Dataset for: Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma

Molecular markers are not used in the determination of prognosis and treatment for HCC patients. We proposed that the identification of the common pro-oncogenic pathways in primary tumor (PT) and adjacent non-malignant tissues (AT) predicting HCC patient risks result in the HCC marker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24-ribosomal gene-based HCC classifier (RGC), which are prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (HR=8.2, p=9.4E-06) and cross-cohort validation (HR=2.63, p=0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (HR=5.0, p=0.03) and cross-validation (HR=1.9, p=0.03) HCC groupsconfirming the accuracy and robustness of RGC. Our experimental and bioinformatics analyses suggested a key role for c-MYC in the pro-oncogenic pattern of ribosomal biogenesis co-regulation in PT and AT. Microarray, qRT-PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co-transcriptional patterns of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, supported by the model of tumor-like metabolic redirection/assimilation in non-malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non-malignant liver tissue alone or in combination with HCC tissue biopsy could be an important target to develop predictive and monitoring strategies and evidence-based therapeutic interventions to reduce the risk of post-surgery relapse of HCC patients.