Jiao Yangchi, Ji Fuqing, Hou Lan, Lv Yonggang, Zhang Juliang
Department of Thyroid, Breast and Vascular Surgery, Xijing Hospital, Air Force Military Medical University, Xi'an, Shaanxi, China.
Department of Thyroid Breast Surgery, Xi'an NO.3 Hospital, The Affiliated Hospital of Northwest University, Xi'an, Shaanxi, China.
Heliyon. 2024 Jan 19;10(3):e24777. doi: 10.1016/j.heliyon.2024.e24777. eCollection 2024 Feb 15.
Lactylation is implicated in various aspects of tumor biology, but its relation to breast cancer remains poorly understood. This study aimed to explore the roles of the lactylation-related genes in breast cancer and its association with the tumor microenvironment.
The expression and mutation patterns of lactylation-related genes were analyzed using the breast cancer data from The Cancer Genome Atlas (TCGA) database and GSE20685 datasets. Unsupervised clustering was used to identify two lactylation clusters. A lactylation-related gene signature was developed and validated using the training and validation cohorts. Immune cell infiltration and drug response were assessed.
We analyzed the mRNA expression, copy number variations, somatic mutations, and correlation networks of 22 lactylation-related genes in breast cancer tissues. We identified two distinct lactylation clusters with different survival outcomes and immune microenvironments. We further classified the patients into two gene subtypes based on lactylation clusters and identified a 7-gene signature for breast cancer survival prognosis. The prognostic score based on this signature demonstrated prognostic value and predicted the therapeutic response.
Lactylation-related genes play a critical role in breast cancer by influencing tumor growth, immune microenvironment, and drug response. This lactylation-related gene signature may serve as a prognostic marker and a potential therapeutic target for breast cancer.
乳酰化与肿瘤生物学的各个方面有关,但其与乳腺癌的关系仍知之甚少。本研究旨在探讨乳酰化相关基因在乳腺癌中的作用及其与肿瘤微环境的关联。
使用来自癌症基因组图谱(TCGA)数据库和GSE20685数据集的乳腺癌数据,分析乳酰化相关基因的表达和突变模式。采用无监督聚类来识别两个乳酰化簇。使用训练和验证队列开发并验证了一个乳酰化相关基因特征。评估免疫细胞浸润和药物反应。
我们分析了乳腺癌组织中22个乳酰化相关基因的mRNA表达、拷贝数变异、体细胞突变和相关网络。我们识别出两个具有不同生存结果和免疫微环境的不同乳酰化簇。我们根据乳酰化簇将患者进一步分为两种基因亚型,并确定了一个用于乳腺癌生存预后的7基因特征。基于该特征的预后评分显示出预后价值并预测了治疗反应。
乳酰化相关基因通过影响肿瘤生长、免疫微环境和药物反应在乳腺癌中发挥关键作用。这种乳酰化相关基因特征可能作为乳腺癌的预后标志物和潜在治疗靶点。