Single-Cell Transcriptomic Analysis Reveals BCMA CAR-T Cell Dynamics in a Patient with Refractory Primary Plasma Cell Leukemia

Li, Xue; Guo, Xin; Zhu, Yuqing; Wei, Guoqing; Zhang, Yanlei; Li, Xia; Xu, Huijun; Cui, Jiazhen; Wu, Wenjun; He, Jingsong; Ritchie, Matthew E.; Weiskittel, Taylor M.; Hu, Li; Yu, Hua; Ding, Lijuan; Shao, Mi; Luo, Qian; Xu, Xiaojun; Teng, Xinyi; Chang, Alex H.; Zhang, Jin; Huang, He; Hu, Yongxian

doi:10.1016/j.ymthe.2020.11.028

Cited by 45 publications

(50 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Characterization and dynamics of endogenous T cells Our group longitudinally profiled the transcriptome of T cells in a plasma cell leukemia patient treated with anti-BCMA CAR-T cells and found that CAR-T cells in the CRS peak phase transition from a proliferative to a cytotoxic intermediate state, while the expression of GZMB and PRF1 was observed in endogenous T cells at the CRS peak phase. 110 Meanwhile, in 2020, Chen et al found that CAR-T cells composed only 1-5% of the total T-cell population within the intact tumor microenvironment (TME) in diffuse large B-cell lymphoma patients following CAR-T-cell therapy. 111 Unexpectedly, a large number of non-CAR-T cells (endogenous T cells) within the TME were activated, and these cells were positive for Ki-67, IFN-γ, GZMB, and/or PD-1 and associated with beneficial and pathological effects.…”

Section: Crs In Pathogenic Diseases Crs In Covid-19mentioning

confidence: 99%

“… 23 Then, our group showed significant interactions between highly cytotoxic CAR-T cells and endogenous T cells through the ligand–receptor pairs of CCR5-CCL5, CCL3-CCR5, CD70-CD27, and ICAM1-SPN/ITGAL. 110 In addition to the interactions among CAR-T cells, monocytes and endogenous T cells, the crosstalk between CAR-T cells and tumors has also been studied. In 2020, Liu et al demonstrated that CAR-T cells released GZMB, which activated caspase 3 to cleave GSDME in target tumor cells and caused pyroptosis.…”

Section: Cellular Mechanisms Of Crsmentioning

confidence: 99%

“…For example, lymphopenia (low blood lymphocyte count) is one of the key characteristics of severe COVID-19 patients, 186 while lymphocytes (including CAR-T and endogenous T cells) are activated and increase in number in CAR-T-cell therapy. 110 Our group also compared the clinical characteristics and risk factors associated with severe CRS induced by COVID-19 and CAR-T-cell therapy. 187 We found a significantly higher incidence of grade 4 CRS in the COVID-19 group than in the CAR-T-cell therapy group.…”

Section: Cutting-edge Technologies In Crs-related Studiesmentioning

confidence: 99%

See 2 more Smart Citations

Signaling pathways in the regulation of cytokine release syndrome in human diseases and intervention therapy

Shao

Zhang

et al. 2021

Sig Transduct Target Ther

Self Cite

View full text Add to dashboard Cite

Cytokine release syndrome (CRS) embodies a mixture of clinical manifestations, including elevated circulating cytokine levels, acute systemic inflammatory symptoms and secondary organ dysfunction, which was first described in the context of acute graft-versus-host disease after allogeneic hematopoietic stem-cell transplantation and was later observed in pandemics of influenza, SARS-CoV and COVID-19, immunotherapy of tumor, after chimeric antigen receptor T (CAR-T) therapy, and in monogenic disorders and autoimmune diseases. Particularly, severe CRS is a very significant and life-threatening complication, which is clinically characterized by persistent high fever, hyperinflammation, and severe organ dysfunction. However, CRS is a double-edged sword, which may be both helpful in controlling tumors/viruses/infections and harmful to the host. Although a high incidence and high levels of cytokines are features of CRS, the detailed kinetics and specific mechanisms of CRS in human diseases and intervention therapy remain unclear. In the present review, we have summarized the most recent advances related to the clinical features and management of CRS as well as cutting-edge technologies to elucidate the mechanisms of CRS. Considering that CRS is the major adverse event in human diseases and intervention therapy, our review delineates the characteristics, kinetics, signaling pathways, and potential mechanisms of CRS, which shows its clinical relevance for achieving both favorable efficacy and low toxicity.

show abstract

Section: Crs In Pathogenic Diseases Crs In Covid-19mentioning

confidence: 99%

Section: Cellular Mechanisms Of Crsmentioning

confidence: 99%

Section: Cutting-edge Technologies In Crs-related Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Signaling pathways in the regulation of cytokine release syndrome in human diseases and intervention therapy

Shao

Zhang

et al. 2021

Sig Transduct Target Ther

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although specific methodologies for trajectory inference are outside the scope of this review, key insights from these trajectories can be gleaned by layering systems information on top of pseudotime trajectories. These annotations include sample identity, cluster membership, and gene expression [ 18 ]. This layering approach has provided ample new insights, but future approaches need to integrate systems biology earlier to produce more mechanistically faithful trajectories while simultaneously revealing biological insights.…”

Section: Cell Identities and Trajectoriesmentioning

confidence: 99%

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches

Weiskittel

Correia

et al. 2021

Genes

Self Cite

View full text Add to dashboard Cite

Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has revolutionized biomedical imaging analysis, drug discovery, and systems biology, is an ideal strategy to fill these gaps in single-cell studies. Machine learning additionally has proven to be remarkably synergistic with single-cell data because it remedies unique challenges while capitalizing on the positive aspects of single-cell data. In this review, we describe how systems-biology algorithms have layered machine learning with biological components to provide systems level analyses of single-cell omics data, thus elucidating complex biological mechanisms. Accordingly, we highlight the trifecta of single-cell, systems-biology, and machine-learning approaches and illustrate how this trifecta can significantly contribute to five key areas of scientific research: cell trajectory and identity, individualized medicine, pharmacology, spatial omics, and multi-omics. Given its success to date, the systems-biology, single-cell omics, and machine-learning trifecta has proven to be a potent combination that will further advance biomedical research.

show abstract

“…investigated the dynamics of CAR‐T cell in a plasma cell leukemia (PCL) patient treated with CAR‐T therapy at single‐cell level. They mapped the atlas of CAR‐T and endogenous T cells and revealed stage‐specific gene expression of CAR‐T and endogenous T cells in proliferation, cytotoxicity, and intercellular signaling pathways 28 …”

Section: Single‐cell Genomics: a Powerhouse For Advancing Tumor Immunology And Immunotherapy Researchmentioning

confidence: 99%

Tumor immunology in the age of single-cell genomics

Zhao

Ren

Gao

et al. 2021

Journal of Leukocyte Biology

View full text Add to dashboard Cite

Immunotherapies that were developed based on our understandings of tumor immunology have revolutionized cancer treatment. However, the success of immunotherapy is eclipsed by several grand challenges, including low response rate, intrinsic/acquired resistance and adverse effects. While a deeper understanding of the interaction between tumor and our immune system, especially the tumor immune niche, is essential to overcome those challenges, we are limited by the fact that most of our knowledge about tumor immunology is based on studies analyzing bulk populations of cells, which are often unable to fully characterize the various cell types and states engaged in immune cell functions. The advent of cutting single‐cell genomic technologies empowers us to dissect the tumor immune niche in a genome‐wide and spatially resolved manner in single cells, trace their clonal histories, and unveil their regulatory circuits. Future studies on tumor immunology in the age of single‐cell genomics, therefore, hold the promise to develop more effective and precise immunotherapies for human cancers. In this perspective, we will discuss how advanced single‐cell genomics approaches will revolutionize tumor immunology research and immunotherapies by catering the demand in the field of tumor immunology.

show abstract

Single-Cell Transcriptomic Analysis Reveals BCMA CAR-T Cell Dynamics in a Patient with Refractory Primary Plasma Cell Leukemia

Cited by 45 publications

References 39 publications

Signaling pathways in the regulation of cytokine release syndrome in human diseases and intervention therapy

Signaling pathways in the regulation of cytokine release syndrome in human diseases and intervention therapy

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches

Tumor immunology in the age of single-cell genomics

Contact Info

Product

Resources

About