Exploiting Single-Cell Tools in Gene and Cell Therapy

Single-Cell RNA Sequencing in Organ and Cell Transplantation

Single-cell RNA sequencing is a high-throughput novel method that provides transcriptional profiling of individual cells within biological samples. This method typically uses microfluidics systems to uncover the complex intercellular communication networks and biological pathways buried within highly heterogeneous cell populations in tissues. One important application of this technology sits in the fields of organ and stem cell transplantation, where complications such as graft rejection and other post-transplantation life-threatening issues may occur. In this review, we first focus on research in which single-cell RNA sequencing is used to study the transcriptional profile of transplanted tissues. This technology enables the analysis of the donor and recipient cells and identifies cell types and states associated with transplant complications and pathologies. We also review the use of single-cell RNA sequencing in stem cell implantation. This method enables studying the heterogeneity of normal and pathological stem cells and the heterogeneity in cell populations. With their remarkably rapid pace, the single-cell RNA sequencing methodologies will potentially result in breakthroughs in clinical transplantation in the coming years.

Associating growth factor secretions and transcriptomes of single cells in nanovials using SEC-seq

Cells secrete numerous bioactive molecules that are essential for the function of healthy organisms. However, scalable methods are needed to link individual cell secretions to their transcriptional state over time. Here, by developing and using secretion-encoded single-cell sequencing (SEC-seq), which exploits hydrogel particles with subnanolitre cavities (nanovials) to capture individual cells and their secretions, we simultaneously measured the secretion of vascular endothelial growth factor A (VEGF-A) and the transcriptome for thousands of individual mesenchymal stromal cells. Our data indicate that VEGF-A secretion is heterogeneous across the cell population and is poorly correlated with the VEGFA transcript level. The highest VEGF-A secretion occurs in a subpopulation of mesenchymal stromal cells characterized by a unique gene expression signature comprising a surface marker, interleukin-13 receptor subunit alpha 2 (IL13RA2), which allowed the enrichment of this subpopulation. SEC-seq enables the identification of gene signatures linked to specific secretory states, facilitating mechanistic studies, the isolation of secretory subpopulations and the development of means to modulate cellular secretion.

Coexpression network analysis of the adult brain sheds light on the pathogenic mechanism of DDR1 in schizophrenia and bipolar disorder

DDR1 has been linked to schizophrenia (SCZ) and bipolar disorder (BD) in association studies. DDR1 encodes 58 distinct transcripts, which can be translated into five isoforms (DDR1a-e) and are expressed in the brain. However, the transcripts expressed in each brain cell type, their functions and their involvement in SCZ and BD remain unknown. Here, to infer the processes in which DDR1 transcripts are involved, we used transcriptomic data from the human brain dorsolateral prefrontal cortex of healthy controls (N = 936) and performed weighted gene coexpression network analysis followed by enrichment analyses. Then, to explore the involvement of DDR1 transcripts in SCZ (N = 563) and BD (N = 222), we studied the association of coexpression modules with disease and performed differential expression and transcript significance analyses. Some DDR1 transcripts were distributed across five coexpression modules identified in healthy controls (MHC). MHC1 and MHC2 were enriched in the cell cycle and proliferation of astrocytes and OPCs; MHC3 and MHC4 were enriched in oligodendrocyte differentiation and myelination; and MHC5 was enriched in neurons and synaptic transmission. Most of the DDR1 transcripts associated with SCZ and BD pertained to MHC1 and MHC2. Altogether, our results suggest that DDR1 expression might be altered in SCZ and BD via the proliferation of astrocytes and OPCs, suggesting that these processes are relevant in psychiatric disorders.

Harnessing the Transcriptional Signatures of CAR-T-Cells and Leukemia/Lymphoma Using Single-Cell Sequencing Technologies

Chimeric antigen receptor (CAR)-T-cell therapy has greatly improved outcomes for patients with relapsed or refractory hematological malignancies. However, challenges such as treatment resistance, relapse, and severe toxicity still hinder its widespread clinical application. Traditional transcriptome analysis has provided limited insights into the complex transcriptional landscape of both leukemia cells and engineered CAR-T-cells, as well as their interactions within the tumor microenvironment. However, with the advent of single-cell sequencing techniques, a paradigm shift has occurred, providing robust tools to unravel the complexities of these factors. These techniques enable an unbiased analysis of cellular heterogeneity and molecular patterns. These insights are invaluable for precise receptor design, guiding gene-based T-cell modification, and optimizing manufacturing conditions. Consequently, this review utilizes modern single-cell sequencing techniques to clarify the transcriptional intricacies of leukemia cells and CAR-Ts. The aim of this manuscript is to discuss the potential mechanisms that contribute to the clinical failures of CAR-T immunotherapy. We examine the biological characteristics of CAR-Ts, the mechanisms that govern clinical responses, and the intricacies of adverse events. By exploring these aspects, we hope to gain a deeper understanding of CAR-T therapy, which will ultimately lead to improved clinical outcomes and broader therapeutic applications.

Contextualizing protein representations using deep learning on protein networks and single-cell data

Understanding protein function and developing molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across diverse biological contexts, such as tissues and cell types, remains a significant challenge for existing algorithms. We introduce Pinnacle, a flexible geometric deep learning approach that is trained on contextualized protein interaction networks to generate context-aware protein representations. Leveraging a human multi-organ single-cell transcriptomic atlas, Pinnacle provides 394,760 protein representations split across 156 cell type contexts from 24 tissues and organs. Pinnacle's contextualized representations of proteins reflect cellular and tissue organization and Pinnacle's tissue representations enable zero-shot retrieval of the tissue hierarchy. Pretrained Pinnacle's protein representations can be adapted for downstream tasks: to enhance 3D structure-based protein representations for important protein interactions in immuno-oncology (PD-1/PD-L1 and B7-1/CTLA-4) and to study the effects of drugs across cell type contexts. Pinnacle outperforms state-of-the-art, yet context-free, models in nominating therapeutic targets for rheumatoid arthritis and inflammatory bowel diseases, and can pinpoint cell type contexts that predict therapeutic targets better than context-free models (29 out of 156 cell types in rheumatoid arthritis; 13 out of 152 cell types in inflammatory bowel diseases). Pinnacle is a graph-based contextual AI model that dynamically adjusts its outputs based on biological contexts in which it operates.

Neoantigen cancer vaccines: a new star on the horizon

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells. One of the most exciting advances within this field is the targeting of neoantigens, which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells. Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment, early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors. Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens. Consequently, personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences. This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines, and also discusses challenges and future perspectives for this innovative approach, particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

Single-cell transcriptomics identifies adipose tissue CD271+ progenitors for enhanced angiogenesis in limb ischemia

Therapeutic angiogenesis using mesenchymal stem/stromal cell grafts have shown modest and controversial effects in preventing amputation for patients with critical limb ischemia. Through single-cell transcriptomic analysis of human tissues, we identify CD271+ progenitors specifically from subcutaneous adipose tissue (AT) as having the most prominent pro-angiogenic gene profile distinct from other stem cell populations. AT-CD271+ progenitors demonstrate robust in vivo angiogenic capacity over conventional adipose stromal cell grafts, characterized by long-term engraftment, augmented tissue regeneration, and significant recovery of blood flow in a xenograft model of limb ischemia. Mechanistically, the angiogenic capacity of CD271+ progenitors is dependent on functional CD271 and mTOR signaling. Notably, the number and angiogenic capacity of CD271+ progenitors are strikingly reduced in insulin-resistant donors. Our study highlights the identification of AT-CD271+ progenitors with in vivo superior efficacy for limb ischemia. Furthermore, we showcase comprehensive single-cell transcriptomics strategies for identification of suitable grafts for cell therapy.

Insights gained from single-cell analysis of chimeric antigen receptor T-cell immunotherapy in cancer

Advances in chimeric antigen receptor (CAR)-T cell therapy have significantly improved clinical outcomes of patients with relapsed or refractory hematologic malignancies. However, progress is still hindered as clinical benefit is only available for a fraction of patients. A lack of understanding of CAR-T cell behaviors in vivo at the single-cell level impedes their more extensive application in clinical practice. Mounting evidence suggests that single-cell sequencing techniques can help perfect the receptor design, guide gene-based T cell modification, and optimize the CAR-T manufacturing conditions, and all of them are essential for long-term immunosurveillance and more favorable clinical outcomes. The information generated by employing these methods also potentially informs our understanding of the numerous complex factors that dictate therapeutic efficacy and toxicities. In this review, we discuss the reasons why CAR-T immunotherapy fails in clinical practice and what this field has learned since the milestone of single-cell sequencing technologies. We further outline recent advances in the application of single-cell analyses in CAR-T immunotherapy. Specifically, we provide an overview of single-cell studies focusing on target antigens, CAR-transgene integration, and preclinical research and clinical applications, and then discuss how it will affect the future of CAR-T cell therapy.

Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on NK cell marker genes to predict prognosis and immunotherapy response in hepatocellular carcinoma

BACKGROUND

Prognostic modeling of NK cell marker genes in patients with hepatocellular carcinoma based on single cell sequencing and transcriptome data analysis.

METHODS

Marker genes of NK cells were analyzed according to single cell sequencing data of hepatocellular carcinoma. Univariate Cox regression, lasso regression analysis, and multivariate Cox regression were performed to estimate the prognostic value of NK cell marker genes. TCGA, GEO and ICGC transcriptomic data were applied to build and validate the model. Patients were divided into high and low risk groups based on the median risk score. XCELL, timer, quantitative sequences, MCP counter, EPIC, CIBERSORT and CIBERSORT-abs were performed to explore the relationship between risk score and tumor microenvironment in hepatocellular carcinoma. Finally the sensitivity of the model to chemotherapeutic agents was predicted.

RESULTS

Single-cell sequencing identified 207 marker genes for NK cells in hepatocellular carcinoma. Enrichment analysis suggested that NK cell marker genes were mainly involved in cellular immune function. Eight genes were selected for prognostic modeling after multifactorial COX regression analysis. The model was validated in GEO and ICGC data. Immune cell infiltration and function were higher in the low-risk group than in the high-risk group. The low-risk group was more suitable for ICI and PD-1 therapy. Half-maximal inhibitory concentrations of Sorafenib, Lapatinib, Dabrafenib, and Axitinib were significantly different on the two risk groups.

CONCLUSION

A new signature of hepatocyte NK cell marker genes possesses a powerful ability to predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma.

Immunotherapy in hematologic malignancies: achievements, challenges and future prospects

The immune-cell origin of hematologic malignancies provides a unique avenue for the understanding of both the mechanisms of immune responsiveness and immune escape, which has accelerated the progress of immunotherapy. Several categories of immunotherapies have been developed and are being further evaluated in clinical trials for the treatment of blood cancers, including stem cell transplantation, immune checkpoint inhibitors, antigen-targeted antibodies, antibody-drug conjugates, tumor vaccines, and adoptive cell therapies. These immunotherapies have shown the potential to induce long-term remission in refractory or relapsed patients and have led to a paradigm shift in cancer treatment with great clinical success. Different immunotherapeutic approaches have their advantages but also shortcomings that need to be addressed. To provide clinicians with timely information on these revolutionary therapeutic approaches, the comprehensive review provides historical perspectives on the applications and clinical considerations of the immunotherapy. Here, we first outline the recent advances that have been made in the understanding of the various categories of immunotherapies in the treatment of hematologic malignancies. We further discuss the specific mechanisms of action, summarize the clinical trials and outcomes of immunotherapies in hematologic malignancies, as well as the adverse effects and toxicity management and then provide novel insights into challenges and future directions.

Resolving the hematopoietic stem cell state by linking functional and molecular assays

One of the most challenging aspects of stem cell research is the reliance on retrospective assays for ascribing function. This is especially problematic for hematopoietic stem cell (HSC) research in which the current functional assay that formally establishes its HSC identity involves long-term serial transplantation assays that necessitate the destruction of the initial cell state many months before knowing that it was, in fact, an HSC. In combination with the explosion of equally destructive single-cell molecular assays, the paradox facing researchers is how to determine the molecular state of a functional HSC when you cannot concomitantly assess its functional and molecular properties. In this review, we will give a historical overview of the functional and molecular assays in the field, identify new tools that combine molecular and functional readouts in populations of HSCs, and imagine the next generation of computational and molecular profiling tools that may help us better link cell function with molecular state.

Lineage tracing reveals fate bias and transcriptional memory in human B cells

We combined single-cell transcriptomics and lineage tracing to understand fate choice in human B cells. Using the antibody sequences of B cells, we tracked clones during in vitro differentiation. Clonal analysis revealed a subset of IgM+ B cells which were more proliferative than other B-cell types. Whereas the population of B cells adopted diverse states during differentiation, clones had a restricted set of fates available to them; there were two times more single-fate clones than expected given population-level cell-type diversity. This implicated a molecular memory of initial cell states that was propagated through differentiation. We then identified the genes which had strongest coherence within clones. These genes significantly overlapped known B-cell fate determination programs, suggesting the genes which determine cell identity are most robustly controlled on a clonal level. Persistent clonal identities were also observed in human plasma cells from bone marrow, indicating that these transcriptional programs maintain long-term cell identities in vivo. Thus, we show how cell-intrinsic fate bias influences differentiation outcomes in vitro and in vivo.

Single cell transcriptomics identifies adipose tissue CD271+ progenitors for enhanced angiogenesis in limb ischemia

Therapeutic angiogenesis using mesenchymal stem/stromal cell grafts have shown modest and controversial effects in preventing amputation for patients with critical limb ischemia. Through single-cell transcriptomic analysis of human tissues, we identified CD271 + progenitors specifically from subcutaneous adipose tissue (AT) as having the most prominent pro-angiogenic gene profile distinct from other stem cell populations. AT-CD271 + progenitors demonstrated robust in vivo angiogenic capacity, over conventional adipose stromal cell grafts, characterized by long-term engraftment, augmented tissue regeneration, and significant recovery of blood flow in a xenograft model of limb ischemia. Mechanistically, the angiogenic capacity of CD271 + progenitors is dependent on functional CD271 and mTOR signaling. Notably, the number and angiogenic capacity of CD271 + progenitors was strikingly reduced in insulin resistant donors. Our study highlights the identification of AT-CD271 + progenitors with in vivo superior efficacy for limb ischemia. Furthermore, we showcase comprehensive single-cell transcriptomics strategies for identification of suitable grafts for cell therapy.

HIGHLIGHTS

Adipose tissue stromal cells have a distinct angiogenic gene profile among human cell sources. CD271 + progenitors in adipose tissue have a prominent angiogenic gene profile. CD271 + progenitors show superior therapeutic capacities for limb ischemia. CD271 + progenitors are reduced and functionally impaired in insulin resistant donors.

GRAPHICAL ABSTRACT

Hematopoietic stem cells depend on HIM and HER

After a series of pioneering experiments on hematopoietic stem cell (HSC) function, including early evidence of heterogeneous stem cell behavior, Jim Till, Ernest McCulloch, and Lou Simminovitch put forward a stochastic model for stem cell proliferation. In contrast to the alternative model, called the "hemopoietic-inductive microenvironment" ("HIM") in which specific microenvironments drove specific and consistent outcomes, they coined the term "hemopoiesis engendered randomly" ("HER"), in which HSCs have intrinsic differences in the cellular state that introduce a probability of potential outcomes. The HIM (extrinsic) and HER (intrinsic) discussion continues nearly 60 years later, but the metaphor also has relevance beyond cellular decision making if one considers the infrastructure and systems supporting the actual scientists who make these advances-a different kind of HER and HIM, but no less important to sort out. This article concludes with some thoughts on how we might achieve a better balance between the HIMs and HERs undertaking the research as well.

Microfluidic live tracking and transcriptomics of cancer-immune cell doublets link intercellular proximity and gene regulation

Cell–cell communication and physical interactions play a vital role in cancer initiation, homeostasis, progression, and immune response. Here, we report a system that combines live capture of different cell types, co-incubation, time-lapse imaging, and gene expression profiling of doublets using a microfluidic integrated fluidic circuit that enables measurement of physical distances between cells and the associated transcriptional profiles due to cell–cell interactions. We track the temporal variations in natural killer—triple-negative breast cancer cell distances and compare them with terminal cellular transcriptome profiles. The results show the time-bound activities of regulatory modules and allude to the existence of transcriptional memory. Our experimental and bioinformatic approaches serve as a proof of concept for interrogating live-cell interactions at doublet resolution. Together, our findings highlight the use of our approach across different cancers and cell types.

Lessons from early life: understanding development to expand stem cells and treat cancers

Haematopoietic stem cell (HSC) self-renewal is a process that is essential for the development and homeostasis of the blood system. Self-renewal expansion divisions, which create two daughter HSCs from a single parent HSC, can be harnessed to create large numbers of HSCs for a wide range of cell and gene therapies, but the same process is also a driver of the abnormal expansion of HSCs in diseases such as cancer. Although HSCs are first produced during early embryonic development, the key stage and location where they undergo maximal expansion is in the foetal liver, making this tissue a rich source of data for deciphering the molecules driving HSC self-renewal. Another equally interesting stage occurs post-birth, several weeks after HSCs have migrated to the bone marrow, when HSCs undergo a developmental switch and adopt a more dormant state. Characterising these transition points during development is key, both for understanding the evolution of haematological malignancies and for developing methods to promote HSC expansion. In this Spotlight article, we provide an overview of some of the key insights that studying HSC development have brought to the fields of HSC expansion and translational medicine, many of which set the stage for the next big breakthroughs in the field.

Tumor vessel co-option: The past & the future

Tumor vessel co-option (VCO) is a non-angiogenic vascularization mechanism that is a possible cause of resistance to anti-angiogenic therapy (AAT). Multiple tumors are hypothesized to primarily rely on growth factor signaling-induced sprouting angiogenesis, which is often inhibited during AAT. During VCO however, tumors invade healthy tissues by hijacking pre-existing blood vessels of the host organ to secure their blood and nutrient supply. Although VCO has been described in the context of AAT resistance, the molecular mechanisms underlying this process and the profile and characteristics of co-opted vascular cell types (endothelial cells (ECs) and pericytes) remain poorly understood, resulting in the lack of therapeutic strategies to inhibit VCO (and to overcome AAT resistance). In the past few years, novel next-generation technologies (such as single-cell RNA sequencing) have emerged and revolutionized the way of analyzing and understanding cancer biology. While most studies utilizing single-cell RNA sequencing with focus on cancer vascularization have centered around ECs during sprouting angiogenesis, we propose that this and other novel technologies can be used in future investigations to shed light on tumor EC biology during VCO. In this review, we summarize the molecular mechanisms driving VCO known to date and introduce the models used to study this phenomenon to date. We highlight VCO studies that recently emerged using sequencing approaches and propose how these and other novel state-of-the-art methods can be used in the future to further explore ECs and other cell types in the VCO process and to identify potential vulnerabilities in tumors relying on VCO. A better understanding of VCO by using novel approaches could provide new answers to the many open questions, and thus pave the way to develop new strategies to control and target tumor vascularization.

Convergence or divergence: next frontiers toward globalization of current- and next-generation cell and gene therapies

The last decades have seen a massive transformation in the field of advanced therapies, culminating in the marketing approval of different cutting-edge gene, cell- and tissue engineering-based therapies across different regions of the world. Although this success is promising, the global clinical development pathway of such therapies is often hindered by unique manufacturing, preclinical and clinical regulatory challenges; with different expectations, sometimes linked with divergence in opinions between international regulatory authorities. Such technologies call for a science-based approach and an early regulatory dialogue to set the key elements of quality, safety and efficacy for the next generation cell and gene therapies that can be harmonized across different regional jurisdictions, hence speeding up patient access to innovative therapies across the globe.

High efficiency sorting and outgrowth for single-cell cloning of mammalian cell lines

Single-cell selection and cloning is required for multiple bioprocessing and cell engineering workflows. Dispensing efficiency and outgrowth were optimized for multiple common suspension (CHO ES, Expi293F, and Jurkat) and adherent (MCF-7, A549, CHO-K1, and HEK293) cell lines. Single-cell sorting using a low pressure microfluidic cell sorter, the WOLF Cell Sorter, was compared with limiting dilution at 0.5 cells/well to demonstrate the increased efficiency of using flow cytometry selection of cells. In this work, there was an average single cell deposition on Day 0 of 89.1% across all the cell lines tested compared to 41.2% when using limiting dilution. After growth for 14 days, 66.7% of single-cell clones sorted with the WOLF Cell Sorter survived and only 23.8% when using limiting dilution. Using the WOLF Cell Sorter for cell line development results in higher viable single-cell colonies and the ability to select subpopulations of single-cells using multiple parameters.