<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Alexander vom Stein</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15353</full_dataset_link><description>Bulk RNA-seq analysis of CLL cells cocultured for 5 days with (A) HD-MDMs, (B) NLCs, and (C)THP-1 macrophages compared to CLL cells in monoculture.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Cocultures of CLL patient cells (n = 3) and primary human macrophages, THP-1 macrophages, NLCs, and mBMDM were set up as described in the manuscript. After 5 days of coculture, the medium of cocultures was collected, and containing CLL cells were purified using CD19 MicroBeads (Miltenyi Biotec), which magnetically label CD19+ cells and separate them via the magnetic field of a MACS Separator. The purification was performed using MACS LS Columns.</sample_protocol><sample_protocol>Sequencing - Samples were processed and sequenced PE100, 35M reads per sample at the Cologne Center for Genomics according to in-house standards.</sample_protocol><sample_protocol>Growth Protocol - Primary and immortalized macrophage cells were used: mBMDM, NLC, primary human macrophages (HD-MDM), and THP-1 macrophages.  NLCs were generated by seeding patient-derived PBMCs and adherent cells were harvested after 14 days.  THP-1 monocytes were differentiated into macrophages via 100 ng/ml PMA for 48 h.   mBMDM were harvested from femurs and tibias of 8- to 12-week-old mice. Bones were flushed and cells were passed through a 100 μm sterile cell strainer. Erythrocytes were lysed with  ACK buffer and resulting cells cultured in DMEM (+ 1 % P/S, 10 % FBS) containing 20 ng/ml murine M-CSF  to pre-differentiate bone marrow stem cells into adherent M0 murine macrophages. After a minimum of 7 days, mBMDM were harvested.  HD-MDM were generated from buffy coats of healthy donors. After PBMCs isolation cells  were seeded in differentiation medium consisting of RPMI containing 10 % FBS, 1 % P/S, 50 ng/ml M CSF, 1 % NEAA, 1 % Na Pyruvate, 2 mM. Glutamax.  After 7 days, cells were collected.</sample_protocol><sample_protocol>Library Construction - Samples were processed and sequenced PE100, 35M reads per sample at the Cologne Center for Genomics according to in-house standards</sample_protocol><sample_protocol>Nucleic Acid Extraction - For the isolation of RNA for Next Generation mRNA sequencing, the RNeasy Plus Mini Kit (Qiagen) was used according to the manufacturer’s instructions.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - Raw data files from all the aforementioned systems were used to map reads to the human reference genome GRCh38.p14 (GENCODE release 44) using the STAR program version 2.7.10a1. The reads were processed as paired-end reads, followed by quality control analysis. Subsequently, read summarization was performed using the featureCounts program version 2.0.32, generating count matrices as output.  To ensure the sequenced CLL cells were not confounded by inherited macrophages, we applied a filter for macrophage-specific genes. First, single cell RNA sequencing (scRNA-seq) data was retrieved from3, focusing on the blood and immune cell transcriptomes. B-cell- and macrophage cell types were selected, resulting in 348 and 503 genes with elevated expression, respectively. Overlapping genes between the two cell types were excluded, and only genes with elevated expression categorized as “group enriched” in the macrophage cluster were retained. Next, the resulting list of 34 genes was compared with the BMDM system, and intersecting genes were removed. The remaining 24 genes were manually curated to ensure only macrophage-specific genes were included. These genes were subsequently removed from the genome before further data processing.  Next, genes with low expression values were filtered out, retaining only those with sufficiently high counts for statistical analysis. Normalization factors were calculated to scale the raw library sizes using the trimmed mean of M-values (TMM) method. Log2 counts per million (CPM) were computed to quantify gene expression levels. Differentially expressed genes were identified using the voom method with sample quality weights from the limma R package4 based on the criteria of a q-value ≤ 0.05 and 1 ≤ log2-FC ≤ −1.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina HiSeq 2000</instrument_platform><study_type>RNA-seq of coding RNA</study_type><species>Homo sapiens</species><pubmed_title>Comparative analysis of macrophage feeder systems reveals distinct behaviors and key transcriptional shifts in chronic lymphocytic leukemia cells via coculture</pubmed_title><pubmed_authors>Viktoria Kohlhas</pubmed_authors><pubmed_authors>Alexander vom Stein</pubmed_authors><pubmed_authors>Viktoria Kohlhas, Hendrik Jestrabek,  View ORCID ProfileRocio Rebollido-Rios, Thanh Tung Truong, Rebekka Zölzer, Luca D. Schreurs, Anton von Lom,  View ORCID ProfileAlexander F. vom Stein, Michael Hallek,  View ORCID ProfilePhuong-Hien Nguyen</pubmed_authors></additional><is_claimable>false</is_claimable><name>Comparative analysis of macrophage feeder systems reveals distinct behaviors and key transcriptional shifts in chronic lymphocytic leukemia cells via coculture</name><description>Bulk RNA-seq analysis of CLL cells cocultured for 5 days with (A) HD-MDMs, (B) NLCs, and (C)THP-1 macrophages compared to CLL cells in monoculture.</description><dates><release>2025-09-01T00:00:00Z</release><modification>2025-09-01T01:03:08.786Z</modification><creation>2025-07-14T13:03:07.445Z</creation></dates><accession>E-MTAB-15353</accession><cross_references><ENA>ERP176751</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0003789</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0003738</EFO><EFO>EFO_0004184</EFO><doi>10.1101/2025.02.13.638101</doi></cross_references></HashMap>