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增强对多柔比星在乳腺癌治疗中的影响的理解。

Enhancing the understanding of doxorubicin's therapeutic impact in breast cancer.

机构信息

First Clinical Medical College, Guangdong Medical University, Zhanjiang, 524023, Guangdong, China.

General Surgery Day Ward, Department of General Surgery, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, 610000, China.

出版信息

Med Oncol. 2024 Nov 15;42(1):3. doi: 10.1007/s12032-024-02565-5.

Abstract

In this letter, we extend our commendation to the authors of the study titled "Doxorubicin downregulates cell cycle regulatory hub genes in breast cancer cells" for their insightful work. However, we also propose several areas for potential enhancement. We identify the study's limitations, such as a focus on the effects of doxorubicin treatment over a limited 48-h period, potential biases due to algorithmic and database constraints, and the absence of in vivo model validation. We advocate for the application of machine learning to identify biomarkers, the use of molecular docking for target selection, and the incorporation of animal models and patient-derived samples to bolster the study's clinical significance. Our recommendations are intended to refine the research and deepen the comprehension of doxorubicin's therapeutic role in the treatment of breast cancer.

摘要

在这封信中,我们对题为“多柔比星下调乳腺癌细胞周期调控枢纽基因”的研究作者表示赞赏,他们的工作很有见地。然而,我们也提出了一些潜在的改进方向。我们确定了研究的局限性,例如仅关注多柔比星治疗在有限的 48 小时内的影响、由于算法和数据库限制可能产生的偏差,以及缺乏体内模型验证。我们主张应用机器学习来识别生物标志物,使用分子对接进行靶标选择,并结合动物模型和患者来源样本,以增强研究的临床意义。我们的建议旨在完善研究,并加深对多柔比星在乳腺癌治疗中治疗作用的理解。

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