Explore the vast range of titles available.

Fibroblasts are an essential cell population for human skin architecture and function. While fibroblast heterogeneity is well established, this phenomenon has not been analyzed systematically yet. We have used single-cell RNA sequencing to analyze the transcriptomes of more than 5,000 fibroblasts from a sun-protected area in healthy human donors. Our results define four main subpopulations that can be spatially localized and show differential secretory, mesenchymal and pro-inflammatory functional annotations. Importantly, we found that this fibroblast ‘priming’ becomes reduced with age. We also show that aging causes a substantial reduction in the predicted interactions between dermal fibroblasts and other skin cells, including undifferentiated keratinocytes at the dermal-epidermal junction. Our work thus provides evidence for a functional specialization of human dermal fibroblasts and identifies the partial loss of cellular identity as an important age-related change in the human dermis. These findings have important implications for understanding human skin aging and its associated phenotypes. Solé-Boldo et al characterise dermal fibroblasts in human skin not exposed to sunlight by single-cell RNA sequencing. They identify fibroblast subpopulations and see that aging reduces their identity and predicted interactions with other skin cells, providing insights into age-related changes in skin.

Recent studies invoke phase separation as a mechanism underlying the formation of ‘transcriptional condensates’. However, similarities between transcriptional condensates and the previously introduced ‘transcription factories’ model raise the question of what distinguishes the two models. One crucial aspect to consider is the contribution of intrinsically disordered regions in transcription-relevant factors.Rippe and Papantonis suggest that intrinsically disordered regions in transcription-relevant factors underlie the formation of both ‘transcriptional condensates’ and ‘transcription factories’.

Relapsed/refractory multiple myeloma (RRMM) is characterized by a remarkable heterogeneity and high drug resistance. Here, the authors analyse RRMM samples by single-cell RNA-sequencing, revealing molecular features associated with high-risk chromosomal 1q-gain and changes in the tumor microenvironment. Virtually all patients with multiple myeloma become unresponsive to treatment over time. Relapsed/refractory multiple myeloma (RRMM) is accompanied by the clonal evolution of myeloma cells with heterogeneous genomic aberrations and profound changes of the bone marrow microenvironment (BME). However, the molecular mechanisms that drive drug resistance remain elusive. Here, we analyze the heterogeneous tumor cell population and its complex interaction network with the BME of 20 RRMM patients by single cell RNA-sequencing before/after treatment. Subclones with chromosome 1q-gain express a specific transcriptomic signature and frequently expand during treatment. Furthermore, RRMM cells shape an immune suppressive BME by upregulation of inflammatory cytokines and close interaction with the myeloid compartment. It is characterized by the accumulation of PD1 + γδ T-cells and tumor-associated macrophages as well as the depletion of hematopoietic progenitors. Thus, our study resolves transcriptional features of subclones in RRMM and mechanisms of microenvironmental reprogramming with implications for clinical decision-making.

Tumour heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is known to affect the efficacy of cancer therapy, most personalized treatment approaches do not account for intratumour heterogeneity. We addressed this issue by studying the heterogeneity of nodal B-cell lymphomas by single-cell RNA-sequencing and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subpopulations and compared their drug-response and genomic profiles. Malignant subpopulations from the same patient responded strikingly differently to anti-cancer drugs ex vivo, which recapitulated subpopulation-specific drug sensitivity during in vivo treatment. Infiltrating T cells represented the majority of non-malignant cells, whose gene-expression signatures were similar across all donors, whereas the frequencies of T-cell subsets varied significantly between the donors. Our data provide insights into the heterogeneity of nodal B-cell lymphomas and highlight the relevance of intratumour heterogeneity for personalized cancer therapy.Roider et al. combine scRNA-seq and transcriptome-informed flow cytometry, and uncover transcriptionally different malignant subclones with distinct drug responses and T-cell profiles in B-cell non-Hodgkin lymphoma.

In living cells, most proteins diffuse over distances of micrometres within seconds. Protein translocation is constrained due to the cellular organization into subcompartments that impose diffusion barriers and guide enzymatic activities to their targets. Here, we introduce an approach to retrieve structural features from the scale-dependent mobility of green fluorescent protein monomer and multimers in human cells. We measure protein transport simultaneously between hundreds of positions by multi-scale fluorescence cross-correlation spectroscopy using a line-illuminating confocal microscope. From these data we derive a quantitative model of the intracellular architecture that resembles a random obstacle network for diffusing proteins. This topology partitions the cellular content and increases the dwell time of proteins in their local environment. The accessibility of obstacle surfaces depends on protein size. Our method links multi-scale mobility measurements with a quantitative description of intracellular structure that can be applied to evaluate how drug-induced perturbations affect protein transport and interactions. Numerous obstacles posed by cellular subcompartments and structures constrain protein transport in the cell. Here, Baum et al. map the intracellular topology from a diffusing protein’s point of view by measuring the diffusive movements of fluorescently labelled reporter proteins in living cells on multiple time and length scales.

The mammalian epigenome contains thousands of heterochromatin nanodomains (HNDs) marked by di- and trimethylation of histone H3 at lysine 9 (H3K9me2/3), which have a typical size of 3–10 nucleosomes. However, what governs HND location and extension is only partly understood. Here, we address this issue by introducing the chromatin hierarchical lattice framework (ChromHL) that predicts chromatin state patterns with single-nucleotide resolution. ChromHL is applied to analyse four HND types in mouse embryonic stem cells that are defined by histone methylases SUV39H1/2 or GLP, transcription factor ADNP or chromatin remodeller ATRX. We find that HND patterns can be computed from PAX3/9, ADNP and LINE1 sequence motifs as nucleation sites and boundaries that are determined by DNA sequence (e.g. CTCF binding sites), cooperative interactions between nucleosomes as well as nucleosome-HP1 interactions. Thus, ChromHL rationalizes how patterns of H3K9me2/3 are established and changed via the activity of protein factors in processes like cell differentiation. The ability to predict epigenetic regulation is an important challenge in biology. Here the authors describe heterochromatin nanodomains (HNDs) and compare four different types of H3K9me2/3-marked HNDs in mouse embryonic stem cells. They further develop a computational framework to predict genome-wide HND maps from DNA sequence and protein concentrations, at single-nucleotide resolution.

Telomere maintenance by telomerase activation or alternative lengthening of telomeres (ALT) is a major determinant of poor outcome in neuroblastoma. Here, we screen for ALT in primary and relapsed neuroblastomas ( n  = 760) and characterize its features using multi-omics profiling. ALT-positive tumors are molecularly distinct from other neuroblastoma subtypes and enriched in a population-based clinical sequencing study cohort for relapsed cases. They display reduced ATRX/DAXX complex abundance, due to either ATRX mutations (55%) or low protein expression. The heterochromatic histone mark H3K9me3 recognized by ATRX is enriched at the telomeres of ALT-positive tumors. Notably, we find a high frequency of telomeric repeat loci with a neuroblastoma ALT-specific hotspot on chr1q42.2 and loss of the adjacent chromosomal segment forming a neo-telomere. ALT-positive neuroblastomas proliferate slowly, which is reflected by a protracted clinical course of disease. Nevertheless, children with an ALT-positive neuroblastoma have dismal outcome. Alternative lengthening of telomeres (ALT) is associated with a poor outcome in neuroblastoma. Here, the authors find that ALT is associated with mutated ATRX and/or reduced protein abundance, frequent telomeric repeat loci and heterochromatic telomeric chromatin.

The realization that the cell is abundantly compartmentalized into biomolecular condensates has opened new opportunities for understanding the physics and chemistry underlying many cellular processes 1 , fundamentally changing the study of biology 2 . The term biomolecular condensate refers to non-stoichiometric assemblies that are composed of multiple types of macromolecules in cells, occur through phase transitions, and can be investigated by using concepts from soft matter physics 3 . As such, they are intimately related to aqueous two-phase systems 4 and water-in-water emulsions 5 . Condensates possess tunable emergent properties such as interfaces, interfacial tension, viscoelasticity, network structure, dielectric permittivity, and sometimes interphase pH gradients and electric potentials 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 – 14 . They can form spontaneously in response to specific cellular conditions or to active processes, and cells appear to have mechanisms to control their size and location 15 , 16 – 17 . Importantly, in contrast to membrane-enclosed organelles such as mitochondria or peroxisomes, condensates do not require the presence of a surrounding membrane.

Leiomyosarcoma (LMS) is an aggressive mesenchymal malignancy with few therapeutic options. The mechanisms underlying LMS development, including clinically actionable genetic vulnerabilities, are largely unknown. Here we show, using whole-exome and transcriptome sequencing, that LMS tumors are characterized by substantial mutational heterogeneity, near-universal inactivation of TP53 and RB1 , widespread DNA copy number alterations including chromothripsis, and frequent whole-genome duplication. Furthermore, we detect alternative telomere lengthening in 78% of cases and identify recurrent alterations in telomere maintenance genes such as ATRX , RBL2 , and SP100 , providing insight into the genetic basis of this mechanism. Finally, most tumors display hallmarks of “BRCAness”, including alterations in homologous recombination DNA repair genes, multiple structural rearrangements, and enrichment of specific mutational signatures, and cultured LMS cells are sensitive towards olaparib and cisplatin. This comprehensive study of LMS genomics has uncovered key biological features that may inform future experimental research and enable the design of novel therapies. The molecular genetic landscape of leiomyosarcoma (LMS) is largely unknown. Here, the authors identify frequent DNA copy number alterations, whole-genome duplication, TP53 and RB1 inactivation, alternative telomere lengthening, and genomic imprints of defective DNA repair via homologous recombination as a potential therapeutic target in LMS patients.

Background Spatial transcriptomics technologies are revolutionizing our understanding of intra-tumor heterogeneity and the tumor microenvironment by revealing single-cell molecular profiles within their spatial tissue context. The rapid development of spatial transcriptomics methods, each with unique characteristics, makes it challenging to select the most suitable technology for specific research objectives. Here, we compare four imaging-based approaches—RNAscope HiPlex, Molecular Cartography, Merscope, and Xenium—alongside Visium, a sequencing-based method. These technologies were employed to study cryosections of medulloblastoma with extensive nodularity (MBEN), a tumor chosen for its distinct microanatomical features. Results Our analysis reveals that automated imaging-based spatial transcriptomics methods are well-suited to delineate the intricate MBEN microanatomy and capture cell-type-specific transcriptome profiles. We devise approaches to compare the sensitivity and specificity of different methods, along with their unique attributes, to guide method selection based on the research objective. Furthermore, we demonstrate how reimaging slides after the spatial transcriptomics analysis can significantly improve cell segmentation accuracy and integrate additional transcript and protein readouts, expanding the analytical possibilities and depth of insight. Conclusions This study underscores important distinctions between spatial transcriptomics technologies and offers a framework for evaluating their performance. Our findings support informed decisions regarding methods and outline strategies to improve the resolution and scope of spatial transcriptomic analyses, ultimately advancing spatial transcriptomics applications in solid tumor research.