Selective discussion and transparency in microarray research findings for cancer outcomes.
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Thomas A Trikalinos | John P A Ioannidis | J. Ioannidis | T. Trikalinos | Nikolaos P Polyzos | N. Polyzos
[1] John P A Ioannidis,et al. Is molecular profiling ready for use in clinical decision making? , 2007, The oncologist.
[2] Yingdong Zhao,et al. Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness. , 2002, Cancer research.
[3] Ola Larsson,et al. Lack of correct data format and comparability limits future integrative microarray research , 2006, Nature Biotechnology.
[4] L. Staudt,et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. , 2002, The New England journal of medicine.
[5] C. Ball,et al. Submission of Microarray Data to Public Repositories , 2004, PLoS biology.
[6] C. Sotiriou,et al. Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer , 2002, Breast Cancer Research.
[7] Zhiyuan Hu,et al. Classification and risk stratification of invasive breast carcinomas using a real-time quantitative RT-PCR assay , 2006, Breast Cancer Research.
[8] David E. Misek,et al. Gene-expression profiles predict survival of patients with lung adenocarcinoma , 2002, Nature Medicine.
[9] N. Sampas,et al. Molecular classification of cutaneous malignant melanoma by gene expression profiling , 2000, Nature.
[10] E. Devilard,et al. Gene expression profiling defines molecular subtypes of classical Hodgkin's disease , 2002, Oncogene.
[11] J. Ioannidis,et al. Predictive ability of DNA microarrays for cancer outcomes and correlates: an empirical assessment , 2003, The Lancet.
[12] Roland Eils,et al. Gene expression signature predicting pathologic complete response with gemcitabine, epirubicin, and docetaxel in primary breast cancer. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[13] L. Ein-Dor,et al. Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[14] Yudong D. He,et al. Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.
[15] M. Tyers,et al. Molecular profiling of non-small cell lung cancer and correlation with disease-free survival. , 2002, Cancer research.
[16] Eytan Domany,et al. Outcome signature genes in breast cancer: is there a unique set? , 2004, Breast Cancer Research.
[17] Carl Virtanen,et al. Integrated classification of lung tumors and cell lines by expression profiling , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[18] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[19] Yoko Yamamoto,et al. Prediction of sensitivity of rectal cancer cells in response to preoperative radiotherapy by DNA microarray analysis of gene expression profiles. , 2006, Cancer research.
[20] Yudong D. He,et al. A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .
[21] Sergio Contrino,et al. ArrayExpress—a public repository for microarray gene expression data at the EBI , 2004, Nucleic Acids Res..
[22] David Botstein,et al. Variation in gene expression patterns in follicular lymphoma and the response to rituximab , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[23] C. Gluud,et al. Citation bias of hepato-biliary randomized clinical trials. , 2002, Journal of clinical epidemiology.
[24] E. Devilard,et al. Gene expression profiles of poor-prognosis primary breast cancer correlate with survival. , 2002, Human molecular genetics.
[25] N. Iizuka,et al. MECHANISMS OF DISEASE Mechanisms of disease , 2022 .
[26] Hanlee P. Ji,et al. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. , 2006, Nature biotechnology.
[27] M. Vijver,et al. Technology Insight: tuning into the genetic orchestra using microarrays—limitations of DNA microarrays in clinical practice , 2006, Nature Clinical Practice Oncology.
[28] A. Eggermont,et al. Gene expression profiling of primary cutaneous melanoma and clinical outcome. , 2006, Journal of the National Cancer Institute.
[29] J. Ajani,et al. Gene expression profiling of localized esophageal carcinomas: association with pathologic response to preoperative chemoradiation. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[30] D. Botstein,et al. Diversity of gene expression in adenocarcinoma of the lung , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[31] T. Poggio,et al. Prediction of central nervous system embryonal tumour outcome based on gene expression , 2002, Nature.
[32] John P A Ioannidis,et al. Limitations are not properly acknowledged in the scientific literature. , 2007, Journal of clinical epidemiology.
[33] D. Allison,et al. Microarray data analysis: from disarray to consolidation and consensus , 2006, Nature Reviews Genetics.
[34] J. Downing,et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. , 2002, Cancer cell.
[35] J. Ioannidis,et al. An empirical evaluation of multifarious outcomes in pharmacogenetics: beta-2 adrenoceptor gene polymorphisms in asthma treatment , 2006, Pharmacogenetics and genomics.
[36] M Krause,et al. Expression profiling of Wilms tumors reveals new candidate genes for different clinical parameters , 2006, International journal of cancer.
[37] Erik Andries,et al. Gene expression profiling of adult acute myeloid leukemia identifies novel biologic clusters for risk classification and outcome prediction. , 2006, Blood.
[38] C Hill,et al. Interpretation of microarray data in cancer , 2007, British Journal of Cancer.
[39] E. Lander,et al. Gene expression correlates of clinical prostate cancer behavior. , 2002, Cancer cell.
[40] Catherine Brooksbank,et al. An open letter to the scientific journals , 2002, Bioinform..
[41] Duccio Cavalieri,et al. Standards for Microarray Data , 2002, Science.
[42] Jason E. Stewart,et al. Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.
[43] Stefan Michiels,et al. Prediction of cancer outcome with microarrays: a multiple random validation strategy , 2005, The Lancet.
[44] Geoffrey Childs,et al. Molecular classification of head and neck squamous cell carcinoma using cDNA microarrays , 2001, Nature Genetics.
[45] Robert Tibshirani,et al. Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma , 2005, PLoS medicine.
[46] K. Nishio,et al. Identification of expressed genes characterizing long-term survival in malignant glioma patients , 2006, Oncogene.
[47] L. Liotta,et al. Laser capture microdissection and microarray expression analysis of lung adenocarcinoma reveals tobacco smoking- and prognosis-related molecular profiles. , 2002, Cancer research.
[48] Christine Solbach,et al. Identification of high risk breast-cancer patients by gene expression profiling , 2002, The Lancet.
[49] Maurice P H M Jansen,et al. Molecular profiling of platinum resistant ovarian cancer , 2006, International journal of cancer.
[50] Todd,et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning , 2002, Nature Medicine.
[51] R. Tibshirani,et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[52] A. Nobel,et al. Concordance among Gene-Expression – Based Predictors for Breast Cancer , 2011 .
[53] Sandya Liyanarachchi,et al. Prognostic DNA Methylation Biomarkers in Ovarian Cancer , 2006, Clinical Cancer Research.
[54] A. Dupuy,et al. Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting. , 2007, Journal of the National Cancer Institute.
[55] Wei Zhang,et al. Molecular Classification of Human Diffuse Gliomas by Multidimensional Scaling Analysis of Gene Expression Profiles Parallels Morphology‐Based Classification, Correlates with Survival, and Reveals Clinically‐Relevant Novel Glioma Subsets , 2002, Brain pathology.
[56] M. Radmacher,et al. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. , 2003, Journal of the National Cancer Institute.
[57] Alex E. Lash,et al. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..
[58] Ash A. Alizadeh,et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling , 2000, Nature.
[59] Juan F. García,et al. Tumor microenvironment and mitotic checkpoint are key factors in the outcome of classic Hodgkin lymphoma. , 2006, Blood.
[60] Torben F. Ørntoft,et al. Identifying distinct classes of bladder carcinoma using microarrays , 2003, Nature Genetics.
[61] T Tanaka,et al. Prediction of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles. , 2001, Cancer research.
[62] E. Lander,et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[63] C Stratowa,et al. CDNA microarray gene expression analysis of B‐cell chronic lymphocytic leukemia proposes potential new prognostic markers involved in lymphocyte trafficking , 2001, International journal of cancer.
[64] J. Ioannidis. Why Most Published Research Findings Are False , 2005, PLoS medicine.
[65] K. Furge,et al. Gene expression profiling of clear cell renal cell carcinoma: Gene identification and prognostic classification , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[66] L. Recht,et al. Tumor Necrosis Factor-α–Induced Protein 3 As a Putative Regulator of Nuclear Factor-κB–Mediated Resistance to O6-Alkylating Agents in Human Glioblastomas , 2006 .
[67] Richard Horton,et al. The hidden research paper. , 2002, JAMA.
[68] David Elashoff,et al. Relation between resistance of Philadelphia-chromosome-positive acute lymphoblastic leukaemia to the tyrosine kinase inhibitor STI571 and gene-expression profiles: a gene-expression study , 2002, The Lancet.
[69] A. Brazma,et al. Standards for systems biology , 2006, Nature Reviews Genetics.
[70] Carlos Cordon-Cardo,et al. Defining molecular profiles of poor outcome in patients with invasive bladder cancer using oligonucleotide microarrays. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[71] J. Ioannidis. Microarrays and molecular research: noise discovery? , 2005, The Lancet.
[72] M. Loda,et al. Epithelial-Restricted Gene Profile of Primary Cultures from Human Prostate Tumors: A Molecular Approach to Predict Clinical Behavior of Prostate Cancer , 2006, Molecular Cancer Research.