Clinical Impact of Ultra-Fast Whole Genome Sequencing in Paediatric Haematology-Oncology Practice

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Abstract

Background

Whole Genome Sequencing (WGS) enhances paediatric cancer diagnosis and management compared with standard molecular assays. However, its clinical utility could be further improved by reducing the National Health Service England (NHSE) turnaround times (TAT).

Methods

We evaluated an ‘Ultra-Fast WGS’ (UF-WGS) workflow in a tertiary UK paediatric haematology-oncology unit. Children with suspected or confirmed cancer were recruited over two years (2023-2025), and their tumour, bone marrow and/or blood samples were sequenced on the UF-WGS workflow. All patients underwent concurrent NHSE Genomic Medicine Service (GMS) WGS, serving as the validation benchmark.

Results

A total of 54 patients were recruited at diagnosis or relapse. UF-WGS reduced TAT to a mean of 3 days from sample collection, compared with 37 days for GMS-WGS. UF-WGS recalled 95% (143/151) of all clinically actionable somatic and germline variants found by standard NHS GMS-WGS testing. UF-WGS detected an additional 19 clinically actionable variants not found by GMS-WGS. Differences between the two workflows were attributable to tumour heterogeneity in some cases, and low variant allele frequency of those variants identified discrepantly.

Additionally, in 18/35 (51%) prospective cases, UF-WGS enabled demonstrable improvements in care. Clinicians independently judged that 9/19 (47%) of the retrospective cases would have clinically benefited from real-time UF-WGS. UF-WGS provided additional flowcell proximity data, which illustrated the potential to positively impact clinical care.

Conclusions

This study indicates the feasibility and utility of UF-WGS and shows added benefits for the clinical management of paediatric cancers, with wider implications beyond this patient group.

Trial Registration

22/WA/0336, NCT 07201038 ( clinicaltrials.gov )

Article activity feed

  1. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22979458.

    General assessment

    This is an interesting and clinically relevant study evaluating the feasibility and potential clinical utility of ultra-fast whole genome sequencing (UF-WGS) in paediatric haematology-oncology practice. The manuscript addresses an important limitation of current genomic testing: although whole genome sequencing can provide comprehensive molecular information, its clinical value may be reduced when results are not available within the timeframe in which important treatment decisions need to be made.

    The authors evaluate UF-WGS in a real-world tertiary paediatric haematology-oncology setting and compare the workflow with NHS Genomic Medicine Service whole genome sequencing. The study includes 54 patients with a broad range of solid and haematological malignancies, comprising both prospectively recruited and retrospective cases. The combination of analytical comparison, turnaround-time assessment, and evaluation of potential clinical impact makes the study particularly valuable from a translational perspective.

    Overall, the manuscript provides encouraging evidence that comprehensive genomic information can be generated within a timeframe that is much more compatible with routine clinical decision-making in paediatric oncology.

    Strengths of the study

    A major strength is the clear clinical focus of the work. Rather than examining sequencing performance only under laboratory conditions, the authors evaluate UF-WGS in patients undergoing investigation and treatment within an established paediatric oncology service. This increases the relevance of the findings to future clinical implementation.

    The reduction in turnaround time is particularly impressive. UF-WGS achieved a mean turnaround time of approximately three days compared with 37 days for GMS-WGS. In paediatric oncology, where diagnostic classification, risk stratification, surgery, chemotherapy, or targeted treatment may need to be determined rapidly, this difference has potentially important practical implications.

    The analytical concordance is also encouraging. UF-WGS recalled 143 of 151 clinically actionable somatic and germline variants identified through standard testing, corresponding to approximately 95% recall. In addition, UF-WGS identified 19 clinically actionable variants that were not identified by GMS-WGS. These results suggest that the faster workflow does not simply provide genomic information more rapidly but may also contribute additional clinically relevant information.

    Another strength is the inclusion of both prospective and retrospective cohorts. The prospective cohort provides evidence of how UF-WGS can function within contemporary clinical practice, while the retrospective cases allow the authors to examine a broader range of molecular abnormalities and clinically informative scenarios.

    The clinical-impact component is particularly interesting. In 18 of 35 prospective cases, UF-WGS was associated with improvements in clinical care, while clinicians considered that 9 of 19 retrospective patients could have benefited if UF-WGS had been available in real time. These findings help move the discussion beyond analytical performance and illustrate why turnaround time is clinically important.

    The examples presented throughout the manuscript are useful in demonstrating how rapid genomic information can contribute to diagnosis, risk stratification, therapeutic decision-making, and avoidance of unnecessary interventions. This patient-level perspective makes the manuscript accessible to both genomic scientists and clinicians.

    The additional flowcell proximity information is another interesting aspect of the study. The ability to obtain additional information concerning genomic structure and difficult genomic regions from the same sequencing workflow could potentially expand the clinical value of WGS without requiring multiple separate molecular assays.

    Comments and suggestions

    The manuscript is generally clear and well organised. I have several suggestions that may further improve its presentation.

    First, it may be helpful to provide an even clearer description of how "clinical impact" was defined. The individual examples are informative, but a concise predefined classification of clinical benefit—for example, change in diagnosis, change in treatment, altered risk classification, avoidance of an intervention, or provision of additional prognostic information—would make the clinical-impact analysis easier to interpret and potentially easier to reproduce in future studies.

    Similarly, presenting the prospective clinical benefits according to these categories in a table could be useful. This would allow readers to quickly understand which areas of paediatric oncology practice benefited most frequently from rapid genomic information.

    Second, the turnaround-time findings are one of the strongest aspects of the manuscript. Additional information about the distribution of turnaround times, such as median, range, or interquartile range, alongside the reported mean could provide readers with a more complete understanding of workflow reliability. Demonstrating that rapid turnaround is consistently achievable will be particularly important for future routine implementation.

    Third, the manuscript could potentially expand the discussion of how UF-WGS may integrate with existing diagnostic approaches. In current paediatric oncology practice, rapid targeted assays, cytogenetics, FISH, and other molecular tests may remain important in particular clinical situations. It would therefore be interesting to discuss whether UF-WGS is envisaged primarily as a replacement for multiple existing tests, as an early comprehensive genomic test supplemented by selected rapid assays, or as part of a combined diagnostic strategy.

    The additional variants detected by UF-WGS are an interesting finding and could perhaps be described in slightly greater detail. A concise summary according to variant type and clinical relevance would help readers understand where UF-WGS may provide the greatest added value compared with existing workflows.

    The manuscript appropriately acknowledges that this is a single-centre pilot study. This does not diminish its value as a feasibility study, but future multicentre evaluation will be important to determine how easily the workflow can be implemented across laboratories with different infrastructure, staffing, sample volumes, and clinical pathways.

    Similarly, future studies assessing health-economic aspects would be valuable. Rapid comprehensive sequencing could potentially reduce the need for sequential molecular tests, shorten diagnostic pathways, and prevent unnecessary procedures. Evaluation of these potential benefits alongside sequencing and computational costs would provide important information for healthcare systems considering wider implementation.

    Finally, longer-term clinical outcomes would represent a natural next step for this work. The present study provides convincing examples of how rapid genomic information can influence or potentially improve management. A future prospective study examining endpoints such as time to definitive diagnosis, time to treatment decision, number of additional diagnostic procedures, length of hospital stay, treatment modification, and patient outcomes would provide complementary evidence for the clinical value of the approach.

    Conclusions

    This is a strong translational study addressing a practical barrier to the implementation of whole genome sequencing in paediatric oncology. The authors demonstrate that UF-WGS can provide clinically interpretable genomic information within approximately three days while maintaining high concordance with established genomic testing and identifying additional clinically actionable findings.

    An important contribution of the manuscript is the demonstration that genomic turnaround time is not simply a laboratory performance metric but can have direct relevance to patient management. The prospective clinical examples illustrate situations in which having comprehensive genomic information early in the diagnostic pathway may influence meaningful clinical decisions.

    The study also demonstrates the feasibility of introducing a rapid WGS workflow into a tertiary paediatric haematology-oncology service, providing a useful foundation for larger prospective and multicentre evaluations.

    Overall, the findings are encouraging and support further investigation of UF-WGS as a tool for rapidly integrating comprehensive genomic information into paediatric cancer care. The manuscript should be of interest to clinicians, genomic scientists, molecular pathologists, and researchers working on precision oncology and implementation of genomic medicine.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they did not use generative AI to come up with new ideas for their review.

  2. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22979565.

    General assessment

    This is an interesting and clinically relevant study evaluating the feasibility and potential clinical utility of ultra-fast whole genome sequencing (UF-WGS) in paediatric haematology-oncology practice. The manuscript addresses an important limitation of current genomic testing: although whole genome sequencing can provide comprehensive molecular information, its clinical value may be reduced when results are not available within the timeframe in which important treatment decisions need to be made.

    The authors evaluate UF-WGS in a real-world tertiary paediatric haematology-oncology setting and compare the workflow with NHS Genomic Medicine Service whole genome sequencing. The study includes 54 patients with a broad range of solid and haematological malignancies, comprising both prospectively recruited and retrospective cases. The combination of analytical comparison, turnaround-time assessment, and evaluation of potential clinical impact makes the study particularly valuable from a translational perspective.

    Overall, the manuscript provides encouraging evidence that comprehensive genomic information can be generated within a timeframe that is much more compatible with routine clinical decision-making in paediatric oncology.

    Strengths of the study

    A major strength is the clear clinical focus of the work. Rather than examining sequencing performance only under laboratory conditions, the authors evaluate UF-WGS in patients undergoing investigation and treatment within an established paediatric oncology service. This increases the relevance of the findings to future clinical implementation.

    The reduction in turnaround time is particularly impressive. UF-WGS achieved a mean turnaround time of approximately three days compared with 37 days for GMS-WGS. In paediatric oncology, where diagnostic classification, risk stratification, surgery, chemotherapy, or targeted treatment may need to be determined rapidly, this difference has potentially important practical implications.

    The analytical concordance is also encouraging. UF-WGS recalled 143 of 151 clinically actionable somatic and germline variants identified through standard testing, corresponding to approximately 95% recall. In addition, UF-WGS identified 19 clinically actionable variants that were not identified by GMS-WGS. These results suggest that the faster workflow does not simply provide genomic information more rapidly but may also contribute additional clinically relevant information.

    Another strength is the inclusion of both prospective and retrospective cohorts. The prospective cohort provides evidence of how UF-WGS can function within contemporary clinical practice, while the retrospective cases allow the authors to examine a broader range of molecular abnormalities and clinically informative scenarios.

    The clinical-impact component is particularly interesting. In 18 of 35 prospective cases, UF-WGS was associated with improvements in clinical care, while clinicians considered that 9 of 19 retrospective patients could have benefited if UF-WGS had been available in real time. These findings help move the discussion beyond analytical performance and illustrate why turnaround time is clinically important.

    The examples presented throughout the manuscript are useful in demonstrating how rapid genomic information can contribute to diagnosis, risk stratification, therapeutic decision-making, and avoidance of unnecessary interventions. This patient-level perspective makes the manuscript accessible to both genomic scientists and clinicians.

    The additional flowcell proximity information is another interesting aspect of the study. The ability to obtain additional information concerning genomic structure and difficult genomic regions from the same sequencing workflow could potentially expand the clinical value of WGS without requiring multiple separate molecular assays.

    Comments and suggestions

    The manuscript is generally clear and well organised. I have several suggestions that may further improve its presentation.

    First, it may be helpful to provide an even clearer description of how "clinical impact" was defined. The individual examples are informative, but a concise predefined classification of clinical benefit—for example, change in diagnosis, change in treatment, altered risk classification, avoidance of an intervention, or provision of additional prognostic information—would make the clinical-impact analysis easier to interpret and potentially easier to reproduce in future studies.

    Similarly, presenting the prospective clinical benefits according to these categories in a table could be useful. This would allow readers to quickly understand which areas of paediatric oncology practice benefited most frequently from rapid genomic information.

    Second, the turnaround-time findings are one of the strongest aspects of the manuscript. Additional information about the distribution of turnaround times, such as median, range, or interquartile range, alongside the reported mean could provide readers with a more complete understanding of workflow reliability. Demonstrating that rapid turnaround is consistently achievable will be particularly important for future routine implementation.

    Third, the manuscript could potentially expand the discussion of how UF-WGS may integrate with existing diagnostic approaches. In current paediatric oncology practice, rapid targeted assays, cytogenetics, FISH, and other molecular tests may remain important in particular clinical situations. It would therefore be interesting to discuss whether UF-WGS is envisaged primarily as a replacement for multiple existing tests, as an early comprehensive genomic test supplemented by selected rapid assays, or as part of a combined diagnostic strategy.

    The additional variants detected by UF-WGS are an interesting finding and could perhaps be described in slightly greater detail. A concise summary according to variant type and clinical relevance would help readers understand where UF-WGS may provide the greatest added value compared with existing workflows.

    The manuscript appropriately acknowledges that this is a single-centre pilot study. This does not diminish its value as a feasibility study, but future multicentre evaluation will be important to determine how easily the workflow can be implemented across laboratories with different infrastructure, staffing, sample volumes, and clinical pathways.

    Similarly, future studies assessing health-economic aspects would be valuable. Rapid comprehensive sequencing could potentially reduce the need for sequential molecular tests, shorten diagnostic pathways, and prevent unnecessary procedures. Evaluation of these potential benefits alongside sequencing and computational costs would provide important information for healthcare systems considering wider implementation.

    Finally, longer-term clinical outcomes would represent a natural next step for this work. The present study provides convincing examples of how rapid genomic information can influence or potentially improve management. A future prospective study examining endpoints such as time to definitive diagnosis, time to treatment decision, number of additional diagnostic procedures, length of hospital stay, treatment modification, and patient outcomes would provide complementary evidence for the clinical value of the approach.

    Conclusions

    This is a strong translational study addressing a practical barrier to the implementation of whole genome sequencing in paediatric oncology. The authors demonstrate that UF-WGS can provide clinically interpretable genomic information within approximately three days while maintaining high concordance with established genomic testing and identifying additional clinically actionable findings.

    An important contribution of the manuscript is the demonstration that genomic turnaround time is not simply a laboratory performance metric but can have direct relevance to patient management. The prospective clinical examples illustrate situations in which having comprehensive genomic information early in the diagnostic pathway may influence meaningful clinical decisions.

    The study also demonstrates the feasibility of introducing a rapid WGS workflow into a tertiary paediatric haematology-oncology service, providing a useful foundation for larger prospective and multicentre evaluations.

    Overall, the findings are encouraging and support further investigation of UF-WGS as a tool for rapidly integrating comprehensive genomic information into paediatric cancer care. The manuscript should be of interest to clinicians, genomic scientists, molecular pathologists, and researchers working on precision oncology and implementation of genomic medicine.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they did not use generative AI to come up with new ideas for their review.

  3. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22979802.

    General assessment

    This is an interesting and clinically relevant study evaluating the feasibility and potential clinical utility of ultra-fast whole genome sequencing (UF-WGS) in paediatric haematology-oncology practice. The manuscript addresses an important limitation of current genomic testing: although whole genome sequencing can provide comprehensive molecular information, its clinical value may be reduced when results are not available within the timeframe in which important treatment decisions need to be made.

    The authors evaluate UF-WGS in a real-world tertiary paediatric haematology-oncology setting and compare the workflow with NHS Genomic Medicine Service whole genome sequencing. The study includes 54 patients with a broad range of solid and haematological malignancies, comprising both prospectively recruited and retrospective cases. The combination of analytical comparison, turnaround-time assessment, and evaluation of potential clinical impact makes the study particularly valuable from a translational perspective.

    Overall, the manuscript provides encouraging evidence that comprehensive genomic information can be generated within a timeframe that is much more compatible with routine clinical decision-making in paediatric oncology.

    Strengths of the study

    A major strength is the clear clinical focus of the work. Rather than examining sequencing performance only under laboratory conditions, the authors evaluate UF-WGS in patients undergoing investigation and treatment within an established paediatric oncology service. This increases the relevance of the findings to future clinical implementation.

    The reduction in turnaround time is particularly impressive. UF-WGS achieved a mean turnaround time of approximately three days compared with 37 days for GMS-WGS. In paediatric oncology, where diagnostic classification, risk stratification, surgery, chemotherapy, or targeted treatment may need to be determined rapidly, this difference has potentially important practical implications.

    The analytical concordance is also encouraging. UF-WGS recalled 143 of 151 clinically actionable somatic and germline variants identified through standard testing, corresponding to approximately 95% recall. In addition, UF-WGS identified 19 clinically actionable variants that were not identified by GMS-WGS. These results suggest that the faster workflow does not simply provide genomic information more rapidly but may also contribute additional clinically relevant information.

    Another strength is the inclusion of both prospective and retrospective cohorts. The prospective cohort provides evidence of how UF-WGS can function within contemporary clinical practice, while the retrospective cases allow the authors to examine a broader range of molecular abnormalities and clinically informative scenarios.

    The clinical-impact component is particularly interesting. In 18 of 35 prospective cases, UF-WGS was associated with improvements in clinical care, while clinicians considered that 9 of 19 retrospective patients could have benefited if UF-WGS had been available in real time. These findings help move the discussion beyond analytical performance and illustrate why turnaround time is clinically important.

    The examples presented throughout the manuscript are useful in demonstrating how rapid genomic information can contribute to diagnosis, risk stratification, therapeutic decision-making, and avoidance of unnecessary interventions. This patient-level perspective makes the manuscript accessible to both genomic scientists and clinicians.

    The additional flowcell proximity information is another interesting aspect of the study. The ability to obtain additional information concerning genomic structure and difficult genomic regions from the same sequencing workflow could potentially expand the clinical value of WGS without requiring multiple separate molecular assays.

    Comments and suggestions

    The manuscript is generally clear and well organised. I have several suggestions that may further improve its presentation.

    First, it may be helpful to provide an even clearer description of how "clinical impact" was defined. The individual examples are informative, but a concise predefined classification of clinical benefit—for example, change in diagnosis, change in treatment, altered risk classification, avoidance of an intervention, or provision of additional prognostic information—would make the clinical-impact analysis easier to interpret and potentially easier to reproduce in future studies.

    Similarly, presenting the prospective clinical benefits according to these categories in a table could be useful. This would allow readers to quickly understand which areas of paediatric oncology practice benefited most frequently from rapid genomic information.

    Second, the turnaround-time findings are one of the strongest aspects of the manuscript. Additional information about the distribution of turnaround times, such as median, range, or interquartile range, alongside the reported mean could provide readers with a more complete understanding of workflow reliability. Demonstrating that rapid turnaround is consistently achievable will be particularly important for future routine implementation.

    Third, the manuscript could potentially expand the discussion of how UF-WGS may integrate with existing diagnostic approaches. In current paediatric oncology practice, rapid targeted assays, cytogenetics, FISH, and other molecular tests may remain important in particular clinical situations. It would therefore be interesting to discuss whether UF-WGS is envisaged primarily as a replacement for multiple existing tests, as an early comprehensive genomic test supplemented by selected rapid assays, or as part of a combined diagnostic strategy.

    The additional variants detected by UF-WGS are an interesting finding and could perhaps be described in slightly greater detail. A concise summary according to variant type and clinical relevance would help readers understand where UF-WGS may provide the greatest added value compared with existing workflows.

    The manuscript appropriately acknowledges that this is a single-centre pilot study. This does not diminish its value as a feasibility study, but future multicentre evaluation will be important to determine how easily the workflow can be implemented across laboratories with different infrastructure, staffing, sample volumes, and clinical pathways.

    Similarly, future studies assessing health-economic aspects would be valuable. Rapid comprehensive sequencing could potentially reduce the need for sequential molecular tests, shorten diagnostic pathways, and prevent unnecessary procedures. Evaluation of these potential benefits alongside sequencing and computational costs would provide important information for healthcare systems considering wider implementation.

    Finally, longer-term clinical outcomes would represent a natural next step for this work. The present study provides convincing examples of how rapid genomic information can influence or potentially improve management. A future prospective study examining endpoints such as time to definitive diagnosis, time to treatment decision, number of additional diagnostic procedures, length of hospital stay, treatment modification, and patient outcomes would provide complementary evidence for the clinical value of the approach.

    Conclusions

    This is a strong translational study addressing a practical barrier to the implementation of whole genome sequencing in paediatric oncology. The authors demonstrate that UF-WGS can provide clinically interpretable genomic information within approximately three days while maintaining high concordance with established genomic testing and identifying additional clinically actionable findings.

    An important contribution of the manuscript is the demonstration that genomic turnaround time is not simply a laboratory performance metric but can have direct relevance to patient management. The prospective clinical examples illustrate situations in which having comprehensive genomic information early in the diagnostic pathway may influence meaningful clinical decisions.

    The study also demonstrates the feasibility of introducing a rapid WGS workflow into a tertiary paediatric haematology-oncology service, providing a useful foundation for larger prospective and multicentre evaluations.

    Overall, the findings are encouraging and support further investigation of UF-WGS as a tool for rapidly integrating comprehensive genomic information into paediatric cancer care. The manuscript should be of interest to clinicians, genomic scientists, molecular pathologists, and researchers working on precision oncology and implementation of genomic medicine.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they did not use generative AI to come up with new ideas for their review.

  4. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22979910.

    General assessment

    This is an interesting and clinically relevant study evaluating the feasibility and potential clinical utility of ultra-fast whole genome sequencing (UF-WGS) in paediatric haematology-oncology practice. The manuscript addresses an important limitation of current genomic testing: although whole genome sequencing can provide comprehensive molecular information, its clinical value may be reduced when results are not available within the timeframe in which important treatment decisions need to be made.

    The authors evaluate UF-WGS in a real-world tertiary paediatric haematology-oncology setting and compare the workflow with NHS Genomic Medicine Service whole genome sequencing. The study includes 54 patients with a broad range of solid and haematological malignancies, comprising both prospectively recruited and retrospective cases. The combination of analytical comparison, turnaround-time assessment, and evaluation of potential clinical impact makes the study particularly valuable from a translational perspective.

    Overall, the manuscript provides encouraging evidence that comprehensive genomic information can be generated within a timeframe that is much more compatible with routine clinical decision-making in paediatric oncology.

    Strengths of the study

    A major strength is the clear clinical focus of the work. Rather than examining sequencing performance only under laboratory conditions, the authors evaluate UF-WGS in patients undergoing investigation and treatment within an established paediatric oncology service. This increases the relevance of the findings to future clinical implementation.

    The reduction in turnaround time is particularly impressive. UF-WGS achieved a mean turnaround time of approximately three days compared with 37 days for GMS-WGS. In paediatric oncology, where diagnostic classification, risk stratification, surgery, chemotherapy, or targeted treatment may need to be determined rapidly, this difference has potentially important practical implications.

    The analytical concordance is also encouraging. UF-WGS recalled 143 of 151 clinically actionable somatic and germline variants identified through standard testing, corresponding to approximately 95% recall. In addition, UF-WGS identified 19 clinically actionable variants that were not identified by GMS-WGS. These results suggest that the faster workflow does not simply provide genomic information more rapidly but may also contribute additional clinically relevant information.

    Another strength is the inclusion of both prospective and retrospective cohorts. The prospective cohort provides evidence of how UF-WGS can function within contemporary clinical practice, while the retrospective cases allow the authors to examine a broader range of molecular abnormalities and clinically informative scenarios.

    The clinical-impact component is particularly interesting. In 18 of 35 prospective cases, UF-WGS was associated with improvements in clinical care, while clinicians considered that 9 of 19 retrospective patients could have benefited if UF-WGS had been available in real time. These findings help move the discussion beyond analytical performance and illustrate why turnaround time is clinically important.

    The examples presented throughout the manuscript are useful in demonstrating how rapid genomic information can contribute to diagnosis, risk stratification, therapeutic decision-making, and avoidance of unnecessary interventions. This patient-level perspective makes the manuscript accessible to both genomic scientists and clinicians.

    The additional flowcell proximity information is another interesting aspect of the study. The ability to obtain additional information concerning genomic structure and difficult genomic regions from the same sequencing workflow could potentially expand the clinical value of WGS without requiring multiple separate molecular assays.

    Comments and suggestions

    The manuscript is generally clear and well organised. I have several suggestions that may further improve its presentation.

    First, it may be helpful to provide an even clearer description of how "clinical impact" was defined. The individual examples are informative, but a concise predefined classification of clinical benefit—for example, change in diagnosis, change in treatment, altered risk classification, avoidance of an intervention, or provision of additional prognostic information—would make the clinical-impact analysis easier to interpret and potentially easier to reproduce in future studies.

    Similarly, presenting the prospective clinical benefits according to these categories in a table could be useful. This would allow readers to quickly understand which areas of paediatric oncology practice benefited most frequently from rapid genomic information.

    Second, the turnaround-time findings are one of the strongest aspects of the manuscript. Additional information about the distribution of turnaround times, such as median, range, or interquartile range, alongside the reported mean could provide readers with a more complete understanding of workflow reliability. Demonstrating that rapid turnaround is consistently achievable will be particularly important for future routine implementation.

    Third, the manuscript could potentially expand the discussion of how UF-WGS may integrate with existing diagnostic approaches. In current paediatric oncology practice, rapid targeted assays, cytogenetics, FISH, and other molecular tests may remain important in particular clinical situations. It would therefore be interesting to discuss whether UF-WGS is envisaged primarily as a replacement for multiple existing tests, as an early comprehensive genomic test supplemented by selected rapid assays, or as part of a combined diagnostic strategy.

    The additional variants detected by UF-WGS are an interesting finding and could perhaps be described in slightly greater detail. A concise summary according to variant type and clinical relevance would help readers understand where UF-WGS may provide the greatest added value compared with existing workflows.

    The manuscript appropriately acknowledges that this is a single-centre pilot study. This does not diminish its value as a feasibility study, but future multicentre evaluation will be important to determine how easily the workflow can be implemented across laboratories with different infrastructure, staffing, sample volumes, and clinical pathways.

    Similarly, future studies assessing health-economic aspects would be valuable. Rapid comprehensive sequencing could potentially reduce the need for sequential molecular tests, shorten diagnostic pathways, and prevent unnecessary procedures. Evaluation of these potential benefits alongside sequencing and computational costs would provide important information for healthcare systems considering wider implementation.

    Finally, longer-term clinical outcomes would represent a natural next step for this work. The present study provides convincing examples of how rapid genomic information can influence or potentially improve management. A future prospective study examining endpoints such as time to definitive diagnosis, time to treatment decision, number of additional diagnostic procedures, length of hospital stay, treatment modification, and patient outcomes would provide complementary evidence for the clinical value of the approach.

    Conclusions

    This is a strong translational study addressing a practical barrier to the implementation of whole genome sequencing in paediatric oncology. The authors demonstrate that UF-WGS can provide clinically interpretable genomic information within approximately three days while maintaining high concordance with established genomic testing and identifying additional clinically actionable findings.

    An important contribution of the manuscript is the demonstration that genomic turnaround time is not simply a laboratory performance metric but can have direct relevance to patient management. The prospective clinical examples illustrate situations in which having comprehensive genomic information early in the diagnostic pathway may influence meaningful clinical decisions.

    The study also demonstrates the feasibility of introducing a rapid WGS workflow into a tertiary paediatric haematology-oncology service, providing a useful foundation for larger prospective and multicentre evaluations.

    Overall, the findings are encouraging and support further investigation of UF-WGS as a tool for rapidly integrating comprehensive genomic information into paediatric cancer care. The manuscript should be of interest to clinicians, genomic scientists, molecular pathologists, and researchers working on precision oncology and implementation of genomic medicine.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they used generative AI to come up with new ideas for their review.

  5. This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/20046566.

    "Clinical Impact of Ultra-Fast Whole Genome Sequencing in Paediatric Haematology-Oncology Practice"

    Short summary of the research and contribution to the field

    This preprint evaluates an Ultra-Fast Whole Genome Sequencing (UF-WGS) workflow for children with suspected or confirmed cancer in a tertiary pediatric hematology-oncology practice. The authors compare UF-WGS with the standard NHS Genomic Medicine Service WGS (GMS-WGS) workflow and report a major reduction in turnaround time: approximately 3 days from sample collection for UF-WGS versus 37 days for GMS-WGS. UF-WGS recalled 95% of clinically actionable somatic and germline variants identified by standard testing and detected 19 additional clinically actionable variants not found by GMS-WGS.

    The work is important because pediatric oncology often requires rapid molecular diagnosis to guide risk stratification, treatment selection, trial enrollment, germline cancer predisposition assessment, and urgent clinical decision-making. The study moves the field forward by showing that ultra-fast WGS may not only be technically feasible, but also clinically meaningful in real-world pediatric hematology-oncology care. The reported impact on prospective cases is especially valuable because it begins to connect sequencing speed with patient-management decisions.

    Positive feedback / strengths

    1. Highly clinically relevant question. The study addresses a major limitation of routine cancer genomics: clinically useful genomic information often arrives too late to influence early management decisions.

    2. Direct comparison with a real clinical benchmark. Using concurrent NHS GMS-WGS as the validation comparator strengthens the study because the authors are not comparing UF-WGS to an artificial or purely research-based standard.

    3. Strong turnaround-time improvement. Reducing mean turnaround time from 37 days to 3 days is a major practical achievement and could substantially change clinical decision-making in pediatric oncology.

    4. Focus on actionable somatic and germline findings. The study appropriately emphasizes clinically actionable variants rather than purely technical variant detection.

    5. Prospective clinical-impact assessment. Reporting that UF-WGS improved care in 18/35 prospective cases adds important real-world relevance beyond analytical validation.

    6. Useful attention to discrepant findings. The authors note that differences between workflows may relate to tumor heterogeneity and low variant allele frequency, which are realistic challenges in oncology sequencing.

    Major issues

    1. Clarify how "clinically actionable" was defined

    The study's main conclusions depend on the definition of clinically actionable somatic and germline variants. This term can vary widely depending on whether actionability includes diagnosis, prognosis, risk stratification, therapy selection, trial eligibility, germline predisposition, or change in surveillance.

    Suggested improvement: The authors should provide a clear actionability framework, ideally including:

    • variant tiering criteria

    • somatic versus germline actionability categories

    • whether actionability was based on pediatric oncology guidelines, local molecular tumor board review, NHS criteria, or expert consensus

    • examples of management changes triggered by UF-WGS

    • whether variants of uncertain significance were excluded from the actionable category

    This would make the clinical-impact claims easier to interpret.

    2. Provide more detail on the UF-WGS analytical workflow

    The abstract reports excellent turnaround time and high recall, but the manuscript should clearly describe the technical workflow that enabled this speed.

    Suggested improvement: The authors should include details on:

    • sample input requirements

    • tumor-normal strategy

    • DNA extraction workflow

    • library preparation method

    • sequencing platform and run configuration

    • target coverage

    • bioinformatics pipeline

    • variant classes assessed: SNVs, indels, CNVs, structural variants, gene fusions, mutational signatures, and germline variants

    • minimum quality thresholds

    • reporting workflow and clinical review steps

    A workflow figure showing sample collection → sequencing → analysis → clinical report would be very helpful.

    3. The 19 additional actionable variants require deeper explanation and validation

    UF-WGS identified 19 clinically actionable variants not detected by GMS-WGS. This is potentially important but needs careful interpretation.

    Suggested improvement: For each additional actionable variant, the authors should summarize:

    • variant type

    • specimen type

    • tumor purity or disease burden

    • VAF or copy-number level

    • whether orthogonal confirmation was performed

    • whether the finding changed diagnosis, risk assignment, treatment, or germline counseling

    • why GMS-WGS did not detect or report it

    Without this detail, readers may not know whether these were true additional clinically useful findings, pipeline/reporting differences, tumor heterogeneity effects, or low-level findings near detection thresholds.

    4. Discrepant findings need a structured discordance analysis

    The abstract states that discordances were attributable to tumor heterogeneity in some cases and low VAF in others. This is plausible, but the explanation should be evidence-based and case-specific.

    Suggested improvement: The authors should provide a discordance table including:

    • variants detected by both methods

    • variants detected only by UF-WGS

    • variants detected only by GMS-WGS

    • sample source used for each workflow

    • sequencing depth and tumor purity

    • VAF / copy-number estimate

    • orthogonal confirmation status

    • final clinical interpretation

    This would strengthen confidence in the comparative performance claims.

    5. Clinical impact assessment should be described in more detail

    The study reports that UF-WGS improved care in 18/35 prospective cases and that clinicians judged 9/19 retrospective cases would have benefited. These are strong claims, but the methodology needs detail.

    Suggested improvement: The authors should clarify:

    • who adjudicated clinical impact

    • whether reviewers were independent or blinded

    • what counted as "demonstrable improvement in care"

    • whether changes included therapy change, diagnosis clarification, risk stratification, trial enrollment, transplant decision-making, germline counseling, or avoidance of additional testing

    • how disagreements between clinicians were resolved

    • whether patient outcomes were available

    A structured clinical-impact rubric would make the findings more reproducible.

    6. Cohort composition and generalizability need clearer presentation

    The study includes 54 pediatric patients with suspected or confirmed cancer, but pediatric hematology-oncology is highly heterogeneous.

    Suggested improvement: The authors should provide cohort breakdown by:

    • diagnosis group

    • suspected versus confirmed malignancy

    • diagnosis versus relapse

    • hematologic versus solid tumor

    • sample type

    • tumor cellularity / blast percentage

    • prospective versus retrospective cases

    • prior testing performed

    • urgency of clinical decision-making

    This would help readers understand where UF-WGS is most useful and where performance may be less certain.

    7. Germline findings raise consent, counseling, and reporting considerations

    The study includes clinically actionable germline variants. In pediatric oncology, rapid germline reporting can have major implications for the child and family.

    Suggested improvement: The authors should describe:

    • consent process for germline analysis

    • whether germline findings were confirmed in a validated germline workflow

    • genetic counseling process

    • whether parental samples were used

    • reporting policy for secondary or incidental findings

    • turnaround time for germline confirmation

    This is important for real-world implementation.

    8. Turnaround-time analysis should be broken down by workflow step

    The reported 3-day mean TAT is a major finding. To help other laboratories evaluate feasibility, the authors should break down where time was saved.

    Suggested improvement: Report TAT by:

    • sample receipt to extraction

    • extraction to library preparation

    • library preparation to sequencing

    • sequencing runtime

    • bioinformatics analysis

    • variant interpretation

    • clinical sign-out

    This would make the workflow more actionable for other clinical genomic laboratories.

    9. Cost, staffing, and implementation requirements should be discussed

    Ultra-fast WGS may require specialized infrastructure, staffing, computational resources, and rapid clinical interpretation.

    Suggested improvement: The authors should discuss:

    • sequencing cost per case

    • staffing model

    • need for after-hours or weekend workflows

    • computational requirements

    • molecular tumor board or rapid review process

    • whether the workflow is scalable outside a specialized tertiary center

    • comparison with targeted panels, RNA-seq, karyotyping, FISH, and rapid PCR-based testing

    This would help readers assess implementation beyond the study center.

    Minor issues

    1. Define UF-WGS and GMS-WGS clearly at first use. A concise definition of both workflows would help readers outside the UK system.

    2. Clarify "recall" terminology. The term "recalled 95%" should be clearly defined as sensitivity, positive percent agreement, variant-level recall, or case-level recall.

    3. Provide confidence intervals. Recall rate, clinical-impact percentages, and TAT comparisons should include confidence intervals where possible.

    4. Clarify whether the 3-day TAT is mean, median, or operational target. Median and range would be useful because ultra-fast workflows may have outliers.

    5. Clarify whether all variant classes were equally assessed. SNVs, indels, CNVs, structural variants, fusions, mutational signatures, and germline variants may have different detection performance.

    6. Include representative clinical cases. A small number of case vignettes would help show how UF-WGS changed real clinical decisions.

    7. Discuss limitations of retrospective clinician judgment. Retrospective assessment of possible clinical benefit can be valuable but may be vulnerable to hindsight bias.

    8. Explain "flowcell proximity data." This phrase is interesting but unclear from the abstract. The manuscript should define it and explain how it may affect clinical care.

    9. Clarify whether UF-WGS replaced or supplemented standard testing. Readers should understand whether UF-WGS is proposed as a first-line test, triage tool, or add-on workflow.

    10. Discuss data-sharing and reproducibility. The authors should clarify whether pipeline details, workflow parameters, and anonymized benchmark data are available.

    Overall assessment

    This is a clinically important and potentially high-impact study showing that ultra-fast WGS can substantially reduce turnaround time and may improve care in pediatric hematology-oncology practice. The work is strong because it evaluates a real-world clinical workflow, uses concurrent standard GMS-WGS as a benchmark, and focuses on clinically actionable findings rather than purely technical sequencing performance.

    The major improvements needed are clearer definitions of actionability and clinical impact, deeper analysis of discrepant variants, more transparent technical workflow details, and practical implementation information such as staffing, cost, scalability, and TAT breakdown. The study would also benefit from clearer discussion of germline reporting and consent, especially given the pediatric setting.

    With these additions, the manuscript would provide a stronger and more actionable model for implementing rapid WGS in pediatric cancer care and could help guide broader adoption of ultra-fast genomic diagnostics in time-sensitive oncology settings.

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they used generative AI to come up with new ideas for their review.