Transcriptome sequencing of hepatocellular carcinoma biopsies (proteogenomic study)

We performed a proteogenomic analysis of hepatocellular carcinomas (HCCs) across clinical stages and etiologies to define the deregulated pathways and heterogeneity among HCCs. We identified pathways that are differentially regulated on the genomic, transcriptomic, proteomic and phosphoproteomic levels. Integrative clustering identified HCC subgroups that show distinct regulation of biological processes, metabolic reprogramming and kinase activation.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset 4 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001008205	RNA-sequencing of 122 hepatocellular carcinoma biopsies and 15 normal liver biopsies. RNA-seq library prep was performed with 200 ng total RNA using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina) according to manufacturer’s specifications. Single-end 126-bp sequencing was performed on an Illumina HiSeq 2500 using v4 SBS chemistry at the Genomics Facility Basel according to the manufacturer’s guidelines. Primary data analysis was performed with the Illumina RTA version 1.18.66.3.	Illumina HiSeq 2500	137

Publications	Citations
Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages. Ng CKY, Dazert E, Boldanova T, Coto-Llerena M, Nuciforo S, Ercan C, Suslov A, Meier MA, Bock T, Schmidt A, Ketterer S, Wang X, Wieland S, Matter MS, Colombi M, Piscuoglio S, Terracciano LM, Hall MN, Heim MH. Nat Commun 13: 2022 2436	31
Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model. Suter P, Dazert E, Kuipers J, Ng CKY, Boldanova T, Hall MN, Heim MH, Beerenwinkel N. PLoS Comput Biol 18: 2022 e1009767	2
Arginine reprograms metabolism in liver cancer via RBM39. Mossmann D, Müller C, Park S, Ryback B, Colombi M, Ritter N, Weißenberger D, Dazert E, Coto-Llerena M, Nuciforo S, Blukacz L, Ercan C, Jimenez V, Piscuoglio S, Bosch F, Terracciano LM, Sauer U, Heim MH, Hall MN. Cell 186: 2023 5068-5083.e23	5
KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data. Zhang Y, Yao L, Chung CR, Huang Y, Li S, Zhang W, Pang Y, Lee TY. iScience 27: 2024 109333	0