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idr0143-study.txt
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# FILL IN AS MUCH INFORMATION AS YOU CAN. HINTS HAVE BEEN PUT IN SOME FIELDS AFTER THE HASH # SYMBOL. REPLACE THE HINT WITH TEXT WHERE APPROPRIATE.
# STUDY DESCRIPTION SECTION
# Section with generic information about the study including title, description, publication details (if applicable) and contact details
Comment[IDR Study Accession] idr0143
Study Title Comparing the value of mono- versus coculture for high-throughput compound screening in hematological malignancies
Study Type high content screen
Study Type Term Source REF EFO
Study Type Term Accession EFO_0007550
Study Description Large-scale compound screens are a powerful model system for understanding variability of treatment response and for 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 measured ex vivo sensitivity of 108 primary blood cancer samples to 50 drugs in monoculture and in coculture with bone marrow stromal cells. Stromal coculture conferred resistance to 52 % of compounds in chronic lymphocytic leukemia (CLL) and to 36 % of compounds in acute myeloid leukemia (AML), including chemotherapeutics, BCR inhibitors, proteasome inhibitors and BET inhibitors. While most of the remaining drugs were similarly effective in mono- and coculture, oOnly 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 agreed strongly correlated well between mono- and coculture. OverallHowever, effect sizes were lower in coculture, thus with more drug-gene associations were detected in monoculture than in coculture. Our results suggest justifies a two-step strategy for drug perturbation testing, with large-scale screening performed in monoculture, followed by focused evaluation of potential stroma-mediated resistances in coculture.
Study Key Words Chronic lymphocytic leukemia Acute myeloid leukemia Hairy cell leukemia Mantle cell lymphoma co-culture stroma HS-5 mono-culture compounds
Study Organism Homo sapiens
Study Organism Term Source REF NCBITaxon
Study Organism Term Accession 9606
Study Screens Number 1
Study External URL
Study BioImage Archive Accession
Study Public Release Date 2023-10-09
# Study Publication
Study PubMed ID 37352275
Study Publication Title Comparing the value of mono- versus coculture for high-throughput compound screening in hematological malignancies
Study Author List Herbst SA, Kim V, Roider T, Schitter EC, Bruch PM, Liebers N, Kolb C, Knoll M, Lu J, Dreger P, Müller-Tidow C, Zenz T, Huber W, Dietrich S
Study PMC ID
Study DOI https://doi.org/10.1182/bloodadvances.2022009652
# Study Contacts
Study Person Last Name Dietrich
Study Person First Name Sascha
Study Person Email [email protected]
Study Person Address Department of Hematology and Oncology, University Hospital Düsseldorf
Moorenstr. 5, 40225 Düsseldorf, Germany
Study Person ORCID 0000-0002-0648-1832
Study Person Roles submitter
# Study License and Data DOI
Study License CC BY 4.0
Study License URL https://creativecommons.org/licenses/by/4.0/
Study Copyright Herbst, Kim, Roider et al.
Study Data Publisher University of Dundee
Study Data DOI https://doi.org/10.17867/10000194
Term Source Name NCBITaxon EFO CMPO Fbbi
Term Source File http://purl.obolibrary.org/obo/ http://www.ebi.ac.uk/efo/ http://www.ebi.ac.uk/cmpo/ http://purl.obolibrary.org/obo/
# SCREEN SECTION
# Screen Section containing all information relative to each screen in the study including materials used, protocols names and description, phenotype names and description.
# For multiple screens this section should be repeated. Copy and paste the whole section below and fill out for the next screen.
Screen Number 1
Comment[IDR Screen Name] idr0143-herbst-coculture/screenA
Screen Sample Type cell
Screen Description To systematically assess whether coculture studies provide superior biological insights for drug screening, we performed a large-scale study comparing compound efficacy in leukemia monoculture and leukemia-stroma coculture. We used the well-established bone-marrow derived stroma cell line HS-5 and an imaging-based platform to investigate not only drug effects in mono- and leukemia-stroma coculture but also to capture cellular changes due to the stromal environment and drug treatments.
Screen Size Plates: 384 well plate 5D Images: Planes: xyz Average Image Dimension (XYZCT): Total Tb:
Screen Example Images 180413_Plate4 K22
Screen Imaging Method spinning disk confocal microscopy
Screen Imaging Method Term Source REF FBbi
Screen Imaging Method Term Accession FBbi_00000253
Screen Technology Type compound screen
Screen Technology Type Term Source REF EFO
Screen Technology Type Term Accession EFO_0007553
Screen Type primary screen
Screen Type Term Source REF EFO
Screen Type Term Accession EFO_0007556
Screen Organism
Screen Organism Term Source REF NCBITaxon
Screen Organism Term Accession
Screen Comments 180306_Plate1 is missing.
# Library section. The library file should be supplied separately and it should contain the reagents description including, at the absolute minimum: reagent ID, sequences and position in the layout (= plate + position in the plate)
Library File Name idr0143-screenA-annotation
Library File Format tab-delimited text
Library Type compound library
Library Type Term Source REF EFO
Library Type Term Accession EFO_0007569
Library Manufacturer Most compounds were purchased from Selleck Chemicals
Library Version
Library Experimental Conditions
Library Experimental Conditions Term Source REF EFO
Library Experimental Conditions Term Accession
Quality Control Description Patient cell viability and counts were analyzed using Trypan Blue (Thermo Fisher Scientific). Percentages of alive cells always exceeded 90 % at culture start or freezing of pellets. Drug concentrations which were toxic to stroma cells were excluded, as these do not represent proper co-cultures. The degree of stroma cell death was assessed by evaluating the percentage of area covered by stroma cells using the image analysis software Harmony (Perkin Elmer). For this, all nuclei were segmented in the Hoechst channel and CLL nuclei were excluded by setting a size threshold. Next, the cytoplasm of stroma cells was found using the signal from the lysosomal dye as proxy. Conditions in which less than 40% of the image area was covered by stroma were classified as toxic conditions.
# Protocols
Protocol Name growth protocol treatment protocol HCS library protocol HCS image acquisition and feature extraction protocol HCS data analysis protocol
Protocol Type growth protocol treatment protocol HCS library protocol HCS image acquisition and feature extraction protocol HCS data analysis protocol
Protocol Type Term Source REF EFO EFO EFO EFO EFO
Protocol Type Term Accession EFO_0003789 EFO_0003969 EFO_0007571 EFO_0007572 EFO_0007573
Protocol Description HS-5 cells were cultured in DMEM (Thermo Fisher Scientific) supplemented with 10 % fetal bovine serum (FBS; Thermo Fisher Scientific), 1 % penicillin/streptomycin (Thermo Fisher Scientific) and 1 % glutamine (Thermo Fisher Scientific) in a humidified atmosphere at 37° C and 10 % CO2. Patient samples were selected based on availability and tumor cell content higher than 80 %. Clinical flow cytometry data were used to estimate the proportion of malignant cells in collected blood samples. Peripheral blood mononuclear cells (PBMCs) were isolated using Ficoll density gradient centrifugation. Cells were viably frozen in RPMI (Thermo Fisher Scientific) containing 45 % FBS (Thermo Fisher Scientific) and 10 % DMSO (SERVA Electrophoresis GmbH) and kept on liquid nitrogen until use. Cells were thawed freshly before the experiment and rolled in serum containing medium for 3 hours on a roll mixer at room temperature to allow cells to recover. To deplete dead cells, which form clumps during this procedure, the suspension was filtered through a 40 μm cell strainer (Sarstedt). Drug screens were carried out in CellCarrier-384 Ultra Microplates (Perkin Elmer) with a seeding density of HS-5 stromal cells of 1x104 cells/well and 2x10 4 patient cells per well. The screen was carried out in DMEM (Thermo Fisher Scientific) supplemented with 10 % human serum (male AB, H6914-100ml Batch SLBT2873, Sigma-Aldrich), 1 % penicillin/streptomycin (Thermo Fisher Scientific) and 1 % glutamine (Thermo Fisher Scientific) at a final volume of 40 μL in the culture plates. Cells were incubated at 37 °C in a humidified atmosphere and 10 % CO 2 for 3 days. For the screen, 50 drugs were probed at 3 different concentrations (Supplementary Table 1). Drug concentrations ranged from subnanomolar to low micromolar and were chosen based on previous experience with the drugs [3]. Increase of the concentration was 15-fold per step to cover a broad spectrum of concentrations. Drugs were diluted according to the manufacturer's instructions. Further dilution was carried out in DMSO (SERVA Electrophoresis GmbH) and master plates containing 4 μL of diluted drugs were frozen at -20 °C for direct use on the screening days. Compounds were chosen based on whether they are in clincal use for the treatment of leukemia, target pathways known to be important in leukemia or have been described in the context of co-cultures. High-throughput screening was conducted using Opera Phenix High Content Screening System (Perkin Elmer). CLL screening plates were stained with 4 μg/ml Hoechst 33342 (Invitrogen) and 1 μl/ml lysosomal dye NIR (Abcam). Plates of non-CLL entities were additionally stained with 1 μM Calcein AM (Invitrogen). All dyes were diluted using serum-free medium and staining solution was added to each well. After an incubation period of 45 minutes at 37 °C, three positions per well with a stack of ten images at a distance of 1.2 μm were acquired with a 40x water objective in confocal mode. Images of CLL samples were processed using the image analysis software Harmony (Perkin Elmer). Results were further analyzed in the statistical programming language R (R Core Team, 2018).Maximum intensity projection and gamma correction (gamma = 0.3) was applied to all images. All 3 color channels (lysosomal dye, Calcein and Hoechst) were combined to generate RGB overlays. Each image (2160 x 2160, omitting the color channel axis) was cut into 9 blocks of size 720 x 720 to speed up training and prediction. Faster R-CNN object detection model [37] with Inception v2 [38] backbone architecture was used to detect patient-derived leukemia and lymphoma cells. The two defined classes were viable and apoptotic leukemia cells. The object detection model implemented in TensorFlow 1.14 was trained for 21,000 epochs on coculture images from 5 AML samples. 5 control and 5 drug-treated well images were randomly selected from each of the five AML plates, resulting in 5 * 10 * 9 = 450 images that were split into train / test sets with 80% / 20% ratio. The average precision (AP) on the test set was 0.99 and 0.93 for viable and apoptotic leukemia cells, respectively. The area under the ROC curve (AUCROC) was 0.98 for both viable and apoptotic leukemia cells.
# Phenotypes
Phenotype Name
Phenotype Description
Phenotype Score Type
Phenotype Term Source REF CMPO
Phenotype Term Name
Phenotype Term Accession
# Raw Data Files
Raw Image Data Format
Raw Image Organization In total 113 plates were screened. Each plate contained cells from one individual patient. Three positions per well with a stack of ten images at a distance of 1.2 μm were acquired with a 40x water objective in confocal mode.
# Feature Level Data Files
Feature Level Data File Name
Feature Level Data File Description
Feature Level Data File Format
Feature Level Data Column Name
Feature Level Data Column Description
# Processed Data Files
Processed Data File Name
Processed Data File Format tab-delimited text
Processed Data File Description
Processed Data Column Name
Processed Data Column Type
Processed Data Column Annotation Level
Processed Data Column Description
Processed Data Column Link To Library File