Background: Breast cancer (BC), the leading cause of cancer-related deaths among women, remains a serious threat to human health worldwide. The biological function and prognostic value of disulfidptosis as a novel strategy for BC treatment via induction of cell death remain unknown.Methods: Gene mutations and copy number variations (CNVs) in 10 disulfidptosis genes were evaluated. Differential expression, prognostic, and univariate Cox analyses were then performed for 10 genes, and BC-specific disulfidptosis-related genes (DRGs) were screened. Unsupervised consensus clustering was used to identify different expression clusters. In addition, we screened the differentially expressed genes (DEGs) among different expression clusters and identified hub genes. Moreover, the expression level of DEGs was detected by RT-qPCR in cellular level. Finally, we used the least absolute shrinkage and selection operator (LASSO) regression algorithm to establish a prognostic feature based on DEGs, and verified the accuracy and sensitivity of its prediction through prognostic analysis and subject operating characteristic curve analysis. The correlation of the signature with the tumor immune microenvironment and tumor stemness was analyzed.Results: Disulfidptosis genes showed significant CNVs. Two clusters were identified based on three DRGs (DNUFS1, LRPPRC, SLC7A11). Cluster A was found to be associated with better survival outcomes(p < 0.05) and higher levels of immune cell infiltration(p < 0.05). A prognostic signature of four disulfidptosis-related DEGs (KIF21A, APOD, ALOX15B, ELOVL2) was developed by LASSO regression analysis. The signature showed a good prediction ability. In addition, the prognostic signature in this study were strongly related to the tumor microenvironment (TME), tumor immune cell infiltration, tumor mutation burden (TMB), tumor stemness, and drug sensitivity.Conclusion: The prognostic signature we constructed based on disulfidptosis-DEGs is a good predictor of prognosis in patients with BC. This prognostic signature is closely related to TME, and its potential correlation provides clues for further studies.

Background: The oncogenic drivers of triple-negative breast cancer (TNBC), which is characterized by worst prognosis compared with other subtypes, are poorly understood. Although next-generation sequencing technology has facilitated identifying potential targets, few of the findings have been translated into daily clinical practice. The present study is aimed to explore ZNF703 (Zinc finger 703) function and its underlying mechanism in TNBC. Methods: ZNF703 expressions in tissue microarray were retrospectively examined by immunohistochemistry. The cell proliferation by SRB assay and colony formation assay, as well as cell cycle distribution by flow cytometry were assessed. The protein levels associated with possible underlying molecular mechanisms were evaluated by western blotting. Kaplan-Meier analysis was used to plot survival analysis. Results: Our data suggest that ZNF703 expressed in 34.2% of triple-negative human breast tumors by immunohistochemistry. In vitro, ZNF703 knockdown had potent inhibitory effects on TNBC cell proliferation and cell cycle, with cyclin D1, CDK4, CDK6, and E2F1 downregulated, while Rb1 upregulated. Moreover, Kaplan-Meier analysis showed that high mRNA expression of ZNF703 was correlated to worse overall survival (HR for high expression was 3.04; 95% CI, 1.22 to 7.57, P = 0.017). Conclusions: Taken together, the results identified that targeting ZNF703 contributed to the anti-proliferative effects in TNBC cells, due to induced G1-phase arrest. This study is the first to identify ZNF703 as a potentially important protein that is involved in TNBC progression.

Breast cancer (BC), with complex tumorigenesis and progression, remains the most common malignancy in women. We aimed to explore some novel and significant genes with unfavorable prognoses and potential pathways involved in BC initiation and progression via bioinformatics methods. BC tissue-specific microarray datasets of GSE42568, GSE45827 and GSE54002, which included a total of 651 BC tissues and 44 normal breast tissues, were obtained from the Gene Expression Omnibus (GEO) database, and 124 differentially expressed genes (DEGs) were identified between BC tissues and normal breast tissues via R software and an online Venn diagram tool. Database for Annotation, Visualization and Integration Discovery (DAVID) software showed that 65 upregulated DEGs were mainly enriched in the regulation of the cell cycle, and Search Tool for the Retrieval of Interacting Genes (STRING) software identified the 39 closest associated upregulated DEGs in protein-protein interactions (PPIs), which validated the high expression of genes in BC tissues by the Gene Expression Profiling Interactive Analysis (GEPIA) tool. In addition, 36 out of 39 BC patients showed significantly worse outcomes by Kaplan-Meier plotter (KM plotter), and an additional Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that seven genes (cyclin E2 (CCNE2), cyclin B1 (CCNB1), cyclin B2 (CCNB2), mitotic checkpoint serine/threonine kinase B (BUB1B), dual-specificity protein kinase (TTK), cell division cycle 20 (CDC20), and pituitary tumor transforming gene 1 (PTTG1)) were markedly enriched in the cell cycle pathway. Analysis of the clinicopathological characteristics of hub genes revealed that seven cell cycle-related genes (CCRGs) were significantly highly expressed in four BC subtypes (luminal A, luminal B, HER2-positive and triple-negative (TNBC)), and except for the CCNE2 gene, high expression levels were significantly associated with tumor pathological grade and stage and metastatic events of BC. Furthermore, genetic mutation analysis indicated that genetic alterations of CCRGs could also significantly affect BC patients' prognosis. A quantitative real-time polymerase chain reaction (qRT-PCR) assay found that the seven CCRGs were significantly differentially expressed in BC cell lines. Integration of published multilevel expression data and a bioinformatics computational approach were used to predict and construct a regulation mechanism: a transcription factor (TF)-microRNA (miRNA)-messenger RNA (mRNA) regulation network. The present work is the first to construct a regulatory network of TF-miRNA-mRNA in BC for CCRGs and provides new insights into the molecular mechanism of BC.

Background: Our study aims to investigate the clinicopathological characteristics and survival outcomes of mucinous breast cancer (MBC), and explore the effect of histology type on the breast cancer-specific survival (BCSS) by different subtypes. Methods: we identified 7,083 patients who were diagnosed with MBC and 248,751 with infiltrating ductal carcinoma (IDC) by using the Surveillance, Epidemiology and End Results (SEER) database. The propensity score matching was used to match baseline characteristics among MBC and IDC, and multivariable cox proportional hazards models were used to analyze the relationship between histology type stratified by subtype and BCSS. Results: MBC patients were associated with a fewer nodal involvement, lower grade, earlier stage, more estrogen receptor (ER) or progesterone receptor (PR) positive, and more favorable prognosis compared to the overall IDC population. After 1:1 matching of MBC with IDC by other factors, we found that MBC patients presented better prognosis than the Matched IDC for BCSS. Analysis among ER+PR+ subgroup revealed that MBC patients was significantly better than that Matched IDC patients for BCSS (HR =0.78, 95% CI, 0.63–0.96). However, the survival analysis in the ER+PR− or ER−PR− subgroups suggested that no significant difference was seen between MBC patients and matched IDC patients for BCSS. Conclusions: Our findings support that MBC seems to be an independent factor for the better prognosis for breast cancer patients with ER+PR+ breast cancer but not in those with ER+PR− or ER−PR− disease.

Introduction: Recently, the significant regulatory effects of lncRNAs on the oncogenesis and growth of tumor have been demonstrated by an increasing number of research projects. A previous study showed that LL22NC03-N64E9.1 could promote the development of colorectal cancer, especially via enhanced cell proliferation. Similarly, this lncRNA should have comparable functions in breast cancer (BC), which requires in-depth investigation. Therefore, this study was designed to explore the correlation of LL22NC03-N64E9.1 with BC. Methods: qRT-PCR was used to assess the relative expression of LL22NC03-N64E9.1 in BC tissues. Cell viability examination and colony formation experiments were performed to investigate the role of LL22NC03-N64E9.1 in BC cell’s proliferation. Transwell assays were used to explore the effects of LL22NC03-N64E9.1 on BC cell’s migration. RNA immunoprecipitation, chromosome immunoprecipitation assay and rescue experiments were performed to analyze the association of LL22NC03-N64E9.1 with target proteins and genes in BC cells. Results: We identified that LL22NC03-N64E9.1 is an oncogene, upregulated in BC, which was verified in a cohort of 48 pairs of BC tissues. Based on the loss-of-function experiments, silencing LL22NC03-N64E9.1 expression significantly inhibited malignancy progression. In terms of the mechanism, LL22NC03-N64E9.1 acted on the enhancer of zeste homolog 2 (EZH2) by direct binding, which promoted BC cell growth. Furthermore, in the promoters of KLF2, the trimethylation of H3K27 could be regulated by LL22NC03-N64E9.1 as the mediator. Conclusion: Relying on the LL22NC03-N64E9.1/EZH2/KLF2 pathway, the lncRNA LL22NC03-N64E9.1 was significantly associated with BC development and could, therefore, be a potential therapeutic target to block BC growth.