Theranostics 2021; 11(19):9415-9430. doi:10.7150/thno.59533 This issue

Research Paper

Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform

Fuqiang Xing1,2,3,6, Yu-Cheng Liu1, Shigao Huang1, Xueying Lyu1,2, Sek Man Su1,2, Un In Chan1,2, Pei-Chun Wu1, Yinghan Yan1, Nana Ai4, Jianjie Li1,2, Ming Zhao1,2, Barani Kumar Rajendran1,2, Jianlin Liu1,2, Fangyuan Shao1,2, Heng Sun1,2,3, Tak Kan Choi1,2, Wenli Zhu5, Guanghui Luo5, Shuiming Liu5, De Li Xu5, Kin Long Chan5, Qi Zhao1,2,3, Kai Miao1,2,3, Kathy Qian Luo1,2,3, Wei Ge3,4, Xiaoling Xu1,2,3, Guanyu Wang6✉, Tzu-Ming Liu1,2,3✉, Chu-Xia Deng1,2,3✉

1. Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China.
2. Centre for Precision Medicine Research and Training, Faculty of health Sciences, University of Macau, Macau SAR, China.
3. MOE Frontier Science Centre for Precision Oncology, University of Macau, Macau SAR, China.
4. Centre of Reproduction, Development and Aging, Faculty of Health Sciences, University of Macau, Macau SAR, China.
5. Kiang Wu Hospital, Macau SAR, China.
6. Department of Biology, School of Life Sciences & Guangdong Provincial Key Laboratory of Computational Science and Material Design, Southern University of Science and Technology, Shenzhen, China.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Xing F, Liu YC, Huang S, Lyu X, Su SM, Chan UI, Wu PC, Yan Y, Ai N, Li J, Zhao M, Rajendran BK, Liu J, Shao F, Sun H, Choi TK, Zhu W, Luo G, Liu S, Xu DL, Chan KL, Zhao Q, Miao K, Luo KQ, Ge W, Xu X, Wang G, Liu TM, Deng CX. Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform. Theranostics 2021; 11(19):9415-9430. doi:10.7150/thno.59533. Available from https://www.thno.org/v11p9415.htm

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Abstract

Graphic abstract

The feasibility of personalized medicine for cancer treatment is largely hampered by costly, labor-intensive and time-consuming models for drug discovery. Herein, establishing new pre-clinical models to tackle these issues for personalized medicine is urgently demanded.

Methods: We established a three-dimensional tumor slice culture (3D-TSC) platform incorporating label-free techniques for time-course experiments to predict anti-cancer drug efficacy and validated the 3D-TSC model by multiphoton fluorescence microscopy, RNA sequence analysis, histochemical and histological analysis.

Results: Using time-lapse imaging of the apoptotic reporter sensor C3 (C3), we performed cell-based high-throughput drug screening and shortlisted high-efficacy drugs to screen murine and human 3D-TSCs, which validate effective candidates within 7 days of surgery. Histological and RNA sequence analyses demonstrated that 3D-TSCs accurately preserved immune components of the original tumor, which enables the successful achievement of immune checkpoint blockade assays with antibodies against PD-1 and/or PD-L1. Label-free multiphoton fluorescence imaging revealed that 3D-TSCs exhibit lipofuscin autofluorescence features in the time-course monitoring of drug response and efficacy.

Conclusion: This technology accelerates precision anti-cancer therapy by providing a cheap, fast, and easy platform for anti-cancer drug discovery.

Keywords: 3D tumor slice culture, apoptosis, FRET technique, label-free, personalized medicine