Project description:Background: It is a challenge to identify those patients who, after undergoing potentially curative treatments for hepatocellular carcinoma, are at greatest risk of recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissues. Methods: We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results: The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (p = 0.04). Conclusions: We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlating with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. This SuperSeries is composed of the following subset Series: GSE10140: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, Liver) GSE10141: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Training Set, HCC) GSE10142: Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma (Validation Set) Keywords: Hepatocellular carcinoma, Expression array, Illumina, Signatures, Outcome prediction Training cohort: 80 tumor and 82 non-tumor liver tissues surgically resected from patients with hepatocellular carcinoma (HCC); Validation cohort: 225 non-tumor liver tissues surgically resected from patients with HCC. Clinical data has been withheld from GEO due to privacy concerns.

Project description:Background & Aims: Fibrolamellar hepatocellular carcinoma (FLC) is a rare primary hepatic cancer usually developed in non-cirrhotic livers of children and young adults with unknown etiology. Treatment is limited to surgical intervention. To date, molecular pathogenesis of FLC has been poorly characterized. Herein, we aim to provide an integrative genomic analysis from a large series of FLC patients. Methods: A clinically annotated cohort of 77 FLCs was analyzed through wholetranscriptome, SNP-array and whole-exome sequencing. Non-negative matrix factorization was performed for class discovery, and GSEA, NTP, IPA and immunohistochemistry for functional annotation. GISTIC algorithm identified chromosomal aberrations; Mutect and VarScan2, somatic mutations, and Random survival forest the prognostic signature, validated in an independent cohort. Results: Unsupervised gene expression clustering revealed 3 robust molecular classes: Proliferation-51%, enriched with liver cancer proliferation signatures and mTOR signaling activation, Inflammation-26%, with pro-inflammatory cytokines signatures, and Unannotated-23%, with non-liver-related cancer signatures. Neuroendocrine genes and cholangiocyte and hepatocyte histological markers were present in all classes. FLC showed few copy number variations, being the most frequent: focal amplification at 8q24.3(12.5%), and deletions at 19p13(28%) and 22q13.32(25%). DNAJB1-PRKACA fusion transcript was observed in 79% of cases. FLC tumors had 32 damaging mutations on average, affecting uncommon genes in liver neoplasms (BRCA2, U2AF1). An 8-gene prognostic signature predicted survival in FLC patients. Conclusions: FLC genomic analysis reveals a unique molecular portrait characterized by uncommon damaging mutations and chromosomal aberrations, and a highly prevalent fusion protein. Three molecular classes, including Proliferation and Inflammation, define the biological behavior. Prognostic signature will allow better patient stratification. Gene-expression profiles of fresh frozen human fibrolamellar hepatocellular carcinoma

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