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基于深度学习的癌症免疫疗法筛选的微流控技术。

Microfluidics guided by deep learning for cancer immunotherapy screening.

机构信息

Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN 47405.

Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202.

出版信息

Proc Natl Acad Sci U S A. 2022 Nov 16;119(46):e2214569119. doi: 10.1073/pnas.2214569119. Epub 2022 Nov 7.


DOI:10.1073/pnas.2214569119
PMID:36343225
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9674214/
Abstract

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of the T cells to penetrate the tumor stroma, thereby significantly limiting the development of effective treatments for solid tumors. Here, we present an automated high-throughput microfluidic platform for simultaneous tracking of the dynamics of T cell infiltration and cytotoxicity within the 3D tumor cultures with a tunable stromal makeup. By recourse to a clinical tumor-infiltrating lymphocyte (TIL) score analyzer, which is based on a clinical data-driven deep learning method, our platform can evaluate the efficacy of each treatment based on the scoring of T cell infiltration patterns. By screening a drug library using this technology, we identified an epigenetic drug (lysine-specific histone demethylase 1 inhibitor, LSD1i) that effectively promoted T cell tumor infiltration and enhanced treatment efficacy in combination with an immune checkpoint inhibitor (anti-PD1) in vivo. We demonstrated an automated system and strategy for screening immunocyte-solid tumor interactions, enabling the discovery of immuno- and combination therapies.

摘要

免疫细胞浸润和细胞毒性在炎症和免疫治疗中都起着关键作用。然而,目前的癌症免疫治疗筛选方法忽略了 T 细胞穿透肿瘤基质的能力,从而极大地限制了针对实体瘤的有效治疗方法的发展。在这里,我们提出了一种自动化高通量微流控平台,用于同时跟踪具有可调基质组成的 3D 肿瘤培养物中 T 细胞浸润和细胞毒性的动力学。通过使用基于临床数据驱动的深度学习方法的临床肿瘤浸润淋巴细胞 (TIL) 评分分析器,我们的平台可以根据 T 细胞浸润模式的评分来评估每种治疗方法的疗效。通过使用该技术筛选药物库,我们发现了一种表观遗传药物(赖氨酸特异性组蛋白去甲基化酶 1 抑制剂,LSD1i),它可有效促进 T 细胞浸润肿瘤,并与免疫检查点抑制剂(抗 PD1)联合在体内增强治疗效果。我们展示了一种用于筛选免疫细胞-实体瘤相互作用的自动化系统和策略,从而能够发现免疫治疗和联合治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/b4c938b1c775/pnas.2214569119fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/97d11a20487c/pnas.2214569119fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/a90cd552f04c/pnas.2214569119fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/32367db1fddd/pnas.2214569119fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/99ec1d659f1b/pnas.2214569119fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/b4c938b1c775/pnas.2214569119fig05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/97d11a20487c/pnas.2214569119fig01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/a90cd552f04c/pnas.2214569119fig02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/32367db1fddd/pnas.2214569119fig03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/99ec1d659f1b/pnas.2214569119fig04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ce6/9674214/b4c938b1c775/pnas.2214569119fig05.jpg

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本文引用的文献

[1]
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Theranostics. 2022

[2]
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Adv Sci (Weinh). 2022-8

[3]
High-throughput automated organoid culture via stem-cell aggregation in microcavity arrays.

Nat Biomed Eng. 2020-6-8

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CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities.

Nature. 2020-3-11

[5]
The Dark Side of Fibroblasts: Cancer-Associated Fibroblasts as Mediators of Immunosuppression in the Tumor Microenvironment.

Front Immunol. 2019-8-2

[6]
Infiltration of CD8 T cells into tumor cell clusters in triple-negative breast cancer.

Proc Natl Acad Sci U S A. 2019-2-7

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Dissimilar patterns of tumor-infiltrating immune cells at the invasive tumor front and tumor center are associated with response to neoadjuvant chemotherapy in primary breast cancer.

BMC Cancer. 2019-2-4

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Genomic evolution of cancer models: perils and opportunities.

Nat Rev Cancer. 2019-2

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Nat Rev Genet. 2018-12

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Oncogene. 2018-8-15

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