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Mutations in the kinase binding domain of BTK at position C481 are associated with resistance to BTK inhibitor (BTKi) therapy in chronic lymphocytic leukemia (CLL). Nearly half of patients manifesting clinical progression with these alterations exhibit a subclonal burden of resistance. Intriguingly, measured BTKC481 variant allelic fractions (VAF) are commonly lower than 10% [Ahn et al, Blood 2017]. This raises the important question of how BTKC481-mutated (MUT) and wildtype (WT) cells differ in their response to therapeutic challenge, and how low-burden MUT subclones facilitate escape from therapy. While the admixture of MUT and WT cells within the same individual presents an opportunity to directly study the downstream effects of subclonal resistance mutations, these cells cannot be separated through sorting. To overcome this limitation, we utilized Genotyping of Transcriptomes (GoT)-a strategy to jointly capture genotyping of a locus of interest together with whole transcriptomes at the single cell level (Fig. 1A). Importantly, GoT eliminates patient-specific and technical confounders, enabling direct linkage of BTK genotypes to transcriptional phenotypes. We applied GoT to 64,099 CD19+ cells across a cohort of seven patients with clinically progressive CLL found to have low-burden BTKC481 subclones (Fig. 1B). Samples were obtained at the time of progression and were screened for mutations in PLCG2. We genotyped 33.3% of cells, consistent with 34.0% of cells expressing BTK in whole transcriptome data. Clustering of the gene expression profiles showed that MUT and WT clones did not segregate by genotype in most (6/7) patients (Fig. 1C), implying a large degree of transcriptional similarity between MUT and WT cells, and further highlighting the need for multi-omics single-cell sequencing to directly link genotype to phenotype in this context. We note that the single exception with distinct genotypic clustering (CLL06, Fig. 1D) was driven by co-occurring large chromosomal aberrations within the MUT cells, including del(8p), which is associated with BTKi resistance [Burger et al, Nat Comm 2016]. CLL cells are known to cycle between the peripheral blood and protective microenvironmental niches, which is a process modulated by BTKi. We applied CXCR4/CD5 expression as a read out to these migration patterns [Chen et al, Leukemia 2016], and observed that MUT cells were comparatively enriched in CXCR4lowCD5hi CLL, which is associated with recent emigration from the stromal niche and increased BCR signaling (Fig. 1E). Conversely, WT cells were the majority of CXCR4hiCD5low CLL, which is associated with a resting peripheral cellular state and BCR downregulation, suggesting WT quiescence with limited stromal support. To explore the phenotypic changes associated with BTK mutations, we first measured the activity of reported BTKi response expression signatures. WT cells showed higher mean response scores compared to MUT (Fig. 1F), demonstrating that the WT cells preserve BTKi responsiveness. To unbiasedly interrogate transcriptional differences, we applied a set of 336 predefined gene modules representing B-cell cellular functions and processes. Enriched modules in MUT cells implicated restoration of B-cell receptor (BCR) signaling and recovery of CLL cell identity (NF-kB, IRF4, CD40, Fig. 1G), a finding also supported by de novo differential gene expression analysis (Fig. 1H), and gene set enrichment of differentially expressed genes (Fig. 1I). In contrast, WT cells showed increases in modules related to quiescence, hypoxia, cellular stress (HIF-1α, XBP1) and terminal B-cell development (Blimp-1). Intriguingly, changes in gene targets associated with restoration of NOTCH1 and IL4 activity were also observed. As these pathways are impaired in patients responding to BTKi and implicated in resistance [Del Papa et al, CCR 2019; Chen et al, ASH 2019], their re-emergence may reflect a cytoprotective strategy. In summary, we utilized multi-omics single-cell sequencing to identify the distinct transcriptional programs of admixed MUT and WT cells in subclonal BTKC481 progression. MUT cells showed robust escape from BTKi inhibition via increased immune receptor signaling and restoration of CLL cell identity program, while WT cells demonstrated a signature of hypoxia and stress response, with NOTCH1 and IL4 activation implicated as mechanisms of clonal persistence. Disclosures Trisal: Celgene: Current Employment, Current equity holder in publicly-traded company. Gandhi:Celgene: Current Employment, Current equity holder in publicly-traded company. Wiestner:Pharmacyclics LLC, an AbbVie Company, Acerta, Merck, Nurix, Verastem, and Genmab: Research Funding; NIH: Patents & Royalties: NIH. Allan:Acerta, Genentech, Abbvie, Sunesis, Ascentage, Pharmacyclics, Janssen, AstraZeneca, BeiGene: Consultancy; Celgene, Genentech, Janssen, TG Therapeutics: Research Funding; Abbvie, Janssen, AstraZeneca, Pharmacyclics: Honoraria. Furman:Genentech: Consultancy; Beigene: Consultancy; AstraZeneca: Consultancy, Research Funding; Acerta: Consultancy; Verastem: Consultancy; Pharmacyclics: Consultancy; TG Therapeutics: Consultancy, Research Funding; Incyte: Consultancy; Janssen: Consultancy, Speakers Bureau; Oncotarget: Consultancy; Loxo Oncology: Consultancy; Abbvie: Consultancy; Sunesis: Consultancy. Landau:Bristol Myers Squibb: Research Funding; Illumina: Research Funding.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy. A single-cell approach is used to follow the heritable stochastic changes to DNA methylation that occur in primary chronic lymphocytic leukaemia and healthy B cells, allowing the tracing of cell lineage histories and evolution during treatment with ibrutinib.

Cellular proteins continuously undergo non-enzymatic covalent modifications (NECMs) that accumulate under normal physiological conditions and are stimulated by changes in the cellular microenvironment. Glycation, the hallmark of diabetes, is a prevalent NECM associated with an array of pathologies. Histone proteins are particularly susceptible to NECMs due to their long half-lives and nucleophilic disordered tails that undergo extensive regulatory modifications; however, histone NECMs remain poorly understood. Here we perform a detailed analysis of histone glycation in vitro and in vivo and find it has global ramifications on histone enzymatic PTMs, the assembly and stability of nucleosomes, and chromatin architecture. Importantly, we identify a physiologic regulation mechanism, the enzyme DJ-1, which functions as a potent histone deglycase. Finally, we detect intense histone glycation and DJ-1 overexpression in breast cancer tumors. Collectively, our results suggest an additional mechanism for cellular metabolic damage through epigenetic perturbation, with implications in pathogenesis., Proteins continuously undergo non-enzymatic modifications such as glycation, which accumulate under physiological conditions but can be enhanced in disease. Here the authors characterise histone glycation, provide evidence that it affects chromatin, particularly in breast cancer, and identify DJ-1 as a deglycase.

In many areas of oncology, we lack sensitive tools to track low-burden disease. Although cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low-disease-burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole-genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10−5. The WGS approach enabled dynamic tumor burden tracking and postoperative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome-wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance and empowering treatment optimization in low-disease-burden oncology care. A new approach for whole-genome sequencing of plasma circulating tumor DNA allows for dynamic monitoring of disease burden and ultra-sensitive detection of minimal residual disease.

Interferon-alpha (IFN), the first approved immunotherapy for cancer, remains an effective therapy for patients with myeloproliferative neoplasms (MPN). The mechanisms of action of IFN on MPN cells are poorly understood, particularly in patients with CALR mutated (MUT) MPNs, who often exhibit clinical but not molecular responses. Previously, by developing Genotyping of Transcriptomes (GoT) that captures mutation status and single-cell RNA-seq (scRNA-seq) in high-throughput, we observed that CALR mutations led to cell identity-dependent effects on CD34 + cells, including a strong megakaryocytic progenitor (MkP) differentiation bias and fitness. We hypothesized that the IFN effects may be cell identity and mutation status dependent; thus we applied GoT to serial bone marrow aspirates (BM) from 5 patients with CALRmutated ET treated with pegylated-IFN-alfa2a who participated in MPD-RC-111/112 clinical trials. To capture the transcriptional impact of IFN, we removed experimental batch effects with Cell Hashing, in which CD34 + cells from serial BM were uniquely labeled and combined for the same GoT experiment (Fig. 1A). Cell clustering based on transcriptomic data alone revealed that the cells on active treatment clustered based on cell identity and IFN effects (Fig. 1B). When off therapy for 3 weeks, the strong transcriptional effects of IFN were largely lost (Fig. 1B). Next, we batch corrected and integrated across time points for each BM sample (Fig. 1C). We observed that IFN caused large shifts in the composition of wildtype (WT) and MUT cell subsets (Fig. 1D). IFN resulted in a dramatic expansion of WT lymphoid progenitors with a corresponding diminution of other progenitors (Fig. 1E). MUT cells at baseline were enriched for MkPs, compared to WT cells; after treatment, we observed an expansion of the immature myeloid (IMP) and neutrophil progenitors, with a less striking expansion of lymphoid progenitors (Fig. 1E). As IFN has been reported to induce cell cycling of murine hematopoietic progenitor cells, we examined whether a differential increase in proliferation by IFN underlies the differentiation shifts in WT and MUT cells. Cell cycle gene expression of ProB cells increased after treatment similarly in MUT and WT cells, while cell cycle expression of IMPs was increased to a greater extent in MUT cells (Fig. 1F), consistent with the differential shifts in populations. Next, we performed differential expression analysis between baseline and treated WT and MUT cells, respectively. We observed enrichment of the IFN pathways post-therapy, whereas TNF-a signaling was downregulated (Fig. 1G). Uniquely in the MUT cells, TGF-b signaling was downregulated, which may underlie improvements in marrow fibrosis following IFN therapy (Fig. 1G). Finally, as the differentiation biases of IFN persisted after discontinuation, we hypothesized that IFN results in chromatin remodeling of the earliest hematopoietic stem progenitor cells (HSPCs), with respect to transcription factor (TF) accessibility. We leveraged single nuclei chromatin accessibility (snATAC-seq) as a powerful measure of TF regulatory activities. We developed GoT-ATAC, an adaptation of the Multiome platform (10x Genomics), to capture snRNA-seq, snATAC-seq and somatic genotyping within the same cells in high-throughput (Fig. 1H). We applied GoT-ATAC to CD34 + cells from the same clinical trial cohorts (Fig. 1I, n = 3 patients: 3 baseline, 2 treated) and identified the expected enrichment of IRFs and STAT2 in treated HSPCs (Fig. 1J). Accessibility of BCL11A, critical for early lymphoid development, was increased in treated MUT and WT HSPCs. We also identified enhanced motif accessibility of PU.1 which can associate with IRF and is essential for myeloid and lymphoid differentiation. Uniquely within the treated MUT cells, we observed enhanced CEBPA motif enrichment, which regulates myeloid differentiation, together with PU.1. In conclusion, GoT revealed that IFN reshapes the differentiation landscape by promoting early lymphoid development and, uniquely in MUT cells, myeloid differentiation, providing a novel mechanism of actions underlying the effects of IFN in MPN patients. Downregulations of TNF-a and TGF-b signaling were other key molecular consequences of IFN. Lastly, GoT-ATAC demonstrated that IFN governs master regulators of hematopoietic differentiation as a function of the underlying mutational status. Figure 1 Figure 1. Disclosures Mimitou: Immunai: Current Employment. Smibert: Immunai: Current Employment. Hoffman: AbbVie Inc.: Other: Data Safety Monitoring Board, Research Funding; Novartis: Other: Data Safety Monitoring Board, Research Funding; Protagonist Therapeutics, Inc.: Consultancy; Kartos Therapeutics, Inc.: Research Funding.

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.

Defining the transcriptomic identity of clonally related malignant cells is challenging in the absence of cell surface markers that distinguish cancer clones from one another or from admixed non-neoplastic cells. While single-cell methods have been devised to capture both the transcriptome and genotype, these methods are not compatible with droplet-based single-cell transcriptomics, limiting their throughput. To overcome this limitation, we present single-cell Genotyping of Transcriptomes (GoT), which integrates cDNA genotyping with high-throughput droplet-based single-cell RNA-seq. We further demonstrate that multiplexed GoT can interrogate multiple genotypes for distinguishing subclonal transcriptomic identity. We apply GoT to 26,039 CD34+ cells across six patients with myeloid neoplasms, in which the complex process of hematopoiesis is corrupted by CALR-mutated stem and progenitor cells. We define high-resolution maps of malignant versus normal hematopoietic progenitors, and show that while mutant cells are comingled with wildtype cells throughout the hematopoietic progenitor landscape, their frequency increases with differentiation. We identify the unfolded protein response as a predominant outcome of CALR mutations, with significant cell identity dependency. Furthermore, we identify that CALR mutations lead to NF-κB pathway upregulation specifically in uncommitted early stem cells. Collectively, GoT provides high-throughput linkage of single-cell genotypes with transcriptomes and reveals that the transcriptional output of somatic mutations is heavily dependent on the native cell identity.

Somatic mutations in hematopoietic precursors underlie the development of myeloid disorders, such as myeloproliferative neoplasms (MPN). However, our ability to interrogate the transcriptional impact of these mutations on human hematopoiesis is limited by the frequent admixing of mutant (MUT) with wildtype (WT) cells or with other subclones. Recently, digital single-cell RNA-sequencing has provided high-resolution maps of normal hematopoiesis. Nonetheless, due to their 3' bias, these methods do not capture the cell's mutational status. Efficient linking of single-cell genotype and transcriptomes would allow direct comparison of WT and MUT progenitors within the same sample, eliminating patient-specific and technical confounders. Thus, we developed single-cell Genotyping of Transcriptomes (GoT) to link genotypes of expressed genes to transcriptional profiling of thousands of cells by adapting the 10x Genomics platform. We capture the target locus from cDNA generated at an intermediate step, thus enabling linkage of genotype to whole transcriptomes via shared barcodes (Fig. 1A). We tested this approach via a species-mixing experiment, whereby mouse cells with MUT CALR were mixed with human cells with WT CALR. GoT of 1291 admixed cells provided genotyping for 97.5% of cells, and 96.7% matched the expected species (Fig. 1B). To demonstrate the ability of this technology to probe hematopoietic differentiation in MPN, we applied GoT to 20,908 CD34+ cells across five patients with CALR-mutated essential thrombocythemia (ET) or myelofibrosis (MF), resulting in genotyping of 82% of cells. We first performed clustering agnostic to genotype, based on transcriptome data alone, and found that cells clustered according to progenitor cell identity, rather than mutational status (Fig. 1C). Furthermore, projection of GoT data demonstrated that MUT cells were present across all progenitor clusters (Fig. 1D). However, the frequency of CALR-mutated cells was higher in committed progenitors, especially megakaryocytic progenitors (MkPs) compared to CD34+, CD38- hematopoietic stem progenitor cells (HSCPs, Fig. 1E). Thus, CALR mutation may confer a greater fitness impact in lineage-committed cells vs. HSPCs. Indeed, we found a significant increase in the number of MkPs in cell cycle in MUT cells compared to WT cells (Fig. 1F). Moreover, this increase in cell cycle activity correlated with the platelet count (Fig. 1G). This suggests that interrogation of MUT and WT progenitors may inform our understanding of patient phenotypic variability despite shared genotypes. GoT enables de novo differential expression discovery in MUT vs. WT cells within the same progenitor subset. MUT MkPs upregulated genes in the unfolded protein response, such as PDIA6, HSPA5 and XBP1 (Fig. 1H), consistent with the central role of CALR as a chaperone protein. On the other hand, MUT HSPCs showed upregulation of the NF-kB pathway (Fig. 1I), most significantly in the subcluster enriched with the earliest HSCs (Fig. 1J). Since the NF-kB pathway has been implicated in HSC self-renewal, our data provides a potential mechanism for clonal expansion and maintenance of CALR-mutated HSCs. Collectively, these findings demonstrate that the transcriptomic output of CALR mutations is closely dependent on cell identity. To further evaluate the potential of GoT to detect multiple genotypes in clonally complex neoplasms, we targeted three genes, clonal SF3B1 (VAF 47.5% by bulk exon sequencing), and subclonal CALR (43.5%) and NFE2 (33%), in CD34+ cells from a patient with MF (Fig. 1K). Through GoT, the subclonal transcriptional output was interrogated; for example, CALR mutation conferred proliferative advantage to megakaryocytic-erythroid progenitors even in the presence of SF3B1 mutation, while additional NFE2 mutation did not further increase cell cycle activity. In summary, GoT is a powerful tool for linking transcriptional changes to somatic genotypes at the single-cell level. Specifically, it uncovered the transcriptional impact of mutations in myeloid clonal growths in the context of distinct progenitor identities. Further application of GoT to additional MPN contexts as well as clonal hematopoiesis is thus anticipated to provide critical insights into the transcriptional programs that enable clonal expansion and evolution in human hematopoiesis. Disclosures Hoffman: Merus: Research Funding; Janssen: Research Funding; Summer Road: Research Funding; Incyte: Research Funding; Formation Biologics: Research Funding.