumors. It was found in this study that upregulated expression of DJ-1 was closely correlated with the prognosis of OS patients by promoting the proliferation, migration and chemotherapy resistance of OS cells in vitro through regulating the activity of CDK4 but not through the oxidation mechanism or AKT pathway. The combination of DJ-1 and CDK4 promoted RB phosphorylation, leading to the dissociation of E2F1 into the nucleus to regulate the expression of cell cycle-related genes. The tumor xenograft mouse model demonstrated that DJ-1 knockout suppressed tumor growth in vivo. All these findings indicate that DJ-1 can affect the occurrence and progression of OS by regulating the CDK/RB/E2F1axis, suggesting a novel therapeutic opportunity for OS patients.

Identification of risk model based on glycolysis-related genes in the metastasis of osteosarcoma

BACKGROUND

Glycolytic metabolic pathway has been confirmed to play a vital role in the proliferation, survival, and migration of malignant tumors, but the relationship between glycolytic pathway-related genes and osteosarcoma (OS) metastasis and prognosis remain unclear.

METHODS

We performed Gene set enrichment analysis (GSEA) on the osteosarcoma dataset in the TARGET database to explore differences in glycolysis-related pathway gene sets between primary osteosarcoma (without other organ metastases) and metastatic osteosarcoma patient samples, as well as glycolytic pathway gene set gene difference analysis. Then, we extracted OS data from the TCGA database and used Cox proportional risk regression to identify prognosis-associated glycolytic genes to establish a risk model. Further, the validity of the risk model was confirmed using the GEO database dataset. Finally, we further screened OS metastasis-related genes based on machine learning. We selected the genes with the highest clinical metastasis-related importance as representative genes for in vitro experimental validation.

RESULTS

Using the TARGET osteosarcoma dataset, we identified 5 glycolysis-related pathway gene sets that were significantly different in metastatic and non-metastatic osteosarcoma patient samples and identified 29 prognostically relevant genes. Next, we used multivariate Cox regression to determine the inclusion of 13 genes (ADH5, DCN, G6PD, etc.) to construct a prognostic risk score model to predict 1- (AUC=0.959), 3- (AUC=0.899), and 5-year (AUC=0.895) survival under the curve. Ultimately, the KM curves pooled into the datasets GSE21257 and GSE39055 also confirmed the validity of the prognostic risk model, with a statistically significant difference in overall survival between the low- and high-risk groups (P<0.05). In addition, machine learning identified INSR as the gene with the highest importance for OS metastasis, and the transwell assay verified that INSR significantly promoted OS cell metastasis.

CONCLUSIONS

A risk model based on seven glycolytic genes (INSR, FAM162A, GLCE, ADH5, G6PD, SDC3, HS2ST1) can effectively evaluate the prognosis of osteosarcoma, and in vitro experiments also confirmed the important role of INSR in promoting OS migration.