Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer

Last updated: 05-01-2020

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Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer

Safety and feasibility of CRISPR-edited T cells in patients with refractory non-small-cell lung cancer
Phase I trials
Abstract
Clustered regularly interspaced short palindromic repeats (CRISPR)–Cas9 editing of immune checkpoint genes could improve the efficacy of T cell therapy, but the first necessary undertaking is to understand the safety and feasibility. Here, we report results from a first-in-human phase I clinical trial of CRISPR–Cas9 PD-1-edited T cells in patients with advanced non-small-cell lung cancer (ClinicalTrials.gov NCT02793856 ). Primary endpoints were safety and feasibility, and the secondary endpoint was efficacy. The exploratory objectives included tracking of edited T cells. All prespecified endpoints were met. PD-1-edited T cells were manufactured ex vivo by cotransfection using electroporation of Cas9 and single guide RNA plasmids. A total of 22 patients were enrolled; 17 had sufficient edited T cells for infusion, and 12 were able to receive treatment. All treatment-related adverse events were grade 1/2. Edited T cells were detectable in peripheral blood after infusion. The median progression-free survival was 7.7 weeks (95% confidence interval, 6.9 to 8.5 weeks) and median overall survival was 42.6 weeks (95% confidence interval, 10.3–74.9 weeks). The median mutation frequency of off-target events was 0.05% (range, 0–0.25%) at 18 candidate sites by next generation sequencing. We conclude that clinical application of CRISPR–Cas9 gene-edited T cells is generally safe and feasible. Future trials should use superior gene editing approaches to improve therapeutic efficacy.
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Fig. 1: Schematic showing patient flow and study design, including patient enrollment, planned dose cohorts, interventions, follow-up and outcome assessments.
Fig. 2: CRISPR–Cas9-mediated PD-1 gene editing in T cells.
Fig. 3: Off-target analysis by NGS and WGS.
Fig. 4: Persistence, TCR clones, cytokines and clinical outcomes of patients who received therapy with the gene-edited T cells.
Fig. 5: Outcomes of B-01.
Data availability
All requests for raw and analyzed data and materials are promptly reviewed by the West China Hospital to verify whether the request is subject to any intellectual property or confidentiality obligations. Patient-related data not included in the paper were generated as part of clinical trials and may be subject to patient confidentiality. Any data and materials that can be shared will be released via a material transfer agreement. All other data that support the findings of this study will be provided by the corresponding author upon reasonable request when possible. Raw data for Figs. 2 – 4 and Extended Data Figs. 1 – 3 , 6 and 8 – 10 are in the Source Data. The raw sequencing data reported in the study have been deposited in the Genome Sequence Archive for Human ( http://bigd.big.ac.cn/gsa-human/ ) at the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, under accession number PRJCA002488 .
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Acknowledgements
This clinical trial was supported by the 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (grant no. ZYJC18001); the West China Hospital Foundation of New Technology (grant nos. XJS2016003 and 190160012); the Sichuan Cancer Society Foundation (grant no. SCS-KT001); the National Science and Technology Major Project (grant no. 2017ZX09304023); and the National Natural Science Foundation of China (grant no. 81672982). We thank all of the study participants, H. Wakelee and G. P. Gao for providing insightful advice on this study, J.S. Kim for advice on the off-target effects, J.Y. Li and the nursing team for clinical care, Q. Lu for data collection, Q. Zhang for clinical ECG diagnosis, L. Wang for supporting preclinical study, J. Jiang for data and safety monitoring, M. Zhao for data management and S. Wang for statistical support.
Author information
These authors contributed equally: You Lu, Jianxin Xue, Tao Deng, Xiaojuan Zhou, Kun Yu.
Affiliations
Department of Thoracic Oncology, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
You Lu
Chengdu MedGenCell, Co., Ltd, Chengdu, China
Tao Deng
Jacobi Medical Center, NYC Health Hospitals, Albert Einstein College of Medicine, New York, NY, USA
Lei Deng
Center of GCP, West China Hospital, Sichuan University, Chengdu, China
Maozhi Liang
ZenRhyme Consulting Service, Ltd, Shanghai, China
Yu Wang
 & Haige Shen
National Research Center for Translational Medicine, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
Wenbo Wang
Berry Oncology Co. Ltd, Fujian, China
Xiaoxing Su
Department of Pathology, West China Hospital, Sichuan University, Chengdu, China
Qiao Zhou
Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China
Binwu Ying
State Key Laboratory of Biotherapy and Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China
Chong Chen
 & Yuquan Wei
Department of Respiratory and Critical Care Medicine and Frontier Science Center of Disease Molecular Network, West China Hospital, Sichuan University, Chengdu, China
Weimin Li
State Key Laboratory of Translational Oncology, Department of Clinical Oncology, Chinese University of Hong Kong, Hong Kong, China
Tony Mok
Google Scholar
Contributions
Y. Lu, J.X., L.D. and T.M. were involved in study design. Y. Lu and T.D. contributed to study concepts. T.D., K.Y. and Y. Zeng were responsible for manufacturing of therapeutic cells. X. Zhou, M.H., R.T., Z.D., Y.G., J.Z., Yongsheng Wang, L.L., Y. Zhang, Y. Liu, B.Z., M.Y., L.Z., Y. Li, Q. Z. and B.Y. were involved in data acquisition. Y. Lu, Yu Wang, H.S. and M.L were involved in quality control of data and algorithms. J.X., X. Zhou, X.Y., J.S., J.L., Yuqi Wang, X.S., W.W., X. Zhang, L.Y., X.X. and C.C. were involved in data analysis and interpretation. Yu Wang and H.S. contributed to statistical analysis. Y. Lu, J.X., R.T. and T.M. wrote the manuscript. Yuquan Wei and W.L. were involved in administrative support and supervision. All authors approved the article for submission and publication.
Corresponding author
The authors declare no competing interests.
Additional information
Peer review information Saheli Sadanand was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 T7E1 cleavage assay, TA cloning sequencing of PD-1 disruption in cultured T cells.
a, DNA amplified from edited or unedited T cells were subjected to T7E1 cleavage assay. T cells from a healthy person served as a control. The blue arrow indicates the expected bands for uncut (no mismatch) PD-1; the red arrow, expected bands from the T7E1 assay. Marker, DL2000 Marker (Innova GENE Biosciences, Ontario, Canada). b, The efficiency of PD-1 editing was analyzed by TA cloning on day 21 after electroporation. Source data
Extended Data Fig. 2 Long-term effects of PD-1 disruption in cultured T cells in Patient B-01 and C-02.
Viability of PD-1 disruption in long-term cultured T cells. Compared to the rapid decrease in viability of unedited T cells after day 30, the viability of edited T cells was over 90% and remained high until day 40. Total cell numbers of PD-1 disruption in long-term cultured T cells. The numbers of edited T cells increased slowly until around day 30, reflecting delayed proliferation likely due to the electroporation procedure; after day 30, the numbers of edited T cells increased rapidly. By contrast, the numbers of unedited cells, decreased rapidly after day 30. Source data
Extended Data Fig. 3 Off-target analysis by next generation sequencing (NGS).
Characteristics of on-target and off-target mutation types, frequencies and numbers determined by next-generation sequencing (NGS) for the edited T cells of 7 patients prior to the second cycle of infusion. Bar graph and pie graph above represent the types, the numbers and the composition of off-target mutation, color-coded according to the legend in the top-right corner. Intergenic (44.4%) and intronic (39.1%) mutations composed the majority proportion. Heatmap shows the mutation number of predicted off-target sites (18 off-target sites, OT1-18) and on-target site for individuals. Bar graph on right represents mean mutation frequencies of each site among the 7 patients. The mutation frequencies at these off-target sites and the on-target site were 0.05% (range 0.00–0.22%) and 4.09%, respectively. The modification ratio of on-target/off-target was 105.2. Pie graph on bottom-right shows the composition of on-target mutation. The mutation types of on-target consisted of frameshift or nonframeshift (deletion/insertion mutation), and stopgain, while the vast majority was the deletion mutation (88.5%). Data in bar graph are shown as mean ± s.d. Source data
Extended Data Fig. 4 Electrocardiograph and echocardiography of patient Pre-A-01 during treatment.
a, Electrocardiograph images of patient Pre-A-01 during T-cell therapy. Patient Pre-A-01 had no history of heart disease. The baseline electrocardiograph (before infusion) showed normal results. However, the electrocardiograph on day 1 after the first infusion showed a premature beat; the electrocardiograph on the day 113 showed a premature beat similar to that on day 1. Each image is representative of 3 independent tests. b, Representative images from baseline echocardiography (before infusion, left) and echocardiography conducted on day 26 after the first infusion (right). No cardiac lesion or obvious change in functional parameters was found.


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