Mehmood Aamir, Li Rongpei, Kaushik Aman Chandra, Wei Dong-Qing
Department of Bioinformatics and Biostatistics, State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China.
Department of Bioinformatics and Biostatistics College of Life Sciences and Biotechnology, The State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District China, Shanghai, 200240 China.
In Silico Pharmacol. 2025 Jan 15;13(1):15. doi: 10.1007/s40203-024-00301-5. eCollection 2025.
Breast cancer (BC) remains a highly heterogeneous disease, complicating diagnosis and treatment. This study investigates the prognostic significance of Anillin () and Kinase Insert Domain Receptor () genes, focusing on their mutational and expression landscapes in BC using data from The Cancer Genome Atlas (TCGA). We found that high expression is strongly associated with poor overall survival, highlighting its potential as a robust prognostic marker. In contrast, , despite its higher mutation frequency, showed a less significant correlation with survival outcomes. Machine learning (ML) models incorporating transcriptional and translational data further supported prognostic value, demonstrating superior accuracy in survival stage prediction when both genes were analyzed together. Functional enrichment analysis revealed that is primarily involved in cell cycle regulation, while is linked to angiogenesis, suggesting that combined targeting of these pathways could enhance therapeutic efficacy. These findings underscore the potential of and as complementary biomarkers in BC prognosis and highlight the need for further validation in diverse cohorts.
The online version contains supplementary material available at 10.1007/s40203-024-00301-5.
乳腺癌（BC）仍然是一种高度异质性的疾病，使诊断和治疗变得复杂。本研究调查了膜收缩蛋白（Anillin）和激酶插入结构域受体（Kinase Insert Domain Receptor）基因的预后意义，利用来自癌症基因组图谱（TCGA）的数据重点研究它们在乳腺癌中的突变和表达情况。我们发现高Anillin表达与较差的总生存期密切相关，凸显了其作为一个可靠预后标志物的潜力。相比之下，Kinase Insert Domain Receptor尽管突变频率较高，但与生存结果的相关性较弱。纳入转录和翻译数据的机器学习（ML）模型进一步支持了Anillin的预后价值，当对这两个基因一起分析时，在生存阶段预测中显示出更高的准确性。功能富集分析表明，Anillin主要参与细胞周期调控，而Kinase Insert Domain Receptor与血管生成有关，这表明联合靶向这些途径可能会提高治疗效果。这些发现强调了Anillin和Kinase Insert Domain Receptor作为乳腺癌预后补充生物标志物的潜力，并突出了在不同队列中进一步验证的必要性。
在线版本包含可在10.1007/s40203-024-00301-5获取的补充材料。
