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Robust gene expression signature from formalin-fixed paraffin-embedded samples predicts prognosis of non-small-cell lung cancer patients.
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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.
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“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).”
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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
An epigenetically distinct breast cancer cell subpopulation promotes collective invasion
Westcott, J. M., Prechtl, A. M., Maine, E. A., Dang, T. T., Esparza, M. A., Sun, H., Zhou, Y., Xie, Y., & Pearson, G. W. (2015) · Journal of Clinical Investigation · doi:10.1172/jci77767 · Cited by 176
Self-citationPadinharayil, H., Varghese, J., John, M. C., Rajanikant, G. K., Wilson, C. M., Al-Yozbaki, M., Renu, K., Dewanjee, S., Sanyal, R., Dey, A., et al. (2022) · Genes & Diseases · doi:10.1016/j.gendis.2022.07.023 · Cited by 172
Individual-level analysis of differential expression of genes and pathways for personalized medicine
Wang, H., Sun, Q., Zhao, W., Qi, L., Gu, Y., Li, P., Zhang, M., Li, Y., Liu, S., & Guo, Z. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu522 · Cited by 131
MUC1-C integrates PD-L1 induction with repression of immune effectors in non-small-cell lung cancer
Bouillez, A., Rajabi, H. N., Jin, C., Samur, M., Tagde, A., Alam, M., Hiraki, M., Maeda, T., Hu, X., Adeegbe, D. O., et al. (2017) · Oncogene · doi:10.1038/onc.2017.47 · Cited by 124
Profiling cancer testis antigens in non–small-cell lung cancer
Djureinovic, D., Hallström, B. M., Horie, M., Mattsson, J. S. M., Fleur, L. L., Fagerberg, L., Brunnström, H., Lindskog, C., Madjar, K., Rahnenführer, J., et al. (2016) · JCI Insight · doi:10.1172/jci.insight.86837 · Cited by 117
Qi, L., Chen, L., Li, Y., Qin, Y., Pan, R., Zhao, W., Gu, Y., Wang, H., Wang, R., Chen, X., et al. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv064 · Cited by 118
Yang, H., Sun, B., Fan, L., Ma, W., Xu, K., Hall, S. R. R., Wang, Z., Schmid, R. A., Peng, R., Marti, T. M., et al. (2022) · Theranostics · doi:10.7150/thno.69590 · Cited by 107
Chen, D., Hsu, Y., Fulp, W. J., Coppola, D., Haura, E. B., Yeatman, T. J., & Cress, W. D. (2011) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djr420 · Cited by 103
Shi, R., Bao, X., Unger, K., Sun, J., Lu, S., Manapov, F., Wang, X., Belka, C., & Li, M. (2021) · Theranostics · doi:10.7150/thno.56202 · Cited by 98
An Integrative Analysis of the Tumorigenic Role of TAZ in Human Non–Small Cell Lung Cancer
Noguchi, S. F., Saito, A., Horie, M., Mikami, Y., Suzuki, H. I., Morishita, Y., Ohshima, M., Abiko, Y., Mattsson, J. S. M., König, H., et al. (2014) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-3328 · Cited by 89
A Robust 8-Gene Prognostic Signature for Early-Stage Non-small Cell Lung Cancer
He, R., & Zuo, S. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.00693 · Cited by 88
Preković, S., Schuurman, K. G., Mayayo‐Peralta, I., Manjón, A. G., Buijs, M., Yavuz, S., Wellenstein, M. D., Barrera, A., Monkhorst, K., Huber, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24537-3 · Cited by 87
Wang, X., Yao, S., Xiao, Z., Gong, J., Zuo, L., Han, B., & Zhang, Z. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02321-z · Cited by 59
Leusink, F. K. J., van Es, R. J. J., de Bree, R., de Jong, R. J. B., van Hooff, S. R., Holstege, F. C. P., Slootweg, P. J., Brakenhoff, R. H., & Takes, R. P. (2012) · The Lancet Oncology · doi:10.1016/s1470-2045(12)70395-9 · Cited by 60
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Orang, A., & Barzegari, A. (2014) · Asian Pacific Journal of Cancer Prevention · doi:10.7314/apjcp.2014.15.17.6989 · Cited by 59
Jabs, V., Edlund, K., König, H., Grinberg, M., Madjar, K., Rahnenführer, J., Ekman, S., Bergkvist, M., Holmberg, L., Ickstadt, K., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187246 · Cited by 58
ITPRIPL1 binds CD3ε to impede T cell activation and enable tumor immune evasion
Deng, S., Zhang, Y., Wang, H., Liang, W., Xie, L., Li, N., Fang, Y., Wang, Y., Liu, J., Chi, H., et al. (2024) · Cell · doi:10.1016/j.cell.2024.03.019 · Cited by 59
Zhuang, Z., Chen, L., Mao, Y., Qun, Z., Li, H., Huang, Y.-Y., Hu, Z., & Jin, Y. (2020) · International Journal of Biological Sciences · doi:10.7150/ijbs.39046 · Cited by 57
Glutamine synthetase licenses APC/C-mediated mitotic progression to drive cell growth
Zhao, J., Shi, S., Qu, H.-Y., Keckesova, Z., Cao, Z.-J., Yang, L., Yu, X., Feng, L., Shi, Z., Krakowiak, J., et al. (2022) · Nature Metabolism · doi:10.1038/s42255-021-00524-2 · Cited by 58
Ren, J., Du, Y., Li, S., Ma, S., Jiang, Y., & Wu, C. (2019) · Genetic Epidemiology · doi:10.1002/gepi.22194 · Cited by 52
Molecular biomarkers in early stage lung cancer
Rodríguez, M. F., Ajona, D., Seijo, L. M., Sanz‐Ortega, J., Valencia, K., Corral, J., Mesa, M., Pı́o, R., Calvo, A., Lozano, M. D., et al. (2021) · Translational Lung Cancer Research · doi:10.21037/tlcr-20-750 · Cited by 48
Distinct Roles of VEGFA and ANGPT2 in Lung Adenocarcinoma and Squamous Cell Carcinoma
Qin, S., Yi, M., Jiao, D., Li, A., & Wu, K. (2019) · Journal of Cancer · doi:10.7150/jca.34693 · Cited by 51
CXCL1 as an Unfavorable Prognosis Factor Negatively Regulated by DACH1 in Non-small Cell Lung Cancer
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Yu, Y., & He, J. (2013) · Frontiers of Medicine · doi:10.1007/s11684-013-0272-4 · Cited by 46
The clinical significance of CXCL5 in non-small cell lung cancer
Wu, K., Yu, S., Liu, Q., Bai, X., Zheng, X., & Wu, K. (2017) · OncoTargets and Therapy · doi:10.2147/ott.s148772 · Cited by 47
Gene–Environment Interaction: A Variable Selection Perspective
Zhou, F., Ren, J., Xi, L., Ma, S., & Wu, C. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-0947-7_13 · Cited by 48
Deng, L., Győrffy, B., Na, F., Chen, B., Lan, J., Xue, J., Zhou, L., & Lü, Y. (2015) · Journal of Thoracic Oncology · doi:10.1097/jto.0000000000000550 · Cited by 45
Survival Impact Index and Ultrahigh-Dimensional Model-Free Screening with Survival Outcomes
Li, J., Zheng, Q., Peng, L., & Huang, Z. (2016) · Biometrics · doi:10.1111/biom.12499 · Cited by 44
Qi, L., Li, Y., Qin, Y., Shi, G., Li, T., Wang, J., Chen, L., Gu, Y., Zhao, W., & Guo, Z. (2016) · British Journal of Cancer · doi:10.1038/bjc.2016.370 · Cited by 44
Shee, K., Wells, J. D., Jiang, A., & Miller, T. W. (2019) · PLOS ONE · doi:10.1371/journal.pone.0224267 · Cited by 43
“The following datasets were obtained and analyzed: GSE37751 [10], GSE29013 [11], GSE37745 [12], GSE17260 [13], GSE32646 [14], and GSE63885 [15].”
BackgroundZhou, B., Bie, F., Zang, R., Zhang, M., Song, P., Liu, L., Peng, Y., Bai, G., Zhao, J., & Gao, S. (2022) · EBioMedicine · doi:10.1016/j.ebiom.2022.104268 · Cited by 43
Ezra, D. G., Krell, J., Rose, G. E., Bailly, M., Stebbing, J., & Castellano, L. (2012) · Journal of Clinical Pathology · doi:10.1136/jclinpath-2012-200719 · Cited by 40
High-dimensional genomic data bias correction and data integration using MANCIE
Zang, C., Wang, T., Deng, K., Li, B., Hu, S. S., Qin, Q., Xiao, T., Zhang, S., Meyer, C. A., He, H. H., et al. (2016) · Nature Communications · doi:10.1038/ncomms11305 · Cited by 39
Self-citationPark, S., Lim, J., Chun, J. N., Lee, S., Kim, T. I., Kim, D., Kim, S., Bae, D., Bae, S. M., So, I., et al. (2019) · International Journal of Oncology · doi:10.3892/ijo.2019.4953 · Cited by 40
Prognostic value of microRNA expression in operable non-small cell lung cancer patients
Skrzypski, M. T., Czapiewski, P., Goryca, K., Jassem, E., Wyrwicz, L. S., Pawłowski, R., Rzyman, W., Biernat, W., & Jassem, J. (2014) · British Journal of Cancer · doi:10.1038/bjc.2013.786 · Cited by 38
Balachandran, V. P., Arora, A., Gönen, M., Ito, H., Turcotte, S., Shia, J., Viale, A. J., Snoeren, N., van Hooff, S. R., Rinkes, I. H. M. B., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-15-1071 · Cited by 38
Wu, C., Jiang, Y., Ren, J., Cui, Y., & Ma, S. (2017) · Statistics in Medicine · doi:10.1002/sim.7518 · Cited by 38
Martínez‐Terroba, E., Behrens, C., de Miguel, F. J., Agorreta, J., Monsó, E., Millares, L., Sainz, C., Mesa, M., Perez‐Gracia, J. L., Lozano, M. D., et al. (2018) · The Journal of Pathology · doi:10.1002/path.5096 · Cited by 38
Self-citationCigarette smoke-induced LKB1/AMPK pathway deficiency reduces EGFR TKI sensitivity in NSCLC
Cheng, F., Chen, C., Tsai, W., Wang, B., Yu, M.-C., Hsia, T., Wei, Y.-L., Hsiao, Y.-C., Hu, D.-W., Ho, C.-Y., et al. (2020) · Oncogene · doi:10.1038/s41388-020-01597-1 · Cited by 41
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Qi, L., Li, T., Shi, G., Wang, J., Li, X., Zhang, S., Chen, L., Qin, Y., Gu, Y., Zhao, W., et al. (2017) · Molecular Oncology · doi:10.1002/1878-0261.12137 · Cited by 36
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Huang, Y., Zhang, Q., Zhang, S., Huang, J., & Ma, S. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2016.1139497 · Cited by 34
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Wu, C., Shi, X., Cui, Y., & Ma, S. (2015) · Statistics in Medicine · doi:10.1002/sim.6609 · Cited by 35
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Shahid, M., Choi, T. G., Nguyen, M. N., Matondo, A., Jo, Y. H., Yoo, J. Y., Nguyen, N. N. Y., Yun, H. R., Kim, J., Akter, S., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.13357 · Cited by 33
Zhang, Z., Liu, T., Wang, K., Qu, X. H., Pang, Z., Liu, S., Liu, Q., & Du, J. (2017) · Gene · doi:10.1016/j.gene.2017.08.001 · Cited by 32
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Gordián, E. R., Welsh, E. A., Gimbrone, N. T., Siegel, E. M., Shibata, D., Creelan, B., Cress, W. D., Eschrich, S. A., Haura, E. B., & Muñoz-Antonia, T. (2019) · Oncotarget · doi:10.18632/oncotarget.26574 · Cited by 31
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Choi, H., & Na, K. J. (2018) · BioMed Research International · doi:10.1155/2018/2914280 · Cited by 30
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Zhang, J., Fu, B., Li, M., & Mi, S. (2020) · Small · doi:10.1002/smll.202004750 · Cited by 30
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Yan, Z., Wang, Q., Lu, Z., Sun, X., Song, P., Dang, Y., Xie, L., Zhang, L., Li, Y., Zhu, W., et al. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00420 · Cited by 27
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Shi, X., Liu, J., Huang, J., Zhou, Y., Xie, Y., & Ma, S. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21795 · Cited by 28
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Solis, L. M., & Wistuba, I. I. (2012) · Springer eBooks · doi:10.1007/978-1-4419-0787-5_14 · Cited by 27
Self-citationSfakianos, G. P., Iversen, E. S., Whitaker, R. S., Akushevich, L., Schildkraut, J. M., Murphy, S. K., Marks, J. R., & Berchuck, A. (2012) · Gynecologic Oncology · doi:10.1016/j.ygyno.2012.12.030 · Cited by 27
Mattsson, J. S. M., Bergman, B., Grinberg, M., Edlund, K., Marincevic, M., Jirström, K., Pontén, F., Hengstler, J. G., Rahnenführer, J., Karlsson, M. G., et al. (2014) · Cancer Letters · doi:10.1016/j.canlet.2014.10.032 · Cited by 26
Wu, J., Zhou, L., Huang, L., Gu, J., Li, S., Liu, B., Feng, J., & Zhou, Y. (2017) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-016-0477-x · Cited by 25
Compound haploinsufficiency of Dok2 and Dusp4 promotes lung tumorigenesis
Chen, M., Zhang, J., Berger, A. H., Diolombi, M. S., Ng, C., Fung, J., Bronson, R. T., Castillo-Martín, M., Thin, T. H., Cordon‐Cardo, C., et al. (2018) · Journal of Clinical Investigation · doi:10.1172/jci99699 · Cited by 25
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Liu, J., Huang, J., & Ma, S. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21697 · Cited by 23
Gámez‐Pozo, A., Carrión, R. M. P., Manso, L., Crespo, C., Mendiola, C., López‐Vacas, R., Berges‐Soria, J., Álvarez, I., Vila, M. M., Calero, J. L. B., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0109611 · Cited by 24
TMEM229A suppresses non‑small cell lung cancer progression via inactivating the ERK pathway
Zhang, X., He, Y., Jiang, Y., Bao, Y., Chen, Q., Xie, D., Yu, H., & Wang, X. (2021) · Oncology Reports · doi:10.3892/or.2021.8127 · Cited by 21
Xia, X., Jiang, B., Li, J., & Zhang, W. (2015) · Lifetime Data Analysis · doi:10.1007/s10985-015-9350-z · Cited by 21
Mount, D. W., Putnam, C. W., Centouri, S. M., Manziello, A., Pandey, R., Garland, L. L., & Martinez, J. D. (2014) · BMC Medical Genomics · doi:10.1186/1755-8794-7-33 · Cited by 21
Chen, J., Liao, Y., & Fan, X. (2021) · Expert Review of Anticancer Therapy · doi:10.1080/14737140.2021.1908132 · Cited by 21
Adaptive Prediction Model in Prospective Molecular Signature–Based Clinical Studies
Xiao, G., Ma, S., Minna, J. D., & Xie, Y. (2013) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-13-2127 · Cited by 21
Self-citationIntegrative Analysis of High‐throughput Cancer Studies With Contrasted Penalization
Shi, X., Liu, J., Huang, J., Zhou, Y., Shia, B., & Ma, S. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21781 · Cited by 20
Identification of cuproptosis-related subtypes in lung adenocarcinoma and its potential significance
Pan, S., Song, C., Meng, H., Li, N., Li, D., Hao, B., Lu, Z., & Geng, Q. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.934722 · Cited by 20
Ben‐Hamo, R., Boué, S., Martin, F. P., Talikka, M., & Efroni, S. (2013) · Systems Biomedicine · doi:10.4161/sysb.25983 · Cited by 20
Integrative analysis of multiple cancer genomic datasets under the heterogeneity model
Liu, J., Huang, J., & Ma, S. (2013) · Statistics in Medicine · doi:10.1002/sim.5780 · Cited by 19
Grinberg, M., Djureinovic, D., Brunnström, H., Mattsson, J. S., Edlund, K., Hengstler, J. G., Fleur, L. L., Ekman, S., Koyi, H., Brandén, E., et al. (2017) · Modern Pathology · doi:10.1038/modpathol.2017.14 · Cited by 19
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Yu, M., Ji, W., Xu, Y., Tian, K., Ma, X., Yu, S., Chen, L., & Zhao, X. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1279735 · Cited by 18
Zhang, J., Wang, X., Song, C., & Li, Q. (2023) · BMC Cancer · doi:10.1186/s12885-023-10622-x · Cited by 17
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Merrick, B. A., Auerbach, S. S., Stockton, P. S., Foley, J. F., Malarkey, D. E., Sills, R. C., Irwin, R. D., & Tice, R. R. (2012) · Chemical Research in Toxicology · doi:10.1021/tx3000945 · Cited by 17
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Yue, M., Li, J., & Ma, S. (2017) · Statistics in Medicine · doi:10.1002/sim.7544 · Cited by 17
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Wang, S., Huang, E. W., Cairns, J., Peng, J., Wang, L., & Sinha, S. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006864 · Cited by 17
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Zhang, Q., Zhang, S., Liu, J., Huang, J., & Ma, S. (2015) · Statistica Sinica · doi:10.5705/ss.2014.194 · Cited by 17
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Cova, T. F. G. G., Pereira, J., & Pais, A. A. C. C. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.09.005 · Cited by 17
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Zhu, R., Zhao, H., & Ma, S. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21807 · Cited by 17
Iglesias-Ussel, M. D., Marchionni, L., & Romerio, F. (2013) · Journal of Immunological Methods · doi:10.1016/j.jim.2013.02.003 · Cited by 16
Stratification of resectable lung adenocarcinoma by molecular and pathological risk estimators
Rakha, E. A., Pajares, M. J., Ilié, M., Pío, R., Echeveste, J. I., Hughes, E., Soomro, I. N., Long-Mira, É., Idoate, M. A., Wagner, S., et al. (2015) · European Journal of Cancer · doi:10.1016/j.ejca.2015.07.015 · Cited by 15
Histopathological imaging features- versus molecular measurements-based cancer prognosis modeling
Zhang, S., Fan, Y., Zhong, T., & Ma, S. (2020) · Scientific Reports · doi:10.1038/s41598-020-72201-5 · Cited by 15
Leung, A. W. Y., Veinotte, C. J., Melong, N., Oh, M. H., Chen, K., Enfield, K. S. S., Backstrom, I., Warburton, C., Yapp, D. T. T., Berman, J. N., et al. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-0700 · Cited by 15
Early2 factor (E2F) deregulation is a prognostic and predictive biomarker in lung adenocarcinoma
Chen, L., Kurtyka, C. A., Welsh, E. A., Rivera, J. I., Engel, B. E., Muñoz-Antonia, T., Yoder, S., Eschrich, S. A., Creelan, B., Chiappori, A., et al. (2016) · Oncotarget · doi:10.18632/oncotarget.12672 · Cited by 14
Jia, G., Wang, X., Li, Q., Lü, W., Tang, X., Wistuba, I. I., & Xie, Y. (2019) · The Annals of Applied Statistics · doi:10.1214/19-aoas1249 · Cited by 13
Self-citationSparse group penalized integrative analysis of multiple cancer prognosis datasets
Liu, J., Huang, J., Xie, Y., & Ma, S. (2013) · Genetics Research · doi:10.1017/s0016672313000086 · Cited by 14
Self-citationYin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis
Xu, W. W., Banerji, S. O., Davie, J., Kassie, F., Yee, D., & Kratzke, R. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068742 · Cited by 14
Luo, L., Li, A., Fu, S., Du, W. T., He, L.-N., Zhang, X., Wang, Y., Zhou, Y., Yunpeng, Y., Li, Z., et al. (2022) · Immunologic Research · doi:10.1007/s12026-022-09335-3 · Cited by 13
Yuan, J., Yuan, B., Zeng, L., Liu, B., Chen, Y., Meng, X., Sun, R., Lv, X., Wang, W., & Yang, S. (2020) · Oncology Letters · doi:10.3892/ol.2020.11735 · Cited by 12
Lung Cancer Gene Signatures and Clinical Perspectives
Kuner, R. (2013) · Microarrays · doi:10.3390/microarrays2040318 · Cited by 13
Yue, M., & Li, J. (2017) · The International Journal of Biostatistics · doi:10.1515/ijb-2017-0024 · Cited by 13
Martínez‐Terroba, E., Behrens, C., Agorreta, J., Monsó, E., Millares, L., Felip, E., Rosell, R., Ramírez, J. L., Remírez, A., Torre, W., et al. (2018) · Thorax · doi:10.1136/thoraxjnl-2018-212194 · Cited by 12
Self-citationFeng, Y., Xiong, X., Wang, Y., Ding, H., Zeng, C., & Mao, H. Z. (2022) · Lung · doi:10.1007/s00408-022-00537-y · Cited by 11
Peinado, J., Quintanal-Villalonga, À., Muñoz-Galván, S., Verdugo‐Sivianes, E. M., Mateos, J. C., Ortiz-Gordillo, M. J., & Carnero, A. (2022) · Cancers · doi:10.3390/cancers14092054 · Cited by 11
Zhang, J., Bing, Z., Yan, P., Tian, J., Shi, X., Wang, Y., & Yang, K. (2019) · The Journal of Gene Medicine · doi:10.1002/jgm.3105 · Cited by 11
Shin, B., Park, S. S., Hong, J. H., An, H. J., Chun, S. H., Kang, K., Ahn, Y., Ko, Y. H., & Kang, K. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00662 · Cited by 11
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
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