Bioinformatics is a rapidly evolving field charged with cataloging, disseminating, and analyzing biological data. Bioinformatics started with genomics, but while genomics focuses more narrowly on the genes comprising a genome, bioinformatics now encompasses a much broader range of omics technologies. Overcoming barriers of scale and effort that plagued earlier sequencing methods, bioinformatics adopted an ambitious strategy involving high-throughput and highly automated assays. However, as the list of omics technologies continues to grow, the field of bioinformatics has changed in two fundamental ways. Despite enormous success in expanding our understanding of the biological world, the failure of bulk methods to account for biologically important variability among cells of the same or different type has led to a major shift toward single-cell and spatially resolved omics methods, which attempt to disentangle the conflicting signals contained in heterogeneous samples by examining individual cells or cell clusters. The second major shift has been the attempt to integrate two or more different classes of omics data in a single multimodal analysis to identify patterns that bridge biological layers. For example, unraveling the cause of disease may reveal a metabolite deficiency caused by the failure of an enzyme to be phosphorylated because a gene is not expressed due to aberrant methylation as a result of a rare germline variant. Conclusions: There is a fine line between superficial understanding and analysis paralysis, but like a detective novel, multi-omics increasingly provides the clues we need, if only we are able to see them.

A small-animal model for hepatitis C virus (HCV) infection was developed using severe combined immunodeficiency (SCID) mice encoding homozygous urokinase-type plasminogen activator (uPA) transplanted with human hepatocytes. Currently, limited information is available concerning the HCV clearance rate in the SCID mouse model and the virion production rate in engrafted hepatocytes. In this study, several cohorts of uPA+/+/SCID+/+ mice with nearly half of their livers repopulated by human hepatocytes were infected with HCV genotype 1b and used to evaluate HCV dynamics by pharmacokinetic and pharmacodynamic analyses of a specific NS3-4A protease inhibitor (telaprevir). A dose-dependent reduction in serum HCV RNA was observed. At telaprevir exposure equivalent to that in clinical studies, rapid turnover of serum HCV was also observed in this mouse model and the estimated slopes of virus decline were 0.11–0.17 log10 h−1. During the initial phase of treatment, the log10 reduction level of HCV RNA was dependent on the drug concentration, which was about fourfold higher in the liver than in plasma. HCV RNA levels in the liver relative to human endogenous gene expression were correlated with serum HCV RNA levels at the end of treatment for up to 10 days. A mathematical model analysis of viral kinetics suggested that 1 g of the chimeric human liver could produce at least 108 virions per day, and this may be comparable to HCV production in the human liver.

Objective We recently demonstrated that combination treatment with NS3 protease and NS5B polymerase inhibitors succeeded in eradicating the virus in genotype 1b hepatitis C virus (HCV)-infected mice. In this study, we investigated the effect of combining an NS5A replication complex inhibitor (RCI) with either NS3 protease or NS5B inhibitors on elimination of HCV genotypes 1b, 2a and 2b. Design The effects of Bristol-Myers Squibb (BMS)-605339 (NS3 protease inhibitor; PI), BMS-788329 (NS5A RCI) and BMS-821095 (NS5B non-nucleoside analogue inhibitor) on HCV genotypes 1b and 2a were examined using subgenomic HCV replicon cells. HCV genotype 1b, 2a or 2b-infected human hepatocyte chimeric mice were also treated with BMS-605339, BMS-788329 or BMS-821095 alone or in combination with two of the drugs for 4 weeks. Genotypic analysis of viral sequences was achieved by direct and ultra-deep sequencing. Results Anti-HCV effects of BMS-605339 and BMS-821095 were more potent against genotype 1b than against genotype 2a. In in-vivo experiments, viral breakthrough due to the development of a high prevalence of drug-resistant variants was observed in mice treated with BMS-605339, BMS-788329 and BMS-821095 in monotherapy. In contrast to monotherapy, 4 weeks of combination therapy with the NS5A RCI and either NS3 PI or NS5B inhibitor succeeded in completely eradicating the virus in genotype 1b HCV-infected mice. Conversely, these combination therapies failed to eradicate the virus in mice infected with HCV genotypes 2a or 2b. Conclusions These oral combination therapies may serve as a Peg-alfa-free treatment for patients chronically infected with HCV genotype 1b.

In patients with advanced hepatocellular carcinoma (HCC), evidence is unclear as to whether hepatic arterial infusion chemotherapy (HAIC) or sorafenib is superior. We performed a prospective, open-label, non-comparative phase II study to assess survival with HAIC or HAIC converted to sorafenib. Fifty-five patients were prospectively enrolled. Patients received HAIC as a second course if they had complete response, partial response, or stable disease (SD) with an alpha fetoprotein (AFP) ratio < 1 or a des-γ-carboxy prothrombin (DCP) ratio < 1. Patients were switched to sorafenib if they had SD with an AFP ratio > 1 and a DCP ratio > 1 or disease progression. The primary endpoint was the 1-year survival rate. Secondary endpoints were the 2-year survival rate, HAIC response, survival rate among HAIC responders, progression-free survival, and adverse events. Of the 55 patients in the intent-to-treat population, the 1-year and 2-year survival rates were 64.0 and 48.3%, respectively. After the first course of HAIC, one (1.8%) patient showed complete response, 13 (23.6%) showed partial response, 30 (54.5%) had SD, and 10 (18.1%) patients had progressive disease. Twenty-three patients (41.8%) had SD with AFP ratios < 1 or DCP ratios < 1, and 7 (12.7%) had SD with AFP ratios > 1 and DCP ratios > 1. Thirty-seven patients (68.5%) were responders and 17 (30.9%) were non-responders to HAIC. In responders, the 1-year and 2-year survival rates were 78 and 62%, respectively. Given the results of this study, this protocol deserves consideration for patients with advanced HCC. This trial was registered prospectively from December 12. 2012 to September 1. 2016.

The efficacy and safety of immune-checkpoint inhibitors (ICI) for the treatment of unresectable hepatocellular carcinoma are known. We explored ICI rechallenges with direct switching from 1 ICI regimen to another. This retrospective study included 16 patients who received atezolizumab–bevacizumab (Atezo+Bev) and durvalumab–tremelimumab (Dur+Tre) as the first-line and second-line combination therapy, respectively, at Hiroshima University Hospital. The radiological response and adverse event were evaluated in all patients. Of the 16 patients, 12 were male, and the median age at Atezo+Bev induction was 71 years. The reasons for medication changes were disease progression in 11 patients and adverse events in 5 patients. With Atezo+Bev and Dur+Tre initiation, the Barcelona-Clinic Liver-Cancer stage (A/B/C) progressed in 9/6/3 and 3/4/9 patients and the Child–Pugh classification (A/B/C) progressed in 12/4/0 and 9/6/3 patients, respectively. The disease control rate and overall response rate of Atezo+Bev were 87.5% and 58.3%, respectively, and of Dur+Tre were 62.5% and 0%, respectively. The most common immune-related adverse event in both the Atezo+Bev and Dur+Tre groups was colitis; 3 of the 5 patients with colitis on Atezo+Bev treatment had colitis with Dur+Tre, and 2 had exacerbations. Regarding liver function, ALBI score significantly decreased during Atezo+Bev, but not Dur+Tre, treatment. In patients with colitis following Atezo+Bev, subsequent Dur+Tre treatment may induce colitis recurrence or exacerbation. For immune-related adverse events other than colitis, Dur+Tre could provide relatively safe disease control while maintaining liver function.