Zuo Zanwen, Wen Ruihua, Jing Shuang, Chen Xianghui, Liu Ruisang, Xue Jianping, Zhang Lei, Li Qizhang
Innovative Drug R&D Center, Innovative Drug Research Center, College of Life Sciences, Huaibei Normal University, Huaibei 235000, China.
School of Medicine, Shanghai University, Shanghai 200444, China.
Pharmaceuticals (Basel). 2024 Dec 16;17(12):1695. doi: 10.3390/ph17121695.
: Breast cancer in women is the most commonly diagnosed and most malignant tumor. Although luminal A breast cancer (LumA) has a relatively better prognosis, it still has a persistent pattern of recurrence. (Curtis) P. Karst. is a kind of traditional Chinese medicine and has antitumor effects. In this study, we aimed to identify the genes relevant to prognosis, find novel targets, and investigate the function of the bioactive protein from , called FIP-glu, in improving prognosis. : Gene expression data and clinical information of LumA breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Using bioinformatics methods, a predictive risk model was constructed to predict the prognosis for each patient. The cell counting kit-8 (CCK8) and clone formation assays were used to validate gene function. The ability of FIP-glu to regulate RNA levels of risk genes was validated. : Six risk genes (slit-roundabout GTPase-activating protein 2 (SRGAP2), solute carrier family 35 member 2 (SLC35A2), sequence similarity 114 member A1 (FAM114A1), tumor protein P53-inducible protein 11 (TP53I11), transmembrane protein 63C (TMEM63C), and polymeric immunoglobulin receptor (PIGR)) were identified, and a prognostic model was constructed. The prognosis was worse in the high-risk group and better in the low-risk group. The receiver operating characteristic (ROC) curve confirmed the model's accuracy. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the differentially expressed genes (DEGs) between the high- and low-risk groups were significantly enriched in the immune responses. TMEM63C could promote tumor viability, growth, and proliferation in vitro. FIP-glu significantly regulated these risk genes, and attenuated the promoting effect of TMEM63C in breast cancer cells. : SRGAP2, SLC35A2, FAM114A1, TP53I11, TMEM63C, and PIGR were identified as the potential risk genes for predicting the prognosis of patients. TMEM63C could be a potential novel therapeutic target. Moreover, FIP-glu was a promising drug for improving the prognosis of LumA breast cancer.
女性乳腺癌是最常被诊断出且恶性程度最高的肿瘤。尽管管腔A型乳腺癌(LumA)预后相对较好,但仍存在持续的复发模式。(柯蒂斯)P. 卡斯特是一种中药,具有抗肿瘤作用。在本研究中,我们旨在鉴定与预后相关的基因,寻找新的靶点,并研究来自[具体来源未明确]的生物活性蛋白FIP - glu在改善预后方面的功能。:从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)下载LumA乳腺癌患者的基因表达数据和临床信息。使用生物信息学方法构建预测风险模型以预测每位患者的预后。采用细胞计数试剂盒 - 8(CCK8)和克隆形成试验验证基因功能。验证了FIP - glu调节风险基因RNA水平的能力。:鉴定出六个风险基因(缝隙 - 环绕型GTP酶激活蛋白2(SRGAP2)、溶质载体家族35成员2(SLC35A2)、序列相似性114成员A1(FAM114A1)、肿瘤蛋白P53诱导蛋白11(TP53I11)、跨膜蛋白63C(TMEM63C)和多聚免疫球蛋白受体(PIGR)),并构建了预后模型。高风险组预后较差,低风险组预后较好。受试者工作特征(ROC)曲线证实了模型的准确性。基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析表明,高风险组和低风险组之间的差异表达基因(DEG)在免疫反应中显著富集。TMEM63C在体外可促进肿瘤的活力、生长和增殖。FIP - glu显著调节这些风险基因,并减弱TMEM63C对乳腺癌细胞的促进作用。:SRGAP2、SLC35A2、FAM114A1、TP53I11、TMEM63C和PIGR被确定为预测患者预后的潜在风险基因。TMEM63C可能是一个潜在的新治疗靶点。此外,FIP - glu是改善LumA乳腺癌预后的一种有前景的药物。