Androgen receptor (AR) is strong association with breast cancer (BRCA). We aimed to investigate the effect of the androgen receptor signaling pathway-related long non-coding RNAs (ARSP-related lncRNAs) on the process of subtype classification and the tumor microenvironment (TME) of breast cancer (BRCA). Our study screen ARSP-related lncRNAs for the construction of a risk model. The single-sample gene set enrichment analysis (ssGSEA) method was used to detect the differences between the immune responses generated by the patients belonging to the low- and high-risk groups. The relationship between the ARSP-related lncRNAs and TME was explored following the process of cluster analysis. The univariate Cox analysis and the Lasso regression analysis method was used to screen nine of these lncRNAs to develop a risk model. It was observed that risk score could function as an independent prognostic factor, affecting the prognoses of patients suffering from BRCA. The validity of the model was assessed by analyzing the generated calibration curves and a nomogram. Additionally, the effect of the risk score on the extent of immune cell infiltration realized in TME was explored. M2 macrophages correlated positively, whereas NK cells, CD4+ T cells, and naive B cells correlated negatively with the risk score. Results obtained using the cluster analysis indicated that immune scores correlated with clustered subtypes. Finally, the risk score and cluster subtypes were analyzed to study the sensitivity of the patients toward different drugs to identify the appropriate therapeutic agents. The prognoses of patients suffering from BRCA can be accurately predicted by ARSP-related lncRNAs.

Understanding the association of pyroptosis with tumor progression, prognosis and effect on immunotherapeutic response in breast cancer (BC) is limited. This study analysed forty pyroptosis-related genes to construct the pyroptosis score. Association of the pyroptosis score with the overall survival, clinical features, tumor mutation load, immune cell infiltration, and treatment sensitivity of patients with BC was analysed. Out of 983 BC samples, 304 (30.93%) had genetic alterations with the highest TP53 frequency. We identified three separate subtypes associated with pyroptosis action. These subtypes correlate with the clinicopathological characteristics, TME immune cell infiltration, and disease prognosis. Based on the expression levels of the pyroptosis genes, we divided the pyroptosis score into a high group and a low group. The immune-activated pyroptosis subtype had a higher score with a better prognosis. We also observed that the pyroptosis score correlates with the tumor mutation burden. The pyroptosis score and disease prognosis were directly proportional. A higher pyroptosis score indicated a better prognosis. Results suggest that the pyroptosis-related gene prognosis model is closely related to the immune cell infiltration of BC. The three pyroptosis subtypes associated with BC assist in accurately identifying the tumor subtype, the prognosis of immunotherapy drugs and the patient’s therapeutic response.

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.

Objective Efferocytosis, a process of apoptotic cell clearance, is implicated in the initiation and progression of breast cancer. This study aims to construct an efferocytosis-related genetic risk model to evaluate its prognostic value and its association with immune infiltration in breast cancer. Methods The expression patterns of efferocytosis-related genes in breast cancer were analyzed, followed by clustering analysis to explore their relationship with tumor immune infiltration across different subtypes. A risk model based on efferocytosis-related genes was developed to predict breast cancer prognosis and assess its correlation with immune infiltration. Using this model, the association between ALOX15B expression and breast cancer survival was evaluated. In Vitro Functional Assays, the biological role of ALOX15B in breast cancer progression was investigated using the following approaches: Cellular Proliferation: MTT assay, EdU incorporation assay, and colony formation assay were performed to assess proliferation in MCF7 and MDA-MB-231 cells. Transwell was used to quantify migratory and invasive. Flow cytometry was conducted to evaluate cell cycle distribution. Western blotting was performed to assess Epithelial-Mesenchymal Transition marker expression. Results Clustering analysis of the expression of efferocytosis-related genes in breast cancer, Cluster A had a good prognosis and was closely associated with immune cell infiltration. Functional enrichment analysis of the activation and adaptation of immune response in Cluster A clustering may be an important factor in improving breast cancer prognosis. In addition, an immune-related gene risk model was constructed, which was found to be a valid predictor of breast cancer prognosis. Finally, it was highlighted that the expression of ALOX15B inhibited the proliferation, movement, invasion, and DNA replication capability of breast cancer cells. The growth of breast cancer cells was also impeded by ALOX15B, which hindered cell division during the G1 phase. The expression of ALOX15B is associated with the sensitivity of a variety of chemotherapeutic agents. Conclusion Efferocytosis-related models can be used for the assessment of breast cancer prognosis, while the efferocytosis-related gene ALOX15B can affect the migration and invasive ability of breast cells.