Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.

Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.

Project description:Purpose: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-associated mortality worldwide. Although the molecular mechanisms underpinning HCC are unknown, gene copy number and associated mRNA expression changes are frequently reported. Experimental Design: Comparative genomic hybridization arrays spotted with 4,041 bacterial artificial chromosome clones were used to assess copy number changes in 45 HCC tissues to identify chromosomal regions associated with the pathogenesis of HCC. Seventy more HCC tissues were used to validate candidate genes by using western blots and immunohistochemistry. Results: A total of 259 clones were associated with copy number changes that significantly differed between normal liver and HCC samples. The chromosomal region 1q32.1 containing the nuclear casein kinase and cyclin-dependent kinase substrate 1 (NUCKS1) gene was associated with tumor vascular invasion. Western blot analysis demonstrated that NUCKS1 was up-regulated in 37 of 70 (52.8%) HCC tissues compared with adjacent non-tumor tissues, and over-expressed in a vast majority of HCCs (44/52, 84.6%) as determined by immunohistochemical staining. Furthermore, immunostaining of both NUCKS1 and glypican-3 improved the diagnostic prediction of HCC. Knock-down of NUCKS1 by siRNA decreased the cell viability of the Hep3B cell line and reduced tumor formation in a xenograft mouse model. Functional enrichment analysis revealed the association of NUCKS1 with signal transduction, immunity and defense, and nucleotide metabolism pathways. Conclusions: NUCKS1 was identified as a potential oncogene at chromosomal 1q32.1 in patients with HCC, and it might be a valuable immunodiagnostic marker for HCC. Comparative genomic hybridization arrays spotted with 4,041 bacterial artificial chromosome clones were used to assess copy number changes in 45 HCC tissues and 25 normal liver tissues to identify chromosomal regions associated with the pathogenesis of HCC

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Integrative omics analysis in HCC samples [mRNA expression]

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