The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations
Open accessAbstract
BACKGROUND & AIMS: Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous and respond poorly to treatment. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed large-scale genome sequencing analyses on BTCs to investigate their somatic and germline driver events and characterize their genomic landscape. METHODS: We analyzed 412 BTC samples from Japanese and Italian populations, 107 by whole-exome sequencing (WES), 39 by whole-genome sequencing (WGS), and a further 266 samples by targeted sequencing. The subtypes were 136 intrahepatic cholangiocarcinomas (ICCs), 101 distal cholangiocarcinomas (DCCs), 109 peri-hilar type cholangiocarcinomas (PHCs), and 66 gallbladder or cystic duct cancers (GBCs/CDCs). We identified somatic alterations and searched for driver genes in BTCs, finding pathogenic germline variants of cancer-predisposing genes. We predicted cell-of-origin for BTCs by combining somatic mutation patterns and epigenetic features. RESULTS: We identified 32 significantly and commonly mutated genes including TP53, KRAS, SMAD4, NF1, ARID1A, PBRM1, and ATR, some of which negatively affected patient prognosis. A novel deletion of MUC17 at 7q22.1 affected patient prognosis. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes such as BRCA1, BRCA2, RAD51D, MLH1, or MSH2 were detected in 11% (16/146) of BTC patients. CONCLUSIONS: BTCs have distinct genetic features including somatic events and germline predisposition. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information. LAY SUMMARY: We here analyzed genomic features of 412 BTC samples from Japanese and Italian populations. A total of 32 significantly and commonly mutated genes were identified, some of which negatively affected patient prognosis, including a novel deletion of MUC17 at 7q22.1. Cell-of-origin predictions using WGS and epigenetic features suggest hepatocyte-origin of hepatitis-related ICCs. Deleterious germline mutations of cancer-predisposing genes were detected in 11% of patients with BTC. BTCs have distinct genetic features including somatic events and germline predisposition.
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
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
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
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Self-citationSensitive detection of somatic point mutations in impure and heterogeneous cancer samples
Cibulskis, K., Lawrence, M. S., Carter, S. L., Sivachenko, A., Jaffe, D., Sougnez, C., Gabriel, S., Meyerson, M., Lander, E. S., & Getz, G. (2013) · Nature Biotechnology · doi:10.1038/nbt.2514 · Cited by 4,981
Self-citationMermel, C. H., Schumacher, S. E., Hill, B., Meyerson, M. L., Beroukhim, R., & Getz, G. (2011) · Genome Biology · doi:10.1186/gb-2011-12-4-r41 · Cited by 3,550
Self-citationDiscovery and saturation analysis of cancer genes across 21 tumour types
Lawrence, M. S., Stojanov, P., Mermel, C. H., Robinson, J. T., Garraway, L. A., Golub, T. R., Meyerson, M., Gabriel, S. B., Lander, E. S., & Getz, G. (2014) · Nature · doi:10.1038/nature12912 · Cited by 3,096
Self-citationA promoter-level mammalian expression atlas
The FANTOM Consortium and the RIKEN PMI and CLST (DGT) (2014) · Nature · doi:10.1038/nature13182 · Cited by 1,982
Strelka: accurate somatic small-variant calling from sequenced tumor–normal sample pairs
Saunders, C. T., Wong, W. S. W., Swamy, S., Becq, J., Murray, L. J., & Cheetham, R. K. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts271 · Cited by 1,635
Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor
McLaren, W., Pritchard, B., Rios, D., Chen, Y., Flicek, P., & Cunningham, F. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq330 · Cited by 1,586
A flexible R package for nonnegative matrix factorization
Gaujoux, R., & Seoighe, C. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-367 · Cited by 1,547
Cited by
Xue, R., Chen, L., Zhang, C., Fujita, M., Li, R., Yan, S.-M., Ong, C. K., Liao, X., Gao, Q., Sasagawa, S., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.04.007 · Cited by 296
Self-citationProbing the Tumor Suppressor Function of BAP1 in CRISPR-Engineered Human Liver Organoids
Artegiani, B., van Voorthuijsen, L., Lindeboom, R. G. H., Seinstra, D., Heo, I., Tapia, P., López-Iglesias, C., Postrach, D., Dayton, T., Oka, R., et al. (2019) · Cell Stem Cell · doi:10.1016/j.stem.2019.04.017 · Cited by 218
Xiang, X., Liu, Z., Zhang, C., Li, Z., Gao, J., Zhang, C., Cao, Q., Cheng, J., Liu, H., Chen, D., et al. (2021) · Advanced Science · doi:10.1002/advs.202101230 · Cited by 71
Human Hepatocytes Can Give Rise to Intrahepatic Cholangiocarcinomas
Hsu, B. Y., Driscoll, J., Ishida, Y., Pino, C., Kim, E., Zhang, K., Tateno, C., Mattis, A. N., Kelley, R. K., & Willenbring, H. (2024) · Gastroenterology · doi:10.1053/j.gastro.2024.05.033 · Cited by 10
Metadata
- Authors
- Wardell, C. P., Fujita, M., Yamada, T., Simbolo, M., Fassan, M., Karlic, R., Polak, P., Kim, J., Hatanaka, Y., Maejima, K., Lawlor, R. T., Nakanishi, Y., Mitsuhashi, T., Fujimoto, A., Furuta, M., Ruzzenente, A., Conci, S., Oosawa, A., Sasaki-Oku, A., Nakano, K., Tanaka, H., Yamamoto, Y., Michiaki, K., Kawakami, Y., Aikata, H., Ueno, M., Hayami, S., Gotoh, K., Ariizumi, S.-I., Yamamoto, M., Yamaue, H., Chayama, K., Miyano, S., Getz, G., Scarpa, A., Hirano, S., Nakamura, T., & Nakagawa, H.
- Venue
- Journal of Hepatology
- Publisher
- Elsevier BV
- Published
- 2018-05
- Volume
- 68
- Issue
- 5
- Pages
- 959-969
- ISSN
- 0168-8278 (ISSN-L)
- OpenAlex
- W2786714651
- Cited by
- 373
- References
- 38
- FWCI
- 32.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations. https://app.cochat.ai/papers/10.1016/j.jhep.2018.01.009
- The paper
- Wardell, C. P., Fujita, M., Yamada, T., Simbolo, M., Fassan, M., Karlic, R., Polak, P., Kim, J., Hatanaka, Y., Maejima, K., Lawlor, R. T., Nakanishi, Y., Mitsuhashi, T., Fujimoto, A., Furuta, M., Ruzzenente, A., Conci, S., Oosawa, A., Sasaki-Oku, A., . . . Nakagawa, H. (2018). Genomic characterization of biliary tract cancers identifies driver genes and predisposing mutations. Journal of Hepatology. https://doi.org/10.1016/j.jhep.2018.01.009
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.