Biology subjects

Gjertsen, B. T.

Publications and source records attributed to Gjertsen, B. T..

5 recordsLinked to original sources

bioRxiv2025

Deep single-cell immune and signaling profiles predict long term therapy response in chronic myeloid leukemia within hours

Chronic myeloid leukemia (CML) is effectively treated with small molecule BCR::ABL1 tyrosine kinase inhibitors (TKIs) but like in all cancers, early identification of suboptimal- and non-responders is a challenge. Through mass cytometry analysis of peripheral blood leukocytes, we collected high-dimensional data from de novo chronic phase CML patients enrolled in two multicenter clinical trials (clinicaltrials.gov NCT01725204 and NCT01061177). In leukocytes, dasatinib and nilotinib inhibited intracellular signaling within one or three hours after first per oral dose, and each TKI had a unique signaling signature reflecting its kinase specificity profile beyond BCR::ABL1. An immune and signaling profile was constructed for each patient, predicting the treatment response (BCR::ABL1IS, %) the first 12 months of treatment. These results show that single cell immune and signaling profiles within hours of first dose can predict 12 months treatment response, anticipating future optimalization of kinase inhibitor treatment within days rather than months.

cancer biology↗

bioRxiv2025

High-dimensional Immune Profiling Following Autologous Hematopoietic Stem Cell Transplantation in Relapsing-Remitting Multiple Sclerosis

Background and ObjectivesAutologous hematopoietic stem cell transplantation (aHSCT) induces durable remission in treatment-refractory relapsing-remitting multiple sclerosis (RRMS). However, to what extent post-transplant immune recovery reflects restoration of pre-treatment state versus selective remodeling remains incompletely understood. We used high-dimensional whole-blood immune profiling to characterize lineage-specific remodeling in patients with RRMS following aHSCT and to compare trajectories with healthy reference profiles. MethodsPeripheral blood from 25 patients with RRMS treated with aHSCT in the RAM-MS trial was analyzed longitudinally at baseline, 100 days, and 6, 12, and 24 months post-transplant. Samples were compared with those from 9 age- and sex-matched healthy controls using a 41-marker mass cytometry panel. Unsupervised clustering and multi-level modeling were used to quantify lineage-level abundance changes and phenotypic remodeling across adaptive and innate compartments. ResultsImmune recovery after aHSCT was characterized by selective and sustained reshaping of specific T-and B-cell subsets rather than uniform restoration of pre-treatment composition. Naive CD4+ and CD8+ T cells gradually repopulated, whereas memory CD4+ T cells remained reduced at 24 months. Memory CD8+ T cells showed a transient early expansion before declining toward baseline levels. Naive B cells expanded early and remained elevated, while memory B cells were durably reduced. B-cell reconstitution involved expansion of activation-associated naive populations alongside contraction of selected memory subsets. Across T-cell compartments, CD161-expressing chemokine receptor-enriched subsets were selectively depleted. Several of these alterations persisted despite partial normalization of overall cell counts. These trajectories were consistent across patients, supporting a robust and reproducible effect of aHSCT on immune architecture. DiscussionaHSCT induces durable, lineage-specific reorganization of adaptive immunity along a shared trajectory across patients, characterized by contraction of inflammatory T-cell programs and hierarchical restructuring of B-cell maturation rather than simple immune restoration.

immunology↗

bioRxiv2025

Nuclear Phase Separation Drives NPM1-mutant Acute Myeloid Leukemia

During cancer development, mutations promote gene expression changes that cause transformation. Leukemia is frequently associated with aberrant HOXA expression driven by translocations in nucleoporin genes or KMT2A, and mutations in NPM1. How disparate mutations converge on this regulatory pathway is not understood. Here we demonstrate that mutant NPM1 (NPM1c) forms nuclear condensates in multiple human cell lines, mouse models, and primary patient samples. We show NPM1c phase separation is necessary and sufficient to coordinate the recruitment of NUP98 and KMT2A to condensates. Through extensive mutagenesis and pharmacological destabilization of phase separation, we find that NPM1c condensates are necessary for regulating gene expression, promoting in vivo expansion, and maintaining the undifferentiated leukemic state. Finally, we show that nucleoporin and KMT2A fusion proteins form condensates that are biophysically indistinguishable from NPM1c condensates. Together, these data define a new condensate underlying leukemias that we term coordinating bodies (C-bodies), and propose C-bodies as a therapeutic vulnerability.

biophysics↗

bioRxiv2022

Identifying predictors of survival in patients with leukemia using single-cell mass cytometry and machine learning

Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for in-depth characterisation of cellular heterogeneity in cancer and other diseases. However, computational identification of cell populations from CyTOF, and utilisation of single cell data for biomarker discoveries faces several technical limitations, and although some computational approaches are available, high-dimensional analyses of single cell data remains quite demanding. Here, we deploy a bioinformatics framework that tackles two fundamental problems in CyTOF analyses namely: a) automated annotation of cell populations guided by a reference dataset, and b) systematic utilisation of single cell data for more effective patient stratification. By applying this framework on several publicly available datasets, we demonstrate that the Scaffold approach achieves good tradeoff between sensitivity and specificity for automated cell type annotation. Additionally, a case study focusing on a cohort of 43 leukemia patients, reported salient interactions between signalling proteins that are sufficient to predict short-term survival at time of diagnosis using the XGBoost algorithm. Our work introduces an automated and versatile analysis framework for CyTOF data with many applications in future precision medicine projects. Datasets and codes are publicly available at: https://github.com/dkleftogi/singleCellClassification

cancer biology↗

bioRxiv2018

Increased Adhesion Of CML Cells By ABL1 Tyrosine Kinase Inhibitors Induce Tunneling Nanotubes

Summary statementThis study describes the effects of tyrosine kinase inhibitors on tunneling nanotube formation via increased adhesion through {beta}-integrin in chronic myeloid leukemia cells.\n\nAbstractThe actin-containing cell-to-cell communicator tunneling nanotube (TNT) is involved in regulation of cell death threshold of leukemic cells, while the mechanism of TNT regulation is mostly unknown. We have investigated TNT formation and its response to treatment in chronic myeloid leukemia (CML) cells with the pathognomonic chimeric fusion kinase BCR-ABL1 after treatment with the tyrosine kinase inhibitor nilotinib and interferon-. Bone marrow cells of chronic phase CML patients and the CML cell line Kcl-22 formed few or no TNTs. Nilotinib and interferon- treatment induced TNT formation in Kcl-22 cells and were found to be linked to increased adherence to fibronectin coated surfaces by restoration of {beta}1-integrin function. This suggests modulation of TNT cell-cell communication in CML as a novel mechanism in kinase inhibitor therapy of CML.

cell biology↗