Biology subjects

Nelander, S.

Publications and source records attributed to Nelander, S..

10 recordsLinked to original sources

bioRxiv2025

A Phenotype-Driven Multi-Omic Atlas of Glioblastoma Invasion

BackgroundGlioblastoma (GBM) invasion is clinically decisive but difficult to model systematically. Existing patient-derived xenograft (PDX) resources rarely couple reproducible in vivo invasion phenotypes with matched multi-omic profiles at scale, limiting mechanistic insight and phenotype-informed therapeutic hypotheses. MethodsWe established the HGCC Phenobank, comprising 65 patient-derived GBM stem-like cultures with matched multi-omic profiling and orthotopic engraftment in 449 mice. Blinded histopathology quantified ten invasion traits per case. These phenotypes were integrated with RNA sequencing, DNA methylation, and mass-spectrometry-based proteomics. Multi-Omic Factor Analysis (MOFA) identified latent molecular programs. Phenotype-specific RNA signatures were matched to LINCS drug-perturbation profiles and validated in 3D gliomasphere and ex vivo brain-slice assays. ResultsTwo dominant, reproducible invasion modes emerged across models: diffuse parenchymal infiltration and perivascular/condensed growth. Proneural cultures formed more aggressive tumors in immunodeficient mice, and mouse survival showed a modest correlation with patient survival in matched cases (Pearson r = 0.1832, p = 0.045). MOFA identified 15 latent factors; Factor 1, enriched for ASCL1/OLIG1/OLIG2 programs and associated with TP53/DCHS2/WNK2 alterations, was linked to increased tumor formation, diffuse invasion, and shorter mouse survival, and stratified GBM patients in TCGA and in our matched patient cohort. Drug-signature matching separated mechanisms targeting diffuse versus perivascular invasion. Experimental validation confirmed phenotype-selective sensitivities, and inhibitors PIK-75 and buparlisib suppressed invasion dynamics across representative models in 3D and brain-slice assays. ConclusionsThe HGCC Phenobank provides the first openly available PDX resource that systematically links GBM invasion phenotypes to multi-omic programs and therapeutic predictions. This framework enables reproducible model selection, mechanistic dissection of invasion modes, and phenotype-guided therapeutic discovery. Key PointsO_LIDiffuse and perivascular invasion define orthogonal GBM axes C_LIO_LIASCL1/OLIG factor links initiation, diffuse growth, and survival C_LIO_LIPhenotype-matched drugs validated; PIK-75 and buparlisib curb invasion dynamics C_LI Importance of the StudyGlioblastoma invasion varies substantially between patients, yet existing patient-derived xeno-graft resources rarely combine reproducible in vivo phenotyping with matched multi-omic profiling at scale. The HGCC Phenobank addresses this gap with standardized, blinded scoring of ten invasion traits across 449 orthotopic xenografts from 65 molecularly characterized GBM stem-like cultures, integrated with transcriptomic, methylomic, and proteomic data. We identify two dominant, reproducible invasion modes and a cross-modal neurodevelopmental program, the ASCL1/OLIG1/2-associated Factor 1, that links tumor initiation, diffuse growth, and survival in mice, and stratifies GBM patients in TCGA and in our matched patient cohort. In a spatially resolved xenograft section, Factor 1 signal localizes to the invasive tumor periphery. By matching phenotype-specific RNA signatures to drug-induced transcriptional responses, we show that invasion phenotypes nominate selective vulnerabilities, exemplified by PIK-75. This openly shared resource enables reproducible model selection, mechanistic dissection of invasion programs, and phenotype-guided therapeutic discovery.

cancer biology↗

bioRxiv2025

Reconstructing the Single-Cell Spatiotemporal Dynamics of Glioblastoma Invasion

Glioblastoma invasion into healthy brain tissue remains a major barrier to effective treatment, yet current models fail to capture its full complexity in a scalable and patient-specific manner. Here, we introduce GlioTrace, a novel ex vivo imaging and AI-based analytical framework that enables real-time, spatiotemporal tracking of glioblastoma invasion dynamics in patient-derived glioma cell culture xenograft (PDCX) brain slices. By integrating whole-specimen confocal microscopy, vascular counterstaining, and an advanced computational pipeline combining convolutional neural networks and Hidden Markov Models, GlioTrace identifies distinct invasion modes, including dynamic morphological switching, vessel-guided migration, and immune cell interactions and quantifies patient-specific variations in invasion plasticity. Using GlioTrace, we demonstrate that targeted therapies can selectively modulate invasion phenotypes, revealing spatially and temporally distinct drug responses. This scalable platform provides an unprecedented window into glioblastoma progression and treatment response, offering a powerful tool for precision oncology and anti-invasion therapeutic development.

cancer biology↗

bioRxiv2024

The invasion phenotypes of glioblastoma depend on plastic and reprogrammable cell states

Glioblastoma (GBM), the most common primary brain cancer in adults, is characterized by rapid local invasion along diverse routes, such as infiltration of white matter tracts and penetration of perivascular spaces. We investigate the hypothesis that GBM invasion routes correlate with the transcriptional states of individual cells and identify regulators of route-specific invasion. Utilizing patient-derived GBM xenograft models, we integrate single-cell transcriptomics and spatial proteomics, revealing that mesenchymal and oligodendrocyte progenitor-like GBM cells migrate perivascularly, while neural progenitor and astrocyte-like GBM cells invade diffusely. Computational reconstruction identifies ANXA1 as a perivascular invasion driver and lineage-restricted transcription factors RFX4 and HOPX as drivers of diffuse invasion, predictive of patient survival. Genetic ablation of these genes alters invasion phenotypes and extends survival in xenografted mice, clarifying the role of cell states in GBM invasion, and highlighting potential therapeutic targets for selective invasion route targeting in GBM patients.

cancer biology↗

bioRxiv2023

Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers

Nervous system cancers contain a large spectrum of transcriptional cell states, reflecting processes active during normal development, injury response and growth. However, we lack a good understanding of these states regulation and pharmacological importance. Here, we describe the integrated reconstruction of such cellular regulatory programs and their therapeutic targets from extensive collections of single-cell RNA sequencing data (scRNA-seq) from both tumors and developing tissues. Our method, termed single-cell Regulatory-driven Clustering (scRegClust), predicts essential kinases and transcription factors in little computational time thanks to a new efficient optimization strategy. Using this method, we analyze scRNA-seq data from both adult and childhood brain cancers to identify transcription factors and kinases that regulate distinct tumor cell states. In adult glioblastoma, our model predicts that blocking the activity of PDGFRA, DDR1, ERBB3 or SOX6, or increasing YBX1 -activity, would potentiate temozolomide treatment. We further perform an integrative study of scRNA-seq data from both cancer and the developing brain to uncover the regulation of emerging meta-modules. We find a meta-module regulated by the transcription factors SPI1 and IRF8 and link it to an immune-mediated mesenchymal-like state. Our algorithm is available as an easy-to-use R package and companion visualization tool that help uncover the regulatory programs underlying cell plasticity in cancer and other diseases.

cancer biology↗

bioRxiv2022

Global hypo-methylation in a subgroup of glioblastoma enriched for an astrocytic signature is associated with increased invasion and altered immune landscape

We describe a new molecular subgroup of glioblastoma, the most prevalent malignant adult brain tumour, harbouring a bias towards hypomethylation at defined differentially methylated regions. This epigenetic signature correlates with an enrichment for an astrocytic gene signature, which together with the identification of enriched predicted binding sites of transcription factors known to cause demethylation and to be involved in astrocytic/glial lineage specification, point to a shared ontogeny between this glioblastoma subgroup and astroglial progenitors. At functional level, increased invasiveness, at least in part mediated by SRPX2, and macrophage infiltration characterise this glioblastoma subgroup.

cancer biology↗

bioRxiv2021

Autocrine signaling explains the emergence of Allee effects in cancer cell populations

In many human cancers, the rate of cell growth depends crucially on the size of the tumour cell population. Low, zero, or negative growth at low population densities is known as the Allee effect; this effect has been studied extensively in ecology, but so far lacks a good explanation in the cancer setting. Here, we formulate and analyze an individual-based model of cancer, in which cell division rates are increased by the local concentration of an autocrine growth factor produced by the cancer cells themselves. We show, analytically and by simulation, that autocrine signaling suffices to cause both strong and weak Allee effects. Whether low cell densities lead to negative (strong effect) or reduced (weak effect) growth rate depends directly on the ratio of cell death to proliferation, and indirectly on cellular dispersal. Our model is consistent with experimental observations of brain tumor cells grown at different densities. We propose that further studying and quantifying population-wide feedback, impacting cell growth, will be central for advancing our understanding of cancer dynamics and treatment, potentially exploiting Allee effects for therapy.

cancer biology↗

bioRxiv2019

NF1 regulates mesenchymal glioblastoma plasticity and aggressiveness through the AP-1 transcription factor FOSL1

The molecular basis underlying Glioblastoma (GBM) heterogeneity and plasticity are not fully understood. Using transcriptomic data of patient-derived brain tumor stem cell lines (BTSCs), classified based on GBM-intrinsic signatures, we identify the AP-1 transcription factor FOSL1 as a key regulator of the mesenchymal (MES) subtype. We provide a mechanistic basis to the role of the Neurofibromatosis type 1 gene (NF1), a negative regulator of the RAS/MAPK pathway, in GBM mesenchymal transformation through the modulation of FOSL1 expression. Depletion of FOSL1 in NF1-mutant human BTSCs and Kras-mutant mouse neural stem cells results in loss of the mesenchymal gene signature, reduction in stem cell properties and in vivo tumorigenic potential. Our data demonstrate that FOSL1 controls GBM plasticity and aggressiveness in response to NF1 alterations.

cancer biology↗

bioRxiv2019

Monotherapy efficacy of BBB-permeable small molecule activators of PP2A in glioblastoma

Glioblastoma (GB) is a fatal disease in which most targeted therapies have clinically failed. However, pharmacological reactivation of tumor suppressors has not been thoroughly studied as yet as a GB therapeutic strategy. Tumor suppressor Protein Phosphatase 2A (PP2A), is inhibited by non-genetic mechanisms in GB, and thus it would be potentially amendable for therapeutic reactivation. Here we demonstrate, that small molecule activators of PP2A (SMAPs), NZ-8-061 and DBK-1154, effectively cross the in vitro model of blood-brain barrier (BBB), and in vivo partition to mouse brain tissue after oral dosing. In vitro, SMAPs exhibit robust cell killing activity against five established GB cell lines, and nine patient-derived primary glioma cell lines. Collectively these cell lines have heterogenous genetic background, kinase inhibitor resistance profile, and stemness properties; and they represent different clinical GB subtypes. Oral dosing of either of the SMAPs significantly reduced growth of infiltrative intracranial GB tumors. DBK-1154, with both higher degree of brain/blood distribution, and more potent in vitro activity against all tested GB cell lines, also significantly increased survival of mice bearing orthotopic GB xenografts. In summary, this report presents a proof-of-principle data for BBB-permeable tumor suppressor reactivation therapy for glioblastoma cells of heterogenous molecular background.

cancer biology↗

bioRxiv2019

Quantifying cell line specific proliferation and migration rates in glioblastoma cells

We have characterised the migration and proliferation rates of a large number of patient-derived glioblastoma cell lines using an individual-based model coupled to an Approximate Bayesian Computation algorithm. We found that the cell lines exhibited a negative correlation between the rate of migration and rate of division. This observation agrees with the Go or Grow hypothesis and highlights patient-specific differences in migration and proliferation.

cancer biology↗

bioRxiv2019

Live detection of neural stem and glioblastoma cells by an oligothiophene derivative

Here we report a luminescent conjugated oligothiophene (LCO), named p-HTMI, for non-invasive and non-amplified real-time detection of live human patient-derived glioblastoma (GBM) cells and embryonic neural stem cells (NSCs). While p-HTMI stained only a small fraction of other cell types investigated, the mere addition of p-HTMI to the cell culture resulted in efficient detection of NSCs or GBM cells from rodents and humans within minutes. p-HTMI is functionalized with a methylated imidazole moiety resembling the side chain of histidine/histamine, and non-methylated analogues were not functional. p-HTMI were readily able to detect a subpopulation of human cells in vivo in mouse brain sections with tumors developed from orthotopically transplanted patient-derived GBM cells. Cell sorting experiments of human GBM cells demonstrated that p-HTMI labeled the same population as CD271, a proposed marker for stem cell-like cells and rapidly migrating cells in glioblastoma. Our results suggest that the LCO p-HTMI is a versatile tool for immediate and selective detection of subpopulations of neural stem and glioma cells.

bioengineering↗