{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Ashwin Ajith"],"organism":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16395"],"description":["Renal cell carcinoma (RCC) frequently exhibits high expression of the immunomodulatory molecule HLA-G, which promotes immune tolerance and tumor progression. To define the cell-intrinsic transcriptional programs driven specifically by HLA-G1 neo-expression, we generated RCC7/HLA-G1 cells by lentiviral overexpression and compared them with parental RCC7wt cells that lack endogenous HLA-G. Phenotypically, RCC7/HLA-G1 cells display increased proliferation, enhanced migratory capacity, resistance to apoptosis, and accelerated tumor growth in vivo. The purpose of this bulk RNA-sequencing experiment is to characterize the global transcriptional changes induced by HLA-G1 and to identify signaling pathways, gene networks, and regulatory modules that underlie its pro-tumorigenic activity. By comparing RCC7/HLA-G1 tumors with RCC7wt controls, this dataset enables analysis of oncogenic pathways, immune-associated transcriptional suppression (e.g., IFN-γ–responsive chemokines), metabolic reprogramming, extracellular matrix remodeling, and enrichment of stem-cell–associated signatures. Overall, these data define the molecular consequences of HLA-G1 expression in RCC and provide mechanistic insight into how HLA-G contributes to tumor aggressiveness and immune evasion."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Library Construction - RNA libraries were prepared by the Integrated Genomics Core Shared Resources at Augusta University (RRID: SCR_026483). Libraries were constructed according to standard Illumina protocols for bulk RNA-seq.","Sequencing - Sequencing was performed on an Illumina NovaSeq 6000 platform to generate paired-end reads.  Instrument: Illumina NovaSeq 6000 Library Layout: PAIRED","Nucleic Acid Extraction - Total RNA was extracted using the RNeasy Mini Kit (Qiagen). RNA integrity was assessed using the Agilent 2100 Bioanalyzer, and only samples with RIN ≥ 8 were used for library preparation and sequencing.","Sample Collection - Tumor tissues derived from xenografts of RCC7/HLA-G1 and RCC7-WT cells were harvested 20 days post-implantation. Tumors were processed into single-cell suspensions using the gentleMACS Octo Dissociator with Heaters (Miltenyi Biotec, Cat. No. 130-096-427) together with the Human Tumor Dissociation Kit (Miltenyi Biotec, Cat. No. 130-095-929), following the manufacturer’s instructions."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","Processed Data","MAGE-TAB Files"],"data_protocol":["Data Transformation - Filtered clean reads were aligned to the human reference genome (GRCh38) using HISAT2. Alignment quality and read distribution across transcripts were evaluated using the Integrative Genomics Viewer (IGV). Gene-level quantification was performed with featureCounts. Normalized count matrices were analyzed in R using the limma-voom pipeline. Differentially expressed genes (DEGs) were defined as those with absolute log₂ fold change ≥ 1 and Benjamini–Hochberg adjusted p < 0.05.Functional enrichment analysis of DEGs was performed using the clusterProfiler R package with KEGG, GO, and Reactome databases. Gene Set Enrichment Analysis (GSEA) was performed using ranked log₂ fold-change values to identify enriched pathways in RCC7/HLA-G1 tumors. Data visualization, including heatmaps, volcano plots, and enrichment curves, was generated using ggplot2, pheatmap, and enrichplot in R."],"omics_type":["Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["Genomics Core Shared Resources at Augusta University (RRID: SCR_026483)","gentleMACS Octo Dissociator with Heaters (Miltenyi Biotec, Cat. No. 130-096-427) together with the Human Tumor Dissociation Kit (Miltenyi Biotec, Cat. No. 130-095-929),","Illumina NovaSeq 6000","RNeasy Mini Kit (Qiagen)"],"study_type":["RNA-seq of coding RNA"],"species":["Homo sapiens"],"pubmed_authors":["Ashwin Ajith"],"additional_accession":[]},"is_claimable":false,"name":"Pro-tumorigenic effects of HLA-G in Renal Cell Carcinoma","description":"Renal cell carcinoma (RCC) frequently exhibits high expression of the immunomodulatory molecule HLA-G, which promotes immune tolerance and tumor progression. To define the cell-intrinsic transcriptional programs driven specifically by HLA-G1 neo-expression, we generated RCC7/HLA-G1 cells by lentiviral overexpression and compared them with parental RCC7wt cells that lack endogenous HLA-G. Phenotypically, RCC7/HLA-G1 cells display increased proliferation, enhanced migratory capacity, resistance to apoptosis, and accelerated tumor growth in vivo. The purpose of this bulk RNA-sequencing experiment is to characterize the global transcriptional changes induced by HLA-G1 and to identify signaling pathways, gene networks, and regulatory modules that underlie its pro-tumorigenic activity. By comparing RCC7/HLA-G1 tumors with RCC7wt controls, this dataset enables analysis of oncogenic pathways, immune-associated transcriptional suppression (e.g., IFN-γ–responsive chemokines), metabolic reprogramming, extracellular matrix remodeling, and enrichment of stem-cell–associated signatures. Overall, these data define the molecular consequences of HLA-G1 expression in RCC and provide mechanistic insight into how HLA-G contributes to tumor aggressiveness and immune evasion.","dates":{"release":"2026-05-01T00:00:00Z","modification":"2026-05-01T01:03:25.123Z","creation":"2025-12-16T14:08:17.123Z"},"accession":"E-MTAB-16395","cross_references":{"ENA":["ERP186631"],"EFO":["EFO_0002944","EFO_0004170","EFO_0005518","EFO_0003816","EFO_0003738","EFO_0004184"]}}