The DOI matches its Crossref record; 49 of the 51 references it cites were found in a registry or an index.
Robust gene expression signature from formalin-fixed paraffin-embedded samples predicts prognosis of non-small-cell lung cancer patients.
Open accessPublished version of a preprint
Abstract
PURPOSE: The requirement of frozen tissues for microarray experiments limits the clinical usage of genome-wide expression profiling by using microarray technology. The goal of this study is to test the feasibility of developing lung cancer prognosis gene signatures by using genome-wide expression profiling of formalin-fixed paraffin-embedded (FFPE) samples, which are widely available and provide a valuable rich source for studying the association of molecular changes in cancer and associated clinical outcomes. EXPERIMENTAL DESIGN: We randomly selected 100 Non-Small-Cell lung cancer (NSCLC) FFPE samples with annotated clinical information from the UT-Lung SPORE Tissue Bank. We microdissected tumor area from FFPE specimens and used Affymetrix U133 plus 2.0 arrays to attain gene expression data. After strict quality control and analysis procedures, a supervised principal component analysis was used to develop a robust prognosis signature for NSCLC. Three independent published microarray datasets were used to validate the prognosis model. RESULTS: This study showed that the robust gene signature derived from genome-wide expression profiling of FFPE samples is strongly associated with lung cancer clinical outcomes and can be used to refine the prognosis for stage I lung cancer patients, and the prognostic signature is independent of clinical variables. This signature was validated in several independent studies and was refined to a 59-gene lung cancer prognosis signature. CONCLUSIONS: We conclude that genome-wide profiling of FFPE lung cancer samples can identify a set of genes whose expression level provides prognostic information across different platforms and studies, which will allow its application in clinical settings.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“In two datasets of 55 and 196 non-small-cell lung cancer patients [11, 12], there was no significant differences in OS between patients with high vs. low SLFN11 expression (HR = 1.60 and 1.16, p = 0.348 and 0.368, respectively) (Fig 3B and 3C).”
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
1 retracted
Hsu, D. S., Balakumaran, B. S., Acharya, C. R., Vlahovic, V., Walters, K. S., Garman, K. S., Anders, C. K., Riedel, R. F., Lancaster, J. M., Harpole, D. H., et al. (2007) · Journal of Clinical Oncology · doi:10.1200/jco.2007.11.0593 · Cited by 106
RetractedNonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1992) · Springer series in statistics · doi:10.1007/978-1-4612-4380-9_25 · Cited by 45,239
Nonparametric Estimation from Incomplete Observations
Kaplan, E. L., & Meier, P. (1958) · Journal of the American Statistical Association · doi:10.1080/01621459.1958.10501452 · Cited by 39,158
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,030
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
Classification and regression trees
Praagman, J. (1985) · European Journal of Operational Research · doi:10.1016/0377-2217(85)90321-2 · Cited by 10,053
Jemal, A., Siegel, R., Ward, E., Hao, Y., Xu, J., & Thun, M. J. (2009) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20006 · Cited by 9,709
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,328
Cited by
Sorted by citations
Győrffy, B., Surowiak, P., Budczies, J., & Lánczky, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082241 · Cited by 1,768
Wu, J.-Y., Huang, T., Hsieh, Y.-T., Wang, Y., Yen, C.-C., Lee, G.-L., Yeh, C., Peng, Y., Kuo, Y.-Y., Wen, H.-T., et al. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.10.023 · Cited by 549
Li, B., Cui, Y., Diehn, M., & Li, R. (2017) · JAMA Oncology · doi:10.1001/jamaoncol.2017.1609 · Cited by 514
Tang, H., Xiao, G., Behrens, C., Schiller, J. H., Allen, J., Chow, C.-W. B., Suraokar, M. B., Corvalán, A. H., Mao, J., White, M. A., et al. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-2321 · Cited by 284
Self-citationPredicting Anticancer Drug Responses Using a Dual-Layer Integrated Cell Line-Drug Network Model
Zhang, N., Wang, H., Fang, Y., Wang, J., Zheng, X., & Liu, X. S. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004498 · Cited by 208
Metadata
- Authors
- Xie, Y., Xiao, G., Coombes, K. R., Behrens, C., Solis, L. M., Raso, G., Girard, L., Erickson, H. S., Roth, J., Heymach, J. V., Moran, C., Danenberg, K., Minna, J. D., & Wistuba, I. I.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Authors' Affiliations: Departments of 1Clinical Sciences, 2Simmons Cancer Center, 3Internal Medicine, 4Pharmacology, and 5Hamon Center for Therapeutic Oncology Research, The University of Texas Southwestern Medical Center, Dallas; Departments of 6Bioinformatics and Computational Biology, 7Thoracic/Head and Neck Medical Oncology, 8Pathology and 9Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas; and 10Response Genetics, Inc., Los Angeles, California
- Corresponding author
- Wistuba, Ignacio I.
- ORCID
- Venue
- Clinical Cancer Research
- Published
- 2011-09-01
- Volume
- 17
- Issue
- 17
- Pages
- 5705-5714
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC3166982
- OpenAlex
- W2167736999
- Cited by
- 162
- References
- 51
- Citations by year
- 2026: 1 · 2025: 9 · 2024: 4 · 2023: 10 · 2022: 24 · 2021: 13 · 2020: 11 · 2019: 12 · 2018: 5 · 2017: 13 · 2016: 9 · 2015: 11 · 2014: 14 · 2013: 14 · 2012: 10
- FWCI
- 5.20
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Drug Abuse (R33DA027592, R21DA027592)
- National Cancer Institute (CA-16672, (P50-CA70907, R01CA152301, P50CA070907, P30CA016672)
- National Center for Research Resources (UL1RR024982)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Health Sciences › Medicine › Oncology › Lung Cancer Research Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- non-small cell lung cancer, prognostic gene signature, formalin-fixed paraffin-embedded tissue, gene expression profiling, tumor microdissection, stage I lung cancer, prognostic model validation
- MeSH terms
- Carcinoma, Non-Small-Cell Lung, Female, Formaldehyde, Humans, Lung Neoplasms, Male, Prognosis, Paraffin Embedding, Tissue Fixation, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
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
