Evidence map›Paper›PMID 37171617›Full record

ArticleCellular and molecular life sciences : CMLS2023

Single-cell molecular profiling using ex vivo functional readouts fuels precision oncology in glioblastoma.

Dena Panovska, Pouya Nazari, Basiel Cole, Pieter-Jan Creemers, Marleen Derweduwe, Lien Solie, Sofie Van Gassen, Annelies Claeys, Tatjana Verbeke, Elizabeth F Cohen and 13 more

Open access · greenAbstract read
In one paragraph

Article in Cellular and molecular life sciences : CMLS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors at 9 institutions in 2 countries.

Dena PanovskaDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Pouya NazariDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Basiel ColeDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Pieter-Jan CreemersDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Marleen DerweduweDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Lien SolieDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Sofie Van GassenData Mining and Modeling for Biomedicine Group, VIB Inflammation Research Center, Ghent University, Ghent, Belgium.
Annelies ClaeysDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Tatjana VerbekeDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Elizabeth F CohenDepartment of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.
Michael Y TolstorukovDepartment of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.
Yvan SaeysData Mining and Modeling for Biomedicine Group, VIB Inflammation Research Center, Ghent University, Ghent, Belgium.
David Van der PlankenAZNikolaas Ziekenhuis, Sint-Niklaas, Belgium.
Francesca M BosisioDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Eric PutNeurosurgery Department, Faculty of Medicine and Life Sciences UHasselt, Hasselt, Belgium.
Sven BampsNeurosurgery Department, Faculty of Medicine and Life Sciences UHasselt, Hasselt, Belgium.
Paul M ClementDepartment of Oncology, KU Leuven/UZ Leuven, Leuven, Belgium.
Michiel VerfaillieEuropaziekenhuizen, Cliniques de l'Europe, Sint-Elisabeth, Brussels, Belgium.
Raf SciotDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Keith L LigonDepartment of Informatics and Analytics, Dana-Farber Cancer Institute, Boston, MA, USA.
Steven De VleeschouwerDepartment of Neurosurgery, University Hospitals (UZ) Leuven, Leuven, Belgium.
Asier AntoranzDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium.
Frederik De SmetDepartment of Imaging and Pathology, KU Leuven, Herestraat 49, Box 1032, Leuven, Belgium. frederik.desmet@kuleuven.be.ORCID http://orcid.org/0000-0002-6669-3335
KU Leuven · BEUniversitair Ziekenhuis Leuven · BEDana-Farber Cancer Institute · USGhent University · BEHasselt University · BEBrigham and Women's Hospital · USEurope Hospitals · BEVIB-KU Leuven Center for Microbiology · BEVlaamse Vereniging voor Obstetrie en Gynaecolo · BE

Funding

Genetic evolution of glioblastomas during radiation and temozolomide therapyR01CA188228 · NCI · DANA-FARBER CANCER INST · PI BEROUKHIM, RAMEEN, CHAKRAVARTI, ARNAB · 2015 to 2025
$6.9M
Fonds Wetenschappelijk Onderzoek G0B3722NFonds Wetenschappelijk Onderzoek G0I1118NFonds Wetenschappelijk Onderzoek I007418NKom op tegen Kanker ZKE0076NCI NIH HHS R01 CA188228Onderzoeksraad, KU Leuven C14/17/084
6 · The paper itself

Abstract

backgroundFunctional profiling of freshly isolated glioblastoma (GBM) cells is being evaluated as a next-generation method for precision oncology. While promising, its success largely depends on the method to evaluate treatment activity which requires sufficient resolution and specificity.

methodsHere, we describe the 'precision oncology by single-cell profiling using ex vivo readouts of functionality' (PROSPERO) assay to evaluate the intrinsic susceptibility of high-grade brain tumor cells to respond to therapy. Different from other assays, PROSPERO extends beyond life/death screening by rapidly evaluating acute molecular drug responses at single-cell resolution.

resultsThe PROSPERO assay was developed by correlating short-term single-cell molecular signatures using mass cytometry by time-of-flight (CyTOF) to long-term cytotoxicity readouts in representative patient-derived glioblastoma cell cultures (n = 14) that were exposed to radiotherapy and the small-molecule p53/MDM2 inhibitor AMG232. The predictive model was subsequently projected to evaluate drug activity in freshly resected GBM samples from patients (n = 34). Here, PROSPERO revealed an overall limited capacity of tumor cells to respond to therapy, as reflected by the inability to induce key molecular markers upon ex vivo treatment exposure, while retaining proliferative capacity, insights that were validated in patient-derived xenograft (PDX) models. This approach also allowed the investigation of cellular plasticity, which in PDCLs highlighted therapy-induced proneural-to-mesenchymal (PMT) transitions, while in patients' samples this was more heterogeneous.

conclusionPROSPERO provides a precise way to evaluate therapy efficacy by measuring molecular drug responses using specific biomarker changes in freshly resected brain tumor samples, in addition to providing key functional insights in cellular behavior, which may ultimately complement standard, clinical biomarker evaluations.

Indexed as

Antineoplastic AgentsBrain NeoplasmsGlioblastomaCell Line, TumorHumansPrecision MedicineXenograft Model Antitumor AssaysAntineoplastic AgentsEx vivo treatmentFunctional diagnosticsGlioblastomaPrecision medicineSingle-cell

Identifiers

PMID37171617
PMCPMC11071868
OpenAlexW4376224941

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.