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BACKGROUND: Bisphenol A (BPA) is a common environmental pollutant, and its specific mechanisms in cancer development and its impact on the tumor immune microenvironment are not yet fully understood. METHODS: Transcriptome data from osteosarcoma (OS) patients were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. BPA-related genes were identified through the Comparative Toxicogenomics Database (CTD), yielding 177 genes. Differentially expressed genes were analyzed using the GSE162454 dataset from the Tumor Immune Single Cell Hub 2 (TISCH2). We constructed the prognostic model using univariate Cox regression and LASSO analysis. The model was validated using the GSE16091 dataset. GO, KEGG, and GSEA analyses were performed to investigate the mechanisms of BPA-related genes. RESULTS: A total of 15 BPA-related genes were identified as differentially expressed in OS. Univariate Cox regression and LASSO analysis identified four key prognostic genes (FOLR1, MYC, ESRRA, VEGFA). The prognostic model exhibited strong predictive performance with area under the curve (AUC) values of 0.89, 0.6, and 0.79 for predicting 1-, 2-, and 3-year survival, respectively. External validation using the GSE16091 dataset confirmed the model's high accuracy with AUC values exceeding 0.88. Our results indicated that the prognosis of the high-risk population is generally poorer, which may be associated with alterations in the tumor immune microenvironment. In the high-risk group, immune cells showed predominantly low expression levels, while immune checkpoint genes were significantly overexpressed, along with markedly elevated tumor purity. These findings revealed a correlation between upregulation of BPA-related genes and formation of an immunosuppressive microenvironment, leading to unfavorable patient outcomes. CONCLUSION: Our study highlighted the significant association of BPA with OS biology, particularly in its potential role in modulating the tumor immune microenvironment. We offered a fresh insight into the influence of BPA on cancer development, thus providing valuable insights for future clinical interventions and treatment strategies.
RESUMEN
BACKGROUND: Breast cancer (BC) patients tend to suffer from distant metastasis, especially bone metastasis. METHODS: All the analysis based on open-accessed data was performed in R software, dependent on multiple algorithms and packages. The RNA levels of specific genes were detected using quantitative Real-time PCR as a method of detecting the RNA levels. To assess the ability of BC cells to proliferate, we utilized the CCK8 test, colony formation, and the 5-Ethynyl-20-deoxyuridine assay. BC cells were evaluated for invasion and migration by using Transwell assays and wound healing assays. RESULTS: In our study, we identified the molecules involved in BC bone metastasis based on the data from multiple BC cohorts. Then, we comprehensively investigated the effect pattern and underlying biological role of these molecules. We found that in the identified molecules, the EMP1, ACKR3, ITGA10, MMP13, COL11A1, and THY1 were significantly correlated with patient prognosis and mainly expressed in CAFs. Therefore, we explored the CAFs in the BC microenvironment. Results showed that CAFs could activate multiple carcinogenic pathways and most of these pathways play an important role in cancer metastasis. Meanwhile, we noticed the interaction between CAFs and malignant, endothelial, and M2 macrophage cells. Moreover, we found that CAFs could induce the remodeling of the BC microenvironment and promote the malignant behavior of BC cells. Then, we identified MMP13 for further analysis. It was found that MMP13 can enhance the malignant phenotype of BC cells. Meanwhile, biological enrichment and immune infiltration analysis were conducted to present the effect pattern of MMP13 in BC. CONCLUSIONS: Our result can improve the understanding of researchers on the underlying mechanisms of BC bone metastasis.
