Breast cancer promotes the expression of neurotransmitter receptor related gene groups and image simulation of prognosis model.

Breast cancer (BC), a prevalent and severe malignancy, detrimentally affects women globally. Its prognostic implications are profoundly influenced by gene expression patterns. This study retrieved 509 BCE-associated oncogenes and 1,012 neurotransmitter receptor-related genes from the GSEA and KEGG databases, intersecting to identify 98 relevant genes. Clinical and transcriptomic expression data related to BC were downloaded from the TCGA, and differential genes were identified based on an FDR value <0.05 & |log2FC| ≥ 0.585. Univariate analysis of these genes revealed that high expression of NSF and low expression of HRAS, KIF17, and RPS6KA1 are closely associated with BC survival prognosis. A prognostic model constructed for these four genes demonstrated significant prognostic relevance for BC-TCGA patients (P < 0.001). Subsequently, an immunofunctional analysis of the BC oncogene-neurotransmitter receptor-related gene cluster revealed the involvement of immune cells such as T cells CD8, T cells CD4 memory resting, and Macrophages M2. Further analysis indicated that immune functions were primarily concentrated in APC_co_inhibition, APC_co_stimulation, CCR, and Check-point, among others. Lastly, a prognostic nomogram model was established, and ROC curve analysis revealed that the nomogram is a vital indicator for assessing BC prognosis, with 1-year, 3-year, and 5-year survival rates of 0.981, 0.897, and 0.802, respectively. This model demonstrates high calibration, clinical utility, and predictive capability, promising to offer an effective preliminary tool for clinical diagnostics.

Research on the shared function of central neurons and breast cancer based on gene expression profile data mining: The role of EMID1 protein antibody expression.

In recent years, the incidence of breast cancer has gradually increased, and the research on it has become a hot spot in the scientific community. Central neurons play an important role in breast cancer. This study aims to explore the application of gene expression profile data mining in the study of shared function between central neurons and breast cancer, and focuses on the expression of EMID1 protein antibody. The study collected biomedical images and gene expression profile data of breast cancer patients. Then, we use image processing and analysis technology to extract and analyze features of biomedical images to obtain quantitative features of breast cancer. Gene expression profile data were preprocessed and analyzed to obtain information about breast cancer related genes. Integrating and fusing biomedical images and gene expression profile data, and exploring the sharing function between central neurons and breast cancer through data mining algorithms and statistical analysis methods. The results showed that the expression of EMID1 protein was high in breast cancer tissues, and the expression pattern was similar to that of central neurons. Further functional studies have shown that EMID1 protein is involved in the regulation of proliferation and invasion of breast cancer cells. By regulating the expression level of EMID1 protein, we observed that the proliferation and invasion ability of breast cancer cells were significantly affected. The research results show that through the comprehensive analysis of biomedical images and gene expression profile data, we found the sharing function between central neurons and breast cancer. The central neuronal cell marker genes EMID1 and GREB1L may be used as key biomarkers to regulate the pathogenesis of breast cancer and affect the occurrence and development of breast cancer.

Oncological safety of nipple-sparing mastectomy in young patients with breast cancer compared with conventional mastectomy.

Although nipple-sparing mastectomy (NSM) is being used more frequently, the oncological safety of NSM remains unclear, particularly in young patients (<35 years). The aim of the present study was to compare the rates of local recurrence (LR), disease-free survival (DFS) and overall survival (OS) in young patients with breast cancer who had undergone NSM or conventional mastectomy (CM). The clinicopathological data of young patients with stage 0-IIB breast cancer who had undergone NSM (163 cases) or CM (194 cases) between 2007 and 2016 were retrospectively analyzed. The log-rank test was used to analyze the differences in the LR, DFS and OS rates between the two groups and multivariate analysis was used to analyze the patient prognostic factors for DFS. The median follow-up time was 49 months. Patients who had undergone CM were more likely to exhibit stage II disease (68.4 vs. 58.3%; P=0.015) and positive lymph nodes (45.9 vs. 33.1%; P=0.014). In the NSM group, LR occurred in 7 (4.3%) cases, systemic recurrence in 15 (9.2%) cases and mortality in 9 (5.5%) cases. In the CM group, LR occurred in 6 (3.1%) cases, systemic recurrence in 27 (13.9%) cases and mortality in 15 (7.7%) cases. There were no statistical differences in the LR, DFS and OS rates between the two groups (P>0.05). Following adjustment for clinical stage, the LR and DFS rates between the two groups exhibited no significant differences. Analysis of the prognostic factors demonstrated that clinical stage, lymph node status, estrogen and progesterone receptor status and human epidermal growth factor receptor 2 status were associated with DFS (P<0.05). NSM is safe for young patients with early-stage breast cancer and provides patients with an improved cosmetic outcome. Furthermore, nipple-areola complex preservation does not increase the risk of recurrence.