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Bulk RNAseq data for bladder cancer specimens [UC cohort]

ABSTRACT: When applying deconvolution methods to bulk RNAseq data, a limitation of most prior studies is the lack of paired scRNA-seq and bulk RNA-seq data from the same samples to serve as ground truth for deconvolution. Our UC cohort, containing matched scRNA-seq and bulk RNA-seq data therefore provided a unique opportunity. (The scRNAseq datasets have been published before [PMID: 32111252 PMID: 36129800 PMID: 36099881 PMID: 33837006 ]. Please see linked manuscript for details) We assembled a scRNA-seq dataset of 100,667 cells from 30 UC tissue samples (20 unique patients). Bulk RNA sequencing was performed on a subset of patients(14) in the single-cell RNA sequencing cohort due to tissue availability.

ORGANISM(S): Homo sapiens

PROVIDER: GSE223971 | GEO | 2024/01/01

REPOSITORIES: GEO

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Project description:Pancreatic cancer is a complex disease with a desmoplastic stroma, extreme hypoxia, and inherent resistance to therapy. Understanding the signaling and adaptive response of such an aggressive cancer is key to making advances in therapeutic efficacy and understanding disease progression. Redox factor-1 (Ref-1), a redox signaling protein, regulates the DNA binding activity of several transcription factors, including HIF-1. The conversion of HIF-1 from an oxidized to reduced state leads to enhancement of its DNA binding. In our previously published work, knockdown of Ref-1 under normoxia resulted in altered gene expression patterns on pathways including EIF2, protein kinase A, and mTOR. In this study, single cell RNA sequencing (scRNA-seq) and proteomics were used to explore the effects of Ref-1 on metabolic pathways under hypoxia.Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions. Experimental Methods: scRNA-seq comparing pancreatic cancer cells expressing less than 20% of the Ref-1 protein was analyzed using left truncated mixture Gaussian model. Matched samples were also collected for bulk proteomic analysis of the four conditions. scRNA-seq data was validated using proteomics and qRT-PCR. Ref-1’s role in mitochondrial function was confirmed using mitochondrial function assays and qRT-PCR. Results: We also integrated the scRNA data analysis with the proteomic analysis and found that the differentially expressed genes and pathways identified from the scRNA-seq data are highly consistent to the significant proteins observed in the proteomics data, especially for the upregulated cell cycle and transcription pathways and downregulated metabolic, apoptosis and signaling pathways under hypoxia. Conclusion: The scRNA-seq and proteomics data consistently demonstrated down-regulated central metabolism pathways in APE1/Ref-1 knockdown vs scrambled control under both normoxia and hypoxia conditions.

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Bulk RNAseq data for bladder cancer specimens [UC cohort]

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