Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modeling glioblastoma heterogeneity as a dynamic network of cell states
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-5422-4243
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Neuro-Oncology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..ORCID iD: 0000-0003-0272-9893
Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..ORCID iD: 0000-0002-2592-3448
Uppsala Univ, Dept Immunol Genet & Pathol, Uppsala, Sweden..
Show others and affiliations
2021 (English)In: Molecular Systems Biology, ISSN 1744-4292, E-ISSN 1744-4292, Vol. 17, no 9, article id e10105Article in journal (Refereed) Published
Abstract [en]

Tumor cell heterogeneity is a crucial characteristic of malignant brain tumors and underpins phenomena such as therapy resistance and tumor recurrence. Advances in single-cell analysis have enabled the delineation of distinct cellular states of brain tumor cells, but the time-dependent changes in such states remain poorly understood. Here, we construct quantitative models of the time-dependent transcriptional variation of patient-derived glioblastoma (GBM) cells. We build the models by sampling and profiling barcoded GBM cells and their progeny over the course of 3 weeks and by fitting a mathematical model to estimate changes in GBM cell states and their growth rates. Our model suggests a hierarchical yet plastic organization of GBM, where the rates and patterns of cell state switching are partly patient-specific. Therapeutic interventions produce complex dynamic effects, including inhibition of specific states and altered differentiation. Our method provides a general strategy to uncover time-dependent changes in cancer cells and offers a way to evaluate and predict how therapy affects cell state composition.

Place, publisher, year, edition, pages
WILEY John Wiley & Sons, 2021. Vol. 17, no 9, article id e10105
Keywords [en]
cell state, cellular barcoding, patient-derived brain tumor cells, single-cell lineage tracing, time-dependent computational models
National Category
Cell Biology Cell and Molecular Biology
Identifiers
URN: urn:nbn:se:uu:diva-495138OAI: oai:DiVA.org:uu-495138DiVA, id: diva2:1730461
Funder
Swedish Cancer SocietySwedish Research CouncilSwedish Foundation for Strategic ResearchAvailable from: 2023-01-24 Created: 2023-01-24 Last updated: 2024-01-15
In thesis
1. Glioblastoma heterogeneity and plasticity: Investigating the roles of BMP4 and SOX2
Open this publication in new window or tab >>Glioblastoma heterogeneity and plasticity: Investigating the roles of BMP4 and SOX2
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The malignant primary brain tumor glioblastoma has a dismal prognosis and is distinguished by its heterogeneous character. Current treatment with surgical resection, radiotherapy and adjuvant chemotherapy with the alkylating agent temozolomide does not provide a cure, but simply prolongs survival by a few months. Since the tumors recur, cells remaining after treatment can act as cancer stem cells and are able to reform the tumor. 

This thesis provides insights into glioblastoma heterogeneity and how dominant transcriptional programs have a substantial impact on glioblastoma cell responses to altered levels of the intrinsic proteins BMP4 and SOX2. SOX2 has a role as a stem cell transcription factor in the normal nervous system and in glioblastoma, while BMP4 acts as a cue for astrocytic differentiation during normal nervous system development. As a response to BMP4, we find a wide spectrum of growth-inhibition across 40 human glioblastoma cell lines and correlate the extent of the response with baseline gene expression in the cells. We discover a connection between high SOX2 expression and a more pronounced growth-inhibitory response and establish a causative relationship between SOX2 downregulation and reduced proliferation in BMP4-responsive cell lines. We also find how BMP4 can induce a senescence-like phenotype in glioblastoma and connect it to a mesenchymal phenotype on a proneural-mesenchymal scale by investigating clonally derived cultures from the same tumor. Through elimination of senescent cells by senolytic treatment and generation p21-knockout cells we also establish a p21-dependence for BMP4-induced senescence.

Studies on cellular organization identify a hierarchical cell-state pattern which the cells move through during culture and show that external perturbations (here by BMP4 and temozolomide) alter this hierarchy, demonstrating a substantial cellular plasticity.

Also, we establish a strategy to eradicate endogenous SOX2 with the inducible exogenous SOX2-system present, demonstrating that SOX2 is not an essential transcription factor in all glioblastomas. 

In summary, this thesis highlights several aspects of inter- and intratumoral heterogeneity as well as cellular plasticity, providing valuable insights that could help guide the glioblastoma community in the pursuit of more effective therapies against glioblastoma. 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2023. p. 55
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1900
Keywords
Glioblastoma, SOX2, BMP4, senescence, plasticity
National Category
Cancer and Oncology Cell and Molecular Biology
Research subject
Oncology; Medical Science; Biology with specialization in Molecular Biology
Identifiers
urn:nbn:se:uu:diva-495137 (URN)978-91-513-1699-4 (ISBN)
Public defence
2023-03-17, Fåhraeussalen, Rudbecklaboratoriet, Dag Hammarskjölds väg 20, Uppsala, 13:00 (English)
Opponent
Supervisors
Available from: 2023-02-23 Created: 2023-01-27 Last updated: 2023-02-23
2. Integrative modeling of intratumoral heterogeneity, plasticity and regulation in nervous system cancers
Open this publication in new window or tab >>Integrative modeling of intratumoral heterogeneity, plasticity and regulation in nervous system cancers
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The adult brain tumor glioblastoma (GBM) is characterized by short survival and a lack of efficient treatments. Median survival is 15 months from time of diagnosis and the 5-year survival rate is only 7 %. There is an urgent need for more efficient treatment against GBM, but there are many challenges, including the high extent of heterogeneity of GBM. The tumoral heterogeneity of GBM ranges from interpatient to intratumoral. The aim of this thesis has been to address unanswered questions relating to the intratumoral heterogeneity of GBM, with three specific focuses; (1) the organization of GBM cell state transitions (paper I and III), (2) the regulation of cell states and cell state transitions (paper II), and (3) targeted interventions against cell states (paper II and IV).

In paper I, we develop an experimental-computational method to measure and quantify cell state transitions. We find that GBM cell states organize hierarchically, with a clear “source state” feeding cells downwards in the hierarchy towards a “sink state” with negative growth rate, but with multi-directional transitions between intermediate states. 

In paper II, we address the lack of computational methods to identify regulators of intratumoral heterogeneity by developing an algorithm called scRegClust that uses scRNA-seq data to estimate regulatory programs. Through an integrative study of the regulatory landscape of neuro-oncology we find two potential regulators of the macrophage-induced mesenchymal transition in GBM.

In paper III, we explore the energy-concept as a way of measuring differentiation potential of single cells, instead of relying on gene markers or gene signatures of stemness. We fit a model called the Ising model from statistical mechanics to scRNA-seq data and show both on synthetic and real data that the estimated Ising energy is a good measure of a cell’s differentiation potential, where high Ising energy indicate a high degree of stemness.

Finally, in paper IV, another experimental-computational method is developed to investigate drug-induced effects on both inter- and intratumoral heterogeneity. 

In summary, the high extent of intratumoral heterogeneity in nervous system cancer is a major caveat for the development of more efficient treatments. In this thesis we have taken a systems biology approach to understand how this heterogeneity is structured and how we can exploit that knowledge for therapeutic purposes. 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2023. p. 53
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1920
Keywords
Nervous system cancer, Glioblastoma, Heterogeneity, Plasticity, Mathematical modeling
National Category
Bioinformatics and Systems Biology
Research subject
Oncology
Identifiers
urn:nbn:se:uu:diva-498239 (URN)978-91-513-1753-3 (ISBN)
Public defence
2023-05-05, Rudbecksalen, Rudbecklaboratoriet, Dag Hammarskjölds väg 20, Uppsala, 13:00 (English)
Opponent
Supervisors
Available from: 2023-04-12 Created: 2023-03-12 Last updated: 2023-04-12

Open Access in DiVA

No full text in DiVA

Authority records

Larsson, IdaDalmo, ErikaDoroszko, MilenaSegerman, AnnaWestermark, BengtNelander, Sven

Search in DiVA

By author/editor
Larsson, IdaDalmo, ErikaElgendy, RamyDoroszko, MilenaSegerman, AnnaWestermark, BengtNelander, Sven
By organisation
Neuro-OncologyScience for Life Laboratory, SciLifeLab
In the same journal
Molecular Systems Biology
Cell BiologyCell and Molecular Biology

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 250 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf