The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)
Eisenhauer, E. A., Therasse, P., Bogaerts, J., Schwartz, L. H., Sargent, D., Ford, R., Dancey, J., Arbuck, S., Gwyther, S., Mooney, M., et al. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2008.10.026 · Cited by 29,534
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Signatures of mutational processes in human cancer
Initiative, A. P. C. G., Alexandrov, L. B., ICGC Breast Cancer Consortium, ICGC MMML-Seq Consortium, PedBrain, I., Nik-Zainal, S., Wedge, D. C., Aparicio, S. A. J. R., Behjati, S., Biankin, A. V., et al. (2013) · Nature · doi:10.1038/nature12477 · Cited by 9,660
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citationVan der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., del Angel, G., Levy‐Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., et al. (2013) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1110s43 · Cited by 6,687
CADD: predicting the deleteriousness of variants throughout the human genome
Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J., & Kircher, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1016 · Cited by 3,534
Pan-cancer analysis of whole genomes
The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, Aaltonen, L. A., Abascal, F., Abeshouse, A., Aburatani, H., Adams, D. J., Agrawal, N., Ahn, K. S., Ahn, S.-M., Aikata, H., et al. (2020) · Nature · doi:10.1038/s41586-020-1969-6 · Cited by 3,064
Self-citationEfficacy of Larotrectinib in TRK Fusion–Positive Cancers in Adults and Children
Drilon, A., Laetsch, T. W., Kummar, S., DuBois, S. G., Lassen, U. N., Demetri, G. D., Nathenson, M., Doebele, R. C., Farago, A. F., Pappo, A. S., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1714448 · Cited by 2,824
Cited by
Manickam, K., McClain, M. R., Demmer, L. A., Biswas, S., Kearney, H. M., Malinowski, J., Massingham, L. J., Miller, D., Yu, T. W., & Hisama, F. M. (2021) · Genetics in Medicine · doi:10.1038/s41436-021-01242-6 · Cited by 639
Palmer, E. E., Howell, K., & Scheffer, I. E. (2021) · Neurotherapeutics · doi:10.1007/s13311-021-01133-3 · Cited by 53
Metadata
- Authors
- Wong, M., Mayoh, C., Lau, L. M. S., Khuong-Quang, D.-A., Pinese, M., Kumar, A., Barahona, P., Wilkie, E. E., Sullivan, P., Bowen-James, R., Syed, M., Martincorena, I., Abascal, F., Sherstyuk, A., Bolanos, N. A., Baber, J., Priestley, P., Dolman, M. E. M., Fleuren, E. D. G., Gauthier, M.-E., Mould, E. V. A., Gayevskiy, V., Gifford, A. J., Grebert-Wade, D., Strong, P. A., Manouvrier, E., Warby, M., Thomas, D. M., Kirk, J., Tucker, K., O’Brien, T., Alvaro, F., McCowage, G. B., Dalla-Pozza, L., Gottardo, N. G., Tapp, H., Wood, P., Khaw, S.-L., Hansford, J. R., Moore, A. S., Norris, M. D., Trahair, T. N., Lock, R. B., Tyrrell, V., Haber, M., Marshall, G. M., Ziegler, D. S., Ekert, P. G., & Cowley, M. J.
- Venue
- Nature Medicine
- Published
- 2020-10-05
- Volume
- 26
- Issue
- 11
- Pages
- 1742-1753
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3090838011
- Cited by
- 393
- References
- 20
- FWCI
- 14.31
- Type
- journal article
- Language
- en
- Open access
- diamond
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer. https://app.cochat.ai/papers/10.1038/s41591-020-1072-4
- The paper
- Wong, M., Mayoh, C., Lau, L. M. S., Khuong-Quang, D.-A., Pinese, M., Kumar, A., Barahona, P., Wilkie, E. E., Sullivan, P., Bowen-James, R., Syed, M., Martincorena, I., Abascal, F., Sherstyuk, A., Bolanos, N. A., Baber, J., Priestley, P., Dolman, M. E. M., Fleuren, E. D. G., . . . Cowley, M. J. (2020). Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer. Nature Medicine. https://doi.org/10.1038/s41591-020-1072-4
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
