Comprehensive bioinformatics analyses of APOBECs family and identification of APOBEC3D as the unfavorable prognostic biomarker in clear cell renal cell carcinoma

The role of APOBEC3C in modulating the tumor microenvironment and stemness properties of glioma: evidence from pancancer analysis

Background

It is now understood that APOBEC3 family proteins (A3s) are essential in tumor progression, yet their involvement in tumor immunity and stemness across diverse cancer types remains poorly understood.

Methods

In the present study, comprehensive genome-wide statistical and bioinformatic analyses were conducted to elucidate A3 family expression patterns, establishing clinically relevant correlations with prognosis, the tumor microenvironment(TME), immune infiltration, checkpoint blockade, and stemness across cancers. Different experimental techniques were applied, including RT-qPCR, immunohistochemistry, sphere formation assays, Transwell migration assays, and wound-healing assays, to investigate the impact of A3C on low-grade glioma (LGG) and glioblastoma multiforme (GBM), as well as its function in glioma stem cells(GSCs).

Results

Dysregulated expression of A3s was observed in various human cancer tissues. The prognostic value of A3 expression differed across cancer types, with a link to particularly unfavorable outcomes in gliomas. A3s are associated with the the TME and stemness in multiple cancers. Additionally, we developed an independent prognostic model based on A3s expression, which may be an independent prognostic factor for OS in patients with glioma. Subsequent validation underscored a strong association between elevated A3C expression and adverse prognostic outcomes, higher tumor grades, and unfavorable histology in glioma. A potential connection between A3C and glioma progression was established. Notably, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses implicated A3C in immune system-related diseases, with heightened A3C levels contributing to an immunosuppressive tumor microenvironment (TME) in glioma. Furthermore, in vitro experiments substantiated the role of A3C in sustaining and renewing glioma stem cells, as A3C deletion led to diminished proliferation, invasion, and migration of glioma cells.

Conclusion

The A3 family exhibits heterogeneous expression across various cancer types, with its expression profile serving as a predictive marker for overall survival in glioma patients. A3C emerges as a regulator of glioma progression, exerting its influence through modulation of the tumor microenvironment and regulation of stemness.

The Pyroptosis-Related Risk Genes APOBEC3D, TNFRSF14, and RAC2 Were Used to Evaluate Prognosis and as Tumor Suppressor Genes in Breast Cancer

Background

Pyroptosis is a type of cell death that plays an important role in predicting prognosis and immunoregulation in cancers. However, the pyroptosis-related gene signature for prognosis and immune infiltration prediction has not been studied in breast cancer (BC).

Methods

The Gene Expression Omnibus (GEO) and Cancer Genome Atlas (TCGA) databases were used to obtain the expression and clinical data of genes. 52 pyroptosis-related genes were obtained from TCGA-BC and estimated differentially expressed genes by the limma program. To categorize the molecular subtypes of pyroptosis-related genes, the ConsensusClusterPlus tool was utilized. Cox and Lasso regression analyses were used to create a signature. TCGA-BC dataset as the training set and the GSE37751 test set for risk research. Gene set enrichment analysis (GSEA) was used to conduct KEGG and GO studies of subtype groups. We also used the ssGSEA approach in the GSVA package to calculate the risk score of immune cells. Finally, pyroptosis-related genes in BC were validated using qPCR and immunohistochemical assays. Clone formation and EDU assays were used to explore the ability of signature genes to regulate the proliferation of BC cells.

Results

Based on pyroptosis-related genes, the C1 and C2 subtypes were obtained. Survival analysis results showed that the C2 group had a better prognosis. Then, a three-gene signature (APOBEC3D, TNFRSF14, and RAC2) were created by Lasso regression analysis, which had a good prediction effect in the TCGA-BC and GSE37751 datasets. Our nomogram has a fair degree of accuracy in predicting the survival rates of BC patients. The pyroptosis-related signature has a good predictive effect in evaluating the tumour microenvironment score, 28 types of immune cells and response to immune checkpoint therapy. Finally, qPCR and immunohistochemistry staining results indicated that APOBEC3D, TNFRSF14, and RAC2 expression in BC tissues was low. The results of clone formation and EdU assays showed that high expression of signature genes inhibited the proliferation ability of BC cells.

Conclusions

Based on pyroptosis-related genes (APOBEC3D, TNFRSF14, and RAC2), we built a novel prognostic molecular model for BC that might be used to assess prognostic risk and immune infiltration in BC patients. These signature genes are also tumor suppressor genes and may serve as potential targets for BC.