The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors
Open accessAbstract
Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: “type I LCNECs” with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and “type II LCNECs” enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh, and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.
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
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
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
Self-citationComprehensive molecular profiling of lung adenocarcinoma
The Cancer Genome Atlas Research Network (2014) · Nature · doi:10.1038/nature13385 · Cited by 5,732
Comprehensive genomic characterization of squamous cell lung cancers
The Cancer Genome Atlas Research Network (2012) · Nature · doi:10.1038/nature11404 · Cited by 3,994
Molecular and genetic properties of tumors associated with local immune cytolytic activity
Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G., & Hacohen, N. (2015) · Cell · doi:10.1016/j.cell.2014.12.033 · Cited by 3,825
Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing
Imielinski, M., Berger, A. H., Hammerman, P. S., Hernandez, B., Pugh, T. J., Hodis, E., Cho, J., Suh, J., Capelletti, M., Sivachenko, A., et al. (2012) · Cell · doi:10.1016/j.cell.2012.08.029 · Cited by 1,789
Self-citationBullard, J. H., Purdom, E., Hansen, K. D., & Dudoit, S. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-94 · Cited by 1,680
MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery
Wang, K., Singh, D., Zeng, Z., Coleman, S. J., Huang, Y., Savich, G. L., He, X., Mieczkowski, P., Grimm, S. A., Perou, C. M., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq622 · Cited by 1,193
Clonal status of actionable driver events and the timing of mutational processes in cancer evolution
McGranahan, N., Favero, F., de Bruin, E. C., Birkbak, N. J., Szallasi, Z., & Swanton, C. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa1408 · Cited by 685
Cited by
Rindi, G., Klimstra, D. S., Abedi-Ardekani, B., Asa, S. L., Bosman, F. T., Brambilla, E., Busam, K. J., de Krijger, R. R., Dietel, M., El-Naggar, A. K., et al. (2018) · Modern Pathology · doi:10.1038/s41379-018-0110-y · Cited by 1,163
Self-citation
Metadata
- Authors
- George, J., Walter, V., Peifer, M., Alexandrov, L. B., Seidel, D., Leenders, F., Maas, L., Müller, C., Dahmen, I., Delhomme, T. M., Ardin, M., Leblay, N., Byrnes, G., Sun, R., De Reynies, A., McLeer-Florin, A., Bosco, G., Malchers, F., Menon, R., Altmüller, J., Becker, C., Nürnberg, P., Achter, V., Lang, U., Schneider, P. M., Bogus, M., Soloway, M. G., Wilkerson, M. D., Cun, Y., McKay, J. D., Moro-Sibilot, D., Brambilla, C. G., Lantuejoul, S., Lemaitre, N., Soltermann, A., Weder, W., Tischler, V., Brustugun, O. T., Lund-Iversen, M., Helland, Å., Solberg, S., Ansén, S., Wright, G., Solomon, B., Roz, L., Pastorino, U., Petersen, I., Clement, J. H., Sänger, J., Wolf, J., Vingron, M., Zander, T., Perner, S., Travis, W. D., Haas, S. A., Olivier, M., Foll, M., Büttner, R., Hayes, D. N., Brambilla, E., Fernandez-Cuesta, L., & Thomas, R. K.
- Venue
- Nature Communications
- Published
- 2018-03-13
- Volume
- 9
- Issue
- 1
- Pages
- 1048-1048
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2792828274
- Cited by
- 377
- References
- 13
- FWCI
- 12.55
- Type
- journal article
- Language
- en
- Open access
- gold
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: Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors. https://app.cochat.ai/papers/10.1038/s41467-018-03099-x
- The paper
- George, J., Walter, V., Peifer, M., Alexandrov, L. B., Seidel, D., Leenders, F., Maas, L., Müller, C., Dahmen, I., Delhomme, T. M., Ardin, M., Leblay, N., Byrnes, G., Sun, R., De Reynies, A., McLeer-Florin, A., Bosco, G., Malchers, F., Menon, R., . . . Thomas, R. K. (2018). Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors. Nature Communications. https://doi.org/10.1038/s41467-018-03099-x
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.