Biomedical subjects

Richard Simon

Publications and source records attributed to Richard Simon.

64 records · Page 4Linked to original sources

PubMed2002

Initiating oncogenic event determines gene-expression patterns of human breast cancer models.

Molecular expression profiling of tumors initiated by transgenic overexpression of c-myc, c-neu, c-ha-ras, polyoma middle T antigen (PyMT) or simian virus 40 T/t antigen (T-ag) targeted to the mouse mammary gland have identified both common and oncogene-specific events associated with tumor formation and progression. The tumors shared great similarities in their gene-expression profiles as compared with the normal mammary gland with an induction of cell-cycle regulators, metabolic regulators, zinc finger proteins, and protein tyrosine phosphatases, along with the suppression of some protein tyrosine kinases. Selection and hierarchical clustering of the most variant genes, however, resulted in separating the mouse models into three groups with distinct oncogene-specific patterns of gene expression. Such an identification of targets specified by particular oncogenes may facilitate development of lesion-specific therapeutics and preclinical testing. 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.

Animals↗

PubMed2002

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 clone.

The use of synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) has emerged recently as an alternative approach for the identification of peptides recognized by T lymphocytes. The choice of both the PS-SCL used for screening experiments and the method used for data analysis are crucial for implementing this approach. With this aim, we tested the recognition of different PS-SCL by a tyrosinase 368-376-specific CTL clone and analyzed the data obtained with a recently developed biometric data analysis based on a model of independent and additive contribution of individual amino acids to peptide antigen recognition. Mixtures defined with amino acids present at the corresponding positions in the native sequence were among the most active for all of the libraries. Somewhat surprisingly, a higher number of native amino acids were identifiable by using amidated COOH-terminal rather than free COOH-terminal PS-SCL. Also, our data clearly indicate that when using PS-SCL longer than optimal, frame shifts occur frequently and should be taken into account. Biometric analysis of the data obtained with the amidated COOH-terminal nonapeptide library allowed the identification of the native ligand as the sequence with the highest score in a public human protein database. However, the adequacy of the PS-SCL data for the identification for the peptide ligand varied depending on the PS-SCL used. 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.

Biometry↗

PubMed2002

Combinatorial peptide library-based identification of peptide ligands for tumor-reactive cytolytic T lymphocytes of unknown specificity.

A novel approach for the identification of tumor antigen-derived sequences recognized by CD8(+) cytolytic T lymphocytes (CTL) consists in using synthetic combinatorial peptide libraries. Here we have screened a library composed of 3.1 x 10(11) nonapeptides arranged in a positional scanning format, in a cytotoxicity assay, to search the antigen recognized by melanoma-reactive CTL of unknown specificity. The results of this analysis enabled the identification of several optimal peptide ligands, as most of the individual nonapeptides deduced from the primary screening were efficiently recognized by the CTL. The results of the library screening were also analyzed with a mathematical approach based on a model of independent and additive contribution of individual amino acids to antigen recognition. This biometrical data analysis enabled the retrieval, in public databases, of the native antigenic peptide SSX-2(41-49), whose sequence is highly homologous to the ones deduced from the library screening, among the ones with the highest stimulatory score. These results underline the high predictive value of positional scanning synthetic combinatorial peptide library analysis and encourage its use for the identification of CTL ligands.

Antigens, Neoplasm↗

PubMed2002

Design of studies using DNA microarrays.

DNA microarrays are assays that simultaneously provide information about expression levels of thousands of genes and are consequently finding wide use in biomedical research. In order to control the many sources of variation and the many opportunities for misanalysis, DNA microarray studies require careful planning. Different studies have different objectives, and important aspects of design and analysis strategy differ for different types of studies. We review several types of objectives of studies using DNA microarrays and address issues such as selection of samples, levels of replication needed, allocation of samples to dyes and arrays, sample size considerations, and analysis strategies.

Computational Biology↗

PubMed2002

A paradigm for class prediction using gene expression profiles.

We propose a general framework for prediction of predefined tumor classes using gene expression profiles from microarray experiments. The framework consists of 1) evaluating the appropriateness of class prediction for the given data set, 2) selecting the prediction method, 3) performing cross-validated class prediction, and 4) assessing the significance of prediction results by permutation testing. We describe an application of the prediction paradigm to gene expression profiles from human breast cancers, with specimens classified as positive or negative for BRCA1 mutations and also for BRCA2 mutations. In both cases, the accuracy of class prediction was statistically significant when compared to the accuracy of prediction expected by chance. The framework proposed here for the application of class prediction is designed to reduce the occurrence of spurious findings, a legitimate concern for high-dimensional microarray data. 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.

Algorithms↗

PubMed2002

T-cell epitope prediction with combinatorial peptide libraries.

T cell receptors (TCR) recognize antigenic peptides in complex with the major histocompatibility complex (MHC) molecules and this trimolecular interaction initiates antigen-specific signaling pathways in the responding T lymphocytes. For the study of autoimmune diseases and vaccine development, it is important to identify peptides (epitopes) that can stimulate a given TCR. The use of combinatorial peptide libraries has recently been introduced as a powerful tool for this purpose. A combinatorial library of n-mer peptides is a set of complex mixtures each characterized by one position fixed to be a specified amino acid and all other positions randomized. A given TCR can be fingerprinted by screening a variety of combinatorial libraries using a proliferation assay. Here, we present statistical models for elucidating the recognition profile of a TCR using combinatorial library proliferation assay data and known MHC binding data.

Combinatorial Chemistry Techniques↗

PubMed2002

Methods for assessing reproducibility of clustering patterns observed in analyses of microarray data.

MOTIVATION: Recent technological advances such as cDNA microarray technology have made it possible to simultaneously interrogate thousands of genes in a biological specimen. A cDNA microarray experiment produces a gene expression 'profile'. Often interest lies in discovering novel subgroupings, or 'clusters', of specimens based on their profiles, for example identification of new tumor taxonomies. Cluster analysis techniques such as hierarchical clustering and self-organizing maps have frequently been used for investigating structure in microarray data. However, clustering algorithms always detect clusters, even on random data, and it is easy to misinterpret the results without some objective measure of the reproducibility of the clusters. RESULTS: We present statistical methods for testing for overall clustering of gene expression profiles, and we define easily interpretable measures of cluster-specific reproducibility that facilitate understanding of the clustering structure. We apply these methods to elucidate structure in cDNA microarray gene expression profiles obtained on melanoma tumors and on prostate specimens.

Cluster Analysis↗

PubMed2002

A bioinformatics tool to select sequences for microarray studies of mouse models of oncogenesis.

UNLABELLED: One of the challenges to the effective utilization of cDNA microarray analysis in mouse models of oncogenesis is the choice of a critical set of probes that are informative for human disease. Given the thousands of genes with a potential role in human oncogenesis and the hundreds of thousands of mouse sequences available for use as probes, selection of an informative set of mouse probes can be an overwhelming task. We have developed a web based sequence mining tool using DataBase Independent (DBI) Perl to annotate publicly available sequences. The Mouse Oncochip Design Tool uses the Mouse Genome Database (MGD) developed and maintained by the Jackson Laboratories for mouse DNA sequences. There are over 380 000 sequences in their database. The output list has been ordered to present the genes more likely to be informative in a mouse model of human cancer using a candidate set of oncogenes to order the list. Mouse sequences that represent genes that are homologous with a member of a human oncogene set are listed first. In addition it provides a set of links for information on clone source gene function. CONTACT: http://nciarray.nci.nih.gov/cgi-bin/me/mouse_design.cgi

Animals↗

PubMed2002

Treatment of recurrent malignant gliomas with stereotactic intensity modulated radiation therapy.

Malignant gliomas are usually refractory to aggressive combined-modality therapy, and the incidence of recurrence and death after treatment is very high. State-of-the-art techniques such as stereotactic intensity-modulated radiation therapy (IMRT) are now available to deliver a high dose of radiation to the tumor with relative preservation of surrounding tissues to achieve optimal tumor coverage with minimal toxicity. We report 10 patients (median age 48 years) with recurrent malignant gliomas that were treated with stereotactic directed IMRT. Initial tumor histologies included one low grade glioma (upgraded to anaplastic astrocytoma at recurrence), four anaplastic astrocytomas, and four glioblastomas multiforme. One patient was originally presumed to have a brain metastasis secondary to renal cell carcinoma but was pathologically confirmed as having glioblastoma multiforme at the time of recurrence. Before recurrence, all patients had been treated with external beam radiation therapy (median 59.7 Gy). All recurrences were confirmed by a subtotal resection (5/10) or by imaging (5/10). The median Karnofsky performance score at the time of IMRT was 80. The median tumor volume was 34.69 cm. Treatment was delivered on a 10-MV linear accelerator with a mini-multileaf collimator, MIMiC, and planned with Peacock/Corvus software. Radiation was delivered in daily fractions of 5 Gy, to a total median dose of 30 Gy at the 71% to 93% median isodose line. Median overall survival time was 10.1 months from the date of stereotactic treatment, with 1- and 2-year survival rates of 50% and 33.3%, respectively. Fractionated stereotactic intensity modulated radiation therapy is a novel technique used in the treatment of recurrent malignant gliomas, which produces results comparable to other currently used stereotactic techniques.

Adult↗

PubMed2002

The feasibility of using fine needle aspiration from primary breast cancers for cDNA microarray analyses.

PURPOSE: Our aims in this pilot study were to determine whether fine needle aspirates (FNAs) provide a sufficient quantity of mRNA for cDNA microarray analysis, produce a set of quality control criteria to accept individual arrays, and determine whether gene expression profiles obtained from FNAs were representative of the source tumor. EXPERIMENTAL DESIGN: Twenty-seven women with breast cancer for treatment with primary surgery had a FNA before and at the time of surgery, and a portion of excised tumor was taken for array analysis. Control experiments were performed using two Ewing's sarcoma xenograft models. mRNA was extracted from the samples and hybridized with the reference (MCF7 cell line) on cDNA microarrays. Statistical methods were applied to identify acceptability criteria for the arrays. RESULTS: Statistical analyses demonstrated that an adequate array could be identified by calculating the SD of the log of fluorescence intensities from the arrays. Using this criterion, only 4 of the 27 patients (15%) had FNA samples suitable for array analysis. Gene expression profiles from the FNAs closely resembled that of the corresponding source tumors and were clearly distinguished from FNAs derived from the xenografts. CONCLUSIONS: SD is a useful quality index for the clinical application of cDNA microarrays. This "proof of principle" study demonstrates that FNAs from primary breast cancers can be used for microarray analysis, although without amplification, it is feasible in only a small proportion of patients. For this to be clinically useful, validated amplification techniques for FNA samples are probably required.

Adult↗