The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cells. A recent study by Park and colleagues titled "A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors," epitomizes this intersection by leveraging an interpretable deep learning model grounded in a comprehensive map of multiprotein assemblies in cancer, known as Nested Systems in Tumors (NeST). This study not only elucidates mechanisms underlying the response to CDK4/6 inhibitors in breast cancer therapy but also highlights the critical role of model interpretability leading to new mechanistic insights.

中文翻译：

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人工智能如何揭示癌症药物反应的复杂网络

精准医学和人工智能 (AI) 的交叉对癌症治疗具有深远的影响，有可能显着增进我们对基于肿瘤细胞复杂结构的药物反应的理解。 Park 及其同事最近进行的一项题为“肿瘤细胞结构的深度学习模型阐明了对 CDK4/6 抑制剂的反应和耐药性”的研究，通过利用基于癌症多蛋白组装综合图谱的可解释深度学习模型来概括这种交叉点，已知作为肿瘤嵌套系统（NeST）。这项研究不仅阐明了乳腺癌治疗中 CDK4/6 抑制剂反应的潜在机制，还强调了模型可解释性的关键作用，从而获得新的机制见解。