The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Gene Expression Patterns in Human Liver Cancers
Open accessAbstract
Hepatocellular carcinoma (HCC) is a leading cause of death worldwide. Using cDNA microarrays to characterize patterns of gene expression in HCC, we found consistent differences between the expression patterns in HCC compared with those seen in nontumor liver tissues. The expression patterns in HCC were also readily distinguished from those associated with tumors metastatic to liver. The global gene expression patterns intrinsic to each tumor were sufficiently distinctive that multiple tumor nodules from the same patient could usually be recognized and distinguished from all the others in the large sample set on the basis of their gene expression patterns alone. The distinctive gene expression patterns are characteristic of the tumors and not the patient; the expression programs seen in clonally independent tumor nodules in the same patient were no more similar than those in tumors from different patients. Moreover, clonally related tumor masses that showed distinct expression profiles were also distinguished by genotypic differences. Some features of the gene expression patterns were associated with specific phenotypic and genotypic characteristics of the tumors, including growth rate, vascular invasion, and p53 overexpression.
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
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Self-citationTranscriptional regulation and function during the human cell cycle
Cho, R. J., Huang, M., Campbell, M. J., Dong, H., Steinmetz, L., Sapinoso, L., Hampton, G., Elledge, S. J., Davis, R. W., & Lockhart, D. J. (2001) · Nature Genetics · doi:10.1038/83751 · Cited by 455
Cited by
Radiomics: the bridge between medical imaging and personalized medicine
Lambin, P., Leijenaar, R. T. H., Deist, T. M., Peerlings, J., de Jong, E. E. C., van Timmeren, J., Sanduleanu, S., Larue, R. T. H. M., Even, A. J. G., Jochems, A., et al. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.141 · Cited by 5,688
Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets
Boyault, S., Rickman, D. S., de Reyniès, A., Balabaud, C., Rebouissou, S., Jeannot, E., Hérault, A., Saric, J., Belghiti, J., Franco, D., et al. (2007) · Hepatology · doi:10.1002/hep.21467 · Cited by 1,258
Hoshida, Y., Nijman, S. M. B., Kobayashi, M., Chan, J. A., Brunet, J.-P., Chiang, D. Y., Villanueva, A., Newell, P., Ikeda, K., Hashimoto, M., et al. (2009) · Cancer Research · doi:10.1158/0008-5472.can-09-1089 · Cited by 1,238
Transcription factors as targets for cancer therapy
Darnell, J. E. (2002) · Nature Reviews Cancer · doi:10.1038/nrc906 · Cited by 1,194
Deep learning-based multi-omics integration robustly predicts survival in liver cancer
Chaudhary, K., Poirion, O. B., Lu, L., & Garmire, L. X. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-0853 · Cited by 1,091
Metadata
- Authors
- Chen, X., Cheung, S. T., So, S., Fan, S. T., Barry, C., Higgins, J., Lai, K.-M., Ji, J., Dudoit, S., Ng, I. O. L., van de Rijn, M., Botstein, D., & Brown, P. O.
- Venue
- Molecular Biology of the Cell
- Published
- 2002-06
- Volume
- 13
- Issue
- 6
- Pages
- 1929-1939
- ISSN
- 1059-1524 (ISSN-L)
- 1939-4586
- OpenAlex
- W2105912300
- Cited by
- 878
- References
- 2
- FWCI
- 12.74
- Type
- journal article
- Language
- en
- Open access
- green
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: Gene Expression Patterns in Human Liver Cancers. https://app.cochat.ai/papers/10.1091/mbc.02-02-0023
- The paper
- Chen, X., Cheung, S. T., So, S., Fan, S. T., Barry, C., Higgins, J., Lai, K.-M., Ji, J., Dudoit, S., Ng, I. O. L., van de Rijn, M., Botstein, D., & Brown, P. O. (2002). Gene Expression Patterns in Human Liver Cancers. Molecular Biology of the Cell. https://doi.org/10.1091/mbc.02-02-0023
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.