The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis
Open accessAbstract
The molecular mechanisms of pulmonary fibrosis are poorly understood. We have used oligonucleotide arrays to analyze the gene expression programs that underlie pulmonary fibrosis in response to bleomycin, a drug that causes lung inflammation and fibrosis, in two strains of susceptible mice (129 and C57BL/6). We then compared the gene expression patterns in these mice with 129 mice carrying a null mutation in the epithelial-restricted integrin β6 subunit (β6−/−), which develop inflammation but are protected from pulmonary fibrosis. Cluster analysis identified two distinct groups of genes involved in the inflammatory and fibrotic responses. Analysis of gene expression at multiple time points after bleomycin administration revealed sequential induction of subsets of genes that characterize each response. The availability of this comprehensive data set should accelerate the development of more effective strategies for intervention at the various stages in the development of fibrotic diseases of the lungs and other organs.
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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
CELLULAR RESPONSES TO INTERFERON-γ
Boehm, U., Klamp, T., Groot, M., & Howard, J. C. (1997) · Annual Review of Immunology · doi:10.1146/annurev.immunol.15.1.749 · Cited by 2,890
Munger, J. S., Huang, X., Kawakatsu, H., Griffiths, M. J. D., Dalton, S. L., Wu, J., Pittet, J.-F., Kaminski, N., Garat, C., Matthay, M. A., et al. (1999) · Cell · doi:10.1016/s0092-8674(00)80545-0 · Cited by 2,076
Self-citationDer, S. D., Zhou, A., Williams, B. R. G., & Silverman, R. H. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.26.15623 · Cited by 1,816
JAKS AND STATS: Biological Implications
Leonard, W. J., & O'Shea, J. J. (1998) · Annual Review of Immunology · doi:10.1146/annurev.immunol.16.1.293 · Cited by 1,804
Genome-wide expression monitoring in Saccharomyces cerevisiae
Wodicka, L., Dong, H., Mittmann, M., Ho, M.-H., & Lockhart, D. J. (1997) · Nature Biotechnology · doi:10.1038/nbt1297-1359 · Cited by 973
The epidemiology of interstitial lung diseases.
Coultas, D. B., Zumwalt, R. E., Black, W. C., & Sobonya, R. E. (1994) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/ajrccm.150.4.7921471 · Cited by 946
Regulation ofp53downstream genes
El-Deiry, W. S. (1998) · Seminars in Cancer Biology · doi:10.1006/scbi.1998.0097 · Cited by 800
Altered wound healing in mice lacking a functional osteopontin gene (spp1).
Liaw, L., Birk, D. E., Ballas, C. B., Whitsitt, J. S., Davidson, J. M., & Hogan, B. L. (1998) · Journal of Clinical Investigation · doi:10.1172/jci2131 · Cited by 663
Eitzman, D. T., McCoy, R. D., Zheng, X., Fay, W. P., Shen, T., Ginsburg, D., & Simon, R. H. (1996) · Journal of Clinical Investigation · doi:10.1172/jci118396 · Cited by 558
Cited by
Cellular and molecular mechanisms of fibrosis
Wynn, T. (2008) · The Journal of Pathology · doi:10.1002/path.2277 · Cited by 4,495
Fibrotic disease and the TH1/TH2 paradigm
Wynn, T. A. (2004) · Nature Reviews Immunology · doi:10.1038/nri1412 · Cited by 1,765
TGF-β Activation and Function in Immunity
Travis, M. A., & Sheppard, D. (2014) · Annual Review of Immunology · doi:10.1146/annurev-immunol-032713-120257 · Cited by 856
Self-citationTGF-β1 Signaling and Tissue Fibrosis
Kim, K. K., Sheppard, D., & Chapman, H. A. (2018) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a022293 · Cited by 800
Self-citationMatrix Metalloproteinase-9 in Lung Remodeling
Atkinson, J. J., & Senior, R. M. (2003) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2002-0166tr · Cited by 587
Metadata
- Authors
- Kaminski, N., Allard, J. D., Pittet, J. F., Zuo, F., Griffiths, M. J. D., Morris, D., Huang, X., Sheppard, D., & Heller, R. A.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2000-02-15
- Volume
- 97
- Issue
- 4
- Pages
- 1778-1783
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2038482344
- Cited by
- 417
- References
- 29
- FWCI
- 36.06
- Type
- journal article
- Language
- en
- Open access
- green
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- Kaminski, N., Allard, J. D., Pittet, J. F., Zuo, F., Griffiths, M. J. D., Morris, D., Huang, X., Sheppard, D., & Heller, R. A. (2000). Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.97.4.1778
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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