InterARTIC: an interactive web application for whole-genome nanopore sequencing analysis of SARS-CoV-2 and other viruses.

MOTIVATION: InterARTIC is an interactive web application for the analysis of viral whole-genome sequencing (WGS) data generated on Oxford Nanopore Technologies (ONT) devices. A graphical interface enables users with no bioinformatics expertise to analyze WGS experiments and reconstruct consensus genome sequences from individual isolates of viruses, such as SARS-CoV-2. InterARTIC is intended to facilitate widespread adoption and standardization of ONT sequencing for viral surveillance and molecular epidemiology. RESULTS: We demonstrate the use of InterARTIC for the analysis of ONT viral WGS data from SARS-CoV-2 and Ebola virus, using a laptop computer or the internal computer on an ONT GridION sequencing device. We showcase the intuitive graphical interface, workflow customization capabilities and job-scheduling system that facilitate execution of small- and large-scale WGS projects on any common virus. AVAILABILITY AND IMPLEMENTATION: InterARTIC is a free, open-source web application implemented in Python that executes best-practice command line workflows from the ARTIC network. The application can be downloaded as a set of pre-compiled binaries that are compatible with all common Linux distributions, Windows with Linux subsystems, MacOSX and ARM systems. All code can be found on GitHub at https://github.com/Psy-Fer/interARTIC/ and documentation can be found at https://github.com/Psy-Fer/interARTIC/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer.

BACKGROUND: Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. METHODS: We combined immunohistochemistry (IHC) with RNA sequencing and whole-genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Furthermore, we explored transcriptional features of immune archetypes and T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions and assessed the common adult biomarkers such as neoantigen load and TMB. RESULTS: A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. CONCLUSIONS: Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer.

The Zero Childhood Cancer Program is a precision medicine program to benefit children with poor-outcome, rare, relapsed or refractory cancer. Using tumor and germline whole genome sequencing (WGS) and RNA sequencing (RNAseq) across 252 tumors from high-risk pediatric patients with cancer, we identified 968 reportable molecular aberrations (39.9% in WGS and RNAseq, 35.1% in WGS only and 25.0% in RNAseq only). Of these patients, 93.7% had at least one germline or somatic aberration, 71.4% had therapeutic targets and 5.2% had a change in diagnosis. WGS identified pathogenic cancer-predisposing variants in 16.2% of patients. In 76 central nervous system tumors, methylome analysis confirmed diagnosis in 71.1% of patients and contributed to a change of diagnosis in two patients (2.6%). To date, 43 patients have received a recommended therapy, 38 of whom could be evaluated, with 31% showing objective evidence of clinical benefit. Comprehensive molecular profiling resolved the molecular basis of virtually all high-risk cancers, leading to clinical benefit in some patients.