The dual role of transforming growth factor-beta signatures in human B viral multistep hepatocarcinogenesis: early and late responsive genes

Background/Aim Transforming growth factor-beta (TGF-β) has a dichotomous role, functioning as a tumor suppressor and tumor promoter. TGF-β signatures, explored in mouse hepatocytes, have been reported to predict the clinical outcomes of hepatocellular carcinoma (HCC) patients; HCCs exhibiting early TGF-β signatures showed a better prognosis than those with late TGF-β signatures. The expression status of early and late TGF-β signatures remains unclear in defined lesions of human B-viral multistep hepatocarcinogenesis. Methods The expression of TGF-β signatures, early and late responsive signatures of TGF-β were investigated and analyzed for their correlation in cirrhosis, low-grade dysplastic nodules (DNs), high-grade DNs, early HCCs and progressed HCCs (pHCCs) by real-time PCR and immunohistochemistry. Results The expression levels of TGF-β signaling genes (TGFB1, TGFBR1, TGFBR2 and SMAD4) gradually increased with the progression of hepatocarcinogenesis, peaking in pHCCs. The expression of early responsive genes of TGF-β (GADD45B, FBP1, CYP1A2 and CYP3A4) gradually decreased, and that of the late TGF-β signatures (TWIST and SNAI1) significantly increased according to the progression of multistep hepatocarcinogenesis. Furthermore, mRNA levels of TWIST and SNAI1 were well correlated with those of stemness markers, with upregulation of TGF-β signaling, whereas FBP1 expression was inversely correlated with that of stemness markers. Conclusions The enrichment of the late responsive signatures of TGF-β with induction of stemness is considered to be involved in the progression of the late stage of multistep hepatocarcinogenesis, whereas the early responsive signatures of TGF-β are suggested to have tumor-suppressive roles in precancerous lesions of the early stage of multistep hepatocarcinogenesis

SEQprocess: a modularized and customizable pipeline framework for NGS processing in R package

Abstract Backgrounds Next-Generation Sequencing (NGS) is now widely used in biomedical research for various applications. Processing of NGS data requires multiple programs and customization of the processing pipelines according to the data platforms. However, rapid progress of the NGS applications and processing methods urgently require prompt update of the pipelines. Recent clinical applications of NGS technology such as cell-free DNA, cancer panel, or exosomal RNA sequencing data also require appropriate customization of the processing pipelines. Here, we developed SEQprocess, a highly extendable framework that can provide standard as well as customized pipelines for NGS data processing. Results SEQprocess was implemented in an R package with fully modularized steps for data processing that can be easily customized. Currently, six pre-customized pipelines are provided that can be easily executed by non-experts such as biomedical scientists, including the National Cancer Institute’s (NCI) Genomic Data Commons (GDC) pipelines as well as the popularly used pipelines for variant calling (e.g., GATK) and estimation of allele frequency, RNA abundance (e.g., TopHat2/Cufflink), or DNA copy numbers (e.g., Sequenza). In addition, optimized pipelines for the clinical sequencing from cell-free DNA or miR-Seq are also provided. The processed data were transformed into R package-compatible data type ‘ExpressionSet’ or ‘SummarizedExperiment’, which could facilitate subsequent data analysis within R environment. Finally, an automated report summarizing the processing steps are also provided to ensure reproducibility of the NGS data analysis. Conclusion SEQprocess provides a highly extendable and R compatible framework that can manage customized and reproducible pipelines for handling multiple legacy NGS processing tools