Project description:Purpose: To gain molecular insights of HBV integration that may contribute to HCC tumorigenesis, we performed whole transcriptome sequencing and whole genome copy number profiling of hepatocellular carcinoma (HCC) samples from 50 Chinese patients. Results: We identified a total of 33 HBV-human integration sites in 16 of 44 HBV-positive HCC tissues, which were enriched in HBV genotype C-infected patients. In addition, significantly recurrent HBV-MLL4 integration (18%). This dataset is part of the TransQST collection.
Project description:Purpose: To gain molecular insights of HBV integration that may contribute to HCC tumorigenesis, we performed whole transcriptome sequencing and whole genome copy number profiling of hepatocellular carcinoma (HCC) samples from 50 Chinese patients. Conclusions: This is the first report on the molecular basis of the MLL4 integration driving MLL4 over-expression. HBV-MLL4 integration occurred frequently in Chinese HCC patients, representing a unique molecular segment for HCC with HBV infection. We profiled 50 Chinese Hepatocellular Carcinoma patients and 14 adjacent tissues using Agilent 244K array CGH technology. 50 Tumor samples also did RNASeq profiling.
Project description:In this study, we used the Affymetrix HG-U133A 2.0 GeneChip for deriving a multigenic classifier capable of predicting HCV+cirrhosis with vs without concomitant HCC. We studied gene expression in cirrhotic tissues with (N=16) and without (N=47) HCC. Keywords: cross-sectional Liver tissue samples were obtained from patients waiting for liver transplantation. For each sample, RNA was extracted and hybridized to an Affymetrix GeneChip. This dataset is part of the TransQST collection.
Project description:The purpose of this study is to identify the characteristics of different HCC subtypes through next generation sequencing and metabolome analysis.The samples for transcriptome sequencing were collected from 60 cases of HCC, 30 of which were also used for whole exome sequencing and LC-MS/MS.
Project description:In this study, we identified and validated a molecular classification of hepatocellular carcinoma (HCC) based on 42 fatty acid degradation (FAD) genes in clinical samples. We further searched PubMed for the RNA sequencing datasets of mouse models to identify the FAD subtypes in mouse HCC models. A total of 90 samples were collected from five publicly available datasets including 11 mouse HCC models. In addition, the transcriptome sequencing data of 8 samples from our two mouse models (NRAS.MYC.ND and AKT1.MYC.KD) were also included. This dataset aims to explore the transcriptomic characteristics of these two models.
Project description:RNAseq was done on Breast cancer PDX samples uisng Library protocol =llumina TruSeq Stranded Total RNA Kit with Ribo-Zero Gold , HiSeq 125 Cycle Paired-End Sequencing v4
Project description:RNAseq was done on Breast cancer PDX samples uisng Library protocol =llumina TruSeq Stranded Total RNA Kit with Ribo-Zero Gold , HiSeq 50 Cycle Single-Read Sequencing v4
Project description:We profiled the mutations and gene expressions of early and advanced hepatocellular carcinoma (HCC) related with Hepatitis B-viral infection. Integrative analysis was performed with whole-exome sequencing and gene expression profiles of the 12 cases of early and advanced HCCs and paired non-tumoral adjacent liver tissues. 12 HCC Samples
Project description:We have generated a collection of patient-derived xenograft (PDX) tumor models and characterized them at the molecular level to facilitate precision oncology. Surgically resected HCC specimens were subcutaneously implanted in immunodeficient mice. Resulting xenografts were serially implanted to establish transplantable PDX models, which were sequentially subject to whole exome sequencing (WES), gene expression array, genome-wide human single nucleotide polymorphism (SNP) array 6.0, and serum a–fetoprotein (AFP) detection assay. The feasibility as a preclinical model was validated by efficacy studies using a standard-of-care (SOC) and a targeted agent, respectively.
Project description:Tumor budding (TB) has become a crucial factor for predicting the malignancy grade and prognostic outcome for multiple solid cancers.Studies have investigated the prognostic value of TB within hepatocellular carcinoma (HCC). However, its molecular mechanism within HCC remains unclear. This is the first study to discover and compare the expression of differentially expressed genes (DEGs) between TB-positive and TB-negative HCC tissues. Total RNA was extracted from 40 fresh HCC tissue samples with different TB statuses and then sequenced. This study provides insights into the possible mechanisms of TB in HCC and revealed potential predictive diagnosis markers and treatment targets for HCC.