A Patient-Derived Cell Atlas Informs Precision Targeting of Glioblastoma

Johansson, Patrik; Krona, Cecilia; Kundu, Soumi; Doroszko, Milena; Baskaran, Sathishkumar; Schmidt, Linnéa; Vinel, Claire; Almstedt, Elin; Elgendy, Ramy; Elfineh, Ludmila; Gallant, Caroline J.; Lindström, Sara; Gago, F.J.F.; Hakkarainen, Aleksi; Sipilä, Petra; Häggblad, Maria; Märtens, Ulf; Lundgren, Bo; Frigault, Melanie M.; Lane, David P.; Swartling, Fredrik J.; Uhrbom, Lene; Nestor, Marika; Marino, Silvia; Nelander, Sven

doi:10.1016/j.celrep.2020.107897

Cited by 49 publications

(68 citation statements)

References 75 publications

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“…In summary, these results complementing the distinct advantages of patient-derived 2D and 3D models present a novel workflow for screening small groups of drugs with the potential for a more personalized approach in the treatment of recurrent glioblastoma. Moreover, it is possible to scale up this process further to include additional drugs that also shown promise in the clinical trial setup (e.g., regorafenib [ 128 ], and other Phase II-IV clinical trials drugs as recently reviewed by Cruz DaSilva et al [ 129 ]) as well as drug candidates identified in large scale screenings using 2D cultures of patient-derived cells [ 130 ], which have not been yet tested in 3D GBO models.…”

Section: Discussionmentioning

confidence: 99%

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

Lenin

Ponthier

Scheer

et al. 2021

IJMS

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Glioblastoma is one of the most common and lethal types of primary brain tumor. Despite aggressive treatment with chemotherapy and radiotherapy, tumor recurrence within 6–9 months is common. To overcome this, more effective therapies targeting cancer cell stemness, invasion, metabolism, cell death resistance and the interactions of tumor cells with their surrounding microenvironment are required. In this study, we performed a systematic review of the molecular mechanisms that drive glioblastoma progression, which led to the identification of 65 drugs/inhibitors that we screened for their efficacy to kill patient-derived glioma stem cells in two dimensional (2D) cultures and patient-derived three dimensional (3D) glioblastoma explant organoids (GBOs). From the screening, we found a group of drugs that presented different selectivity on different patient-derived in vitro models. Moreover, we found that Costunolide, a TERT inhibitor, was effective in reducing the cell viability in vitro of both primary tumor models as well as tumor models pre-treated with chemotherapy and radiotherapy. These results present a novel workflow for screening a relatively large groups of drugs, whose results could lead to the identification of more personalized and effective treatment for recurrent glioblastoma.

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Section: Discussionmentioning

confidence: 99%

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

Lenin

Ponthier

Scheer

et al. 2021

IJMS

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“…Mutually exclusive expression can be observed as genetic alterations [34, 35, 36, 37] and negative correlations [38, 39] between two specific genes. Genetic alterations lead to protein production because mutually exclusive gene pairs might be amplified in different cell populations [34].…”

Section: Methodsmentioning

confidence: 99%

Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

Nakajima

Hayashi

Fujiki

et al. 2021

Preprint

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Single-cell RNA-seq (scRNA-seq) can be used to characterize cellular heterogeneity in thousands of cells. The reconstruction of a gene network based on coexpression patterns is a fundamental task in scRNA-seq analyses, and the mutual exclusivity of gene expression can be critical for understanding such heterogeneity. Here, we propose an approach for detecting communities from a genetic network constructed on the basis of coexpression properties. The community-based comparison of multiple coexpression networks enables the identification of functionally related gene clusters that cannot be fully captured through differential gene expression-based analysis. We also developed a novel metric referred to as the exclusively expressed index (EEI) that identifies mutually exclusive gene pairs from sparse scRNA-seq data. EEI quantifies and ranks the exclusive expression levels of all gene pairs from binary expression patterns while maintaining robustness against a low sequencing depth. We applied our methods to glioblastoma scRNA-seq data and found that gene communities were partially conserved after serum stimulation despite a considerable number of diﬀerentially expressed genes. We also demonstrate that the identification of mutually exclusive gene sets with EEI can improve the sensitivity of capturing cellular heterogeneity. Our methods complement existing approaches and provide new biological insights, even for a large, sparse dataset, in the single-cell analysis field.

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“…A superior alternative to these permanent cells is patient-derived cell lines in low passages. Published biobanks reflect all kinds of molecular subtypes of glioblastoma [ 174 , 175 , 176 , 177 ]. If the molecular status of the primary tumor is known and the corresponding clinical patient data are available, the correspondingly derived cell lines are of particular value for preclinical studies.…”

Section: Preclinical Models To Study Glutamate Interaction and Tumor-associated Epilepsymentioning

confidence: 99%

Glutamatergic Mechanisms in Glioblastoma and Tumor-Associated Epilepsy

Lange

Hörnschemeyer

Kirschstein

2021

Cells

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The progression of glioblastomas is associated with a variety of neurological impairments, such as tumor-related epileptic seizures. Seizures are not only a common comorbidity of glioblastoma but often an initial clinical symptom of this cancer entity. Both, glioblastoma and tumor-associated epilepsy are closely linked to one another through several pathophysiological mechanisms, with the neurotransmitter glutamate playing a key role. Glutamate interacts with its ionotropic and metabotropic receptors to promote both tumor progression and excitotoxicity. In this review, based on its physiological functions, our current understanding of glutamate receptors and glutamatergic signaling will be discussed in detail. Furthermore, preclinical models to study glutamatergic interactions between glioma cells and the tumor-surrounding microenvironment will be presented. Finally, current studies addressing glutamate receptors in glioma and tumor-related epilepsy will be highlighted and future approaches to interfere with the glutamatergic network are discussed.

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A Patient-Derived Cell Atlas Informs Precision Targeting of Glioblastoma

Abstract: Highlights d A resource of 100 pharmacologically characterized patientderived glioblastoma lines d Integrated analyses define associations between drug response, pathways, and mutations d The response to proteasome inhibitors is linked to TP53 and CDKN2A/B aberrations

Cited by 49 publications

References 75 publications

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

A Drug Screening Pipeline Using 2D and 3D Patient-Derived In Vitro Models for Pre-Clinical Analysis of Therapy Response in Glioblastoma

Codependency and mutual exclusivity for gene community detection from sparse single-cell transcriptome data

Glutamatergic Mechanisms in Glioblastoma and Tumor-Associated Epilepsy

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