Individual cell‐based modeling of tumor cell plasticity‐induced immune escape after CAR‐T therapy. Issue 3 (23rd September 2021)

• Record Type: Journal Article
• Authors: Zhang, Can; Shao, Changrong; Jiao, Xiaopei; Bai, Yue; Li, Miao; Shi, Hanping; Lei, Jinzhi; Zhong, Xiaosong
• Is Part Of: Computational and systems oncology. Volume 1:Issue 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-23
• Subjects: B‐cell acute lymphoblastic leukemia -- cancer immunotherapy -- CAR‐T -- cell plasticity -- immune escape -- individual cell‐based modeling; Oncology -- Data processing -- Periodicals; Oncology -- Periodicals; Systems biology -- Periodicals; Medical Oncology; Neoplasms; Electronic journals; Periodicals; 616.994
• DOI: 10.1002/cso2.1029
• Languages: English
• ISSNs: 2689-9655

Abstract

Abstract: Chimeric antigen receptor (CAR) therapy targeting CD19 is an effective treatment for refractory B cell malignancies, especially B‐cell acute lymphoblastic leukemia (B‐ALL). The majority of patients achieve a complete response following a single infusion of CD19‐targeted CAR‐modified T cells (CAR‐19 T cells); however, many patients suffer relapse after therapy, and the underlying mechanism remains unclear. To better understand the mechanism of tumor relapse, we developed an individual cell‐based computational model based on major assumptions of the tumor cells heterogeneity and plasticity as well as the heterogeneous responses to CAR‐T treatment. Model simulations reproduced the process of tumor relapse and predicted that cell plasticity induced by CAR‐T stress can lead to tumor relapse in B‐ALL. Model predictions were in agreement with experimental results of applying the second‐generation CAR‐T cells to mice injected with NALM‐6‐GL leukemic cells, in which 60% of the mice relapse within 3 months, relapsed tumors retained CD19 expression but exhibited a subpopulation of cells with high level CD34 transcription. The computational model suggests that the experimental data are compatible with a CAR‐T cell‐induced transition of tumor cells to hematopoietic stem‐like cells and myeloid‐like cells, which are resistant to the treatment. The proposed computational model framework was successfully developed to recapitulate the individual evolutionary dynamics and potentially allows to predict the outcomes of CAR‐T treatment through model simulation based on early‐stage observations of tumor burden and tumor cells analysis.