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pmid:26981348

Transcriptomic analysis of monocytes and macrophages derived from CLL patients which display differing abilities to respond to therapeutic antibody immune complexes.

M Burgess · J J Ellis · S Mapp · P Mollee · R Mazzieri · S R Mattarollo · D Gill · N A Saunders

Genomics data · 2016 doi:10.1016/j.gdata.2015.11.010

Paper

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Experiment

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Data

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Analysis

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Execution

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title
Transcriptomic analysis of monocytes and macrophages derived from CLL patients which display differing abilities to respond to therapeutic antibody immune complexes.
doi
10.1016/j.gdata.2015.11.010
pmid
26981348
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M Burgess
[1]
J J Ellis
[2]
S Mapp
[3]
P Mollee
[4]
R Mazzieri
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S R Mattarollo
[6]
D Gill
[7]
N A Saunders
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Genomics data
year
2016
abstract
Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. While therapeutic antibodies show clinical activity in CLL patients, resistance inevitably develops resulting in treatment failure. Identifying mechanisms of antibody resistance and methods to reduce resistance would be valuable in managing CLL. Monocyte derived cells (MDCs), also known as nurse like cells (NLCs) in CLL [1], [2], are known to be crucial components of the CLL microenvironment network and following "maturation" in in vitro culture systems are able to provide support for the survival of the malignant B cells from CLL patients. In addition to their protective role, MDCs are key effector cells in mediating responses to therapeutic antibody therapies [3]. We have determined that macrophages from patients with early stable CLL are able to elicit superior cytotoxic response to therapeutic antibodies than macrophages derived from patients with progressive CLL. We have exploited this unique finding to gain insight into antibody resistance. Thus, we have profiled monocytes on day 0 and MDCs on day 7 from antibody sensitive and antibody resistant CLL patients (GEO accession number GEO: GSE71409). We show that there are no significant differences in transcriptomes from the monocytes or MDCs derived from sensitive or resistant patient samples. However, we show that MDCs acquire an M2-like macrophage transcriptomic signature following 7 days culture regardless of whether they were derived from sensitive or resistant patient samples.
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Large platform specific batch effects were observed between the two datasets, so an unsupervised empirical Bayes method was used to remove these batch effects after as implemented in the ‘virtualArray’ package [13].
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After normalization and correction for platform-specific batch effects using an unsupervised empirical Bayes method, the study found no statistically significant differentially expressed transcripts distinguishing MDCs from antibody-sensitive versus antibody-resistant CLL patients; the source microarray data were deposited in GEO under accession GSE71409.
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Gene expression analysis of monocytes and monocyte derived cells (MDCs) in CLL patients with differing antibody sensitivity
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3]. We have determined that macrophages from patients with early stable CLL are able to elicit superior
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tic antibodies than macrophages derived from patients with progressive CLL. We have exploited this uniq
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termine antibody sensitivity, CLL PBMCs were cultured in RPMI + 10% fetal calf serum in the presence
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CD62L antibody in vitro. (A) CLL PBMCs were cultured in the presence of anti-human CD62L antibody (D
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i Biotec). Purity of samples was examined by flow cytometry and all samples ≥ 85% based on CD14 positivi
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Complete file
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While therapeutic antibodies show clinical activity in CLL patients, resistance inevitably develops resulting in treatment failure. Identifying mechanisms of antibody resistance and methods to reduce resistance would be valuable in managing CLL. Monocyte derived cells (MDCs), also known as nurse like cells (NLCs) in CLL [1], [2], are known to be crucial components of the CLL microenvironment network and following \"maturation\" in in vitro culture systems are able to provide support for the survival of the malignant B cells from CLL patients. In addition to their protective role, MDCs are key effector cells in mediating responses to therapeutic antibody therapies [3]. We have determined that macrophages from patients with early stable CLL are able to elicit superior cytotoxic response to therapeutic antibodies than macrophages derived from patients with progressive CLL. We have exploited this unique finding to gain insight into antibody resistance. Thus, we have profiled monocytes on day 0 and MDCs on day 7 from antibody sensitive and antibody resistant CLL patients (GEO accession number GEO: GSE71409). We show that there are no significant differences in transcriptomes from the monocytes or MDCs derived from sensitive or resistant patient samples. However, we show that MDCs acquire an M2-like macrophage transcriptomic signature following 7 days culture regardless of whether they were derived from sensitive or resistant patient samples.", "claims": [{"id": "claim-data-access", "statement": "Deposited data can be found here: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71409", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26981348", "locator": "sections[2] \"Direct link to deposited data\" paragraph 2", "quote": "Deposited data can be found here: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71409"}], "state": "complete"}, {"id": "claim-target-result", "statement": "After normalization and correction for platform-specific batch effects using an unsupervised empirical Bayes method, the study found no statistically significant differentially expressed transcripts distinguishing MDCs from antibody-sensitive versus antibody-resistant CLL patients; the source microarray data were deposited in GEO under accession GSE71409.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:26981348", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We show that there are no significant differences in transcriptomes from the monocytes or MDCs derived from sensitive or resistant patient samples."}, {"asset": "source:pmid:26981348", "locator": "sections[6] \"Gene expression analysis\" paragraph 3", "quote": "Large platform specific batch effects were observed between the two datasets, so an unsupervised empirical Bayes method was used to remove these batch effects after as implemented in the ‘virtualArray’ package [13]."}, {"asset": "source:pmid:26981348", "locator": "sections[6] \"Gene expression analysis\" paragraph 3", "quote": "Microarray data have been uploaded to Gene Expression Omnibus under the reference: GSE71409."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After normalization and correction for platform-specific batch effects using an unsupervised empirical Bayes method, the study found no statistically significant differentially expressed transcripts distinguishing MDCs from antibody-sensitive versus antibody-resistant CLL patients; the source microarray data were deposited in GEO under accession GSE71409.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:26981348"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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