Full-length Single-cell RNA Sequencing Research Articles

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis.

Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.

Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in ovarian cancer

Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Here, we perform long-read single-cell RNA sequencing (scRNA-seq) on clinical samples from three ovarian cancer patients presenting with omental metastasis and increase the PacBio sequencing depth to 12,000 reads per cell. Our approach captures 152,000 isoforms, of which over 52,000 were not previously reported. Isoform-level analysis accounting for non-coding isoforms reveals 20% overestimation of protein-coding gene expression on average. We also detect cell type-specific isoform and poly-adenylation site usage in tumor and mesothelial cells, and find that mesothelial cells transition into cancer-associated fibroblasts in the metastasis, partly through the TGF-β/miR-29/Collagen axis. Furthermore, we identify gene fusions, including an experimentally validated IGF2BP2::TESPA1 fusion, which is misclassified as high TESPA1 expression in matched short-read data, and call mutations confirmed by targeted NGS cancer gene panel results. With these findings, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

1740-P: Regulation of Endocrine Cell Alternative Splicing Revealed by Single-Cell RNA Sequencing in Type 2 Diabetes

The prevalent RNA alternative splicing (AS) underlies molecular diversity, which has been demonstrated in regulating cellular functions and diseases. However, the contribution of AS in pancreatic islets remains unclear during diabetes progression. Here, we reanalyzed the full-length single-cell RNA sequencing data from the deposited database to investigate AS regulation across human pancreatic endocrine cell types in nondiabetic (ND) and type 2 diabetes (T2D) individuals. Our analysis demonstrated the significant association between AS profiles and cell-type-specificity, which could be applied to distinguish the clustering of major endocrine cell types. Moreover, AS profiles were enabled to clearly define the mature subset of β-cells in healthy controls, which was completely lost in T2D. Further analysis revealed that RNA-binding proteins (RBPs), hnRNPs and FXR1 family proteins were predicted to induce the functional impairment of β-cells through regulating AS profiles. Finally, trajectory analysis of endocrine cells suggested the β-cell identity shift through dedifferentiation and transdifferentiation of β-cells during the progression of T2D. Together, our study provides a new mechanism for regulating β-cell functions and suggests the significant contribution of AS program during diabetes. Disclosure J. Wang: None. S. Wen: None. M. Chen: None. J. Xie: None. G. Shi: None.

Full-Length Single-Cell RNA-Sequencing with FLASH-seq.

The single-cell RNA-sequencing (scRNA-seq) field has evolved tremendously since the first paper was published back in 2009 (Tang et al. Nat Methods 6:377-382, 2009). While the first methods analyzed just a handful of cells, the throughput and performance rapidly increased over a very short time span. However, it was not until the introduction of emulsion droplets methods, such as the well-known kits commercialized by 10x Genomics, that the robust and reproducible analysis of thousands of cells became feasible (Zheng et al Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049, 2017). Despite generating data at a speed and a cost per cell that remains unmatched for full-length protocols like Smart-seq (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), scRNA-seq in droplets still comes with the drawback of addressing only the terminal portion of the transcripts, thus lacking the required sensitivity for comprehensively analyzing the entire transcriptome.Building upon the existing Smart-seq2/3 workflows (Hagemann-Jensen et al Single-cell RNA counting at allele and isoform resolution using Smart-seq3. Nat Biotechnol 38:708-714, 2020; Picelli et al Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods 10:1096-1098, 2013), we developed FLASH-seq (FS), a new full-length scRNA-seq method capable of detecting a significantly higher number of genes than previous versions, requiring limited hands-on time and with a great potential for customization (Hahaut et al. Lightning Fast and Highly Sensitive Full-Length Single-cell sequencing using FLASH-Seq. http://biorxiv.org/lookup/doi/10.1101/2021.07.14.452217. https://doi.org/10.1101/2021.07.14.452217, 2021). Here, we present three variants of the FS protocol.Standard FLASH-seq (FS), which builds upon Smart-seq2 developed in the past, is non-stranded and does not use unique molecular identifiers (UMIs) but still remains the easiest method to measure gene expression in a cell population.FLASH-seq low-amplification (FS-LA) represents the fastest method, which generates sequencing-ready libraries in 4.5 h, without sacrificing performance.FLASH-seq with UMIs (FS-UMI) builds upon the same principle as Smart-seq3 and introduces UMIs for molecule counting and isoform reconstruction. The newly designed template-switching oligonucleotide (TSO) contains a 5-bp spacer, which allows the generation of high-quality data while minimizing the amount of strand-invasion artifacts.

Relative infectivity of the SARS-CoV-2 Omicron variant in human alveolar cells.

With the continuous emergence of highly transmissible SARS-CoV-2 variants, the comparison of their infectivity has become a critical issue for public health. However, a direct assessment of the viral characteristic has been challenging because of the lack of appropriate experimental models and efficient methods. Here, we integrated human alveolar organoids and single-cell transcriptome sequencing to facilitate the evaluation. In a proof-of-concept study with four highly transmissible SARS-CoV-2 variants, including GR (B.1.1.119), Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (BA.1), a rapid evaluation of the relative infectivity was possible. Our system demonstrates that the Omicron variant is 5- to 7-fold more infectious to human alveolar cells than the other SARS-CoV-2 variants at the initial stage of infection. To our knowledge, for the first time, this study measures the relative infectivity of the Omicron variant under multiple virus co-infection and provides new experimental procedures that can be applied to monitor emerging viral variants.

Nivolumab-Based Salvage Therapy to Restore T Cell Fitness in Penta-Refractory Multiple Myeloma with Relapse to Anti-BCMA CAR T Cell Therapy

Background: Idecabtagene Vicleucel (ide-cel) is the first FDA-approved BCMA-directed CAR T cell therapy for the treatment of relapsed/refractory multiple myeloma (RRMM). Despite remarkable activity of 85% objective response rate and a progression-free survival (PFS) of 11.8 months reported in the CRB-401 trial (NCT02658929), most responses to ide-cel are not durable, and nearly all patients (pts) eventually relapse, even those achieving MRD-negative complete remission (CR). Factors associated with clinical relapse to ide-cel include BCMA loss, lack of CAR T persistence, T-cell exhaustion and PD-1/ PD-L1 impaired T-cell fitness. Here, we report clinical data and correlative findings for 4 pts who were salvaged with a nivolumab (anti-PD1)- based triplet therapy at the time of clinical relapse to first or second ide-cel infusion. Methods: Four pts with penta-refractory RRMM were treated as part of the CRB-401 phase 1 study as previously reported (Raje et al.N Engl J Med.2019;380:1726-37). All pts received nivolumab along with lenalidomide-dexamethasone (Nivo-Rd) or pomalidomide-dexamethasone (Nivo-Pd) at the time of relapse to ide-cel. CD3+ T cells (n=1,047) were isolated from the peripheral blood of 2 of these pts and full-length single-cell RNA sequencing (scRNA-seq) was conducted before and upon treatment with Nivo-Rd/-Pd. Response rates were assessed as per IMWG criteria. Results: The median age of pts was 48.5 years (range 37-56). Two out of 4 pts had cytogenetic high-risk MM and all pts were penta-refractory at the time of CRB-401 study inclusion. The median PFS and OS after first ide-cel infusion were 10.4 (range 3.0-13.8) months and 21.5 (range 16.0-34.6) months, respectively. Three pts received a second ide-cel infusion, whereof only 1 pt achieved a partial response (PR) at a PFS of 5.2 months. Two pts each were treated with Nivo-Rd and Nivo-Pd respectively at the time of progression to ide-cel. Responses to anti-PD1- based therapy varied markedly with 1 PR, 1 stable disease (SD) and 2 progressive disease (PD) as per IMWG criteria. The median PFS to nivolumab-based salvage therapy was 3.6 (range 0.4-8.1) months. Interestingly, pts MM1 and MM2 both had a CR to first ide-cel infusion (PFS 13.8 and 11.9 months, respectively), but while both pts did not respond to second CAR T cell infusion, the benefit from anti-PD1 treatment differed markedly in both pts. MM1 reached a PR and PFS of 105 days. In contrast, MM2 experienced immediate PD and succumbed to his disease 3.0 months later. Profiling of CD3+ T cells from MM1 and MM2 by scRNA-seq revealed rapid cellular state changes in response to PD1 inhibition. PAGODA2 clustering and t-Stochastic Neighbor Embedding (t-SNE) visualization revealed 3 distinct clusters, segregating to an individual pre-anti-PD1 cluster for MM1 and MM2 each and a shared post-anti-PD1 cluster comprising CD3+ T cells from both pts. The pre-anti-PD1 cluster for MM1 contained CD3+ T-cells with a memory T cell- like phenotype (IL7Rhigh, CD62Lhigh) and decreased expression of markers correlating with T-cell fitness (GNLY, PRF1, NKG7, GZMH,LY6C, KLRG1). This phenotype could be rescued, and T-cell fitness could be restored by Nivo-Pd treatment, potentially contributing to the clinical response observed in MM1. Opposingly, the pre-anti-PD1 cluster for MM2 showed intact T-cell fitness with low expression of T-cell exhaustion markers. No clinical benefit to Nivo-Rd was noted in this pt. Conclusions: Checkpoint inhibition and IMiD therapy can induce clinical responses at the time of relapse to first or second CAR T infusion. Efficacy however seems to depend on impaired T-cell fitness as premise for PD1 inhibition to re-induce clinical responses in selected pts.

Exploring the cellular landscape of circular RNAs using full-length single-cell RNA sequencing

Previous studies have demonstrated the highly specific expression of circular RNAs (circRNAs) in different tissues and organisms, but the cellular architecture of circRNA has never been fully characterized. Here, we present a collection of 171 full-length single-cell RNA-seq datasets to explore the cellular landscape of circRNAs in human and mouse tissues. Through large-scale integrative analysis, we identify a total of 139,643 human and 214,747 mouse circRNAs in these scRNA-seq libraries. We validate the detected circRNAs with the integration of 11 bulk RNA-seq based resources, where 216,602 high-confidence circRNAs are uniquely detected in the single-cell cohort. We reveal the cell-type-specific expression pattern of circRNAs in brain samples, developing embryos, and breast tumors. We identify the uniquely expressed circRNAs in different cell types and validate their performance in tumor-infiltrating immune cell composition deconvolution. This study expands our knowledge of circRNA expression to the single-cell level and provides a useful resource for exploring circRNAs at this unprecedented resolution.

Fast and highly sensitive full-length single-cell RNA sequencing using FLASH-seq

We present FLASH-seq (FS), a full-length single-cell RNA sequencing (scRNA-seq) method with increased sensitivity and reduced hands-on time compared to Smart-seq3. The entire FS protocol can be performed in ~4.5 hours, is simple to automate and can be easily miniaturized to decrease resource consumption. The FS protocol can also use unique molecular identifiers (UMIs) for molecule counting while displaying reduced strand-invasion artifacts. FS will be especially useful for characterizing gene expression at high resolution across multiple samples.

Single-cell gene fusion detection by scFusion

Gene fusions can play important roles in tumor initiation and progression. While fusion detection so far has been from bulk samples, full-length single-cell RNA sequencing (scRNA-seq) offers the possibility of detecting gene fusions at the single-cell level. However, scRNA-seq data have a high noise level and contain various technical artifacts that can lead to spurious fusion discoveries. Here, we present a computational tool, scFusion, for gene fusion detection based on scRNA-seq. We evaluate the performance of scFusion using simulated and five real scRNA-seq datasets and find that scFusion can efficiently and sensitively detect fusions with a low false discovery rate. In a T cell dataset, scFusion detects the invariant TCR gene recombinations in mucosal-associated invariant T cells that many methods developed for bulk data fail to detect; in a multiple myeloma dataset, scFusion detects the known recurrent fusion IgH-WHSC1, which is associated with overexpression of the WHSC1 oncogene. Our results demonstrate that scFusion can be used to investigate cellular heterogeneity of gene fusions and their transcriptional impact at the single-cell level.

Enriching and Characterizing T Cell Repertoires from 3' Barcoded Single-Cell Whole Transcriptome Amplification Products.

Antigen-specific T cells play an essential role in immunoregulation and many diseases such as cancer. Characterizing the T cell receptor (TCR) sequences that encode T cell specificity is critical for elucidating the antigenic determinants of immunological diseases and designing therapeutic remedies. However, methods of obtaining single-cell TCR sequencing data are labor and cost intensive, typically requiring both cell sorting and full-length single-cell RNA-sequencing (scRNA-seq). New high-throughput 3' cell-barcoding scRNA-seq methods can simplify and scale this process; however, they do not routinely capture TCR sequences during library preparation and sequencing. While 5' cell-barcoding scRNA-seq methods can be used to examine TCR repertoire at single-cell resolution, doing so requires specialized reagents which cannot be applied to samples previously processed using 3' cell-barcoding methods.Here, we outline a method for sequencing TCRα and TCRβ transcripts from samples already processed using 3' cell-barcoding scRNA-seq platforms, ensuring TCR recovery at a single-cell resolution. In short, a fraction of the 3' barcoded whole transcriptome amplification (WTA) product typically used to generate a massively parallel 3' scRNA-seq library is enriched for TCR transcripts using biotinylated probes and further amplified using the same universal primer sequence from WTA. Primer extension using TCR V-region primers and targeted PCR amplification using a second universal primer result in a 3' barcoded single-cell CDR3-enriched library that can be sequenced with custom sequencing primers. Coupled with 3' scRNA-seq of the same WTA, this method enables simultaneous analysis of single-cell transcriptomes and TCR sequences which can help interpret inherent heterogeneity among antigen-specific T cells and salient disease biology. The method presented here can also be adapted readily to enrich and sequence other transcripts of interest from both 3' and 5' barcoded scRNA-seq WTA libraries.

Murine AGM single-cell profiling identifies a continuum of hemogenic endothelium differentiation marked by ACE

AbstractIn vitro generation and expansion of hematopoietic stem cells (HSCs) holds great promise for the treatment of any ailment that relies on bone marrow or blood transplantation. To achieve this, it is essential to resolve the molecular and cellular pathways that govern HSC formation in the embryo. HSCs first emerge in the aorta-gonad-mesonephros (AGM) region, where a rare subset of endothelial cells, hemogenic endothelium (HE), undergoes an endothelial-to-hematopoietic transition (EHT). Here, we present full-length single-cell RNA sequencing (scRNA-seq) of the EHT process with a focus on HE and dorsal aorta niche cells. By using Runx1b and Gfi1/1b transgenic reporter mouse models to isolate HE, we uncovered that the pre-HE to HE continuum is specifically marked by angiotensin-I converting enzyme (ACE) expression. We established that HE cells begin to enter the cell cycle near the time of EHT initiation when their morphology still resembles endothelial cells. We further demonstrated that RUNX1 AGM niche cells consist of vascular smooth muscle cells and PDGFRa+ mesenchymal cells and can functionally support hematopoiesis. Overall, our study provides new insights into HE differentiation toward HSC and the role of AGM RUNX1+ niche cells in this process. Our expansive scRNA-seq datasets represents a powerful resource to investigate these processes further.

Single-cell Long Non-coding RNA Landscape of T Cells in Human Cancer Immunity

The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of T cells. To date, the complete landscape and systematic characterization of long noncoding RNAs (lncRNAs) in T cells in cancer immunity are lacking. Here, by systematically analyzing full-length single-cell RNA sequencing (scRNA-seq) data of more than 20,000 libraries of T cells across three cancer types, we provided the first comprehensive catalog and the functional repertoires of lncRNAs in human T cells. Specifically, we developed a custom pipeline for de novotranscriptome assembly and obtained a novel lncRNA catalog containing 9433 genes. This increased the number of current human lncRNA catalog by 16% and nearly doubled the number of lncRNAs expressed in T cells. We found that a portion of expressed genes in single T cells were lncRNAs which had been overlooked by the majority of previous studies. Based on metacell maps constructed by the MetaCell algorithm that partitions scRNA-seq datasets into disjointed and homogenous groups of cells (metacells), 154 signature lncRNA genes were identified. They were associated with effector, exhausted, and regulatory T cell states. Moreover, 84 of them were functionally annotated based on the co-expression networks, indicating that lncRNAs might broadly participate in the regulation of T cell functions. Our findings provide a new point of view and resource for investigating the mechanisms of T cell regulation in cancer immunity as well as for novel cancer-immune biomarker development and cancer immunotherapies

Single-cell RNA-seq reveals developmental plasticity with coexisting oncogenic states and immune evasion programs in ETP-ALL

Lineage plasticity and stemness have been invoked as causes of therapy resistance in cancer, because these flexible states allow cancer cells to dedifferentiate and alter their dependencies. We investigated such resistance mechanisms in relapsed/refractory early T-cell progenitor acute lymphoblastic leukemia (ETP-ALL) carrying activating NOTCH1 mutations via full-length single-cell RNA sequencing (scRNA-seq) of malignant and microenvironmental cells. We identified 2 highly distinct stem-like states that critically differed with regard to cell cycle and oncogenic signaling. Fast-cycling stem-like leukemia cells demonstrated Notch activation and were effectively eliminated in patients by Notch inhibition, whereas slow-cycling stem-like cells were Notch independent and rather relied on PI3K signaling, likely explaining the poor efficacy of Notch inhibition in this disease. Remarkably, we found that both stem-like states could differentiate into a more mature leukemia state with prominent immunomodulatory functions, including high expression of the LGALS9 checkpoint molecule. These cells promoted an immunosuppressive leukemia ecosystem with clonal accumulation of dysfunctional CD8+ T cells that expressed HAVCR2, the cognate receptor for LGALS9. Our study identified complex interactions between signaling programs, cellular plasticity, and immune programs that characterize ETP-ALL, illustrating the multidimensionality of tumor heterogeneity. In this scenario, combination therapies targeting diverse oncogenic states and the immune ecosystem seem most promising to successfully eliminate tumor cells that escape treatment through coexisting transcriptional programs.

Tissue-specific transcriptional imprinting and heterogeneity in human innate lymphoid cells revealed by full-length single-cell RNA-sequencing

The impact of the microenvironment on innate lymphoid cell (ILC)-mediated immunity in humans remains largely unknown. Here we used full-length Smart-seq2 single-cell RNA-sequencing to unravel tissue-specific transcriptional profiles and heterogeneity of CD127+ ILCs across four human tissues. Correlation analysis identified gene modules characterizing the migratory properties of tonsil and blood ILCs, and signatures of tissue-residency, activation and modified metabolism in colon and lung ILCs. Trajectory analysis revealed potential differentiation pathways from circulating and tissue-resident naïve ILCs to a spectrum of mature ILC subsets. In the lung we identified both CRTH2+ and CRTH2− ILC2 with lung-specific signatures, which could be recapitulated by alarmin-exposure of circulating ILC2. Finally, we describe unique TCR-V(D)J-rearrangement patterns of blood ILC1-like cells, revealing a subset of potentially immature ILCs with TCR-δ rearrangement. Our study provides a useful resource for in-depth understanding of ILC-mediated immunity in humans, with implications for disease.

Cellular, transcriptomic and isoform heterogeneity of breast cancer cell line revealed by full-length single-cell RNA sequencing

Tumor heterogeneity is generated through a combination of genetic and epigenetic mechanisms, the latter of which plays an important role in the generation of stem like cells responsible for tumor formation and metastasis. Although the development of single cell transcriptomic technologies holds promise to deconvolute this complexity, a number of these techniques have limitations including drop-out and uneven coverage, which challenge the further delineation of tumor heterogeneity. We adopted deep and full-length single-cell RNA sequencing on Fluidigm’s Polaris platform to reveal the cellular, transcriptomic, and isoform heterogeneity of SUM149, a triple negative breast cancer (TNBC) cell line. We first validate the quality of the TNBC sequencing data with the sequencing data from erythroleukemia K562 cell line as control. We next scrutinized well-defined marker genes for cancer stem-like cell to identify different cell populations. We then profile the isoform expression data to investigate the heterogeneity of alternative splicing patterns. Though classified as triple-negative breast cancer, the SUM149 stem cells show heterogeneous expression of marker receptors (ER, PR, and HER2) across the cells. We identified three cell populations that express patterns of stemness: epithelial-mesenchymal transition (EMT) cancer stem cells (CSCs), mesenchymal-epithelial transition (MET) CSCs and Dual-EMT-MET CSCs. These cells also manifested a high level of heterogeneity in alternative splicing patterns. For example, CSCs have shown different expression patterns of the CD44v6 exon, as well as different levels of truncated EGFR transcripts, which may suggest different potentials for proliferation and invasion among cancer stem cells. Our study identified features of the landscape of previously underestimated cellular, transcriptomic, and isoform heterogeneity of cancer stem cells in triple-negative breast cancers.

Defining the Differentiation States of Multiple Myeloma at Single Cell Resolution Reveals Opportunities for Immunotherapy

Introduction: Despite recent advances in the treatment of multiple myeloma, responses may be short-lived and therapeutic resistance develops almost invariably. Non-genetic cellular plasticity and dedifferentiation have recently emerged as a basis for therapeutic resistance in cancer as cells acquire transcriptional states which no longer depend on the drug target. Therefore, a better understanding of plasticity and adaptive state changes in myeloma cells is critical to develop effective therapeutic approaches that can overcome drug resistance. Here we show that cellular plasticity, though frequently invoked as a basis for therapeutic resistance in cancer, can also lead to new therapeutic opportunities. Methods: To define transcriptional states in myeloma at a single cell level, we performed fluorescence activated cell sorting and full-length single-cell RNA sequencing. We assayed a total 6000 CD38+CD138+ plasma cells and CD45+ immune cells from the bone marrow of 8 patients with relapsed and refractory multiple myeloma (RRMM) before and after immuno-modulatory treatment on a clinical trial with elotuzumab, pomalidomide, bortezomib and dexamethasone (Elo-PVD; NCT02718833) and 2 healthy donors. Surface expression of selected markers was validated by flow cytometry. Results: Assessing pre-treatment samples, we discovered that the transcriptional states of single myeloma cells are highly distinct between individual patients, despite the presence of the same established genomic classifiers, such as t(11;14). Furthermore, distinct transcriptional states co-exist within individual patients, indicating there is substantial inter- and intra-individual heterogeneity. Transcriptional states diverge from normal plasma cells towards more immature cells, of the B lymphoid lineage, suggesting a substantial cellular plasticity. Notably, we detected co-expression of myeloid and lymphoid developmental programs in the same single cells. Interestingly, these altered differentiation states were associated with up-regulation of potential immunotherapeutic targets, such as CD20, CD19, and CD33, indicating that this plasticity may result in novel therapeutic vulnerabilities. To define gene-regulatory relationships, we identified a shared core regulatory network present in malignant and normal plasma cells with the active transcription factors XBP1, ATF4, and CREB3, suggesting that myeloma cells retain lineage-specific regulons. However, we further identified patient-specific regulons not detected in any of the mature immune cell populations assayed, such as TEAD4, ELF3 and SNAI1, illustrating an aberrant and promiscuous activation of transcriptional regulators in myeloma cells. Consistent with this finding, we observed an increased number of expressed genes in myeloma cells compared to normal plasma cells as well as an increase in single cell transcriptional entropy, measures that have been linked to cell potency in normal development and cancer. Comparison of pre- and post-treatment samples interestingly revealed a further increase in transcriptional diversity and signatures associated with stemness and developmental potential following treatment. Conclusions: In conclusion, we find that higher transcriptional diversity and activation of alternate gene regulatory programs facilitate the emergence of altered transcriptional states. Interestingly, these altered states are associated with up-regulation of putative immune-therapeutic targets in myeloma cells, thus providing novel therapeutic vulnerabilities. Disclosures Lipe: amgen: Research Funding; Celgene: Consultancy; amgen: Consultancy. O'Donnell:Celgene: Consultancy; Takeda: Consultancy; BMS: Consultancy; Sanofi: Consultancy; Amgen: Consultancy. Munshi:Celgene: Consultancy; Amgen: Consultancy; Oncopep: Consultancy; Janssen: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Adaptive: Consultancy; Oncopep: Consultancy; Takeda: Consultancy. Richardson:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees. Anderson:Gilead Sciences: Other: Advisory Board; Janssen: Other: Advisory Board; Sanofi-Aventis: Other: Advisory Board; OncoPep: Other: Scientific founder ; C4 Therapeutics: Other: Scientific founder . Lohr:T2 Biosystems: Honoraria; Celgene: Research Funding. OffLabel Disclosure: Samples for ancillary research were obtained in the context of a phase II clinical trial evaluating Elotuzumab, pomalidomide, bortezomib, dexamethasone The combination of elo-PVD is off label.

Single Cell RNA-Seq Reveals Deranged Developmental Hierarchy with Coexisting Oncogenic States and Immune Evasion Programs in ETP T-ALL

Introduction: Early T-cell precursor acute lymphoblastic leukemia (ETP T-ALL) is a distinct subtype of T-ALL characterized by higher rates of relapse and induction failure. Large-scale genetic sequencing studies have identified frequently mutated oncogenes and gene fusions in ETP T-ALL, while bulk transcriptome analyses have revealed expression features resembling myeloid precursors and myeloid malignancies. However, the contributions of intra-tumoral functional heterogeneity and microenvironment to tumor biology and treatment failure remain unknown. Methods: We performed full-length single-cell RNA-sequencing of 5,077 malignant and normal immune cells from bone marrow or blood from five patients with relapsed/refractory ETP T-ALL (based on immunophenotyping, all with NOTCH1 mutations), before and after targeted therapy against NOTCH1. These patients were enrolled on a phase I trial with the γ-secretase inhibitor (GSI) BMS-906024 (NCT01363817). Expression of selected genes was validated by RT-PCR, flow cytometry and immunohistochemistry. Results: Single cell transcriptome analyses revealed a deranged developmental hierarchy characterized by co-expression of stemness programs in multiple malignant cells implying ineffectual commitment to either lymphoid or myeloid lineage. Most ETP T-ALL cells co-expressed HSC (hematopoietic stem cell), CMP (common myeloid progenitor) and CLP (common lymphoid progenitor) signatures simultaneously (Pearson correlation: CLP-CMP: R= 0.41, p < 2.2e-16; HSC-CLP: R= 0.53; p < 2.2e-16; HSC-CMP: R = 0.39, p <2.2e-16). Only a fraction of cells (less than 15%) demonstrated mutually exclusive CLP or HSC signatures. In contrast, CLP, CMP and HSC signatures were not co-expressed and always negatively correlated in normal bone marrow cells (CLP-CMP: R= -0.11, p < 2.2e-16; HSC-CLP: R= -0.38; p < 2.2e-16; HSC-CMP: R = -0.67, p <2.2e-16). Direct targeting of NOTCH1 as the driving oncogene has shown disappointing results in the clinical setting due to the rapid development of resistance. PI3K activation has been shown as a genetic mechanism of Notch resistance, however it is unclear if transcriptional rewiring can give rise to PI3K dependent cells after Notch inhibition. To address this question, we predicted the activity of signaling pathways in single cells after Notch inhibitor treatment using PROGENy. Most single cells demonstrated loss of Notch signaling. PI3K signaling activity was the most anti-correlated signaling pathway to Notch signaling (Pearson correlation: R= -0.51, p < 2.2e-16). Of note, this population preexisted at a frequency of ~30% in the untreated population, coexisting with cells with high Notch activation. Analysis of the immune microenvironment revealed an oligoclonal T-cell population in ETP T-ALL compared to normal donor T-cells. CD8+ T-cells from ETP patients expressed markers of T-cell exhaustion (PDCD1, TIGIT, LAG3, HAVCR2). Analyses of expression levels of the respective ligands on leukemic blasts and the predicted interaction with their receptors on endogenous CD8+ T-cells demonstrated the highest interaction score between HAVCR2 and its ligand LGALS9. LGALS9 was universally expressed in all leukemic cells, which was confirmed by flow cytometry staining in leukemic blasts and IHC staining in bone marrow of 8 patients with ETP T-ALL and 7 patients with T-ALL. T-ALL supernatant increased expression levels of the exhaustion markers HAVCR2,TIGIT and decreased effector marker GZMB in polyclonal activated normal donor CD8+ T-cells (RT-PCR). This effect was abrogated by neutralizing LGALS9 and could be rescued with recombinant LGALS9. Conclusion: We identified deranged developmental hierarchy characterized by co-expression of stemness programs in multiple malignant cell states and ineffectual commitment to either lymphoid or myeloid lineage in ETP T-ALL. Leukemic blasts demonstrate preexisting heterogeneity of diverse oncogenic states as evidenced by opposing PI3K and Notch activity, suggesting possible novel combination therapies. Notch inhibition abolishes the Notch high state without effecting the PI3K active state. Finally, we demonstrate a possible role for HAVCR2-LGALS9 interactions in causing CD8+ T-cell dysfunction in ETP T-ALL patients, which may provide a novel therapeutic strategy in this disease. Disclosures Silverman: Takeda: Consultancy; Servier: Consultancy, Research Funding. Lane:AbbVie: Research Funding; Stemline Therapeutics: Research Funding; N-of-One: Consultancy. DeAngelo:Glycomimetics: Research Funding; Amgen, Autolus, Celgene, Forty-seven, Incyte, Jazzs, Pfizer, Shire, Takeda: Consultancy; Blueprint: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Abbvie: Research Funding. Lohr:Celgene: Research Funding; T2 Biosystems: Honoraria.

Defining the differentiation states of multiple myeloma at single cell resolution – Identifying opportunities for immunotherapy

Non-genetic cellular plasticity has recently emerged as a basis for therapeutic resistance in cancer. Therefore, a better understanding of cellular plasticity and adaptive state changes in myeloma cells and the immune microenvironment is critical to develop effective therapeutic approaches that can overcome drug resistance. We performed fluorescence activated cell sorting and full-length single-cell RNA sequencing of myeloma cells and CD45+ immune cells from the bone marrow of 8 patients with relapsed/refractory multiple myeloma (RRMM) treated on a clinical trial with elotuzumab, pomalidomide, bortezomib and dexamethasone (Elo-PVD; NCT02718833) before and after treatment.

Full-Length Single-Cell RNA Sequencing with Smart-seq2.

In the last few years single-cell RNA sequencing (scRNA-seq) has enabled the investigation of cellular heterogeneity at the transcriptional level, the characterization of rare cell types as well as the detailed analysis of the stochastic nature of gene expression. A large number of methods have been developed, varying in their throughput, sensitivity, and scalability. A major distinction is whether they profile only 5'- or 3'-terminal part of the transcripts or allow for the characterization of the entire length of the transcripts. Among the latter, Smart-seq2 is still considered the "gold standard" due to its sensitivity, precision, lower cost, scalability and for being easy to set up on automated platforms. In this chapter I describe how to efficiently generate sequencing-ready libraries, highlight common issues and pitfalls, and offer solutions for generating high-quality data.