Biomedical subjects

Kerby Shedden

Publications and source records attributed to Kerby Shedden.

16 recordsLinked to original sources

PubMed2026

Urinary clusterin as a biomarker of human kidney disease progression and response to the endothelin receptor antagonist atrasentan: An exploratory analysis from the SONAR trial.

The endothelin receptor antagonist atrasentan improved kidney outcomes in the SONAR trial for type 2 diabetes and chronic kidney disease (NCT01858532), though individual responses varied. To identify molecular biomarkers of atrasentan response and outcome, we conducted a nested case-control proteomics study (N = 180) within the SONAR trial population and identified urinary clusterin (uCLU) as the top candidate. Transcriptomic analyses of human kidney biopsies at tissue and single cell level from independent cohorts revealed higher CLU mRNA levels associated with worse kidney function and outcomes. An endothelin signaling activation score derived from pathway genes was reduced by atrasentan in mice with diabetic kidney disease. In the SONAR trial (N = 3,060) population, higher uCLU predicted worse outcomes, while atrasentan reduced uCLU by 42.6% over six weeks. Early uCLU changes independently predict improved kidney outcomes. In summary, uCLU is associated with kidney disease progression and response to atrasentan treatment, supporting its potential as a pharmacodynamic biomarker to target therapy.

Humans↗

PubMed2007

The prognostic role of a gene signature from tumorigenic breast-cancer cells.

BACKGROUND: Breast cancers contain a minority population of cancer cells characterized by CD44 expression but low or undetectable levels of CD24 (CD44+CD24-/low) that have higher tumorigenic capacity than other subtypes of cancer cells. METHODS: We compared the gene-expression profile of CD44+CD24-/low tumorigenic breast-cancer cells with that of normal breast epithelium. Differentially expressed genes were used to generate a 186-gene "invasiveness" gene signature (IGS), which was evaluated for its association with overall survival and metastasis-free survival in patients with breast cancer or other types of cancer. RESULTS: There was a significant association between the IGS and both overall and metastasis-free survival (P<0.001, for both) in patients with breast cancer, which was independent of established clinical and pathological variables. When combined with the prognostic criteria of the National Institutes of Health, the IGS was used to stratify patients with high-risk early breast cancer into prognostic categories (good or poor); among patients with a good prognosis, the 10-year rate of metastasis-free survival was 81%, and among those with a poor prognosis, it was 57%. The IGS was also associated with the prognosis in medulloblastoma (P=0.004), lung cancer (P=0.03), and prostate cancer (P=0.01). The prognostic power of the IGS was increased when combined with the wound-response (WR) signature. CONCLUSIONS: The IGS is strongly associated with metastasis-free survival and overall survival for four different types of tumors. This genetic signature of tumorigenic breast-cancer cells was even more strongly associated with clinical outcomes when combined with the WR signature in breast cancer.

Breast↗

PubMed2005

Molecular classification of papillary thyroid carcinoma: distinct BRAF, RAS, and RET/PTC mutation-specific gene expression profiles discovered by DNA microarray analysis.

Thyroid cancer poses a significant clinical challenge, and our understanding of its pathogenesis is incomplete. To gain insight into the pathogenesis of papillary thyroid carcinoma, transcriptional profiles of four normal thyroids and 51 papillary carcinomas (PCs) were generated using DNA microarrays. The tumors were genotyped for their common activating mutations: BRAF V600E point mutation, RET/PTC1 and 3 rearrangement and point mutations of KRAS, HRAS and NRAS. Principal component analysis based on the entire expression data set separated the PCs into three groups that were found to reflect tumor morphology and mutational status. By combining expression profiles with mutational status, we defined distinct expression profiles for the BRAF, RET/PTC and RAS mutation groups. Using small numbers of genes, a simple classifier was able to classify correctly the mutational status of all 40 tumors with known mutations. One tumor without a detectable mutation was predicted by the classifier to have a RET/PTC rearrangement and was shown to contain one by fluorescence in situ hybridization analysis. Among the mutation-specific expression signatures were genes whose differential expression was a direct consequence of the mutation, as well as genes involved in a variety of biological processes including immune response and signal transduction. Expression of one mutation-specific differentially expressed gene, TPO, was validated at the protein level using immunohistochemistry and tissue arrays containing an independent set of tumors. The results demonstrate that mutational status is the primary determinant of gene expression variation within these tumors, a finding that may have clinical and diagnostic significance and predicts success for therapies designed to prevent the consequences of these mutations.

Base Sequence↗

PubMed2005

Comparison of seven methods for producing Affymetrix expression scores based on False Discovery Rates in disease profiling data.

BACKGROUND: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the expression level of a RNA transcript. Several systematic studies comparing multiple methods for array processing have used tightly controlled calibration data sets as the basis for comparison. Here we compare performances for seven processing methods using two data sets originally collected for disease profiling studies. An emphasis is placed on understanding sensitivity for detecting differentially expressed genes in terms of two key statistical determinants: test statistic variability for non-differentially expressed genes, and test statistic size for truly differentially expressed genes. RESULTS: In the two data sets considered here, up to seven-fold variation across the processing methods was found in the number of genes detected at a given false discovery rate (FDR). The best performing methods called up to 90% of the same genes differentially expressed, had less variable test statistics under randomization, and had a greater number of large test statistics in the experimental data. Poor performance of one method was directly tied to a tendency to produce highly variable test statistic values under randomization. Based on an overall measure of performance, two of the seven methods (Dchip and a trimmed mean approach) are superior in the two data sets considered here. Two other methods (MAS5 and GCRMA-EB) are inferior, while results for the other three methods are mixed. CONCLUSIONS: Choice of processing method has a major impact on differential expression analysis of microarray data. Previously reported performance analyses using tightly controlled calibration data sets are not highly consistent with results reported here using data from human tissue samples. Performance of array processing methods in disease profiling and other realistic biological studies should be given greater consideration when comparing Affymetrix processing methods.

Algorithms↗

PubMed2004

Confidence levels for the comparison of microarray experiments.

A common experimental strategy utilizing microarrays is to develop a signature of genes responding to some treatment in a model system, and then ask whether the same genes respond in an analogous way in a more natural and uncontrolled environment. In statistical terms, the question posed is whether genes score similarly on some statistical test in two independent data sets. Approaches to this problem ignoring gene/gene correlations common to all microarray data sets are known to give overstated statistical confidence levels. Permutation approaches have been proposed to give more accurate confidence levels, but can not be applied when sample sizes are small. Here we argue that the product moment correlation between test statistics in the two experiments is an ideal measure for summarizing concordance between the experiments, as confidence levels accounting for intergene correlations depend only on a single number - the average squared correlation between gene pairs in the data set. The resulting null standard deviation is shown to vary by less than a factor of two over six distinct experimental data sets, suggesting that a universal constant may be used for this quantity. We show how a hidden assumption of the permutation approach may lead to incorrect p-values, while the analytic approach presented here is shown to be resistant to this assumption.

Journal Article↗

PubMed2003

Microarray analysis of gene expression during the cell cycle.

Microarrays have been applied to the determination of genome-wide expression patterns during the cell cycle of a number of different cells. Both eukaryotic and prokaryotic cells have been studied using whole-culture and selective synchronization methods. The published microarray data on yeast, mammalian, and bacterial cells have been uniformly interpreted as indicating that a large number of genes are expressed in a cell-cycle-dependent manner. These conclusions are reconsidered using explicit criteria for synchronization and precise criteria for identifying gene expression patterns during the cell cycle. The conclusions regarding cell-cycle-dependent gene expression based on microarray analysis are weakened by arguably problematic choices for synchronization methodology (e.g., whole-culture methods that do not synchronize cells) and questionable statistical rigor for identifying cell-cycle-dependent gene expression. Because of the uncertainties in synchrony methodology, as well as uncertainties in microarray analysis, one should be somewhat skeptical of claims that there are a large number of genes expressed in a cell-cycle-dependent manner.

Journal Article↗

PubMed2003

Expulsion of small molecules in vesicles shed by cancer cells: association with gene expression and chemosensitivity profiles.

Anticancer drug resistance results from selective pressure of chemotherapy, together with mutations or epigenetic changes that make cells refractory to treatment. In cancer cells, we report that gene expression associated with vesicle shedding correlates with chemosensitivity profiles. Experiments with doxorubicin and other small molecules confirm drug accumulation and expulsion in shed vesicles. Relative differences in the rate of vesicle shedding correspond with doxorubicin resistance across various cell lines. Moreover, accumulation of drug in membrane domains in which vesicles originate accounts for drug expulsion in shed vesicles. These observations implicate vesicle shedding as a drug efflux mechanism potentially involved in drug resistance.

Antineoplastic Agents↗

PubMed2003

A rational approach to personalized anticancer therapy: chemoinformatic analysis reveals mechanistic gene-drug associations.

PURPOSE: To predict the response of cells to chemotherapeutic agents based on gene expression profiles, we performed a chemoinformatic study of a set of standard anticancer agents assayed for activity against a panel of 60 human tumor-derived cell lines from the Developmental Therapeutics Program (DTP) at the National Cancer Institute (NCI). METHODS: Mechanistically-relevant gene:drug activity associations were identified in the scientific literature. The correlations between expression levels of drug target genes and the activity of the drugs against the NCI's 60 cell line panel were calculated across and within each tumor tissue type, using published drug activity and gene expression data. RESULTS: Compared to other mechanistically-relevant gene-drug associations, that of triciribine phosphate (TCN-P) and adenosine kinase (ADK) was exceptionally strong--overall and within tumor tissue types-across the 60 cell lines profiled for chemosensitivity (1) and gene expression (2). CONCLUSION: The results suggest ADK expression may be useful for stratifying TCN-P-responsive vs. non-responsive tumors. Based on TCN-P's mechanism of action and the observed TCN-P:ADK association, we contend that catalytic drug activation provides a rational, mechanistic basis for personalizing cancer treatment based on tumor-specific differences in the expression of drug-activating enzymes.

Acenaphthenes↗

PubMed2003

The application of rule-based methods to class prediction problems in genomics.

We propose a method for constructing classifiers using logical combinations of elementary rules. The method is a form of rule-based classification, which has been widely discussed in the literature. In this work we focus specifically on issues that arise in the context of classifying cell samples based on RNA or protein expression measurements. The basic idea is to specify elementary rules that exhibit a locally strong pattern in favor of a single class. Strict admissibility criteria are imposed to produce a manageable universe of elementary rules. Then the elementary rules are combined using a set covering algorithm to form a composite rule that achieves a perfect fit to the training data. The user has explicit control over a parameter that determines the composite rule's level of redundancy and parsimony. This built-in control, along with the simplicity of interpreting the rules, makes the method particularly useful for classification problems in genomics. We demonstrate the new method using several microarray datasets and examine its generalization performance. We also draw comparisons to other machine-learning strategies such as CART, ID3, and C4.5.

Breast Neoplasms↗

PubMed2002

Analysis of cell-cycle gene expression in Saccharomyces cerevisiae using microarrays and multiple synchronization methods.

Microarray analysis of gene expression during the yeast division cycle has led to the proposal that a significant number of genes in Saccharomyces cerevisiae are expressed in a cell-cycle-specific manner. Four different methods of synchronization were used for cell-cycle analysis. Randomized data exhibit periodic patterns of lesser strength than the experimental data. Thus the cyclicities in the expression measurements in the four experiments presented do not arise from chance fluctuations or noise in the data. However, when the degree of cyclicity for genes in different experiments are compared, a large degree of non-reproducibility is found. Re-examining the phase timing of peak expression, we find that three of the experiments (those using alpha-factor, CDC28 and CDC15 synchronization) show consistent patterns of phasing, but the elutriation synchrony results demonstrate a different pattern from the other arrest-release synchronization methods. Specific genes can show a wide range of cyclical behavior between different experiments; a gene with high cyclicity in one experiment can show essentially no cyclicity in another experiment. The elutriation experiment, possibly being the least perturbing of the four synchronization methods, may give the most accurate characterization of the state of gene expression during the normal, unperturbed cell cycle. Under this alternative explanation, the observed cyclicities in the other three experiments are a stress response to synchronization, and may not reproduce in unperturbed cells.

Cell Cycle↗

PubMed2002

Analysis of cell-cycle-specific gene expression in human cells as determined by microarrays and double-thymidine block synchronization.

Microarray analysis of gene expression patterns for thousands of human genes has led to the proposal that a large number of genes are expressed in a cell-cycle-specific manner. The identification of cyclically expressed genes was based on Affymetrix microarray analysis of gene expression after double-thymidine block synchronization. A statistical reanalysis of the original data leads to three principal findings. (i) Randomized data exhibit periodic patterns of similar or greater strength than the experimental data. This finding suggests that all apparent cyclicities in the expression measurements may arise from chance fluctuations. (ii) The presence of cyclicity and the timing of peak cyclicity in a given gene are not reproduced in two replicate experiments. This fact suggests there is an uncontrolled source of experimental variation that is stronger than the innate variation of gene expression in cells over time. (iii) The amplitude of peak expression in the second cycle is not consistently smaller than the corresponding amplitude in the first cycle. This finding places doubt on the assumption that the cells are actually synchronized. We propose that the microarray results do not support the proposal that there are numerous cell-cycle-specifically expressed genes in human cells.

Cell Cycle↗

PubMedDate not supplied

Chemoinformatic analysis of a supertargeted combinatorial library of styryl molecules.

Styryl dyes are fluorescent, lipophilic cations that have been used as specific labeling probes of mitochondria in living cells. For specific applications such as epifluorescence microscopy or flow cytometry, it is often desirable to synthesize fluorescent derivatives with optimized excitation, emission, and localization properties. Here, we present a chemoinformatic strategy suitable for multiparameter analysis of a combinatorial library of styryl molecules supertargeted to mitochondria. The strategy is based on a simple additive model relating the spectral and subcellular localization characteristics of styryl compounds to the two chemical building blocks that are used to synthesize the molecules. Using a cross-validation approach, the additive model predicts with a high degree of confidence the subcellular localization and spectral properties of the styryl product, from numerical scores that are independently associated with the individual building blocks of the molecule. The fit of the data indicates that more complex, nonadditive interactions between the two building blocks play a minor role in determining the molecule's optical or biological properties. Moreover, the observed additive relationship allows mechanistic inferences to be made regarding the structure-property relationship observed for this particular class of molecules. It points to testable, mechanistic hypotheses about how chemical structure, fluorescence, and localization properties are related.

Journal Article↗

PubMedDate not supplied

System dynamics of subcellular transport.

In pharmacokinetic experiments, interpretations often hinge on treating cells as a "black box": a single, lumped compartment or boundary. Here, a combinatorial library of fluorescent small molecules was used to visualize subcellular transport pathways in living cells, using a kinetic, high content imaging system to monitor spatiotemporal variations of intracellular probe distribution. Most probes accumulate in cytoplasmic vesicles and probe kinetics conform to a nested, two-compartment dynamical system. At steady state, probes preferentially partition from the extracellular medium to the cytosol, and from the cytosol to cytoplasmic vesicles, with hydrophobic molecules favoring sequestration. Altogether, these results point to a general organizing principle underlying the system dynamics of subcellular, small molecule transport. In addition to plasma membrane permeability, subcellular transport phenomena can determine the active concentration of small molecules in the cytosol and the efflux of small molecules from cells. Fundamentally, direct observation of intracellular probe distribution challenges the simple boundary model of classical pharmacokinetics, which considers cells as static permeability barriers.

4-Chloro-7-nitrobenzofurazan↗

PubMedDate not supplied

Exploratory chemoinformatic analysis of cell type-selective anticancer drug targeting.

In pharmaceutical development, structure-activity relationship studies aim to identify characteristics of chemical structures associated with well-defined activity end points. While this goal-driven approach is ideally suited for lead development purposes, a more exploration-driven approach is needed to discover cell type-selective drug targeting mechanisms in complex data sets. Growth inhibition profiles across different cancer cell lines are potentially informative with respect to molecular mechanisms targeting the activity of anticancer agents to specific tumor cells, yet only a small number of mechanistic associations between chemical structure and growth inhibition profiles have been discovered to date. Here, we have applied an exhaustive statistical analysis strategy to more than 10000 compounds in the NCI's anticancer agent database to identify molecular substructures associated with specific cytotoxicity signatures against a panel of human tumor-derived cancer cell lines (the Developmental Therapeutics Program 60-cell line panel). Some of the most significant substructures conferring cell type-selective cytotoxic activity include a large family of delocalized lipophilic cations; chloropurines, chloropyrimidines, and thiazoles; organosulfur chelators and organometallic complexes; and an unexpectedly related family of alkyl-lysophospholipids and phosphate prodrugs. Information from cell-based assays and gene expression measurements have been related to substructures represented in the chemical space covered by the library, yielding several candidate targeting mechanisms.

Antineoplastic Agents↗

PubMedDate not supplied

A cell-based molecular transport simulator for pharmacokinetic prediction and cheminformatic exploration.

In the body, cell monolayers serve as permeability barriers, determining transport of molecules from one organ or tissue compartment to another. After oral drug administration, for example, transport across the epithelial cell monolayer lining the lumen of the intestine determines the fraction of drug in the gut that is absorbed by the body. By modeling passive transcellular transport properties in the presence of an apical to basolateral concentration gradient, we demonstrate how a computational, cell-based molecular transport simulator can be used to define a physicochemical property space occupied by molecules with desirable permeability and intracellular retention characteristics. Considering extracellular domains of cell surface receptors located on the opposite side of a cell monolayer as a drug's desired site of action, simulation of transcellular transport can be used to define the physicochemical properties of molecules with maximal transcellular permeability but minimal intracellular retention. Arguably, these molecules would possess very desirable features: least likely to exhibit nonspecific toxicity, metabolism, and side effects associated with high (undesirable) intracellular accumulation; and most likely to exhibit favorable bioavailability and efficacy associated with maximal rates of transport across cells and minimal intracellular retention, resulting in (desirable) accumulation at the extracellular site of action. Simulated permeability values showed good correlations with PAMPA, Caco-2, and intestinal permeability measurements, without "training" the model and without resorting to statistical regression techniques to "fit" the data. Therefore, cell-based molecular transport simulators could be useful in silico screening tools for chemical genomics and drug discovery.

Biological Availability↗

PubMedDate not supplied

Proteomic analysis of cytokeratin isoforms uncovers association with survival in lung adenocarcinoma.

Cytokeratins (CK) are intermediate filaments whose expression is often altered in epithelial cancer. Systematic identification of lung adenocarcinoma proteins using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry has uncovered numerous CK isoforms. In this study, 93 lung adenocarcinomas (64 stage I and 29 stage III) and 10 uninvolved lung samples were quantitatively examined for protein expression. Fourteen of 21 isoforms of CK 7, 8, 18, and 19 occurred at significantly higher levels (P < .05) in tumors compared to uninvolved adjacent tissue. Specific isoforms of the four types of CK identified correlated with either clinical outcome or individual clinical-pathological parameters. All five of the CK7 isoforms associated with patient survival represented cleavage products. Two of five CK7 isoforms (nos. 2165 and 2091), one of eight CK8 isoforms (no. 439), and one of three CK19 isoforms (no. 1955) were associated with survival and significantly correlated to their mRNA levels, suggesting that transcription underlies overexpression of these CK isoforms. Our data indicate substantial heterogeneity among CK in lung adenocarcinomas resulting from posttranslational modifications, some of which correlated with patient survival and other clinical parameters. Therefore, specific isoforms of individual CK may have utility as diagnostic or predictive markers in lung adenocarcinomas.

Adenocarcinoma↗