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Metacells are cell groupings derived from single-cell sequencing data that represent highly granular, distinct cell states. Here we present single-cell aggregation of cell states (SEACells), an algorithm for identifying metacells that overcome the sparsity of single-cell data while retaining heterogeneity obscured by traditional cell clustering. SEACells outperforms existing algorithms in identifying comprehensive, compact and well-separated metacells in both RNA and assay for transposase-accessible chromatin (ATAC) modalities across datasets with discrete cell types and continuous trajectories. We demonstrate the use of SEACells to improve gene–peak associations, compute ATAC gene scores and infer the activities of critical regulators during differentiation. Metacell-level analysis scales to large datasets and is particularly well suited for patient cohorts, where per-patient aggregation provides more robust units for data integration. We use our metacells to reveal expression dynamics and gradual reconfiguration of the chromatin landscape during hematopoietic differentiation and to uniquely identify CD4 T cell differentiation and activation states associated with disease onset and severity in a Coronavirus Disease 2019 (COVID-19) patient cohort. Single-cell aggregation with archetypes provides intermediate granularity for downstream analyses.

Developmental processes underlying normal tissue regeneration have been implicated in cancer, but the degree of their enactment during tumor progression and under the selective pressures of immune surveillance, remain unknown. Here we show that human primary lung adenocarcinomas are characterized by the emergence of regenerative cell types, typically seen in response to lung injury, and by striking infidelity among transcription factors specifying most alveolar and bronchial epithelial lineages. In contrast, metastases are enriched for key endoderm and lung-specifying transcription factors, SOX2 and SOX9 , and recapitulate more primitive transcriptional programs spanning stem-like to regenerative pulmonary epithelial progenitor states. This developmental continuum mirrors the progressive stages of spontaneous outbreak from metastatic dormancy in a mouse model and exhibits SOX9 -dependent resistance to natural killer cells. Loss of developmental stage-specific constraint in macrometastases triggered by natural killer cell depletion suggests a dynamic interplay between developmental plasticity and immune-mediated pruning during metastasis. Single-cell analysis of lung cancer progression uncovers developmental and regenerative programs co-opted by cancer cells and immune-mediated pruning during metastatic outbreak

Chromosomal instability (CIN) and epigenetic alterations have been implicated in tumor progression and metastasis; yet how these two hallmarks of cancer are related remains poorly understood. By integrating genetic, epigenetic, and functional analyses at the single cell level, we show that progression of uveal melanoma (UM), the most common intraocular primary cancer in adults, is driven by loss of Polycomb Repressive Complex 1 (PRC1) in a subpopulation of tumor cells. This leads to transcriptional de-repression of PRC1-target genes and mitotic chromosome segregation errors. Ensuing CIN leads to the formation of rupture-prone micronuclei, exposing genomic double-stranded DNA (dsDNA) to the cytosol. This provokes tumor cell-intrinsic inflammatory signaling, mediated by aberrant activation of the cGAS-STING pathway. PRC1 inhibition promotes nuclear enlargement, induces a transcriptional response that is associated with significantly worse patient survival and clinical outcomes, and enhances migration that is rescued upon pharmacologic inhibition of CIN or STING. Thus, deregulation of PRC1 can promote tumor progression by inducing CIN and represents an opportunity for early therapeutic intervention. The molecular underpinnings driving uveal melanoma (UM) progression are unknown. Here the authors show that loss of Polycomb Repressive Complex 1 triggers chromosomal instability, which promotes inflammatory signaling and migration in UM.

Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well. Implementing high-throughput single-cell DNA sequencing for the study of solid tumours has been challenging. Here, the authors present an optimised approach for snap-frozen tissue single nuclei extraction and DNA sequencing, which can be applied to study pancreatic ductal adenocarcinoma evolution and heterogeneity.

Biological insights often depend on comparing conditions such as disease and health. Yet, we lack effective computational tools for integrating single-cell genomics data across conditions or characterizing transitions from normal to deviant cell states. Here, we present Decipher, a deep generative model that characterizes derailed cell-state trajectories. Decipher jointly models and visualizes gene expression and cell state from normal and perturbed single-cell RNA-seq data, revealing shared and disrupted dynamics. We demonstrate its superior performance across diverse contexts, including in pancreatitis with oncogene mutation, acute myeloid leukemia, and gastric cancer.

Hydrogel-supported neural cell cultures are more in vivo-relevant compared to monolayers formed on glass or plastic substrates. However, there is a lack of synthetic microenvironment available for obtaining standardized and easily reproducible cultures characterized by tissue-mimicking cell composition, cell–cell interactions, and functional networks. Synthetic peptides representing the biological properties of the extracellular matrix (ECM) proteins have been reported to promote the adhesion-driven differentiation and functional maturation of neural cells. Thus, such peptides can serve as building blocks for engineering a standardized, all-synthetic environment. In this study, we have compared the effect of two chemically crosslinked hydrogel compositions on primary cerebellar cells: collagen-like peptide (CLP), and CLP with an integrin-binding motif arginine-glycine-aspartate (CLP-RGD), both conjugated to polyethylene glycol molecular templates (PEG-CLP and PEG-CLP-RGD, respectively) and fabricated as self-supporting membranes. Both compositions promoted a spontaneous organization of primary cerebellar cells into tissue-like clusters with fast-rising Ca2+ signals in soma, reflecting action potential generation. Notably, neurons on PEG-CLP-RGD had more neurites and better synaptic efficiency compared to PEG-CLP. For comparison, poly-L-lysine-coated glass and plastic surfaces did not induce formation of such spontaneously active networks. Additionally, contrary to the hydrogel membranes, glass substrates functionalized with PEG-CLP and PEG-CLP-RGD did not sufficiently support cell attachment and, subsequently, did not promote functional cluster formation. These results indicate that not only chemical composition but also the hydrogel structure and viscoelasticity are essential for bioactive signaling. The synthetic strategy based on ECM-mimicking, multifunctional blocks in registry with chemical crosslinking for obtaining tissue-like mechanical properties is promising for the development of fast and well standardized functional in vitro neural models and new regenerative therapies.

Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1⁺ and Psca⁺) and a large population of differentiated cells (Nkx3.1⁺, Pbsn⁺). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells.

As cancers progress, they become increasingly aggressive—metastatic tumours are less responsive to first-line therapies than primary tumours, they acquire resistance to successive therapies and eventually cause death 1 , 2 . Mutations are largely conserved between primary and metastatic tumours from the same patients, suggesting that non-genetic phenotypic plasticity has a major role in cancer progression and therapy resistance 3 , 4 – 5 . However, we lack an understanding of metastatic cell states and the mechanisms by which they transition. Here, in a cohort of biospecimen trios from same-patient normal colon, primary and metastatic colorectal cancer, we show that, although primary tumours largely adopt LGR5 + intestinal stem-like states, metastases display progressive plasticity. Cancer cells lose intestinal cell identities and reprogram into a highly conserved fetal progenitor state before undergoing non-canonical differentiation into divergent squamous and neuroendocrine-like states, a process that is exacerbated in metastasis and by chemotherapy and is associated with poor patient survival. Using matched patient-derived organoids, we demonstrate that metastatic cells exhibit greater cell-autonomous multilineage differentiation potential in response to microenvironment cues compared with their intestinal lineage-restricted primary tumour counterparts. We identify PROX1 as a repressor of non-intestinal lineage in the fetal progenitor state, and show that downregulation of PROX1 licenses non-canonical reprogramming. Colorectal cancer metastasis involves dramatic plasticity and loss of PROX1 -mediated repression of non-intestinal lineages.

Metastasis-initiating cells with stem-like properties drive cancer lethality, yet their origins and relationship to primary-tumor-initiating stem cells are not known. We show that L1CAM cells in human colorectal cancer (CRC) have metastasis-initiating capacity, and we define their relationship to tissue regeneration. L1CAM is not expressed in the homeostatic intestinal epithelium, but is induced and required for epithelial regeneration following colitis and in CRC organoid growth. By using human tissues and mouse models, we show that L1CAM is dispensable for adenoma initiation but required for orthotopic carcinoma propagation, liver metastatic colonization and chemoresistance. L1CAM cells partially overlap with LGR5 stem-like cells in human CRC organoids. Disruption of intercellular epithelial contacts causes E-cadherin-REST transcriptional derepression of L1CAM, switching chemoresistant CRC progenitors from an L1CAM to an L1CAM state. Thus, L1CAM dependency emerges in regenerative intestinal cells when epithelial integrity is lost, a phenotype of wound healing deployed in metastasis-initiating cells.