The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Gene expression–based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study
Open accessAbstract
Although prognostic gene expression signatures for survival in early-stage lung cancer have been proposed, for clinical application, it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training–testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.
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
Erlotinib in Previously Treated Non–Small-Cell Lung Cancer
Shepherd, F. A., Rodrigues Pereira, J., Ciuleanu, T., Tan, E. H., Hirsh, V., Thongprasert, S., Campos, D., Maoleekoonpiroj, S., Smylie, M., Martins, R., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa050753 · Cited by 5,419
Self-citationModel-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.
Li, C., & Wong, W. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.31 · Cited by 3,133
Gene-expression profiles predict survival of patients with lung adenocarcinoma
Beer, D. G., Kardia, S. L. R., Huang, C.-C., Giordano, T. J., Levin, A. M., Misek, D. E., Lin, L., Chen, G., Gharib, T. G., Thomas, D. G., et al. (2002) · Nature Medicine · doi:10.1038/nm733 · Cited by 2,025
Self-citation
Cited by
Inferring tumour purity and stromal and immune cell admixture from expression data
Yoshihara, K., Shahmoradgoli, M., Martínez, E., Vegesna, R., Kim, H., Torres-Garcia, W., Treviño, V., Shen, H., Laird, P. W., Levine, D. A., et al. (2013) · Nature Communications · doi:10.1038/ncomms3612 · Cited by 9,778
Self-citationHerbst, R. S., Heymach, J. V., & Lippman, S. M. (2008) · New England Journal of Medicine · doi:10.1056/nejmra0802714 · Cited by 2,389
Radiomics: the process and the challenges
Kumar, V., Gu, Y., Basu, S., Berglund, A., Eschrich, S. A., Schabath, M. B., Forster, K., Aerts, H. J. W. L., Dekker, A., Fenstermacher, D., et al. (2012) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2012.06.010 · Cited by 2,258
Self-citationGyőrffy, B., Surowiak, P., Budczies, J., & Lánczky, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082241 · Cited by 1,760
Phenotype molding of stromal cells in the lung tumor microenvironment
Lambrechts, D., Wauters, E., Boeckx, B., Aibar, S., Nittner, D., Burton, O., Bassez, A., Decaluwé, H., Pircher, A., Van den Eynde, K., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0096-5 · Cited by 1,648
A Genome-wide RNAi Screen Identifies Multiple Synthetic Lethal Interactions with the Ras Oncogene
Luo, J., Emanuele, M. J., Li, D., Creighton, C. J., Schlabach, M. R., Westbrook, T. F., Wong, K.-K., & Elledge, S. J. (2009) · Cell · doi:10.1016/j.cell.2009.05.006 · Cited by 1,017
Volatile Organic Compounds of Lung Cancer and Possible Biochemical Pathways
Hakim, M., Broza, Y. Y., Barash, O., Peled, N., Phillips, M., Amann, A., & Haick, H. (2012) · Chemical Reviews · doi:10.1021/cr300174a · Cited by 953
MAQC Consortium (2010) · Nature Biotechnology · doi:10.1038/nbt.1665 · Cited by 889
Dangaj, D., Bruand, M., Grimm, A. J., Ronet, C., Barras, D., Duttagupta, P. A., Lanitis, E., Duraiswamy, J., Tanyi, J. L., Benencia, F., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.05.004 · Cited by 875
Patra, K. C., Wang, Q., Bhaskar, P. T., Miller, L., Wang, Z., Wheaton, W., Chandel, N., Laakso, M., Muller, W. J., Allen, E. L., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.06.014 · Cited by 853
Hu, Z., Chen, X., Zhao, Y., Tian, T., Jin, G., Shu, Y., Chen, Y., Xu, L., Zen, K., Zhang, C., et al. (2010) · Journal of Clinical Oncology · doi:10.1200/jco.2009.24.9342 · Cited by 798
NRF2 regulates serine biosynthesis in non–small cell lung cancer
DeNicola, G. M., Chen, P.-H., Mullarky, E., Sudderth, J. A., Hu, Z., Wu, D., Tang, H., Xie, Y., Asara, J. M., Huffman, K. E., et al. (2015) · Nature Genetics · doi:10.1038/ng.3421 · Cited by 746
Yao, J., Zhu, X., Jonnagaddala, J., Hawkins, N., & Huang, J. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101789 · Cited by 522
Li, B., Cui, Y., Diehn, M., & Li, R. (2017) · JAMA Oncology · doi:10.1001/jamaoncol.2017.1609 · Cited by 514
Suppression of lung adenocarcinoma progression by Nkx2-1
Winslow, M. M., Dayton, T. L., Verhaak, R. G. W., Kim-Kiselak, C., Snyder, E. L., Feldser, D. M., Hubbard, D. D., DuPage, M. J., Whittaker, C. A., Hoersch, S., et al. (2011) · Nature · doi:10.1038/nature09881 · Cited by 467
Self-citationChansky, K., Sculier, J.-P., Crowley, J. J., Giroux, D., Van Meerbeeck, J., & Goldstraw, P. (2009) · Journal of Thoracic Oncology · doi:10.1097/jto.0b013e3181a7716e · Cited by 456
Jeong, S. M., Xiao, C., Finley, L. W. S., Lahusen, T., Souza, A. L., Pierce, K., Li, Y.-H., Wang, X., Laurent, G., German, N. J., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2013.02.024 · Cited by 445
Predictive Gene Signature in MAGE-A3 Antigen-Specific Cancer Immunotherapy
Ulloa-Montoya, F., Louahed, J., Dizier, B., Gruselle, O., Spiessens, B., Lehmann, F. F., Suciu, S., Kruit, W. H. J., Eggermont, A. M. M., Vansteenkiste, J., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.44.3762 · Cited by 436
Osteoblasts remotely supply lung tumors with cancer-promoting SiglecF high neutrophils
Engblom, C., Pfirschke, C., Zilionis, R., Da Silva Martins, J., Bos, S. A., Courties, G., Rickelt, S., Severe, N., Baryawno, N., Faget, J., et al. (2017) · Science · doi:10.1126/science.aal5081 · Cited by 389
Botling, J., Edlund, K., Lohr, M., Hellwig, B., Holmberg, L., Lambe, M., Berglund, A., Ekman, S., Bergqvist, M., Pontén, F., et al. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-1139 · Cited by 359
Eschrich, S. A., Pramana, J., Zhang, H., Zhao, H., Boulware, D., Lee, J.-H., Bloom, G., Rocha-Lima, C., Kelley, S., Calvin, D. P., et al. (2009) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2009.06.014 · Cited by 360
When is hub gene selection better than standard meta-analysis?
Langfelder, P., Mischel, P. S., & Horvath, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061505 · Cited by 313
WSISA: Making Survival Prediction from Whole Slide Histopathological Images
Zhu, X., Yao, J., Zhu, F., & Huang, J. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.725 · Cited by 292
A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters
Demircioğlu, D., Cukuroglu, E., Kindermans, M., Nandi, T., Calabrese, C., Fonseca, N. A., Kahles, A., Lehmann, K.-V., Stegle, O., Brazma, A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.08.018 · Cited by 250
Kim, H. S., Mendiratta, S., Kim, J., Pecot, C. V., Larsen, J. E., Zubovych, I., Seo, B. Y., Kim, J., Eskiocak, B., Chung, H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.041 · Cited by 172
Xie, Y., Xiao, G., Coombes, K. R., Behrens, C., Solis, L. M., Raso, G., Girard, L., Erickson, H. S., Roth, J., Heymach, J. V., et al. (2011) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-0196 · Cited by 162
An Expression Signature as an Aid to the Histologic Classification of Non–Small Cell Lung Cancer
Girard, L., Rodriguez-Canales, J., Behrens, C., Thompson, D. M., Botros, I. W., Tang, H., Xie, Y., Rekhtman, N., Travis, W. D., Wistuba, I. I., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-2900 · Cited by 154
TGF-β-induced IRAK-M expression in tumor-associated macrophages regulates lung tumor growth
Standiford, T. J., Kuick, R., Bhan, U., Chen, J., Newstead, M., & Keshamouni, V. G. (2011) · Oncogene · doi:10.1038/onc.2010.619 · Cited by 151
Self-citationHIF2α cooperates with RAS to promote lung tumorigenesis in mice
Kim, W. Y., Perera, S., Zhou, B., Carretero, J., Yeh, J. J., Heathcote, S. A., Jackson, A. L., Nikolinakos, P., Ospina, B., Naumov, G., et al. (2009) · Journal of Clinical Investigation · doi:10.1172/jci38443 · Cited by 141
KRAS Protein Stability Is Regulated through SMURF2: UBCH5 Complex-Mediated β-TrCP1 Degradation
Shukla, S., Allam, U. S., Ahsan, A., Chen, G., Krishnamurthy, P. M., Marsh, K., Rumschlag, M., Shankar, S., Whitehead, C., Schipper, M., et al. (2014) · Neoplasia · doi:10.1593/neo.14184 · Cited by 96
Self-citationKaufman, J. M., Amann, J. M., Park, K., Arasada, R. R., Li, H., Shyr, Y., & Carbone, D. P. (2014) · Journal of Thoracic Oncology · doi:10.1097/jto.0000000000000173 · Cited by 87
A predictive model for personalized therapeutic interventions in non-small cell lung cancer
Kureshi, N., Abidi, S. S. R., & Blouin, C. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2377517 · Cited by 83
miR-1298 Inhibits Mutant KRAS-Driven Tumor Growth by Repressing FAK and LAMB3
Zhou, Y., Dang, J., Chang, K.-Y., Yau, E., Aza-Blanc, P., Moscat, J., & Rana, T. M. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-2936 · Cited by 54
YEATS4 Is a Novel Oncogene Amplified in Non–Small Cell Lung Cancer That Regulates the p53 Pathway
Pikor, L. A., Lockwood, W. W., Thu, K. L., Vucic, E. A., Chari, R., Gazdar, A. F., Lam, S., & Lam, W. L. (2013) · Cancer Research · doi:10.1158/0008-5472.can-13-1897 · Cited by 44
Interplay between steroid signalling and microRNAs: implications for hormone-dependent cancers
Fletcher, C. E., Dart, D. A., & Bevan, C. L. (2014) · Endocrine Related Cancer · doi:10.1530/erc-14-0208 · Cited by 37
Metadata
- Authors
- Director's Challenge Consortium for the Molecular Classification of Lung Adenocarcinoma
- Venue
- Nature Medicine
- Published
- 2008-07-20
- Volume
- 14
- Issue
- 8
- Pages
- 822-827
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2132165198
- Cited by
- 1,190
- References
- 3
- FWCI
- 27.67
- 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
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.