Hartwig Medical Foundation and UMCCR collaborate to standardise cancer bioinformatics workflows
The University of Melbourne Centre for Cancer Research (UMCCR) Genomics Platform Group, led by Professor Oliver Hofmann, has collaborated with the Hartwig Medical Foundation in Australia and The Netherlands (Hartwig) to improve and support access to a bioinformatics workflow for genomic sequencing analysis of cancer—an important step in facilitating data exchange between international research partners.
The UMCCR team has implemented the comprehensive cancer genomics toolset “WiGiTS”—developed by Hartwig—in the widely used Nextflow workflow language, and released it as a standardised, user-friendly application called “oncoanalyser”.
It offers a seamlessly integrated toolkit of bioinformatics tools for genomics in oncology; from neoepitopes to copy-number changes, and SNVs and InDels, to fusions and structural variants, all converging into one stream of data and an integrated report.
Importantly, oncoanalyser has been accepted into nf-core—a community-driven effort to collect a curated set of recommended, and streamlined analysis pipelines, aimed to reduce duplication and ultimately increase data utilisation and comparability.
Researchers can now readily analyse cancer genome sequence data across various computing environments, including on-premises systems, public clouds and commercial cloud platforms—ensuring scalability, reproducibility and consistency.
The UMCCR team was driven by its interest in standards development and re-useable workflows, with creation of oncoanalyser enabled and led by their senior bioinformatician Dr Stephen Watts.
“With oncoanalyser being accepted as a community-endorsed pipeline for cancer patient analysis, we are hoping to accelerate the use of genomic testing for cancer patients across labs who previously might not have had the capacity to do so.” Dr Watts said.
Professor Hofmann noted that “the use of a standardised, streamlined workflow will mean that we can collectively increase sample sizes to more accurately find driver genes and other genomic features of different cancer types, which has historically been a massive hurdle worldwide.”
“We are looking forward to working with the international clinical and research community to see if we can harmonise the results from existing cohorts, making them more comparable and encouraging data exchange between partners—with the ultimate aim of contributing to a learning health care system.” he said.
Dr Joep de Ligt, data lead at Hartwig, said that oncoanalyser workflow marks a significant step forward towards an internationally supported standard and end-to-end solution for molecular oncology.
“We are thrilled to announce the results of a collaboration with Professor Hofmann’s team at the University of Melbourne Centre for Cancer Research, who have diligently made the WiGiTs workflow adaptable to any computational environment.” Dr de Ligt said.
“We have been looking for ways to make our toolkit more accessible and portable to different computational environments, while recognising the diverse landscape of bioinformatics, and we are looking forward to working with the international community to support its adoption and future improvements.”
Dr de Ligt said that Hartwig is committed to the continuous validation, support and innovation of the WiGiTS tools to ensure reliability and continuous improvement for both research and diagnostic applications.
“Hartwig has already made uniformly analysed data of more than 6,500 patients available to the community, and is exploring collaboration partnerships for connecting similar resources world-wide to facilitate researchers and improving cancer care.”
The Hartwig Medical Foundation was established to promote scientific research for improving diagnostics and care of cancer patients. Hartwig seeks to achieve this goal by facilitating complete DNA analysis by whole genome and transcriptome sequencing of patients with cancer in the Netherlands. Hartwig develops and provides tooling and services to deliver accredited diagnostic patient reports with tailored treatment recommendations.