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

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 whole transcriptome, 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 formalin-fixed, paraffin-embedded human fibrolamellar hepatocellular carcinoma

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.

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 whole transcriptome, 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.

Dataset Information

Chronic lymphocytic leukemia with IGH::BCL3-translocation is characterized by a homogenous and distinct genetic and epigenetic landscape

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets