Multiplexed molecular imaging with surface enhanced resonance Raman scattering nanoprobes reveals immunotherapy response in mice via multichannel image segmentation.
Multiplexed molecular imaging with surface enhanced resonance Raman scattering nanoprobes reveals immunotherapy response in mice via multichannel image segmentation.
复制标题
表面增强共振拉曼散射纳米探针的多路分子成像通过多通道图像分割揭示了小鼠免疫治疗的反应。
DOI：
10.1039/d2nh00331g
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发表时间：
2022-11-21
影响因子：
9.7
通讯作者：
中科院分区：
文献类型：
--
作者：
可视化肿瘤内多种特异性分子标志物的存在和分布可以揭示其微环境的组成，为诊断提供信息，对患者进行分层并指导治疗。使用多个分子靶向表面增强拉曼散射（Sers）纳米探针的拉曼成像可以帮助临床前研究新兴的癌症治疗或实现个性化治疗评估。在这里，我们报告了一种使用Sers纳米探针和机器学习（ML）进行多重成像的综合策略，以监测荷瘤小鼠中免疫检查点阻断（ICB）的早期影响。我们使用抗体功能化的Sers纳米探针同时可视化7+1免疫治疗相关的靶标。对复用图像进行光谱解析，然后基于未混合的信号在空间上分割成超像素。超像素被用于训练ML模型，成功地将小鼠分类为治疗组和未治疗组，并识别出对治疗有不同反应的肿瘤区域。这种方法可以帮助预测肿瘤的治疗效果，并确定肿瘤变异性和治疗耐药性的区域。
Visualizing the presence and distribution of multiple specific molecular markers within a tumor can reveal the composition of its microenvironment, inform diagnosis, stratify patients, and guide treatment. Raman imaging with multiple molecularly-targeted surface enhanced Raman scattering (SERS) nanoprobes could help investigate emerging cancer treatments preclinically or enable personalized treatment assessment. Here, we report a comprehensive strategy for multiplexed imaging using SERS nanoprobes and machine learning (ML) to monitor the early effects of immune checkpoint blockade (ICB) in tumor-bearing mice. We used antibody-functionalized SERS nanoprobes to visualize 7+1 immunotherapy-related targets simultaneously. The multiplexed images were spectrally resolved and then spatially segmented into superpixels based on the unmixed signals. The superpixels were used to train ML models, leading to the successful classification of mice into treated and untreated groups, and identifying tumor regions with variable responses to treatment. This method may help predict treatment efficacy in tumors and identify areas of tumor variability and therapy resistance.
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