Evidence map›Paper›PMID 37352275›Full record

ArticleBlood advances2023

Comparing the value of mono- vs coculture for high-throughput compound screening in hematological malignancies.

Sophie A Herbst, Vladislav Kim, Tobias Roider, Eva C Schitter, Peter-Martin Bruch, Nora Liebers, Carolin Kolb, Mareike Knoll, Junyan Lu, Peter Dreger and 4 more

Open access · goldAbstract read
In one paragraph

Article in Blood advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

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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

14 authors at 4 institutions in 2 countries.

Sophie A HerbstDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0001-8502-0366
Vladislav KimGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID 0000-0001-5061-7285
Tobias RoiderDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-6973-3531
Eva C SchitterDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Peter-Martin BruchDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-9992-3109
Nora LiebersDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Carolin KolbDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Mareike KnollDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Junyan LuGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Peter DregerDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Carsten Müller-TidowDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-7166-5232
Thorsten ZenzDepartment of Medical Oncology and Hematology, University Hospital Zürich, Zürich, Switzerland.
Wolfgang HuberGenome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.ORCID 0000-0002-0474-2218
Sascha DietrichDepartment of Medicine V, Hematology, Oncology and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.ORCID 0000-0002-0648-1832
Heidelberg University · DEEuropean Molecular Biology Laboratory · DEGerman Cancer Research Center · DEUniversity Hospital of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large-scale compound screens are a powerful model system for understanding variability of treatment response and discovering druggable tumor vulnerabilities of hematological malignancies. However, as mostly performed in a monoculture of tumor cells, these assays disregard modulatory effects of the in vivo microenvironment. It is an open question whether and to what extent coculture with bone marrow stromal cells could improve the biological relevance of drug testing assays over monoculture. Here, we established a high-throughput platform to measure ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52% of compounds in chronic lymphocytic leukemia (CLL) and 36% of compounds in acute myeloid leukemia (AML), including chemotherapeutics, B-cell receptor inhibitors, proteasome inhibitors, and Bromodomain and extraterminal domain inhibitors. Only the JAK inhibitors ruxolitinib and tofacitinib exhibited increased efficacy in AML and CLL stromal coculture. We further confirmed the importance of JAK-STAT signaling for stroma-mediated resistance by showing that stromal cells induce phosphorylation of STAT3 in CLL cells. We genetically characterized the 108 cancer samples and found that drug-gene associations strongly correlated between monoculture and coculture. However, effect sizes were lower in coculture, with more drug-gene associations detected in monoculture than in coculture. Our results justify a 2-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.

Indexed as

Hematologic NeoplasmsLeukemia, Lymphocytic, Chronic, B-CellLeukemia, Myeloid, AcuteCoculture TechniquesDrug Resistance, NeoplasmHumansTumor Microenvironment

Identifiers

PMID37352275
PMCPMC10558604
OpenAlexW4381839100

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.