Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Pro-tumorigenic effects of HLA-G in Renal Cell Carcinoma

ABSTRACT: 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.

INSTRUMENT(S): 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)

ORGANISM(S): Homo sapiens

SUBMITTER: Ashwin Ajith

PROVIDER: E-MTAB-16395 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:BACKGROUND: Studies have reported clinical heterogeneity between right-sided colon cancer (RCC) and left-sided colon cancer (LCC). However, none of these studies used multi-omics analysis combining genetic regulation, microbiota and metabolites to explain the site-specific difference.METHODS: Here, 494 participants from a 16S rRNA gene sequencing cohort (50 RCC, 114 LCC and 100 healthy controls) and a multi-omics cohort (63 RCC, 79 LCC and 88 healthy controls) were analyzed. 16S rRNA gene, metagenomic sequencing and metabolomics analyses of fecal samples were evaluated to identify tumor location-related bacteria and metabolites. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-seq) were conducted to obtain the mutation burden and genomic expression pattern.RESULTS: We found unique profiles of the intestinal microbiome, metabolome, and host genome between RCC and LCC. The bacteria Flavonifractor plautii (Fp) and Fusobacterium nucleatum, the metabolites L-phenylalanine, and the host genes PHLDA1 and WBP1 were the key omics features of RCC; whereas the bacteria Bacteroides sp. A1C1 (B.A1C1) and Parvimonas micra, the metabolites L-citrulline and D-ornithine, and the host genes TCF25 and HLA-DRB5 were considered the dominant omics features in LCC. Multi-omics correlation analysis indicated that RCC-enriched Fp was related to the accumulation of the metabolite L-phenylalanine and the suppressed WBP1 signal in RCC patients. In addition, LCC-enriched B.A1C1 was associated with accumulation of the metabolites D-ornithine and L-citrulline as well as activation of the genes TCF25, HLA-DRB5 and AC079354.1.CONCLUSION: Our findings identify previously unknown links between intestinal microbiota alterations, metabolites and host genomics in RCC vs. LCC, suggesting that it may be possible to treat colorectal cancer (CRC) by targeting the gut microbiota-host interaction.

Dataset Information

Pro-tumorigenic effects of HLA-G in Renal Cell Carcinoma

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets