<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Ashwin Ajith</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16395</full_dataset_link><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.</description><repository>biostudies-arrayexpress</repository><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.</sample_protocol><sample_protocol>Sequencing - Sequencing was performed on an Illumina NovaSeq 6000 platform to generate paired-end reads.  Instrument: Illumina NovaSeq 6000 Library Layout: PAIRED</sample_protocol><sample_protocol>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_protocol><sample_protocol>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.</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 - 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 &lt; 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.</data_protocol><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Genomics Core Shared Resources at Augusta University (RRID: SCR_026483)</instrument_platform><instrument_platform>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),</instrument_platform><instrument_platform>Illumina NovaSeq 6000</instrument_platform><instrument_platform>RNeasy Mini Kit (Qiagen)</instrument_platform><study_type>RNA-seq of coding RNA</study_type><species>Homo sapiens</species><pubmed_authors>Ashwin Ajith</pubmed_authors></additional><is_claimable>false</is_claimable><name>Pro-tumorigenic effects of HLA-G in Renal Cell Carcinoma</name><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.</description><dates><release>2026-05-01T00:00:00Z</release><modification>2026-05-01T01:03:25.123Z</modification><creation>2025-12-16T14:08:17.123Z</creation></dates><accession>E-MTAB-16395</accession><cross_references><ENA>ERP186631</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>