<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Fangyi Lu</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16533</full_dataset_link><description>This study explores the molecular mechanisms underlying variable therapeutic responses to tofacitinib in patients with rheumatoid arthritis (RA). Peripheral blood mononuclear cells (PBMCs) were collected from patients with active RA before tofacitinib treatment. Based on EULAR DAS28-defined clinical outcomes after 8 weeks of therapy, patients were classified as responders or non-responders. RNA sequencing (RNA-seq) was performed to characterize transcriptomic changes associated with treatment response. The resulting dataset provides valuable insights into immune-related transcriptional alterations linked to JAK inhibitor efficacy in RA and offers a useful resource for biomarker discovery and precision medicine research.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - Fourteen female patients with active rheumatoid arthritis (RA) were enrolled. Patients received tofacitinib (Pfizer Inc., 5 mg per tablet) orally, 5 mg twice daily, for 8 weeks. Peripheral blood (20 mL) was collected from each patient in fasting state into EDTA anticoagulant tubes at two time points: before treatment (week 0) and after 8 weeks of tofacitinib therapy (week 8). Peripheral blood mononuclear cells (PBMCs) were isolated using Ficoll density gradient centrifugation according to standard protocols. Isolated PBMCs were immediately resuspended in TRIzol reagent and stored at −80°C until RNA extraction. Patients were later stratified into responders and non-responders based on EULAR DAS28-defined clinical response after 8 weeks of treatment.</sample_protocol><sample_protocol>Nucleic Acid Extraction - PBMCs were collected from RA patients and stored in TRIzol at −80°C. Total RNA was extracted using TRIzol Reagent following the manufacturer’s instructions. RNA concentration, purity, and integrity were assessed using a NanoDrop spectrophotometer.</sample_protocol><sample_protocol>Library Construction - Two micrograms of total RNA per sample were used to construct RNA-seq libraries. Ribosomal RNA was depleted using the Epicentre Ribo-Zero™ rRNA Removal Kit (Human/Mouse/Rat). RNA was fragmented using divalent cations under elevated temperature. First-strand cDNA was synthesized using random primers, followed by RNA degradation with RNaseH. Second-strand cDNA was synthesized using DNA polymerase I with dUTP replacing dTTP. Double-stranded cDNA was purified, end-repaired, adenylated at the 3’ ends, and ligated with sequencing adapters. USER enzyme was applied to degrade the second strand containing uracil. Size selection of 400–500 bp fragments was performed using AMPure XP beads. Libraries were PCR-amplified for 15 cycles and purified with AMPure XP beads. Library quality and fragment size distribution were assessed using the Agilent High Sensitivity DNA Kit on a Bioanalyzer 2100 system.</sample_protocol><sample_protocol>Sequencing - RNA-seq libraries were normalized and sequenced on the Illumina NovaSeq 6000 platform in paired-end 150 bp mode. Raw sequencing reads were output as FASTQ files for downstream analyses.</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - Raw RNA-seq reads were aligned to the human reference genome (GRCh38) using HISAT2. Gene-level read counts were obtained from the aligned, sorted BAM files using HTSeq (v0.9.1). HTSeq was run in exon-counting mode with the \"union\" overlap mode and strandness set to unstranded unless otherwise specified. Raw gene counts produced by HTSeq were used as the primary measure of expression for count-based differential expression analysis (DESeq2). For normalization we converted raw counts to FPKM (Fragments Per Kilobase of transcript per Million mapped reads).</data_protocol><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><instrument_platform>Illumina NovaSeq 6000</instrument_platform><study_type>RNA-seq of coding RNA</study_type><species>Homo sapiens</species><pubmed_authors>Huaxiang Liu</pubmed_authors><pubmed_authors>Yunfeng Li</pubmed_authors><pubmed_authors>Qilin Chen</pubmed_authors><pubmed_authors>Zhen Liu</pubmed_authors><pubmed_authors>Fangyi Lu</pubmed_authors><pubmed_authors>Yanshu Shao</pubmed_authors><pubmed_authors>Qi Liu</pubmed_authors></additional><is_claimable>false</is_claimable><name>Transcriptomic profiling of peripheral blood mononuclear cells from rheumatoid arthritis patients before tofacitinib treatment</name><description>This study explores the molecular mechanisms underlying variable therapeutic responses to tofacitinib in patients with rheumatoid arthritis (RA). Peripheral blood mononuclear cells (PBMCs) were collected from patients with active RA before tofacitinib treatment. Based on EULAR DAS28-defined clinical outcomes after 8 weeks of therapy, patients were classified as responders or non-responders. RNA sequencing (RNA-seq) was performed to characterize transcriptomic changes associated with treatment response. The resulting dataset provides valuable insights into immune-related transcriptional alterations linked to JAK inhibitor efficacy in RA and offers a useful resource for biomarker discovery and precision medicine research.</description><dates><release>2026-01-09T00:00:00Z</release><modification>2026-01-16T18:08:05.411Z</modification><creation>2026-01-16T18:07:32.952Z</creation></dates><accession>E-MTAB-16533</accession><cross_references><ENA>ERP187665</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0003738</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>