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BACKGROUND: Breast cancer accounts for over 1.8 million new cases worldwide annually, and prompt diagnosis and treatment are imperative to prevent mortality. Necroptosis, a form of programmed cell death, is thought to be a critical pathway for cancer cell apoptosis, yet, its relationship with breast cancer progression and molecular mechanisms remains largely unexplored. OBJECTIVES: Our study aims to investigate the molecular characteristics and clinical prognostic value of necroptosis-related genes in breast cancer using a comprehensive approach that involves integrated bioinformatics analysis along with drug sensitivity assessment. METHODS: Transcriptional, clinical, and tumor mutation burden (TMB) data related to breast cancer from the TCGA and GEO databases were integrated, and the necroptosis gene set was downloaded from the GSEA website for analysis. The screening conditions were set as adjusted P<0.05 and |log2FC(fold change)|>0.585 to screen for differential expression genes related to breast cancer necroptosis. Survival prognosis analysis was conducted on breast cancer necroptosis genes. Further analysis was conducted on prognosis-related necroptosis genes, including immune infiltration analysis and GO/KEGG enrichment analysis, to explore the potential biological functions and signaling pathway mechanisms of breast cancer necroptosis genes. Drug sensitivity screening was conducted on the prognosis-related necroptosis to identify potential drugs that target the promotion of necroptosis gene expression, and ultimately, single-gene analysis was performed on the core target genes obtained. RESULTS: Through integrated bioinformatics analysis, 29 differentially expressed mRNAs related to BRCA-Necroptosis were identified, including 18 upregulated mRNAs and 11 downregulated mRNAs. In addition, single-factor analysis of differential genes showed that the expression of HSPA4, PLK1, TNFRSF1B, FLT3, and LEF1 was closely related to BRCA survival prognosis. Based on the expression of these genes, a breast cancer prognosis model was constructed, and it was found that the area under the curve (AUC) of the curve of the risk genes for necroptosis was the largest, indicating that these genes have a certain clinical predictive significance for the occurrence and prognosis of BRCA. Additionally, there were significant differences in clinical characteristics of BRCA patients with different necroptosis gene expressions. Furthermore, GSVA and immune infiltration analysis revealed that Necroptosis-DEGs mainly affect the occurrence and progression of BRCA by participating in immune functions such as APC co-inhibition, APC co-stimulation, CCR, checkpoint, as well as infiltrating immune cells such as B cells naive, plasma cells, and T cells CD8. Moreover, the necroptosis gene group column chart indicated a 1-year survival rate of 0.979, a 3-year survival rate of 0.883, and a 5-year survival rate of 0.774. The necroptosis gene group and column chart are important indicators for evaluating BRCA prognosis. Finally, drug sensitivity screening of BRCA-Necroptosis genes showed that compounds such as A-770041, AC220, AP-24534, Bexarotene, and BMS-509744 have certain effects as potential targeted drugs for the treatment of BRCA necroptosis genes. CONCLUSION: Necroptosis genes are implicated in the pathogenesis and progression of breast cancer and are thought to impact the prognosis and response to drug treatments in individuals with BRCA. Consequently, understanding the role of these genes in breast cancer may aid in identifying more precise and efficacious therapeutic targets.
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OBJECTIVE: Accurately predicting nipple-areola complex (NAC) involvement in breast cancer is essential for identifying eligible patients for a nipple-sparing mastectomy. This study was aimed at developing a pre-operative nomogram for NAC involvement in breast cancer using conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). METHODS: All patients with primary breast cancer confirmed by pre-operative biopsy underwent US and CEUS examinations. Post-operative pathology was used as the gold standard in assessing NAC involvement. Lasso regression was used to select the predictors most associated with NAC involvement. A nomogram was constructed to calculate the diagnostic efficacy. The data were internally verified with 500 bootstrapped replications, and a calibration curve was generated to validate the predictive capability. RESULTS: Seventy-six patients with primary breast cancer were included in this study, which included 16 patients (21.1%) with NAC involvement and 60 patients (78.9%) without NAC involvement. Among the 23 features of US and CEUS, Lasso regression selected one US feature and two CEUS features, namely, ductal echo extending from the lesion, ductal enhancement extending to the nipple and focal nipple enhancement. A nomogram was constructed, and the results revealed that the area under the curve, sensitivity, specificity and accuracy were 0.891, 81.3%, 86.7% and 85.5%, respectively. The calibration curve exhibited good consistency between the predicted probability and the actual probability. CONCLUSION: The nomogram developed based on US and CEUS had good performance in predicting NAC involvement in breast cancer before surgery, which may facilitate the selection of suitable patients for NAC preservation with greater oncological safety.
