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Get the pole position in the CAR-T race: How Single Cell Multi-Omics can accelerate precision medicine

Get the pole position in the CAR-T race: How Single Cell Multi-Omics can accelerate precision medicine

Chimeric Antigen Receptor (CAR) refers to a recombinant transmembrane molecule composed of a single-chain antibody variable region that can bind to an antigen, a hinge transmembrane region and an intracellular signaling domain. It is an artificially constructed receptor that recognizes specific antigens. Chimeric antigen receptor T cells (CAR-T cells) are generated by transferring CAR genes into T cells in vitro through various vectors (1, 2).

CAR-T cell therapy has shown remarkable efficacy in the treatment of acute leukemia and multiple myeloma and is considered to be one of the most promising anti-tumor treatments. However, the related complications of CAR-T cell therapy, such as cytokine release syndrome (immune effector cell-associated neurotoxicity syndrome, ICANS), hematological toxicity and other complications, have become important factors restricting its application. Compared with hematological tumors, solid tumors are more complex, and the problems caused by tumor drug resistance, antigen heterogeneity and immune escape still need to be solved (2 ,3).

Recently, tumor research has gradually progressed from the macro level of tumors to individual tumor cells, revealing the heterogeneity among tumor cells. Single cell sequencing technologies can explain the heterogeneity of different cells at different levels of the genome, epigenomics, transcriptomics or proteomics, identify cell subgroups, study pathogenesis, and dig deeper into therapeutic targets. Therefore, it is of great significance to understand the heterogeneity among tumor cells and explain crucial physiological behaviors at a single cell resolution (1).

We believe that single cell sequencing technologies can support and accelerate the development of more precise and efficient cell and gene therapies all the way from bench to bedside. Single cell sequencing can be used in a pre-clinical setting to promote the discovery of novel biomarkers and to assist technologies investigating the efficiency of recently developed transfection/transduction platforms or new CAR-T cell design strategies. Further, single cell multi-omics could be used during clinical trials, in addition to the final application process by enabling a comprehensive analysis of the quality control system of CAR-T cell therapy products before and after injection into the patient. Thus, further exploring the biological characteristics of CAR-T cells in vivo, the mechanism of tumor immune escape, and the clinical efficacy of different cell components, in order to further improve the clinical efficacy of CAR-T cell therapy and reduce its side effects.

Here, we conducted an inventory of the research progress of single cell sequencing in CAR-T cell therapy for readers.

Single cell sequencing identifies pro-inflammatory Th17.1 T cells promoting a sarcoidosis-like immune reaction in multiple myeloma

Figure 1: scRNA-seq reveals an inflammatory environment within lungs of a MM patient driven by Th17.1 T cells. A) UMAP comprising scRNA-seq data from BAL. B) UMAP embedding scRNA-seq data from T cell populations identified in A) (Figure modified from Leipold, Werner, and Düll et al., 2023 (4);

In the underlying case study, a MM patient treated with ide-cel, an anti-BCMA CAR-T cell therapy, was analyzed using scRNA-seq and PET imaging to better understand the mechanisms following CAR-T cell therapy. This allowed the characteristics of disease progression versus immune cell-mediated adverse effects to be evaluated. scRNA-seq on bronchoalveolar lavage (BAL) fluid identified an inflammatory CD4 Th17.1 T cell population which was in-line with lesions detected via PET scan. An integrated scRNA-seq data analysis revealed transcriptomic similarities between those Th17.1 cells and T cells from sarcoidosis patients. Together, the results showed that following anti-BCMA CAR-T cells therapy an inflammatory subset of Th17.1 cells was driving a sarcoidosis-like immune disease which manifested in the lungs of the patient. Thus, the study shows how using scRNA-seq analysis can be applied to identify potential risk factors prior or during CAR-T cell therapy and further highlights the utilization of scRNA-seq for customized treatments based on existing or potential risk factors (4).

Using single cell RNA technologies to characterize CAR-T cells co-expressing a PD-L1 CSR

Figure 2: Single cell sequencing data of CARMz T cells. 4264 CARMz T cells (1989 sCARMz T cells; 2275 mCARMz T cells) were separated into eight clusters. sCARMz and mCARMz T cells were distributed across these clusters (Figure modified from Qin, Cui, and Yuan et al., 2022 (5);

The PD-1/PD-L1 pathway plays an important role in immunosuppression leading to tumor evasion. In this study, PD-1 CSR (CARP) T cells are described promoting the anti-tumoral properties of mesothelin CAR (CARMz) T cells, which was also associated with a differentiation into memory-like cells. Similar results were obtained using CD19 CSR T cells and PSCA CAR (CARPAz) T cells. Furthermore, the CD70-CD27 axis was identified to be critical for these cytotoxic functions. scRNA-seq was applied to analyze the transcriptional profile of these cells (5).

Single cell RNA sequencing reveals a relapse-promoting mechanism for B-ALL

Figure 3: Single cell analysis showed the presence of CD19neg B-ALL cells prior to CAR-T cell treatment. UMAPs display the main clusters, de-multiplexed clusters before therapy (T1) and post-relapse (T2) and tumor cell identified in T1 CD19neg (Figure modified from Rabilloud, Potier, and Pankaew et al., 2021 (6);

In this study, scRNA-seq was used to sequence pre-CAR-T treatment (T1) and post-relapse (T2) specimens taken from a B cell acute lymphoblastic leukemia (B-ALL) patient. CD19-targeted CAR-T cell therapies show good results in the treatment of hematological malignancies. However, a high number of patients relapse after treatment, and in about 50% of all cases, relapse mediated by antigen escape is associated with CD19neg leukemic cells. Here, the authors addressed the question if the CD19 CAR-T treatment is the direct cause or whether the relapse is based on a selection for unresponsive CD19neg cells. Using scRNA-seq to analyze patient samples, Rabilloud and colleagues found that CD19neg clones were already present in T1 specimens. These negative clones carried a non-functional CD19 transcript which enabled them to resist the treatment. Together, the data indicates that scRNA-seq could be a valuable tool to evaluate patients before and during the treatment to identify potential risks and to adjust the strategy (6).

Single cell sequencing enables a comprehensive antigen expression analysis in multiple tissues

Figure 4: scRNA-seq analysis from heart, kidney, liver and lung tissue samples. UMAPs from indicated tissues and their respective identified cell clusters (Figure modified from Zhang et al., 2021 (7);

Several CAR-T cells therapies are currently in the developmental phase to target various cancer entities, however, recent data also showed that CAR-T cell approaches could trigger “on-target, off-tumor toxicity” and other side effects such as cytokine release syndrome and B cell dysplasia. Therefore, in this study, the authors used single cell data sets from 18 different tissues and organs from human samples to investigate their antigen expression profiles. By comparing the expression of certain target antigens in normal cells compared to malignant cells they found that the expression of these antigens may vary and some non-malignant cells could also express higher antigen levels. Based on these results, the generated atlas provides valuable information that could be used to predict the efficiency and “on-target, off-tumor toxicity” of specific antigens and highlights the need for in-depth analysis of patients to enable efficient stratification and targeted therapies (7).

Analyzing changes in the transcriptional signatures of CD8+ CAR-T by single cell sequencing

Figure 5: Single cell transcriptomics reveal changes in CD8+ CAR-T cells between infusion product and blood over time. t-SNE blot of CD8+ CAR-T cells from four (2x CLL and 2x NHL) patients compiled from the IP, an early, late and very later time point post infusion (Figure modified from Sheih, Voillet, and Hanafi et al., 2020 (8),

To investigate the clonal dynamics and transcriptional profiles of CAR-T cells, CD8+ CAR-T cells from infusion products and blood were analyzed using TCRB sequencing, integration site analysis, and scRNA-seq. TCRB-seq of these samples from patients receiving CD19 CAR-T immunotherapy, showed high clonal diversity of CAR-T cells in infusion products. Also, scRNA-seq analysis revealed transcriptional changes of CD8+ CAR-T cells in the blood compared to CAR-T cells from infusion product. In principle, the study highlights how single cell profiling can be applied to monitor the transcriptional changes and clonal dynamics of CAR-T cells which could promote the development of improved therapies (8).

Explore new possibilities with single cell sequencing

Single cell sequencing has the power to support novel cell and gene approaches from bench to bedside. At Singleron, we offer unique multi-omics solutions that may help you to better understand the underlying mechanisms of complex, heterogenous diseases such as acute myeloid leukemia, multiple myeloma, or solid tumors. Our innovative technologies enable you to improve biomarker discovery, pre-clinical testing and could assist patient stratification. Singleron’s streamlined Single Cell Sequencing Service, from tissue sample to advanced bioinformatic analysis, is specifically tailored to your needs, delivering fast, quality results to promote precision medicine.

Processes such as target discovery, enabling studies, product verification and regular monitoring measures are crucial to allow for the development of an efficient, safe, and high-quality product. Singleron’s innovative single cell sequencing portfolio, from kits and instruments to our advanced bioinformatic pipeline, offers solutions to advocate all these major steps. Our unique FocuSCOPE® Single Cell Targeted Capture Kit, enables the detection of targeted sequences such as driver mutations, viral sequences, and fusion genes. Based on the same principle, the GEXSCOPE® Single Cell V(D)J Kit offers highly efficient V(D)J mapping to support analysis of the TCR/BCR diversity in your sample of interest, together with the whole transcriptome. On top, Singleron’s sCircle® Single Cell Full Length Immunoreceptor Library Kit facilitates high throughput full length B cell and T cell V(D)J sequencing in combination with whole transcriptome profiling.

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Standardized and streamlined processes are crucial to accelerate testing and developmental steps. In this regard, Singleron’s PythoN® Tissue Dissociation System and Matrix® Single Cell Processing System not only enable efficient and versatile sample preparation but also the automatization of sample handling as an integrated part of the library construction workflow.

Singleron’s advanced bioinformatics pipeline comprises the development of accurate machine learning models which can be used to accelerate translational research. By using high-quality single cell sequencing data, these models can be used to predict patient outcomes or to identify novel drug targets.

Singleron offers a unique and innovative portfolio of end-to-end single cell multi-omics solutions that could help to promote cell and gene therapies from bench to bedside. Explore new possibilities, with Singleron.

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  1. 1. Bode D, Cull AH, Rubio-Lara JA and Kent DG (2021) Exploiting Single-Cell Tools in Gene and Cell Therapy. Front. Immunol. 12:702636. doi: 10.3389/fimmu.2021.702636.
  2. 2. Zhang K, Chen H, Li F, Huang S, Chen F and Li Y (2023) Bright future or blind alley? CAR-T cell therapy for solid tumors. Front. Immunol. 14:1045024. doi: 10.3389/fimmu.2023.1045024.
  3. 3. Wang Z, Chen C, Wang L, Jia Y and Qin Y (2022) Chimeric antigen receptor T-cell therapy for multiple myeloma. Front. Immunol. 13:1050522. doi: 10.3389/fimmu.2022.1050522.
  4. 4. Leipold, A.M., Werner, R.A., Düll, J. et al. Th17.1 cell driven sarcoidosis-like inflammation after anti-BCMA CAR T cells in multiple myeloma. Leukemia 37, 650–658 (2023).
  5. 5. Qin, L., Cui, Y., Yuan, T. et al. Co-expression of a PD-L1-specific chimeric switch receptor augments the efficacy and persistence of CAR T cells via the CD70-CD27 axis. Nat Commun 13, 6051 (2022).
  6. 6. Rabilloud, T., Potier, D., Pankaew, S. et al. Single-cell profiling identifies pre-existing CD19-negative subclones in a B-ALL patient with CD19-negative relapse after CAR-T therapy. Nat Commun 12, 865 (2021).
  7. 7. Zhang Y, Li Y, Cao W, Wang F, Xie X, Li Y, Wang X, Guo R, Jiang Z and Guo R (2021) Single-Cell Analysis of Target Antigens of CAR-T Reveals a Potential Landscape of “On-Target, Off-Tumor Toxicity”. Immunol.12:799206. doi: 10.3389/fimmu.2021.799206.
  8. 8. Sheih, A., Voillet, V., Hanafi, LA. et al. Clonal kinetics and single-cell transcriptional profiling of CAR-T cells in patients undergoing CD19 CAR-T immunotherapy. Nat Commun 11, 219 (2020).