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利用基于Transformer的注意力机制理解联合放疗与免疫治疗中的PULSAR效应。

Understanding the PULSAR effect in combined radiotherapy and immunotherapy using transformer-based attention mechanisms.

作者信息

Peng Hao, Moore Casey, Saha Debabrata, Jiang Steve, Timmerman Robert

机构信息

Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States.

Medical Artificial Intelligence and Automation Laboratory, University of Texas Southwestern Medical Center, Dallas, TX, United States.

出版信息

Front Oncol. 2024 Dec 2;14:1497351. doi: 10.3389/fonc.2024.1497351. eCollection 2024.

Abstract

PULSAR (personalized, ultra-fractionated stereotactic adaptive radiotherapy) is the adaptation of stereotactic ablative radiotherapy towards personalized cancer management. It has potential to harness the synergy between radiation therapy and immunotherapy, such as immune checkpoint inhibitors to amplify the anti-tumor immune response. For the first time, we applied a transformer-based attention mechanism to investigate the underlying interactions between combined PULSAR and PD-L1 blockade immunotherapy, based on the preliminary experimental results of a murine cancer model (Lewis Lung Carcinoma, LLC). The radiation and administration of α-PD-L1 were viewed as two external stimulation signals occurring in a temporal sequence. Our study demonstrates the utility of a transformer model in 1) predicting tumor changes in response to specific treatment schemes, and 2) generating self-attention and cross-attention maps. The cross-attention maps serve as a biological representation of the semantic similarity between source and target sentences in neural translation, offering insights into the causal relationships of the PULSAR effect. Our model offers a unique perspective with the potential to enhance the understanding of the temporal dependencies of the PULSAR effect on time, dose, and T cell dynamics. In a broader context, our proposed framework offers the potential to explore varying intervals and doses for subsequent treatments while monitoring the biological parameters impacted by these perturbations. This approach can lead to more personalized and rational radiation or drug interactions.

摘要

脉冲式放疗(个性化、超分割立体定向自适应放疗)是将立体定向消融放疗应用于个性化癌症管理。它有潜力利用放疗与免疫疗法(如免疫检查点抑制剂)之间的协同作用来增强抗肿瘤免疫反应。基于小鼠癌症模型(刘易斯肺癌,LLC)的初步实验结果,我们首次应用基于Transformer的注意力机制来研究联合脉冲式放疗与程序性死亡受体配体1(PD-L1)阻断免疫疗法之间的潜在相互作用。放疗和α-PD-L1给药被视为按时间顺序出现的两个外部刺激信号。我们的研究证明了Transformer模型在以下两方面的效用:1)预测肿瘤对特定治疗方案的反应变化;2)生成自注意力和交叉注意力图。交叉注意力图作为神经翻译中源句和目标句语义相似性的生物学表示,为脉冲式放疗效应的因果关系提供了见解。我们的模型提供了一个独特的视角,有可能增强对脉冲式放疗效应在时间、剂量和T细胞动力学方面的时间依赖性的理解。在更广泛的背景下,我们提出的框架有可能在监测受这些扰动影响的生物学参数的同时,探索后续治疗的不同间隔和剂量。这种方法可以导致更个性化和合理的放疗或药物相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db27/11647037/48d7055ad2e1/fonc-14-1497351-g001.jpg

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