Dataset Information

Hepatocellular carcinoma proteomics

ABSTRACT: A DIA proteome analysis on HCC tissue (CA) and adjacent non-tumorous tissue (NO) samples

ORGANISM(S): Homo Sapiens

SUBMITTER: Tao Tao

PROVIDER: PXD021979 | iProX | Wed Oct 14 00:00:00 BST 2020

REPOSITORIES: iProX

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Publications

ACOX2 is a prognostic marker and impedes the progression of hepatocellular carcinoma via PPARα pathway.

Zhang Qifan Q Zhang Yunbin Y Sun Shibo S Wang Kai K Qian Jianping J Cui Zhonglin Z Tao Tao T Zhou Jie J

Cell death & disease 20210104 1

Hepatocellular carcinoma (HCC) has been extensively studied as one of the most aggressive tumors worldwide. However, its mortality rate remains high due to ideal diagnosis and treatment strategies. Uncovering novel genes with prognostic significance would shed light on improving the HCC patient's outcome. In our study, we applied data-independent acquisition (DIA) quantitative proteomics to investigate the expression landscape of 24 paired HCC patients. A total of 1029 differentially expressed p ...[more]

PMID: 33414412

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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.

Dataset Information

Hepatocellular carcinoma proteomics

Publications

ACOX2 is a prognostic marker and impedes the progression of hepatocellular carcinoma via PPARα pathway.

Similar Datasets

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