Explore Sid Sijbrandij's osteosarcoma research data: single-cell transcriptomics, tissue imaging, cell clusters, and gene set enrichment analysis from his own tumor samples.
RANK is essential for osteoclast and lymph node development
A biweekly scientific journal publishing high-quality research in molecular biology and genetics, cancer biology, biochemistry, and related fields
Hierarchical classification of immune cell transcriptomes at population-scale
Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress is constrained by the lack of independent, high-resolution benchmarks, as the routine integration of datasets introduces statistical dependencies that artificially inflate model generalizability. Here, we present the single-cell universal classification omnibus (Suco), a resource of independent, uniform expert annotations, and Compocyte, a modular hierarchical classifier. Together, they establish a framework designed for the scale of human population immunology. This approach substantially outperforms existing classifiers while facilitating expert review of ambiguous annotations. Applying Compocyte across 50 studies, including three newly generated datasets, we classified 15.6 million leukocytes from 3,965 patients. Within this expansive cohort, we identified a new tumor-associated resorptive macrophage phenotype, a non-canonical monocyte subtype in subclinical cytokine release syndrome, and the programmatic erosion of T cell memory stemness across metastatic sites. Suco and Compocyte thus provide a generalizable architecture and benchmark capable of sustaining high-resolution annotation across massive clinical cohorts. ### Competing Interest Statement CMR has consulted regarding oncology drug development with Amgen, AstraZeneca, Daiichi Sankyo, Genentech, Merck, and Novartis, and has received licensing and royalty payments for DLL3-directed therapeutics. T.W. reports stock ownership for Roche, Astra Zeneca, Bayer, Innate Pharma, Kyntra, Illumina, 10x Genomics, and Merck KGaA as well as research funding from Atrandi Biosciences, Vilnius, Lithuania; CanVirex AG, Basel Switzerland; and Institut fuer Klinische Krebsforschung GmbH, Frankfurt, Germany, and travel funding from Roche, Basel, Switzerland. S.Z. reports advisory board membership and honoraria from Amgen, Astellas, AstraZeneca, Bayer, Bristol-Myers Squibb, Daiichi Sankyo, Eisai, EUSA, Gilead, Ipsen, Johnson&Johnson, Lilly, MedSir, Medtoday, Merck, MSD, Novartis, Pfizer, Roche, Sanofi Aventis, StreamedUp, Urotrials, Urotube, Zentiva and resarch funding from Eisai. S.Z. reports clinical trial support from Amgen, AstraZeneca, AVEO, Bayer, Biontech, Bristol-Myers Squibb, Calithera, Exelixis, Gilead, Lilly, MSD, Novartis, Pfizer, Roche, Seagen/Astellas, Urotrials and travels & conference support from Amgen, Astellas, AstraZeneca, Bayer, EISAI, Ipsen, Johnson&Johnson, Merck, MSD, Pfizer. All remaining authors declare no relevant competing interests. Spanish Association Against Cancer, PI049999 Federal Ministry of Research, Technology and Space, 001001KT2322 National Cancer Institute, R35 CA263816 National Cancer Institute, U24 CA213274 National Cancer Institute, P30 CA008748 Research Council of Lithuania, P-MIP-24-93
Temporal tissue dynamics from a spatial snapshot
Physiological and pathological processes such as inflammation and cancer emerge from interactions between cells over time1. However, methods to follow cell populations over time within the native context of a human tissue are lacking because a biopsy offers only a single snapshot. Here we present one-shot tissue dynamics reconstruction (OSDR), an approach to estimate a dynamical model of cell populations based on a single tissue sample. OSDR uses spatial proteomics to learn how the composition of cellular neighbourhoods influences division rate, providing a dynamical model of cell population change over time. We apply OSDR to human breast cancer data2–4, and reconstruct two fixed points of fibroblasts and macrophage interactions5,6. These fixed points correspond to hot and cold fibrosis7, in agreement with co-culture experiments that measured these dynamics directly8. We then use OSDR to discover a pulse-generating excitable circuit of T and B cells in the tumour microenvironment, suggesting temporal flares of anticancer immune responses. Finally, we study longitudinal biopsies from a triple-negative breast cancer clinical trial3, in which OSDR predicts the collapse of the tumour cell population in responders but not in non-responders, based on early-treatment biopsies. OSDR can be applied to a wide range of spatial proteomics assays to enable analysis of tissue dynamics based on patient biopsies.
Mathematical Discovery of Potential Therapeutic Targets: Application to Rare Melanomas
Patients with rare types of melanoma such as acral, mucosal, or uveal melanoma, have lower survival rates than patients with cutaneous melanoma; these lower survival rates reflect the lower objective response rates to immunotherapy compared to cutaneous melanoma. Understanding tumor-immune dynamics in rare melanomas is critical for the development of new therapies and for improving response rates to current cancer therapies. Progress has been hindered by the lack of clinical data and the need for better preclinical models of rare melanomas. Canine melanoma provides a valuable comparative oncology model for rare types of human melanomas. We analyzed RNA sequencing data from canine melanoma patients and combined this with literature information to create a novel mechanistic mathematical model of melanoma-immune dynamics. Sensitivity analysis of the mathematical model indicated influential pathways in the dynamics, providing support for potential new therapeutic targets and future combinations of therapies. We share our learnings from this work, to help enable the application of this proof-of-concept workflow to other rare disease settings with sparse available data.
LLM-Assisted Reanalysis of Unsolved Rare Disease Genomes Increases Diagnostic Yield
Rare and undiagnosed genetic disorders affect millions of patients globally, and many patients endure years of inconclusive testing. Conventional genomic interpretation can be insufficiently sensit...
Long-term use of denosumab and its association with skeletal-related events and osteonecrosis of the jaw
Denosumab, an inhibitor of receptor activator of nuclear factor kappa-B ligand, reduces skeletal-related events (SREs) and is approved for solid tumors with bone metastases. We studied long-term denosumab efficacy and safety because real-world data is scarce. This single-arm, single-center retrospective study included denosumab-treated breast cancer patients with bone metastases. Kaplan–Meier survival curves assessed exposure, SREs, osteonecrosis of the jaw (ONJ), and death. 132 patients were enrolled. The median denosumab exposure was 28.3 months (range 1.0–84.9). In the first year, 11.1% experienced SREs. This increased to 18.6% in the second, 21% in the third, and 35.1% in the fourth year and beyond. The median time to first on-study SRE has not been reached. 10 denosumab users (7.6%) developed ONJ. ONJ incidence was 0.9% in the first year, 6.2% in the second, 13.6% in the third, and 16.2% in subsequent years. The median time to first on-study ONJ has not been reached yet. Seven patients resumed denosumab after careful management of ONJ. Our data suggest that long-term treatment with denosumab may further prevent or postpone SREs at the cost of an increased risk of ONJ. The majority of patients who resumed denosumab did not experience a recurrence of ONJ.
Martin Krzywinski - Data Visualization, Design, Science and Art - Canada's Michael Smith Genome Sciences Centre
I present clearly, connect broadly, spark imagination and encourage enthusiasm for inquiry and explanation. I create visuals with analytical clarity and artistic dimensions.
On cell types and cell states
The advent of single-cell genomics has brought about new efforts to characterize and catalog all of the cell types in the human body. Despite these efforts, the very definition of a “cell type” is under debate. In this post, I will discuss a conceptual framework for defining cell types as subsets of states in an underlying cellular state space. Moreover, I will link the cellular state space to biomedical ontologies that attempt to capture biological knowledge regarding cell types.
Osteoclast differentiation and activation
Osteoclasts are specialized cells derived from the monocyte/macrophage haematopoietic lineage that develop and adhere to bone matrix, then secrete acid and lytic enzymes that degrade it in a specialized, extracellular compartment. Discovery of the RANK signalling pathway in the osteoclast has provided insight into the mechanisms of osteoclastogenesis and activation of bone resorption, and how hormonal signals impact bone structure and mass. Further study of this pathway is providing the molecular basis for developing therapeutics to treat osteoporosis and other diseases of bone loss.
Osteoimmunology: The Conceptual Framework Unifying the Immune and Skeletal Systems
The immune and skeletal systems share a variety of molecules, including cytokines, chemokines, hormones, receptors, and transcription factors. Bone cells interact with immune cells under physiological and pathological conditions. Osteoimmunology was created as a new interdisciplinary field in large part to highlight the shared molecules and reciprocal interactions between the two systems in both heath and disease. Receptor activator of NF-κB ligand (RANKL) plays an essential role not only in the development of immune organs and bones, but also in autoimmune diseases affecting bone, thus effectively comprising the molecule that links the two systems. Here we review the function, gene regulation, and signal transduction of osteoimmune molecules, including RANKL, in the context of osteoclastogenesis as well as multiple other regulatory functions. Osteoimmunology has become indispensable for understanding the pathogenesis of a number of diseases such as rheumatoid arthritis (RA). We review the various osteoimmune pathologies, including the bone destruction in RA, in which pathogenic helper T cell subsets [such as IL-17-expressing helper T (Th17) cells] induce bone erosion through aberrant RANKL expression. We also focus on cellular interactions and the identification of the communication factors in the bone marrow, discussing the contribution of bone cells to the maintenance and regulation of hematopoietic stem and progenitors cells. Thus the time has come for a basic reappraisal of the framework for understanding both the immune and bone systems. The concept of a unified osteoimmune system will be absolutely indispensable for basic and translational approaches to diseases related to bone and/or the immune system.
Comparing phenotypic manifolds with Kompot: Detecting differential abundance and gene expression at single-cell resolution
Single-cell studies are frequently designed to compare across conditions such as health and disease. However, existing computational approaches typically rely on grouping cells into discrete populations before making comparisons, which can limit resolution for detecting state-dependent changes. Here, we introduce Kompot, a statistical framework for comparative analysis of multi-condition single-cell data. Kompot quantifies both differential abundance, capturing how cells redistribute across the phenotypic space, and differential expression, identifying condition-specific transcriptional changes that may be localized, heterogeneous, or oppositely regulated across states. By modeling cell density and gene expression as continuous functions over a shared cell-state representation, Kompot enables single-cell–resolution inference with principled uncertainty estimates, without requiring predefined clusters or cell types. Applying Kompot to aging murine bone marrow, we identified a continuum of shifts in hematopoietic stem cell and mature cell states, transcriptional remodeling of monocytes independent of compositional changes, and divergent regulation of oxidative stress response genes across cell types. We demonstrate the utility of Kompot in disease settings by identifying cell-state and gene expression changes associated with improved efficacy of combinatorial immunotherapy in melanoma. Additionally, Kompot enables multi-sample comparative analysis by accounting for sample-to-sample heterogeneity. By capturing both global and cell-state–specific effects of perturbation, the Kompot framework is broadly applicable to dissecting condition-specific effects in complex single-cell landscapes. ### Competing Interest Statement The authors have declared no competing interest. National Institutes of Health, R35GM147125, R01CA292932, T32GM136534, S10OD028685 The Mark Foundation for Cancer Research, https://ror.org/00v7th354, Endeavor Award Edward P. Evans Foundation, https://ror.org/03h22gm35, Discovery Research Grant Brotman Baty Institute, https://ror.org/03jxvbk42, Pilot Award
Severe osteopetrosis, defective interleukin‐1 signalling and lymph node organogenesis in <i>TRAF6</i> ‐deficient mice
Background TRAF6, a member of the tumour necrosis factor receptor‐associated factor family, was first identified as a transducer of CD40 and interleukin‐1 receptor (IL‐1R) signals based on the interaction of TRAF6 with the cytoplasmic tail of CD40 and with the IL‐1R associated kinase in vitro . However, the functions of TRAF6 in vivo remain unidentified. Results We show that TRAF6 −/− mice exhibit severe osteopetrosis and are defective in osteoclast formation. In vitro culture experiments revealed that osteoclast precursor cells derived from TRAF6 −/− mice are unable to differentiate to functional osteoclasts in response to osteoclast differentiation factor (ODF). In bone marrow of TRAF6 −/− mice, the number of sIgM + B220 + immature B cells is markedly reduced while the ratio of proB to preB cells is not affected. In contrast, development of thymocytes is not affected. Furthermore, TRAF6 −/− mice are defective in lymph node organogenesis and IL‐1 signalling in thymocytes. Conclusions The results identify TRAF6 as an essential component of ODF signalling pathway, and also show that TRAF6 plays pivotal roles in immune and inflammatory systems in vivo .
Organism-scale annotation with Pan-human Azimuth
Single-cell atlases now span many human tissues, but inconsistent annotations across studies limit their utility as a unified reference. We introduce Pan-human Azimuth, a supervised neural network that maps human cells from diverse tissues and datasets onto a single hierarchical organism-scale typology.
OSTEOIMMUNOLOGY: Interplay Between the Immune System and Bone Metabolism
Studies of bone and the immune system have converged in recent years under the banner of osteoimmunology. The immune system is spawned in the bone marrow reservoir, and investigators now recognize that important niches also exist there for memory lymphocytes. At the same time, various factors produced during immune responses are capable of profoundly affecting regulation of bone. Mechanisms have evolved to prevent excessive interference by the immune system with bone homeostasis, yet pathologic bone loss is a common sequela associated with autoimmunity and cancer. There are also developmental links, or parallels, between bone and the immune system. Cells that regulate bone turnover share a common precursor with inflammatory immune cells and may restrict themselves anatomically, in part by utilizing a signaling network analogous to lymphocyte costimulation. Efforts are currently under way to further characterize how these two organ systems overlap and to develop therapeutic strategies that benefit from this understanding.
Ramez Naam on Twitter / X
There was a site years ago called CureTogether where patients could share information in a structured way on their disease, regimen, and progress, working towards a sort of bottoms-up clinical trial. 23andMe acquired them and it seems to be mostly dead.— Ramez Naam (@ramez) September 14, 2025
Molecular Signaling Pathways and Essential Metabolic Elements in Bone Remodeling: An Implication of Therapeutic Targets for Bone Diseases
Bone is one of the dynamic tissues in the human body that undergoes continuous remodelling through subsequent actions of bone cells, osteoclasts, and osteoblasts. Several signal transduction pathways are involved in the transition of mesenchymal stem cells into osteoblasts. These primarily include Runx2, ATF4, Wnt signaling and sympathetic signalling. The differentiation of osteoclasts is controlled by M-CSF, RANKL, and costimulatory signalling. It is well known that bone remodelling is regulated through receptor activator of nuclear factor-kappa B ligand followed by the binding to RANK, which eventually induces the differentiation of osteoclasts. The resorbing osteoclasts secrete TRAP, cathepsin K, MMP-9 and gelatinase to digest the proteinaceous matrix of type I collagen and form a saucer-shaped lacuna along with resorption tunnels in the trabecular bone. Osteoblasts secrete a soluble decoy receptor, osteoprotegerin that prevents the binding of RANK/RANKL and thus moderating osteoclastogenesis. Moreover, bone homeostasis is also regulated by several growth factors, cytokines, calciotropic hormones, parathyroid hormone and sex steroids. The current review presents a correlation of the probable molecular targets underlying the regulation of bone mass and the role of essential metabolic elements in bone remodelling. Targeting these signaling pathways may help design newer therapies for treating bone diseases.
