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RNA-seq data for tumor and adjacent non-tumor tissues from hepatocellular carcinoma patients with anti-PD-1 therapy

GSE202069 Homo sapiens Expression profiling by high throughput sequencing 66 samples Submitted 2023/05/01 Platform GPL24676
Summary
Immune checkpoint inhibitors elicit durable antitumor effects in multiple cancers, yet not all patients respond. Here, we aimed to develop and validate a molecular classification of hepatocellular carcinoma (HCC) patients based on 42 fatty acid degradation genes and demonstrate its predictive ability in the clinical response of anti-PD1 therapy in HCC patients. We studied global mRNA expression profiles from 41 primary tumor tissues and 25 nontumor tissues derived from 41 HCC patients. 17 patients received anti-PD1 therapy and were available with clinical response. 63 samples were also sent for lipidomics analysis. Methods for the study included gene expression analysis, consensus clustering analysis, pathway enrichment analysis, and Single-Sample Gene Set Enrichment Analysis (ssGSEA). This study identified and validated a novel molecular classification based on fatty acid degradation that predicts clinical response to anti-PD-1 therapy in hepatocellular carcinoma.
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Direct links to NCBI, no account and no request form: the whole study as GSE202069_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 66 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA834139 and SRA study SRP373203. Searching any of these in the dataset finder brings you back here.

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