Research Topics
Species | Richard SimonSummaryAffiliation: National Institutes of Health Country: USA Publications
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Detail Information
Publications
Bias in error estimation when using cross-validation for model selectionSudhir Varma
Biometric Research Branch, National Cancer Institute, Bethesda, MD, USA
BMC Bioinformatics 7:91. 2006..We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data...
Roadmap for developing and validating therapeutically relevant genomic classifiersRichard Simon
National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892, USA
J Clin Oncol 23:7332-41. 2005....- A checklist for evaluating reports of expression profiling for treatment selectionRichard Simon
Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892 7434, USA
Clin Adv Hematol Oncol 4:219-24. 2006..A checklist is presented to help oncologists evaluate publications on expression profiling of human tumors to determine whether the results are ready for use with their patients... - Artificial intelligence methods for predicting T-cell epitopesYingdong Zhao
National Cancer Institute, National Institutes of Health, Rockville, MD, USA
Methods Mol Biol 409:217-25. 2007..For predicting T-cell epitopes for an MHC class II-restricted TCC, we built a shift model that integrated MHC-binding data and data from T-cell proliferation assay against a combinatorial library of peptide mixtures... - Development and validation of predictive indices for a continuous outcome using gene expression profilesYingdong Zhao
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA Email
Cancer Inform 9:105-14. 2010..We have developed a plug-in for BRB-ArrayTools that implements the LAR and the LASSO algorithms with complete cross-validation... - Optimally splitting cases for training and testing high dimensional classifiersKevin K Dobbin
Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
BMC Med Genomics 4:31. 2011..In this paper we address the question of what proportion of the samples should be devoted to the training set. How does this proportion impact the mean squared error (MSE) of the prediction accuracy estimate?.. - The Norton-Simon hypothesis: designing more effective and less toxic chemotherapeutic regimensRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892, USA
Nat Clin Pract Oncol 3:406-7. 2006 - Validation of pharmacogenomic biomarker classifiers for treatment selectionRichard Simon
Biometric Research Branch, National Cancer Institute, NIH, Bethesda, MD 20892 7434, USA
Cancer Biomark 2:89-96. 2006..In this paper we attempt to clarify these issues and to provide guidance on the design of clinical trials for evaluating the clinical utility and robustness of pharmacogenomic classifiers... - Molecular diagnosis of Burkitt's lymphomaSandeep S Dave
National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
N Engl J Med 354:2431-42. 2006..CONCLUSIONS: Gene-expression profiling is an accurate, quantitative method for distinguishing Burkitt's lymphoma from diffuse large-B-cell lymphoma... 
Combining positional scanning peptide libraries, HLA-DR transfectants and bioinformatics to dissect the epitope spectrum of HLA class II cross-restricted CD4+ T cell clonesMireia Sospedra
Cellular Immunology Section, Neuroimmunology Branch, NINDS, National Institutes of Health, Bethesda, Maryland 20892, USA
J Immunol Methods 353:93-101. 2010..In contrast, the use of B cell lines expressing single HLA class II molecules as APCs instead of autologous peripheral blood mononuclear cells markedly improves the capacity to identify target peptides for this type of T cells...- Biomarker-adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effectWenyu Jiang
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, EPN 8122, National Cancer Institute, Bethesda, MD 20892, USA
J Natl Cancer Inst 99:1036-43. 2007..We propose a statistically rigorous biomarker-adaptive threshold phase III design for settings in which a putative biomarker to identify patients who are sensitive to the new agent is measured on a continuous or graded scale... - Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patientsBoris Freidlin
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
Clin Cancer Res 11:7872-8. 2005..Thus, there is a need for development of novel statistical methodology for rapid evaluation of these agents... - An investigation of two multivariate permutation methods for controlling the false discovery proportionEdward L Korn
Biometric Research Branch, National Cancer Institute, EPN 8129, Bethesda, MD 20892 7434, USA
Stat Med 26:4428-40. 2007..We find that the top-down MPT-based method probabilistically controls the FDP, whereas our implementation of the top-down SAM-based method does not. Bottom-up MPT-based or SAM-based methods can result in poor control of the FDP... - Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cellsSandeep S Dave
National Cancer Institute, NIH, Bethesda, MD 20892, USA
N Engl J Med 351:2159-69. 2004..CONCLUSIONS: The length of survival among patients with follicular lymphoma correlates with the molecular features of nonmalignant immune cells present in the tumor at diagnosis... - An adaptive method for cDNA microarray normalizationYingdong Zhao
Biometric Research Branch, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA
BMC Bioinformatics 6:28. 2005..These assumptions can be inappropriate for custom arrays or arrays in which the reference RNA is very different from the experimental samples... - The proliferation gene expression signature is a quantitative integrator of oncogenic events that predicts survival in mantle cell lymphomaAndreas Rosenwald
The Lymphoma/Leukemia Molecular Profiling Project, National Cancer Institute/NIH, Bethesda, MD, USA
Cancer Cell 3:185-97. 2003..We propose a quantitative model of the aberrant cell cycle regulation in MCL that provides a rationale for the design of cell cycle inhibitor therapy in this malignancy... - A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classificationWenyu Jiang
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 6130 Executive Boulevard, Rockville, MD 20852, USA
Stat Med 26:5320-34. 2007..Even with small samples, it does not suffer from large upward bias as the leave-one-out bootstrap and the 0.632+ bootstrap, and it does not suffer from large variability as the leave-one-out cross-validation in microarray applications... - Prediction error estimation: a comparison of resampling methodsAnnette M Molinaro
Biostatistics Branch, Division of Cancer Epidemiology and Genetics, NCI, NIH, Rockville, MD 20852, USA
Bioinformatics 21:3301-7. 2005..With a focus on prediction assessment, we compare several methods for estimating the 'true' prediction error of a prediction model in the presence of feature selection... - The cross-validated adaptive signature designBoris Freidlin
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland 20892, USA
Clin Cancer Res 16:691-8. 2010..However, due to the high-dimensional nature of the genomic data, developing a reliable classifier by the time the definitive phase III trail is designed may not be feasible... - Gene expression-based prognostic signatures in lung cancer: ready for clinical use?Jyothi Subramanian
Biometric Research Branch, Department of Cancer Treatment and Diagnosis, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
J Natl Cancer Inst 102:464-74. 2010.... - Challenges of microarray data and the evaluation of gene expression profile signaturesRichard Simon
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland, USA
Cancer Invest 26:327-32. 2008 - A two-stage Bayesian design for co-development of new drugs and companion diagnosticsStella Wanjugu Karuri
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Stat Med 31:901-14. 2012.... - A paradigm for class prediction using gene expression profilesMichael D Radmacher
Biometric Research Branch, National Cancer Institute, 6130 Executive Boulevard, Bethesda, MD 20892 7434, USA
J Comput Biol 9:505-11. 2002..The prediction paradigm will serve as a good framework for comparing different prediction methods and may accelerate the development of molecular classifiers that are clinically useful... - Methods for assessing reproducibility of clustering patterns observed in analyses of microarray dataLisa M McShane
National Cancer Institute, Biometric Research Branch, DCTD, NIH, Bethesda, MD 20892 7434, USA
Bioinformatics 18:1462-9. 2002..We apply these methods to elucidate structure in cDNA microarray gene expression profiles obtained on melanoma tumors and on prostate specimens... - The use of genomics in clinical trial designRichard Simon
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892, USA
Clin Cancer Res 14:5984-93. 2008..This article reviews some designs for phase III clinical trials that may facilitate movement to a more predictive oncology... - On the dynamics of breast tumor development in women carrying germline BRCA1 and BRCA2 mutationsRichard Simon
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Int J Cancer 122:1916-7. 2008..A second event increasing proliferation of the partially malignant intermediate clone may lead inexorably to production and selection of cells with additional mutations in genes that facilitate tumor progression... - Iterative class discovery and feature selection using Minimal Spanning TreesSudhir Varma
Biometric Research Branch, National Cancer Institute, Rockville, USA
BMC Bioinformatics 5:126. 2004..This has the effect of obscuring clustering in samples that may be evident only when looking at a subset of genes, because noise from irrelevant genes dominates the signal from the relevant genes in the distance calculation... - An evaluation of resampling methods for assessment of survival risk prediction in high-dimensional settingsJyothi Subramanian
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Stat Med 30:642-53. 2011..A k-fold cross-validation with k = 5 or 10 was seen to provide a good balance between bias and variability for a wide range of data settings and should be more widely adopted in practice... - Questions and answers on design of dual-label microarrays for identifying differentially expressed genesKevin Dobbin
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892-7434, USA
J Natl Cancer Inst 95:1362-9. 2003 - Effectiveness of gene expression profiling for response prediction of rectal adenocarcinomas to preoperative chemoradiotherapyB Michael Ghadimi
Genetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bldg 50, Rm 1408, 50 South Dr, Bethesda, MD 20892-8010, USA
J Clin Oncol 23:1826-38. 2005..The implementation of gene expression profiles for treatment stratification and clinical management of cancer patients requires validation in large, independent studies, which are now warranted... - Using DNA microarrays for diagnostic and prognostic predictionRichard Simon
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892, USA
Expert Rev Mol Diagn 3:587-95. 2003..It also attempts to outline some of the steps needed to develop initial microarray research findings into classification systems suitable for broad clinical application... - Microarray-based cancer prediction using single genesXiaosheng Wang
Biometric Research Branch, National Cancer Institute, National Institutes of Health, Rockville, MD 20852, USA
BMC Bioinformatics 12:391. 2011..We first identified the genes with the most powerful univariate class discrimination ability and then constructed simple classification rules for class prediction using the single genes... - Microarray-based expression profiling and informaticsRichard Simon
National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892, United States
Curr Opin Biotechnol 19:26-9. 2008..We review here the current state-of-the-art for design and analysis of microarray-based investigations... - Gene Set Expression Comparison kit for BRB-ArrayToolsXiaojiang Xu
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Bioinformatics 24:137-9. 2008..AVAILABILITY: Gene Set Expression Comparison kit is freely available as a module of BRB-ArrayTools for non-commercial users. BRB-ArrayTools is available at http://linus.nci.nih.gov/BRB-ArrayTools.html... - Interpretation of genomic data: questions and answersRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
Semin Hematol 45:196-204. 2008..Achieving these goals involves challenges in rethinking many paradigms for the conduct of basic and clinical cancer research and for the organization of interdisciplinary collaboration... - Sample size determination in microarray experiments for class comparison and prognostic classificationKevin Dobbin
Biometric Research Branch, National Cancer Institute, 6130 Executive Blvd, Bethesda, MD, 20892 7434, USA
Biostatistics 6:27-38. 2005..We discuss procedures for controlling the false discovery rate. Our calculations are based on relatively simple yet realistic statistical models for the data, and provide straightforward sample size calculation formulae... - A comparison of phase II study strategiesSally Hunsberger
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland 20892, USA
Clin Cancer Res 15:5950-5. 2009..In this article, we compare different phase II study strategies to determine the most efficient drug development path in terms of number of patients and length of time to conclusion of drug efficacy on overall survival... - Candidate epitope identification using peptide property models: application to cancer immunotherapyMyong Hee Sung
Molecular Statistics and Bioinformatics Section, Biometric Research Branch, National Cancer Institute, National Institutes of Health, 6130 Executive Blvd EPN 8146, MSC 7434, Bethesda, MD 20892, USA
Methods 34:460-7. 2004..The candidate epitopes identified by such a computational approach must be evaluated experimentally but the approach can provide an efficient and focused strategy for anti-cancer immunotherapy development... - Expansion and functional relevance of high-avidity myelin-specific CD4+ T cells in multiple sclerosisBibiana Bielekova
Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
J Immunol 172:3893-904. 2004..These data have important implications for autoimmunity research and should be considered in the development of Ag-specific therapies in MS... - Molecular diagnosis of primary mediastinal B cell lymphoma identifies a clinically favorable subgroup of diffuse large B cell lymphoma related to Hodgkin lymphomaAndreas Rosenwald
Metabolism Branch, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA
J Exp Med 198:851-62. 2003..The molecular diagnosis of PMBL should significantly aid in the development of therapies tailored to this clinically and pathogenetically distinctive subgroup of DLBCL... - Molecular differentiation of high- and moderate-grade human prostate cancer by cDNA microarray analysisCarolyn J M Best
Pathogenetics Unit, Laboratory of Pathology and Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
Diagn Mol Pathol 12:63-70. 2003..We suggest that these data provide insight into the molecular nature of clinically aggressive prostate cancer... - In silico simulation of inhibitor drug effects on nuclear factor-kappaB pathway dynamicsMyong Hee Sung
Biometric Research Branch, National Cancer Institute, National Institutes of Health, 6130 Executive Blvd EPN 8146, MSC 7434, Bethesda, MD 20892, USA
Mol Pharmacol 66:70-5. 2004..Such kinetic analyses of the "drugged" molecular system will facilitate optimal drug target selection and the development of treatment protocols for a molecularly targeted therapy... - Construct and Compare Gene Coexpression Networks with DAPfinder and DAPviewJeff Skinner
Bioinformatics and Computational Biosciences Branch BCBB, Office of Cyber Infrastructure and Computational Biology OCICB, National Institute of Allergy and Infectious Disease NIAID, National Institutes if Health NIH, Bethesda, Maryland, USA
BMC Bioinformatics 12:286. 2011..DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes... - What should physicians look for in evaluating prognostic gene-expression signatures?Jyothi Subramanian
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Nat Rev Clin Oncol 7:327-34. 2010.... - Lost in translation: problems and pitfalls in translating laboratory observations to clinical utilityRichard Simon
National Cancer Institute, Division of Cancer Treatment and Diagnosis, Bethesda, MD 20892, USA
Eur J Cancer 44:2707-13. 2008..Some of these issues are addressed here, specifically in the context of developing molecular diagnostics in a manner that moves retrospective correlative science to prospective predictive medicine... - Translational research in oncology: key bottlenecks and new paradigmsRichard Simon
National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Expert Rev Mol Med 12:e32. 2010..I review here some prospective Phase III designs that have been developed for transition from the era of correlative science to one of reliable predictive and personalised oncology... - Redundancy in antigen-presenting function of the HLA-DR and -DQ molecules in the multiple sclerosis-associated HLA-DR2 haplotypeMireia Sospedra
Cellular Immunology Section, Neuroimmunology Branch, National Institute of Neurological Disorders and Stroke, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA
J Immunol 176:1951-61. 2006..A T cell signaling machinery tuned for efficient responses to weak ligands together with structural features of the TCR-HLA/peptide complex result in this promiscuous HLA class II restriction... - Clinical trial designs for therapeutic cancer vaccinesRichard Simon
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892 7434, USA
Cancer Treat Res 123:339-50. 2005..Interim monitoring plans may effectively limit the size of the trials by terminating accrual early when results are not consistent with the targeted improvement... - B cell gene signature with massive intrahepatic production of antibodies to hepatitis B core antigen in hepatitis B virus-associated acute liver failurePatrizia Farci
Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
Proc Natl Acad Sci U S A 107:8766-71. 2010..These data suggest that humoral immunity may exert a primary role in the pathogenesis of HBV-associated ALF... - Probabilistic classifiers with high-dimensional dataKyung In Kim
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC 7434, Bethesda, MD 20892 7434, USA
Biostatistics 12:399-412. 2011..We also present a cross-validation method for evaluating the calibration and refinement of any probabilistic classifier on any data set... - Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsivenessEna Wang
Immunogenetics Section, Department of Transfusion Medicine, Clinical Center, NIH, Bethesda, Maryland 20892, USA
Cancer Res 62:3581-6. 2002..001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition... - Predicting survival in patients with metastatic kidney cancer by gene-expression profiling in the primary tumorJames R Vasselli
Urologic Oncology Branch, National Cancer Institute, Bethesda, MD 20892, USA
Proc Natl Acad Sci U S A 100:6958-63. 2003..We conclude that survival in patients with metastatic renal cell cancer can be correlated with the expression of various genes based solely on the expression profile in the primary kidney tumor... - Evaluating the efficiency of targeted designs for randomized clinical trialsRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, Maryland 20892 7634, USA
Clin Cancer Res 10:6759-63. 2004..This creates the opportunity to conduct targeted clinical trials with eligibility restricted to patients predicted to be responsive to the drug... - Evaluation of randomized discontinuation designBoris Freidlin
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
J Clin Oncol 23:5094-8. 2005..Single-arm phase II trials may not be appropriate for testing cytostatic agents. We evaluate two kinds of randomized designs for the early development of target-based cytostatic agents... - Application of support vector machines for T-cell epitopes predictionYingdong Zhao
Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
Bioinformatics 19:1978-84. 2003..SUPPLEMENTARY INFORMATION: Data for 203 synthesized peptides is available at http://linus.nci.nih.gov/Data/LAU203_Peptide.pdf.. - The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphomaAndreas Rosenwald
Metabolism Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
N Engl J Med 346:1937-47. 2002..CONCLUSIONS: DNA microarrays can be used to formulate a molecular predictor of survival after chemotherapy for diffuse large-B-cell lymphoma... - Design of studies using DNA microarraysRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, Maryland 20892 7434, USA
Genet Epidemiol 23:21-36. 2002.... - Genomewide conserved epitope profiles of HIV-1 predicted by biophysical properties of MHC binding peptidesMyong Hee Sung
Biometric Research Branch, National Cancer Institute, National Institutes of Health, 6130 Executive Boulevard EPN 8146, MSC 7434, Bethesda, MD 20892, USA
J Comput Biol 11:125-45. 2004..As an essential step in designing vaccines, the revealed patterns may provide valuable information in identifying the immunologically important regions... - Analysis of DNA microarray expression dataRichard Simon
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 7434, USA
Best Pract Res Clin Haematol 22:271-82. 2009..This manuscript attempts to provide a non-technical summary of the key principles of statistical design and analysis for studies that utilize microarray expression profiling... - Combined breast ductal lavage and ductal endoscopy for the evaluation of the high-risk breast: a feasibility studyDavid N Danforth
Surgery Branch, The Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
J Surg Oncol 94:555-64. 2006.... - Identifying cancer driver genes in tumor genome sequencing studiesAhrim Youn
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
Bioinformatics 27:175-81. 2011..Several methods have been used for estimating the background mutation rate... - Initiating oncogenic event determines gene-expression patterns of human breast cancer modelsKartiki V Desai
Laboratory of Cell Regulation and Carcinogenesis, National Cancer Institute, Bethesda, MD 20892, USA
Proc Natl Acad Sci U S A 99:6967-72. 2002..Moreover, similarities in gene expression between human breast cancers and the mouse models have been identified, thus providing an important component for the validation of transgenic mammary cancer models... - Pitfalls in the use of DNA microarray data for diagnostic and prognostic classificationRichard Simon
Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
J Natl Cancer Inst 95:14-8. 2003 - Analysis of gene expression data using BRB-ArrayToolsRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
Cancer Inform 3:11-7. 2007.... - Distinguishing right from left colon by the pattern of gene expressionOleg K Glebov
Genetics Branch, Center for Cancer Research, National Cancer Institute (NCI, Bethesda, Maryland 20892, USA
Cancer Epidemiol Biomarkers Prev 12:755-62. 2003.... - Stable disease is not preferentially observed with targeted therapies and as currently defined has limited value in drug developmentTatiana Vidaurre
Medical Oncology Branch, National Cancer Institute, NIH, Bethesda, MD 20892, USA
Cancer J 15:366-73. 2009..Studies that use SD as an end point require an adequate control to distinguish antitumor activity from normal variability in time to progression... - Gene expression deconvolution in clinical samplesYingdong Zhao
Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
Genome Med 2:93. 2010..Consequently, the deconvolution approach can be useful in the analysis of mixtures of cell populations in clinical samples... - Clinical trials for predictive medicine: new challenges and paradigmsRichard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892 7434, USA
Clin Trials 7:516-24. 2010..Heterogeneity of human diseases and new technology for characterizing them presents new opportunities and challenges for the design and analysis of clinical trials... - Estimating the number of rate limiting genomic changes for human breast cancerXinan Zhang
Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA
Breast Cancer Res Treat 91:121-4. 2005.... - New challenges for 21st century clinical trialsRichard Simon
Biometic Research Branch, National Cancer Institute, Bethesda, MD 20892-7434, USA
Clin Trials 4:167-9; discussion 173-7. 2007 - When is a genomic classifier ready for prime time?Richard Simon
Biometric Research Branch, National Cancer Institute, Bethesda, MD 20892, USA
Nat Clin Pract Oncol 1:4-5. 2004 - Laser capture microdissection and microarray expression analysis of lung adenocarcinoma reveals tobacco smoking- and prognosis-related molecular profilesKoh Miura
Laboratory of Human Carcinogenesis, Biometric Research Branch, Division of Cancer Treatment and Diagnosis National Cancer Institute, NIH, 37 Convent Drive, Bethesda, MD 20892, USA
Cancer Res 62:3244-50. 2002..g., hBUB3, hZW10, and APC2, contribute to the molecular pathogenesis and tumor progression of tobacco smoke-induced adenocarcinoma of the lung... - Bayesian subset analysis: application to studying treatment-by-gender interactionsRichard Simon
National Cancer Institute, 6130 Executive Boulevard, Room 8134, Bethesda, MD 20892-7434, USA
Stat Med 21:2909-16. 2002..The methodology is applied to the problem of designing and analysing clinical trials to estimate treatment effects for males and females... - The feasibility of using fine needle aspiration from primary breast cancers for cDNA microarray analysesLaura Assersohn
Royal Marsden Hospital, Surrey SM2 5PT, United Kingdom
Clin Cancer Res 8:794-801. 2002..For this to be clinically useful, validated amplification techniques for FNA samples are probably required... - Evaluation of normalization methods for microarray dataTaesung Park
Department of Statistics, Seoul National University, Seoul, Korea
BMC Bioinformatics 4:33. 2003..Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization... - Calculating confidence intervals for prediction error in microarray classification using resamplingWenyu Jiang
Concordia University, Quebec, Canada
Stat Appl Genet Mol Biol 7:Article8. 2008..The method provides mildly conservative inference under all circumstances studied and outperforms the other methods in microarray applications with small to moderate sample sizes... - Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learningQing Hai Ye
Liver Cancer Institute and Zhongshan Hospital, Fudan University, Shanghai, China
Nat Med 9:416-23. 2003..Thus, osteopontin acts as both a diagnostic marker and a potential therapeutic target for metastatic HCC... - Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTLVerena Rubio-Godoy
Division of Clinical Onco-Immunology, Ludwig Institute for Cancer Research, Lausanne Branch, University Hospital, Lausanne, Switzerland
J Immunol 169:5696-707. 2002..Together, these results underline the high predictive value of PS-SCL for the identification of sequences cross-recognized by Ag-specific T cells... - PSA velocity and prostate cancerLori E Dodd
N Engl J Med 351:1800-2; author reply 1800-2. 2004 - Development and validation of therapeutically relevant multi-gene biomarker classifiersRichard Simon
J Natl Cancer Inst 97:866-7. 2005 - Development and evaluation of therapeutically relevant predictive classifiers using gene expression profilingRichard Simon
J Natl Cancer Inst 98:1169-71. 2006 - Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray dataLara Lusa
Department of Experimental Oncology, Istituto Nazionale per lo Studio e la Cura dei Tumori, Milano, Italy
Stat Med 26:1102-13. 2007..Our results suggest that caution should be exercised in interpreting some of the claims of exceptional prognostic classifier performance that have been reported in prominent biomedical journals in the past few years... - Aneuploidy-dependent massive deregulation of the cellular transcriptome and apparent divergence of the Wnt/beta-catenin signaling pathway in human rectal carcinomasMarian Grade
Department of General Surgery, University Medical Center, , Germany
Cancer Res 66:267-82. 2006.... - Bioinformatics in cancer therapeutics--hype or hope?Richard Simon
Nat Clin Pract Oncol 2:223. 2005 - Diffuse large B-cell lymphoma subgroups have distinct genetic profiles that influence tumor biology and improve gene-expression-based survival predictionSilvia Bea
Department of Pathology and Hematology Hospital Clinic, University of Barcelona, Spain
Blood 106:3183-90. 2005..In addition, gains involving the chromosomal region 3p11-p12 provided prognostic information that was statistically independent of the previously defined gene-expression-based survival model, thereby improving its predictive power... - Gene expression profiling reveals a massive, aneuploidy-dependent transcriptional deregulation and distinct differences between lymph node-negative and lymph node-positive colon carcinomasMarian Grade
Department of General Surgery, University Medical Center, Robert Koch Strasse 40, 37075 Gottingen, Germany
Cancer Res 67:41-56. 2007.... - Targets for treatment successRichard Simon
Nat Clin Pract Oncol 3:1. 2006 - Novel trial designs for novel agents. Interview by Helen SaulRichard Simon
Eur J Cancer 44:170-1. 2008 - Toward synthetic combinatorial peptide libraries in positional scanning format (PS-SCL)-based identification of CD8+ Tumor-reactive T-Cell Ligands: a comparative analysis of PS-SCL recognition by a single tumor-reactive CD8+ cytolytic T-lymphocyte cloneVerena Rubio-Godoy
Division of Clinical Onco-Immunology, Ludwig Institute for Cancer Research, University Hospital (CHUV, 1011 Lausanne, Switzerland
Cancer Res 62:2058-63. 2002..Altogether these results provide insight into the potential of PS-SCL for the identification of CTL-defined tumor-derived antigenic sequences and may significantly implement our ability to interpret the results of these analyses...