Necroptosis of osteoblasts was induced by breast cancer cells in vitro

Inhibition of β2-adrenergic receptor regulates necroptosis in prostate cancer cell

As the malignant tumor with the highest incidence in male, prostate cancer poses a significant threat to the reproductive health of elderly men. Our previous studies have shown that promoting necroptosis of cancer cells can effectively inhibit cancer cell proliferation. This study includes lentivirus-mediated knockdown of β2AR which resulted in stable transfectants that exhibited an increased ability to form clones compared to that of the negative control group. In the protein and mRNA levels, necroptosis associated RIP and mixed lineage kinase domain-like (MLKL) were significantly higher in the treatment group than they were in the control group. Furthermore, cells treated with propranolol exhibited necrotic morphology as observed by transmission electron microscopy. The combination of β2AR suppression and necroptosis inhibitors resulted in a more potent suppression of cell proliferation compared to that observed in the control and negative control groups. Additionally, it elevated in the necrosis rate as determined by flow cytometry. Immunofluorescence staining revealed enhanced RIP and MLKL expression in the sh-β2AR group compared to levels in the negative control group. Co-immunoprecipitation experiments detected an interaction between β2AR and RIP. MLKL and RIPK3 levels were significantly higher in xenograft tumor sections from the sh-β2AR group compared to levels in the sh-NC group. To conclude, our research indicates the proliferation of PC-3 and DU-145 cprostate cancer cells can be suppressed by inhibiting β2AR, and this occurs through the RIP/MLKL-mediated pathway of necroptosis.

Necroptosis-related KLRB1 was a potent tumor suppressor and immunotherapy determinant in breast cancer

Breast cancer is a multifaceted and diverse illness that impacts millions of people globally. Identifying the underlying causes of BRCA and creating efficient treatment plans are urgent. Necroptosis is widely involved in cancer development. However, the specific roles of necroptosis in cancer immunotherapy of breast cancer have not been explored. In this study, we aim to establish the connection between necroptosis and immunotherapy in BRCA. TCGA, METABRIC, GSE103091, GSE159956, and GSE96058 were included for bioinformatics analysis. NMF and CoxBoost algorithms were used to develop the necroptosis-related patterns and model, respectively. A necroptosis-related model was developed and determined KLRB1 as a critical tumor suppressor by in vitro validation. The mutation characteristics, immune characteristics, and molecular functions of KLRB1 were explored. We further examined how necroptosis-related KLRB1 functions in BRCA as a powerful tumor suppressor and regulates the activity of macrophages by in vitro validation, including CCK8, EdU, and Transwell assays. KLRB1 was also revealed to be an immunotherapy determinant.

Prognosis analysis of necroptosis-related genes in colorectal cancer based on bioinformatic analysis

Background: Colorectal cancer (CRC) is one gastrointestinal malignancy, accounting for 10% of cancer diagnoses and cancer-related deaths worldwide each year. Therefore, it is urgent to identify genes involved in CRC predicting the prognosis.

Methods: CRC’s data were acquired from the Gene Expression Omnibus (GEO) database (GSE39582 and GSE41258 datasets) and The Cancer Genome Atlas (TCGA) database. The differentially expressed necroptosis-related genes (DENRGs) were sorted out between tumor and normal tissues. Univariate Cox regression analysis and least absolute shrinkage and selectionator operator (LASSO) analysis were applied to selected DENRGs concerning patients’ overall survival and to construct a prognostic biomarker. The effectiveness of this biomarker was assessed by the Kaplan–Meier curve and the receiver operating characteristic (ROC) analysis. The GSE39582 dataset was utilized as external validation for the prognostic signature. Moreover, using univariate and multivariate Cox regression analyses, independent prognostic factors were identified to construct a prognostic nomogram. Next, signaling pathways regulated by the signature were explored through the gene set enrichment analysis (GSEA). The single sample gene set enrichment analysis (ssGSEA) algorithm and tumor immune dysfunction and exclusion (TIDE) were used to explore immune correlation in the two groups, high-risk and low-risk ones. Finally, prognostic genes’ expression was examined in the GSE41258 dataset.

Results: In total, 27 DENRGs were filtered, and a necroptosis-related prognostic signature based on 6 DENRGs was constructed, which may better understand the overall survival (OS) of CRC. The Kaplan–Meier curve manifested the effectiveness of the prognostic signature, and the ROC curve showed the same result. In addition, univariate and multivariate Cox regression analyses revealed that age, pathology T, and risk score were independent prognostic factors, and a nomogram was established. Furthermore, the prognostic signature was most significantly associated with the apoptosis pathway. Meanwhile, 24 immune cells represented significant differences between two groups, like the activated B cell. Furthermore, 32 immune checkpoints, TIDE scores, PD-L1 scores, and T-cell exclusion scores were significantly different between the two groups. Finally, a 6-gene prognostic signature represented different expression levels between tumor and normal samples significantly in the GSE41258 dataset.

Conclusion: Our study established a signature including 6 genes and a prognostic nomogram that could significantly assess the prognosis of patients with CRC.