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Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice

Abstract

Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.

Key points

  • Whole-genome sequencing analysis detects DNA changes in the whole cancer genome, allowing identification of new, clinically relevant biomarkers, and opening the doors to a new era of tumor diagnostic and personalized cancer medicine.

  • The protocol provides a detailed workflow covering patient selection, sample handling, and interpretation and reporting of the results, facilitating implementation of whole-genome sequencing analysis in routine oncology clinical practice.

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Fig. 1: Overview of the procedures for performing WGS in routine tumor diagnostics.
Fig. 2: Frozen sections showing examples of tissue biopsies with different TCPs.
Fig. 3: Frozen sections showing examples of tissues with different cell density.
Fig. 4: Examples of circos plots from WGS analysis of samples with increasing mTCP.

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Code availability

All code used is open source and available from third parties or developed by Hartwig Medical Foundation (https://github.com/hartwigmedical/). Multiple versions of the pipeline were used during this research (v5.23 and up). Versions of the pipeline are validated and verified according to the Dutch ISO-17025 certification and can be found at https://github.com/hartwigmedical/pipeline5/tags with no restrictions. A schematic overview of the pipeline can be found in Supplementary Fig. 1.

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Acknowledgements

We acknowledge ZonMw (the Netherlands Organization for Health Research and Development) Hartwig Medical Foundation and Illumina for funding the original study on which this protocol is based4.

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Authors and Affiliations

Authors

Contributions

Designed the protocol: K.G.S., L.J.W.B., L.J.S., D.S., P.R., M.C.B., A.J.d.L., E.d.B., H.V.S., L.E.v.d.K., E.C., E.E.V., J.G.v.d.B., T.E.B., F.L., B.M.H.v.L., K.v.D., K.v.d.B., U.U., L.S., E.G.K., G.A.M. and K.M. Performed experiments: D.S., B.M.H.v.L., E.d.B. and I.R. Interpretation of sequencing results: K.G.S., L.J.W.B., L.J.S., P.R., M.C.B., E.H.R., R.K., F.B.L.H., E.C. and K.M. Participated in multidisciplinary clinical decision-making: K.G.S., L.J.S., L.J.W.B., P.R., M.C.B., A.J.d.L., T.E.B., E.H.R., R.K., J.J.M.v.d.H., L.E.v.d.K. and K.M. Funding: K.M., L.J.W.B., H.V.S., E.C., E.E.V., G.A.M. and J.G.v.d.B. Bioinformatics support: L.S. and D.v.B. Radiology support: F.L. and E.G.K. Logistics design: K.G.S., L.J.S., L.J.W.B., D.S., K.M., K.v.D. and I.R. Wrote the manuscript: K.G.S., L.J.W.B., K.M. and G.A.M. Created figures: K.G.S., E.C., D.S. and L.J.W.B. All authors have read, critically revised and approved the manuscript.

Corresponding author

Correspondence to Gerrit A. Meijer.

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Competing interests

A.J.d.L. reports grants from Bristol Myers Squibb (BMS), Merck Sharp & Dohme (MSD), AstraZeneca and Boehringer, nonfinancial support from Merck Serono and Roche. H.v.S. and E.C. report consultancy fees and support for attending meetings and travelling from Illumina. E.E.V. is a member of the supervisory board of Hartwig. G.A.M. is co-founder and board member (CSO) of CRCbioscreen, he has a research collaboration with CZ Health Insurances (cash matching to ZonMW grant) and has research collaborations with Exact Sciences, Sysmex, Sentinel Ch. SpA, Personal Genome Diagnostics and DELFi; these companies provide materials, equipment and/or sample/genomic analyses. G.A.M. is an advisory board member of ‘Missie Tumor Onbekend’. K.M. reports research grants from AstraZeneca and speakers’ fees from MSD, Roche, AstraZeneca and Benecke. K.M. received consultancy fees from Pfizer, BMS, Roche, MSD, Abbvie, AstraZeneca, Diaceutics, Lilly, Bayer, Boehringer and Ingelheim and nonfinancial support from Roche, Takeda, Pfizer, PGDx and DELFi. The remaining authors report no conflicts of interest.

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Key references using this protocol

Samsom, K. G. et al. J. Pathol. 258, 179–188 (2022): https://doi.org/10.1002/path.5988

van der Velden, D. L. et al. Nature 574, 127–131 (2019): https://doi.org/10.1038/s41586-019-1600-x

van de Haar, J. et al. Nat. Med. 27, 1553–1563 (2021): https://doi.org/10.1038/s41591-021-01448-w

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Supplementary Information

Supplementary Procedure (Parts 9 and 10), Figs. 1 and 2 and Results.

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Samsom, K.G., Bosch, L.J.W., Schipper, L.J. et al. Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice. Nat Protoc 19, 700–726 (2024). https://doi.org/10.1038/s41596-023-00933-5

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