Table_2_Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer.docx

IntroductionBreast cancer (BC) is now the most common type of cancer in women. Disulfidptosis is a new regulation of cell death (RCD). RCD dysregulation is causally linked to cancer. However, the comprehensive relationship between disulfidptosis and BC remains unknown. This study aimed to explore the predictive value of disulfidptosis-related genes (DRGs) in BC and their relationship with the TME.MethodsThis study obtained 11 disulfidptosis genes (DGs) from previous research by Gan et al. RNA sequencing data of BC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases. First, we examined the effect of DG gene mutations and copy number changes on the overall survival of breast cancer samples. We then used the expression profile data of 11 DGs and survival data for consensus clustering, and BC patients were divided into two clusters. Survival analysis, gene set variation analysis (GSVA) and ss GSEA were used to compare the differences between them. Subsequently, DRGs were identified between the clusters used to perform Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a prognosis model. Finally, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. CCK-8 and a colony assay obtained by knocking down genes and gene sequencing were used to validate the model.ResultTwo DG clusters were identified based on the expression of 11DGs. Then, 225 DRGs were identified between them. RS, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-RS shows a better prognosis and higher immunotherapy response than high-RS. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. CCK-8 and colony assay obtained by knocking down genes have demonstrated that the knockdown of high-risk genes in the RS model significantly inhibited cell proliferation.DiscussionThis study elucidates the potential relationship between disulfidptosis-related genes and breast cancer and provides new guidance for treating breast cancer.

引言：乳腺癌（BC）现已成为女性中最常见的癌症类型。二硫键降解（Disulfidptosis）是细胞死亡（RCD）的新调节机制。RCD的失调与癌症的因果关系密切。然而，二硫键降解与乳腺癌之间的全面关系尚不明确。本研究旨在探讨二硫键降解相关基因（DRGs）在乳腺癌中的预测价值及其与肿瘤微环境（TME）的关系。方法：本研究从Gan等人的先前研究中获得了11个二硫键降解基因（DGs）。从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载了乳腺癌的RNA测序数据。首先，我们考察了DG基因突变和拷贝数变化对乳腺癌样本总生存期的影响。随后，我们利用11个DGs的表达谱数据和生存数据进行了共识聚类，将乳腺癌患者分为两个簇。通过生存分析、基因集变异分析（GSVA）和单样本GSEA比较了它们之间的差异。随后，在聚类中确定了DRGs，并使用Cox回归和最小绝对收缩和选择算子回归（LASSO）分析构建了预后模型。最后，分析了两种亚型的免疫细胞浸润模式、免疫治疗反应和药物敏感性。通过敲低基因和基因测序获得的CCK-8和集落实验用于验证模型。结果：基于11个DGs的表达，确定了两个DG簇。然后，在它们之间确定了225个DRGs。由六个基因组成的RS与生存、免疫细胞浸润、临床特征、免疫检查点、免疫治疗反应和药物敏感性显示出显著的相关性。低RS比高RS显示出更好的预后和更高的免疫治疗反应。使用特征和临床特征构建的完美稳定的诺模图可以预测每位患者的生存。敲低高风险基因的CCK-8和集落实验表明，RS模型中高风险基因的敲低显著抑制了细胞增殖。讨论：本研究阐明了二硫键降解相关基因与乳腺癌之间的潜在关系，并为乳腺癌治疗提供了新的指导。