Explore the vast range of titles available.

Cancer represents an evolutionary process through which growing malignant populations genetically diversify, leading to tumour progression, relapse and resistance to therapy. In addition to genetic diversity, the cell-to-cell variation that fuels evolutionary selection also manifests in cellular states, epigenetic profiles, spatial distributions and interactions with the microenvironment. Therefore, the study of cancer requires the integration of multiple heritable dimensions at the resolution of the single cell — the atomic unit of somatic evolution. In this Review, we discuss emerging analytic and experimental technologies for single-cell multi-omics that enable the capture and integration of multiple data modalities to inform the study of cancer evolution. These data show that cancer results from a complex interplay between genetic and non-genetic determinants of somatic evolution.Both genetic and non-genetic factors underlie the intratumoural heterogeneity that fuels cancer evolution. This Review discusses the application of single-cell multi-omics technologies to the study of cancer evolution, which capture and integrate the different layers of heritable information and reveal their complex interplay.

Mutations in genes involved in DNA methylation (DNAme; for example, TET2 and DNMT3A ) are frequently observed in hematological malignancies 1 – 3 and clonal hematopoiesis 4 , 5 . Applying single-cell sequencing to murine hematopoietic stem and progenitor cells, we observed that these mutations disrupt hematopoietic differentiation, causing opposite shifts in the frequencies of erythroid versus myelomonocytic progenitors following Tet2 or Dnmt3a loss. Notably, these shifts trace back to transcriptional priming skews in uncommitted hematopoietic stem cells. To reconcile genome-wide DNAme changes with specific erythroid versus myelomonocytic skews, we provide evidence in support of differential sensitivity of transcription factors due to biases in CpG enrichment in their binding motif. Single-cell transcriptomes with targeted genotyping showed similar skews in transcriptional priming of DNMT3A -mutated human clonal hematopoiesis bone marrow progenitors. These data show that DNAme shapes the topography of hematopoietic differentiation, and support a model in which genome-wide methylation changes are transduced to differentiation skews through biases in CpG enrichment of the transcription factor binding motif. Single-cell analysis of mouse hematopoietic stem cells shows that mutations in DNA methylation genes change the frequencies of erythroid versus myelomonocytic progenitors, owing to differential CpG enrichment in transcription factor binding motifs.

Some secreted proteins that assemble into large complexes, such as extracellular matrices or hormones and enzymes in storage granules, must be kept at subaggregation concentrations during intracellular trafficking. We show surfeit locus protein 4 (Surf4) is the cargo receptor that establishes different steady-state concentrations for a variety of soluble cargo proteins within the endoplasmic reticulum (ER) through interaction with the amino-terminal tripeptides exposed after removal of leader sequences. We call this motif the ER-Exit by Soluble Cargo using Amino-terminal Peptide-Encoding motif (ER-ESCAPE motif). Proteins that most readily aggregate in the ER lumen (e.g., dentin sialophosphoprotein [DSPP] and amelogenin, X-linked [AMELX]) have strong ER-ESCAPE motifs to inhibit aggregate formation, while less susceptible cargo exhibits weaker motifs. Specific changes in a single amino acid of the tripeptide result in aggregate formation and failure to efficiently traffic cargo out of the ER. A logical subset of 8,000 possible tripeptides starting a model soluble cargo protein (growth hormone) established a continuum of steady-state ER concentrations ranging from low (i.e., high affinity for receptor) to the highest concentrations associated with bulk flow-limited trafficking observed for nonbinding motifs. Human cells lacking Surf4 no longer preferentially trafficked cargo expressing strong ER-ESCAPE motifs. Reexpression of Surf4 or expression of yeast's ortholog, ER-derived vesicles protein 29 (Erv29p), rescued enhanced ER trafficking in Surf4-null cells. Hence our work describes a new way of preferentially exporting soluble cargo out of the ER that maintains proteins below the concentrations at which they form damaging aggregates.

Somatic mutations in cancer genes have been detected in clonal expansions across healthy human tissue, including in clonal hematopoiesis. However, because mutated and wild-type cells are admixed, we have limited ability to link genotypes with phenotypes. To overcome this limitation, we leveraged multi-modality single-cell sequencing, capturing genotype, transcriptomes and methylomes in progenitors from individuals with DNMT3A R882 mutated clonal hematopoiesis. DNMT3A mutations result in myeloid over lymphoid bias, and an expansion of immature myeloid progenitors primed toward megakaryocytic–erythroid fate, with dysregulated expression of lineage and leukemia stem cell markers. Mutated DNMT3A leads to preferential hypomethylation of polycomb repressive complex 2 targets and a specific CpG flanking motif. Notably, the hypomethylation motif is enriched in binding motifs of key hematopoietic transcription factors, serving as a potential mechanistic link between DNMT3A mutations and aberrant transcriptional phenotypes. Thus, single-cell multi-omics paves the road to defining the downstream consequences of mutations that drive clonal mosaicism. Multi-modality single-cell sequencing determines genotype, transcriptome and methylome information in cells from individuals with DNMT3A R882 mutated clonal hematopoiesis, allowing for the comparison of mutant and wild-type cells from the same individuals.

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. Profiling of over 38,000 CD34 + cells from patients with CALR- mutated myeloproliferative neoplasms, using the ‘Genotyping of Transcriptomes’ procedure, reveals that the transcriptional output of these mutations depends upon native cell identity.

Cancer is driven by somatic mutations that provide a fitness advantage. While targeted therapies often focus on the mutated gene or its direct downstream effectors, imbalances brought on by cell-state alterations may also confer unique vulnerabilities. In myeloproliferative neoplasms (MPN), somatic mutations in the calreticulin (CALR) gene are disease-initiating through aberrant binding of mutant CALR to the thrombopoietin receptor MPL and ligand-independent activation of JAK-STAT signaling. Despite these mechanistic insights into the pathogenesis of CALR-mutant MPN, there are currently no mutant CALR-selective therapies available. Here, we identified differential upregulation of unfolded proteins, the proteasome and the ER stress response in CALR-mutant hematopoietic stem cells (HSCs) and megakaryocyte progenitors. We further found that combined pharmacological inhibition of the proteasome and IRE1-XBP1 axis of the ER stress response preferentially targets Calr-mutated HSCs and megakaryocytic-lineage cells over wild-type cells in vivo, resulting in an amelioration of the MPN phenotype. In serial transplantation assays following combined proteasome/IRE1 inhibition for six weeks, we did not find preferential depletion of Calr-mutant long-term HSCs. Together, these findings leverage altered proteostasis in Calr-mutant MPN to identify combinatorial dependencies that may be targeted for therapeutic benefit and suggest that eradicating disease-propagating Calr-mutant LT-HSCs may require more sustained treatment.

Multi-modal single-cell sequencing enables mapping of mutant and wild-type human hematopoietic stem and progenitor cells within the same person, to define cellular phenotypic and epigenetic perturbations associated with clonal hematopoiesis.

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, we developed Genotyping of Transcriptomes (GoT), integrating genotyping with high-throughput droplet-based single-cell RNA-seq. We applied GoT to study how somatic mutations corrupt the complex process of human hematopoiesis, profiling 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms (MPN). High-resolution mapping of malignant vs. normal hematopoietic progenitors revealed increasing CALR-mutation fitness advantage with myeloid differentiation. We identified the unfolded protein response as a predominant outcome of CALR mutations, with significant cell identity dependency, as well as NF-κB pathway upregulation specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci distant from transcript ends. Collectively, these findings revealed that the transcriptional output of MPN somatic mutations is dependent on the native cell identity.