Cuproptosis/ferroptosis-related gene signature is correlated with immune infiltration and predict the prognosis for patients with breast cancer

Background: Breast invasive carcinoma (BRCA) is a malignant tumor with high morbidity and mortality, and the prognosis is still unsatisfactory. Both ferroptosis and cuproptosis are apoptosis-independent cell deaths caused by the imbalance of corresponding metal components in cells and can affect the proliferation rate of cancer cells. The aim in this study was to develop a prognostic model of cuproptosis/ferroptosis-related genes (CFRGs) to predict survival in BRCA patients. Methods: Transcriptomic and clinical data for breast cancer patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cuproptosis and ferroptosis scores were determined for the BRCA samples from the TCGA cohort using Gene Set Variation Analysis (GSVA), followed by weighted gene coexpression network analysis (WGCNA) to screen out the CFRGs. The intersection of the differentially expressed genes grouped by high and low was determined using X-tile. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in the TGCA cohort to identify the CFRG-related signature. In addition, the relationship between risk scores and immune infiltration levels was investigated using various algorithms, and model genes were analyzed in terms of single-cell sequencing. Finally, the expression of the signature genes was validated with quantitative real-time PCR (qRT‒PCR) and immunohistochemistry (IHC). Results: A total of 5 CFRGs (ANKRD52, HOXC10, KNOP1, SGPP1, TRIM45) were identified and were used to construct proportional hazards regression models. The high-risk groups in the training and validation sets had significantly worse survival rates. Tumor mutational burden (TMB) was positively correlated with the risk score. Conversely, Tumor Immune Dysfunction and Exclusion (TIDE) and tumor purity were inversely associated with risk scores. In addition, the infiltration degree of antitumor immune cells and the expression of immune checkpoints were lower in the high-risk group. In addition, risk scores and mTOR, Hif-1, ErbB, MAPK, PI3K/AKT, TGF-β and other pathway signals were correlated with progression. Conclusion: We can accurately predict the survival of patients through the constructed CFRG-related prognostic model. In addition, we can also predict patient immunotherapy and immune cell infiltration.

Exploring the Association Between Immune Cell Phenotypes and Osteoporosis Mediated by Inflammatory Cytokines: Insights from GWAS and Single-Cell Transcriptomics

BACKGROUND

Patients with osteoporosis experience increased fracture risk and decreased quality of life, which pose significant health burdens and financial challenges. Despite established links between immune cell phenotypes and inflammatory cytokines and osteoporosis, the exact mechanism involved remains unclear, and further understanding is needed for effective prevention and treatment.

METHODS

Here, we performed a two-sample Mendelian randomization (MR) study to estimate the causal effects between 731 immune cell types, 91 and 41 inflammatory factors (which may have some overlap), and 5 types of osteoporosis. In subsequent mediation MR analysis, we assessed whether these inflammatory cytokines mediate the causal relationship between immune cell phenotypes and osteoporosis. Additionally, colo- calization analysis was performed using Bayesian colocalization. Single-cell transcriptomic analysis was performed using datasets from osteoporosis patients available in the Gene Expression Omnibus (GEO) database. Subsequently, single-cell sequencing analysis was performed, including dimensionality reduction, clustering, and pathway enrichment, to investigate the underlying mechanisms. Finally, to confirm the critical role of IgD⁺CD24⁺ B cells and IL-17C in osteoporosis, we established vivo dexamethasone-induced osteoporosis model. Micro-CT was used to assess the effectiveness of model establishment. Flow cytometry was performed to determine the proportion of IgD⁺CD24⁺ B cells within lymphocytes in the blood. ELISA and Western blotting were used to measure IL-17C levels in serum and bone tissue. Immunohistochemistry was conducted to evaluate the expression of IL-17C in bone tissue.

RESULTS

This study found that 32 immune cell phenotypes and 38 inflammatory cytokines were significantly associated with osteoporosis. Mediation analysis indicated that IgD+ CD24+ B cells exacerbated the risk of osteoporosis by influencing the levels of interleukin-17C (IL-17C). The mediated effect was 0.07837, accounting for 15.5% of the total effect. Single-cell transcriptome analysis supported that IgD+ CD24+ B cells play a key role in musculoskeletal-related pathways in osteoporosis patients. Additionally, we have demonstrated the significant involvement of IgD⁺CD24⁺ B cells and IL-17C in the osteoporosis disease model.

CONCLUSION

Inflammatory cytokines play a crucial role in the pathogenesis of immunity-related osteoporosis. In particular, IgD+ CD24+ B cell %lymphocyte increase the risk of osteoporosis by modulating the levels of interleukin-17C. Our results provide evidence to support the link between immunity and osteoporosis and offer new therapeutic strategies for targeting inflammatory pathways in immune-mediated osteoporosis.