Project description:Hepatocellular carcinoma (HCC) is a common malignancy with high mortality due to a lack of effective therapies. HCC represents a collection of highly heterogeneous tumor types but a general molecular classification of HCC is lacking. Here, we define three molecular subtypes of HCC that are observed across various independent patient cohorts and profiling platforms. Analysis of the expression signatures indicates that a limited number of pathways and processes drive the clustering of these subtypes. Notably, TGF-beta signaling is a critical factor that distinguishes two subtypes of high-grade tumors, and is associated with early tumor recurrence. Furthermore, both bioinformatics and functional analyses reveal molecular crosstalk between TGF-beta and WNT signaling pathways. These findings suggest that TGF-beta plays a critical role in a subclass of HCC tumors and may enhance WNT pathway activation in the absence of activating mutations in canonical pathway components. This study is an example of how robust molecular subclassification can be used to interrogate molecular abnormalities in the context of human cancer. Experiment Overall Design: Four hepatocellular carcinoma (HCC) cell line samples treated or untreated by TGF-beta
Project description:Matrisome-focused integrative omics analysis reveals stromal phenotypes associated with consensus molecular subtypes in colorectal cancer
This reseaerch is conducted using colorectal cancer.
TMT 11plex experiment
Project description:WXS files for Mullighan Leventaki ALCL paper titled "Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures."
Project description:This SuperSeries is composed of the following subset Series: GSE35311: Integrative array-based approach identifies MZB1 as a frequently methylated putative tumor-suppressor in hepatocellular carcinoma (expression) GSE35312: Integrative array-based approach identifies MZB1 as a frequently methylated putative tumor-suppressor in hepatocellular carcinoma (MeDIP) Refer to individual Series
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
