MPIC: Molecular Prognostic Indicators in Cirrhosis Database for Clinical Context-Specific in Silico Prognostic Biomarker Validation.

Prognostic biomarkers are vital in the management of progressive chronic diseases such as liver cirrhosis, affecting 1-2% of the global population and causing over 1 million deaths every year. Despite numerous candidate biomarkers in literature, the costly and lengthy process of validation hampers their clinical translation. Existing omics databases are not suitable for in silico validation due to the ignorance of critical factors, i.e., study design, clinical context of biomarker application, and statistical power. To address the unmet need, we have developed the Molecular Prognostic Indicators in Cirrhosis (MPIC) database as a representative example of an omics database tailored for prognostic biomarker validation. MPIC consists of (i) a molecular and clinical database structured by defined disease context and specific clinical outcome and annotated with employed study design and anticipated statistical power by disease domain experts, (ii) a bioinformatics analysis engine for user-provided gene-signature- or gene-based prognostic prediction, and (iii) a user interface for interactive exploration of relevant clinical cohort/scenario and assessment of significance and reliability of the result for prognostic prediction. MPIC assists cost-effective prognostic biomarker development by facilitating the process of validation, and will transform the care of chronic diseases such as cirrhosis. MPIC is freely available at www.mpic-app.org. The website is implemented in Java, Apache, and MySQL with all major browsers supported.

Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data.

Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.

Linnorm: improved statistical analysis for single cell RNA-seq expression data.

Linnorm is a novel normalization and transformation method for the analysis of single cell RNA sequencing (scRNA-seq) data. Linnorm is developed to remove technical noises and simultaneously preserve biological variations in scRNA-seq data, such that existing statistical methods can be improved. Using real scRNA-seq data, we compared Linnorm with existing normalization methods, including NODES, SAMstrt, SCnorm, scran, DESeq and TMM. Linnorm shows advantages in speed, technical noise removal and preservation of cell heterogeneity, which can improve existing methods in the discovery of novel subtypes, pseudo-temporal ordering of cells, clustering analysis, etc. Linnorm also performs better than existing DEG analysis methods, including BASiCS, NODES, SAMstrt, Seurat and DESeq2, in false positive rate control and accuracy.

Real-life efficacy and safety of paritaprevir/ritonavir, ombitasvir, and dasabuvir in chronic hepatitis C patients in Hong Kong.

BACKGROUND AND AIM: In registration studies, combination therapy of paritaprevir/ritonavir, ombitasvir, and dasabuvir (PrOD) with and without ribavirin for 12-24 weeks can achieve > 90% sustained virological response (SVR) for genotype 1 hepatitis C virus (HCV) infection. However, data in Asia is scanty. We aimed to study the efficacy and safety of this combination therapy in chronic hepatitis C patients in Hong Kong. METHODS: We retrospectively analyzed data from six local hospitals that have prescribed PrOD with and without ribavirin to patients with genotype 1 chronic HCV infection as part of a global compassionate program. RESULTS: Among 41 patients treated, 35 (85%) patients had genotype 1b HCV infection, 6 (15%) had co-infection with human immunodeficiency virus, 35 (85%) failed previous peginterferon and ribavirin therapy, 25 (61%) had compensated liver cirrhosis, and 3 (7%) had liver transplantation. Thirty-five (85%) patients received 12-week treatment and six patients received 24-week treatment; 26 (63%) patients received ribavirin combination. Thirty-nine (95%; 95% confidence interval 88.5-100%) patients had undetectable HCV RNA at 12-week post-treatment, that is, SVR. The two patients who did not develop SVR discontinued treatment prematurely; both of them were treatment experienced with liver cirrhosis complicated by acute renal failure unrelated to the treatment of PrOD and ribavirin. No patient had hepatic decompensation. CONCLUSIONS: Paritaprevir/ritonavir, ombitasvir, and dasabuvir with or without ribavirin is effective and safe in patients with genotype 1 HCV infection in real-life clinical setting in Hong Kong.

Functional networks of aging markers in the glomeruli of IgA nephropathy: a new therapeutic opportunity.

IgA nephropathy(IgAN) is the most common primary glomerular disease in China. Primary infections always occur before IgAN. However, the pathology of IgAN is still unclear. Previously we found that LL37, a protein secreted by senescent cells, was specific for the progression of IgAN, and also played a role in the neutrophil function. So we hypothesized that the infiltration of neutrophils, inflammation factors, and aging markers , which were modulated by functional networks, induced the immune response and renal injury. RNA-Sequencing (RNA-seq) can be used to study the whole transcriptome and detect splicing variants that are expressed in a specific cell type or tissue. We separate glomerulus from the renal biopsy tissues. After RNA extraction, the sequences were analyzed with Illumina HiSeq 2000/2500. 381 genes with differential expression between the IgAN patients and the healthy controls were identified. Only PLAU, JUN, and FOS were related to DNA damage, telomere dysfunction-induced aging markers, neutrophil function and IgA nephropathy. The networks showed the possibility of these genes being connected. We conclude that DNA damage and telomere dysfunction could play important roles in IgA nephropathy. In addition, neutrophils are also important factors in this disease. The networks of these markers showed the mechanism pathways that are involved in the duration of the occurrence and progression of IgA nephropathy and might be a new therapeutic opportunity for disease treatment.

A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration.

OBJECTIVE: The number of patients with HCV-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. DESIGN: We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1 mg/dL) and platelet count (<100,000/mm(3)), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10 years). The gene signature test was implemented using a digital transcript counting (nCounter) assay specifically developed for clinical use and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the USA (validation cohort, n=145, median follow-up 8 years). RESULTS: In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001) and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high-risk (16%), intermediate-risk (42%) or low-risk (42%) groups by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001) and all liver-related adverse events (HR=4.98, p<0.001). CONCLUSIONS: A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction and clinical trial stratification and enrichment for preventive interventions.

Confident assignment of site-specific glycosylation in complex glycoproteins in a single step.

A glycoprotein may contain several sites of glycosylation, each of which is heterogeneous. As a consequence of glycoform diversity and signal suppression from nonglycosylated peptides that ionize more efficiently, typical reversed-phase LC-MS and bottom-up proteomics database searching workflows do not perform well for identification of site-specific glycosylation for complex glycoproteins. We present an LC-MS system for enrichment, separation, and analysis of glycopeptides from complex glycoproteins (>4 N-glycosylation sequons) in a single step. This system uses an online HILIC enrichment trap prior to reversed-phase C18-MS analysis. We demonstrated the effectiveness of the system using a set of glycoproteins including human transferrin (2 sequons), human alpha-1-acid glycoprotein (5 sequons), and influenza A virus hemagglutinin (9 sequons). The online enrichment renders glycopeptides the most abundant ions detected, thereby facilitating the generation of high-quality data-dependent tandem mass spectra. The tandem mass spectra exhibited product ions from both glycan and peptide backbone dissociation for a majority of the glycopeptides tested using collisionally activated dissociation that served to confidently assign site-specific glycosylation. We demonstrated the value of our system to define site-specific glycosylation using a hemagglutinin containing 9 N-glycosylation sequons from a single HILIC-C18-MS acquisition.