Department of Thyroid and Breast Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, China.
Department of Breast Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Front Immunol. 2024 Feb 2;15:1331841. doi: 10.3389/fimmu.2024.1331841. eCollection 2024.
Breast cancer (BRCA) is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Abnormal expression of genes is important in the occurrence and development of BRCA and may also affect the prognosis of patients. Although many BRCA prognosis model scores have been developed, they are only applicable to a limited number of disease subtypes. Our goal is to develop a new prognostic score that is more accurate and applicable to a wider range of BRCA patients.
BRCA patient data from The Cancer Genome Atlas database was used to identify breast cancer-related genes (BRGs). Differential expression analysis of BRGs was performed using the 'limma' package in R. Prognostic BRGs were identified using co-expression and univariate Cox analysis. A predictive model of four BRGs was established using Cox regression and the LASSO algorithm. Model performance was evaluated using K-M survival and receiver operating characteristic curve analysis. The predictive ability of the signature in immune microenvironment and immunotherapy was investigated. experiments validated POLQ function.
Our study identified a four-BRG prognostic signature that outperformed conventional clinicopathological characteristics in predicting survival outcomes in BRCA patients. The signature effectively stratified BRCA patients into high- and low-risk groups and showed potential in predicting the response to immunotherapy. Notably, significant differences were observed in immune cell abundance between the two groups. experiments demonstrated that POLQ knockdown significantly reduced the viability, proliferation, and invasion capacity of MDA-MB-231 or HCC1806 cells.
Our 4-BRG signature has the potential as an independent biomarker for predicting prognosis and treatment response in BRCA patients, complementing existing clinicopathological characteristics.
乳腺癌（BRCA）是女性常见的恶性肿瘤，其对免疫治疗的耐药性是一个主要挑战。基因的异常表达在 BRCA 的发生和发展中很重要，也可能影响患者的预后。尽管已经开发了许多 BRCA 预后模型评分，但它们仅适用于有限数量的疾病亚型。我们的目标是开发一种新的预后评分，该评分更准确，适用于更广泛的 BRCA 患者。
使用来自癌症基因组图谱数据库的 BRCA 患者数据来识别与乳腺癌相关的基因（BRGs）。使用 R 中的“limma”包进行 BRGs 的差异表达分析。使用共表达和单因素 Cox 分析鉴定预后 BRGs。使用 Cox 回归和 LASSO 算法建立四个 BRGs 的预测模型。使用 K-M 生存和接收者操作特征曲线分析评估模型性能。研究了signature 在免疫微环境和免疫治疗中的预测能力。进行了实验验证 POLQ 功能。
我们的研究确定了一个由四个 BRG 组成的预后签名，该签名在预测 BRCA 患者的生存结果方面优于传统的临床病理特征。该签名有效地将 BRCA 患者分为高风险和低风险组，并显示出在预测免疫治疗反应方面的潜力。值得注意的是，两组之间的免疫细胞丰度存在显著差异。实验表明，POLQ 敲低显著降低了 MDA-MB-231 或 HCC1806 细胞的活力、增殖和侵袭能力。
我们的 4-BRG 签名有可能成为预测 BRCA 患者预后和治疗反应的独立生物标志物，补充现有的临床病理特征。
