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Richard Simon

Publications and source records attributed to Richard Simon.

At least 19 recordsLinked to original sources
PubMed2007

Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray data.

The goal of many gene-expression microarray profiling clinical studies is to develop a multivariate classifier to predict patient disease outcome from a gene-expression profile measured on some biological specimen from the patient. Often some preliminary validation of the predictive power of a profile-based classifier is carried out using the same data set that was used to derive the classifier. Techniques such as cross-validation or bootstrapping can be used in this setting to assess predictive power, and if applied correctly, can result in a less biased estimate of predictive accuracy of a classifier. However, some investigators have attempted to apply standard statistical inference procedures to assess the statistical significance of associations between true and cross-validated predicted outcomes. We demonstrate in this paper that naïve application of standard statistical inference procedures to these measures of association under null situations can result in greatly inflated testing type I error rates. Under alternatives of small to moderate associations, confidence interval coverage probabilities may be too low, although for very large associations coverage probabilities approach their intended values. 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.

Clinical Trials as Topic↗
PubMed2007

Gene expression profiling reveals a massive, aneuploidy-dependent transcriptional deregulation and distinct differences between lymph node-negative and lymph node-positive colon carcinomas.

To characterize patterns of global transcriptional deregulation in primary colon carcinomas, we did gene expression profiling of 73 tumors [Unio Internationale Contra Cancrum stage II (n = 33) and stage III (n = 40)] using oligonucleotide microarrays. For 30 of the tumors, expression profiles were compared with those from matched normal mucosa samples. We identified a set of 1,950 genes with highly significant deregulation between tumors and mucosa samples (P < 1e-7). A significant proportion of these genes mapped to chromosome 20 (P = 0.01). Seventeen genes had a >5-fold average expression difference between normal colon mucosa and carcinomas, including up-regulation of MYC and of HMGA1, a putative oncogene. Furthermore, we identified 68 genes that were significantly differentially expressed between lymph node-negative and lymph node-positive tumors (P < 0.001), the functional annotation of which revealed a preponderance of genes that play a role in cellular immune response and surveillance. The microarray-derived gene expression levels of 20 deregulated genes were validated using quantitative real-time reverse transcription-PCR in >40 tumor and normal mucosa samples with good concordance between the techniques. Finally, we established a relationship between specific genomic imbalances, which were mapped for 32 of the analyzed colon tumors by comparative genomic hybridization, and alterations of global transcriptional activity. Previously, we had conducted a similar analysis of primary rectal carcinomas. The systematic comparison of colon and rectal carcinomas revealed a significant overlap of genomic imbalances and transcriptional deregulation, including activation of the Wnt/beta-catenin signaling cascade, suggesting similar pathogenic pathways.

Adenocarcinoma↗
PubMed2006

Combined breast ductal lavage and ductal endoscopy for the evaluation of the high-risk breast: a feasibility study.

BACKGROUND AND OBJECTIVES: Evaluation of the ductal epithelium of the breast at increased risk for breast cancer is needed to define the carcinogenic pathway, for risk assessment, and to improve selection of women for chemoprevention therapy. We studied the feasibility of combining breast ductal endoscopy with ductal lavage in the high-risk contralateral breast of women with ipsilateral breast cancer for the evaluation of high-risk ducts and acquisition of ductal epithelial cells for analysis. METHODS: Breast ducts were studied by ductal lavage and ductal endoscopy, and epithelial cell content studied cytologically and quantitatively. RESULTS: Twenty-five subjects and 44 ducts, including 22 (50.0%) which did not produce nipple aspirate fluid (NAF), were studied. Cellular atypia was present in five subjects. Ductal endoscopy was performed on 1 or more ducts in 24 subjects. Structural changes were noted in 63.6% of the ducts, most commonly fibrous stranding or bridging. Ductal sampling with endoscopic brush and coil sampling devices provided additional cellular samples of relatively pure ductal epithelial content (> or = 91% purity) in 8/11 subjects. CONCLUSIONS: Breast ductal endoscopy combined with ductal lavage represents a feasible approach for characterizing the ducts and ductal epithelium of the high-risk breast, especially in a research setting.

Adult↗
PubMed2006

Molecular diagnosis of Burkitt's lymphoma.

BACKGROUND: The distinction between Burkitt's lymphoma and diffuse large-B-cell lymphoma is crucial because these two types of lymphoma require different treatments. We examined whether gene-expression profiling could reliably distinguish Burkitt's lymphoma from diffuse large-B-cell lymphoma. METHODS: Tumor-biopsy specimens from 303 patients with aggressive lymphomas were profiled for gene expression and were also classified according to morphology, immunohistochemistry, and detection of the t(8;14) c-myc translocation. RESULTS: A classifier based on gene expression correctly identified all 25 pathologically verified cases of classic Burkitt's lymphoma. Burkitt's lymphoma was readily distinguished from diffuse large-B-cell lymphoma by the high level of expression of c-myc target genes, the expression of a subgroup of germinal-center B-cell genes, and the low level of expression of major-histocompatibility-complex class I genes and nuclear factor-kappaB target genes. Eight specimens with a pathological diagnosis of diffuse large-B-cell lymphoma had the typical gene-expression profile of Burkitt's lymphoma, suggesting they represent cases of Burkitt's lymphoma that are difficult to diagnose by current methods. Among 28 of the patients with a molecular diagnosis of Burkitt's lymphoma, the overall survival was superior among those who had received intensive chemotherapy regimens instead of lower-dose regimens. CONCLUSIONS: Gene-expression profiling is an accurate, quantitative method for distinguishing Burkitt's lymphoma from diffuse large-B-cell lymphoma.

Adolescent↗
PubMed2006

Bias in error estimation when using cross-validation for model selection.

BACKGROUND: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. 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. RESULTS: We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. CONCLUSION: We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.

Algorithms↗
PubMed2006

Redundancy in antigen-presenting function of the HLA-DR and -DQ molecules in the multiple sclerosis-associated HLA-DR2 haplotype.

The three HLA class II alleles of the DR2 haplotype, DRB1*1501, DRB5*0101, and DQB1*0602, are in strong linkage disequilibrium and confer most of the genetic risk to multiple sclerosis. Functional redundancy in Ag presentation by these class II molecules would allow recognition by a single TCR of identical peptides with the different restriction elements, facilitating T cell activation and providing one explanation how a disease-associated HLA haplotype could be linked to a CD4+ T cell-mediated autoimmune disease. Using combinatorial peptide libraries and B cell lines expressing single HLA-DR/DQ molecules, we show that two of five in vivo-expanded and likely disease-relevant, cross-reactive cerebrospinal fluid-infiltrating T cell clones use multiple disease-associated HLA class II molecules as restriction elements. One of these T cell clones recognizes >30 identical foreign and human peptides using all DR and DQ molecules of the multiple sclerosis-associated DR2 haplotype. 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.

Amino Acid Sequence↗
PubMed2006

Aneuploidy-dependent massive deregulation of the cellular transcriptome and apparent divergence of the Wnt/beta-catenin signaling pathway in human rectal carcinomas.

To identify genetic alterations underlying rectal carcinogenesis, we used global gene expression profiling of a series of 17 locally advanced rectal adenocarcinomas and 20 normal rectal mucosa biopsies on oligonucleotide arrays. A total of 351 genes were differentially expressed (P < 1.0e-7) between normal rectal mucosa and rectal carcinomas, 77 genes had a >5-fold difference, and 85 genes always had at least a 2-fold change in all of the matched samples. Twelve genes satisfied all three of these criteria. Altered expression of genes such as PTGS2 (COX-2), WNT1, TGFB1, VEGF, and MYC was confirmed, whereas our data for other genes, like PPARD and LEF1, were inconsistent with previous reports. In addition, we found deregulated expression of many genes whose involvement in rectal carcinogenesis has not been reported. By mapping the genomic imbalances in the tumors using comparative genomic hybridization, we could show that DNA copy number gains of recurrently aneuploid chromosome arms 7p, 8q, 13q, 18q, 20p, and 20q correlated significantly with their average chromosome arm expression profile. Taken together, our results show that both the high-level, significant transcriptional deregulation of specific genes and general modification of the average transcriptional activity of genes residing on aneuploid chromosomes coexist in rectal adenocarcinomas.

Adenocarcinoma↗
PubMed2006

Identification of peptides from human pathogens able to cross-activate an HIV-1-gag-specific CD4+ T cell clone.

Antigen recognition by T cells is degenerate both at the MHC and the TCR level. In this study, we analyzed the cross-reactivity of a human HIV-1 gag p24-specific CD4(+) T cell clone obtained from an HIV-1-seronegative donor using a positional scanning synthetic combinatorial peptide library (PS-SCL)-based biometrical analysis. A number of decapeptides able to activate the HIV-1 gag-specific clone were identified and shown to correspond to sequences found in other human pathogens. Two of these peptides activated the T cell clone with the same stimulatory potency as the original HIV-1 gag p24 peptide. These findings show that an HIV-1-specific human T helper clone can react efficiently with peptides from other pathogens and suggest that cellular immune responses identified as being specific for one human pathogen (HIV-1) could arise from exposure to other pathogens.

Amino Acid Sequence↗
PubMed2006

Validation of pharmacogenomic biomarker classifiers for treatment selection.

Physicians need improved tools for selecting treatments for individual patients. Many syndromes traditionally viewed as individual diseases are heterogeneous in molecular pathogenesis and treatment responsiveness. This results in treatment of many patients with ineffective drugs and leads to the conduct of large clinical trials to identify small average treatment benefits for heterogeneous groups of patients. New genomic and proteomic technologies provide powerful tools for the selection of patients likely to benefit from a therapeutic without unacceptable adverse events. In spite of the large literature on developing predictive biomarkers and on statistical methodology for analysis of high dimensional data, there is considerable uncertainty about the validation of biomarker based diagnostic classifiers for treatment selection. 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.

Biomarkers↗
PubMed2006

A checklist for evaluating reports of expression profiling for treatment selection.

Oncologists need improved tools for selecting the right treatment for a given patient because many patients do not benefit from administered therapies. The use of expression profiling of tumors has increased dramatically and many claims are made for the value of expression signatures in treatment selection. It is difficult, however, for oncologists to critically evaluate published results in this technology- and statistics-intensive field. 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.

Gene Expression Profiling↗
PubMed2005

Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients.

PURPOSE: A new generation of molecularly targeted agents is entering the definitive stage of clinical evaluation. Many of these drugs benefit only a subset of treated patients and may be overlooked by the traditional, broad-eligibility approach to randomized clinical trials. Thus, there is a need for development of novel statistical methodology for rapid evaluation of these agents. EXPERIMENTAL DESIGN: We propose a new adaptive design for randomized clinical trials of targeted agents in settings where an assay or signature that identifies sensitive patients is not available at the outset of the study. The design combines prospective development of a gene expression-based classifier to select sensitive patients with a properly powered test for overall effect. RESULTS: Performance of the adaptive design, relative to the more traditional design, is evaluated in a simulation study. It is shown that when the proportion of patients sensitive to the new drug is low, the adaptive design substantially reduces the chance of false rejection of effective new treatments. When the new treatment is broadly effective, the adaptive design has power to detect the overall effect similar to the traditional design. Formulas are provided to determine the situations in which the new design is advantageous. CONCLUSION: Development of a gene expression-based classifier to identify the subset of sensitive patients can be prospectively incorporated into a randomized phase III design without compromising the ability to detect an overall effect.

Antineoplastic Agents↗
PubMed2005

High level of cross-reactivity in influenza virus hemagglutinin-specific CD4+ T-cell response: implications for the initiation of autoimmune response in multiple sclerosis.

Viral infections play a role in shaping and maintaining the peripheral T-cell repertoire, as well as in the initiation of autoimmune response via mechanisms of molecular mimicry. In this study, we addressed the flexibility of T-cell receptor (TCR) recognition and the degree of structural and sequence homology required for cross-reactive immune response in the induction of autoimmune response. We studied the extent of cross-reactivity of a CD4+T-cell clone (TCC) specific for the immunodominant influenza virus hemagglutinin (Flu-HA) peptide derived from a patient with multiple sclerosis (MS) using positional scanning synthetic peptide combinatorial libraries (PS-SCL). We documented cross-reactivity against 14 Flu-HA variants, 11 viral, 15 human, and 3 myelin-derived peptides. Moreover, we identified six naturally occurring peptides with higher stimulatory potency than the native ligand, implicating high potential for cross-reactivity even for a virus-specific memory TCC. Our study demonstrates that flexibility of TCR recognition is present even in a clone with a high degree of TCR specificity for an infectious agent. The results have implications for vaccine design and for antigen-specific treatment strategies for autoimmune diseases.

CD4-Positive T-Lymphocytes↗
PubMed2005

Roadmap for developing and validating therapeutically relevant genomic classifiers.

Oncologists need improved tools for selecting treatments for individual patients. The development of therapeutically relevant prognostic markers has traditionally been slowed by poor study design, inconsistent findings, and lack of proper validation studies. Microarray expression profiling provides an exciting new technology for relating tumor gene expression to patient outcome, but it also provides increased challenges for translating initial research findings into robust diagnostics that benefit patients and physicians in therapeutic decision making. This article attempts to clarify some of the misconceptions about the development and validation of multigene expression signature classifiers and highlights the steps needed to move genomic signatures into clinical application as therapeutically relevant and robust diagnostics.

Biomarkers, Tumor↗
PubMed2005

Diffuse large B-cell lymphoma subgroups have distinct genetic profiles that influence tumor biology and improve gene-expression-based survival prediction.

Gene-expression profiling has identified 3 major subgroups of diffuse large B-cell lymphoma (DLBCL): germinal center B-cell-like (GCB), activated B-cell-like (ABC), and primary mediastinal DLBCL (PMBCL). Using comparative genomic hybridization (CGH), we investigated the genetic alterations of 224 cases of untreated DLBCL (87 GCB-DLBCL, 77 ABC-DLBCL, 19 PMBCL, and 41 unclassified DLBCL) previously characterized by gene-expression profiling. The DLBCL subgroups differed significantly in the frequency of particular chromosomal aberrations. ABC-DLBCL had frequent trisomy 3, gains of 3q and 18q21-q22, and losses of 6q21-q22, whereas GCB-DLBCL had frequent gains of 12q12, and PMBCL had gains of 9p21-pter and 2p14-p16. Parallel analysis of CGH alterations, locus-specific gene-expression profiles, and global gene-expression signatures revealed that DNA amplifications and gains had a substantial impact on the expression of genes in the involved chromosomal regions, and some genes were overexpressed in a DLBCL subgroup-specific fashion. Unexpectedly, specific chromosomal alterations were associated with significant changes in gene-expression signatures that reflect various aspects of lymphoma cell biology as well as the host response to the lymphoma. 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.

Chromosomes, Human↗
PubMed2005

Evaluation of randomized discontinuation design.

PURPOSE: 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. METHODS: We compared power of the randomized discontinuation and upfront randomization designs under two models for the treatment effect of targeted cytostatic agents. RESULTS: The randomized discontinuation design is not as efficient as upfront randomization if treatment has a fixed effect on tumor growth rate or if treatment benefit is restricted to slower-growing tumors. On the other hand, the randomized discontinuation design can be advantageous under a model where only a subset of patients, those expressing the molecular target, is sensitive to the agent. To achieve efficiency, the design parameters must be carefully structured to provide adequate enrichment of the randomly assigned patients. CONCLUSION: With careful planning, the randomized discontinuation designs can be useful in some settings in the early development of targeted agents where a reliable assay to select patients expressing the target is not available.

Antineoplastic Agents↗