Biomedical subjects

Debashis Ghosh

Publications and source records attributed to Debashis Ghosh.

At least 37 records · Page 2Linked to original sources

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↗

PubMed2005

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression.

Molecular profiling of cancer at the transcript level has become routine. Large-scale analysis of proteomic alterations during cancer progression has been a more daunting task. Here, we employed high-throughput immunoblotting in order to interrogate tissue extracts derived from prostate cancer. We identified 64 proteins that were altered in prostate cancer relative to benign prostate and 156 additional proteins that were altered in metastatic disease. An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed, revealing only 48%-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.

Disease Progression↗

PubMed2005

Three-dimensional structures of sulfatases.

The sulfatase family of enzymes catalyzes the hydrolysis of sulfate ester bonds of a wide variety of substrates. Nine human sulfatase proteins and their genes have been identified, many of which are associated with genetic disorders leading to reduction or loss of function of the corresponding enzyme. A catalytic cysteine residue, strictly conserved in prokaryotic and eukaryotic sulfatases, is modified posttranslationally into a formylglycine. Hydroxylation of the formylglycine residue by a water molecule forming the activated hydroxylformylglycine (a formylglycine hydrate or a gem-diol) is a necessary step for sulfatase activity of the enzyme. Crystal structures of three human sulfatases, arylsulfatases A and B (ARSA and ARSB) and C, also known as steroid sulfatase or estrone/dehydroepiandrosterone sulfatase (ES), have been determined. In addition, the crystal structure of a homologous bacterial arylsulfatase from Pseudomonas aeruginosa (PAS) is also available. While ARSA, ARSB, and PAS are water-soluble enzymes, ES has a hydrophobic domain and is presumed to be bound to the endoplasmic reticulum membrane. This chapter compares and contrasts four sulfatase structures and revisits the proposed catalytic mechanism in light of available structural and functional data. Examination of the ES active site reveals substrate-specific interactions previously identified in another steroidogenic enzyme. Possible influence of the lipid bilayer in substrate capture and recognition by ES is described. Finally, mapping the genetic mutations into the ES structure provides an explanation for the loss of enzyme function in X-linked ichthyosis.

Animals↗

PubMed2005

Probabilistic model of the human protein-protein interaction network.

A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans-a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.

Chromosome Mapping↗

PubMed2005

Mining for regulatory programs in the cancer transcriptome.

DNA microarrays have been widely applied to cancer transcriptome analysis. The Oncomine database contains a large collection of such data, as well as hundreds of derived gene-expression signatures. We studied the regulatory mechanisms responsible for gene deregulation in these cancer signatures by searching for the coordinate regulation of genes with common transcription factor binding sites. We found that genes with binding sites for the archetypal cancer transcription factor, E2F, were disproportionately overexpressed in a wide variety of cancers, whereas genes with binding sites for other transcription factors, such as Myc-Max, c-Rel and ATF, were disproportionately overexpressed in specific cancer types. These results suggest that alterations in pathways activating these transcription factors may be responsible for the observed gene deregulation and cancer pathogenesis.

Binding Sites↗

PubMed2005

Alpha-methylacyl-CoA racemase protein expression is associated with the degree of differentiation in breast cancer using quantitative image analysis.

Alpha-methylacyl-CoA racemase (AMACR) is an enzyme involved in the metabolism of fatty acids and is an important tissue biomarker in the prostate to distinguish normal glands from prostate cancer. Here, for the first time, we evaluated the expression of AMACR protein in normal breast, ductal carcinoma in situ, and invasive carcinomas. By immunofluorescence and immunohistochemistry, AMACR was seen in cytoplasmic granules consistent with a mitochondrial and peroxisomal localization. AMACR expression was determined by immunohistochemistry on 160 invasive carcinomas with long follow-up, using a high-density tissue microarray, and evaluated by two methods: standard pathology review and quantitative image analysis. AMACR was overexpressed in 42 of 160 (26%) invasive carcinomas, and it was associated with a decrease in tumor differentiation, a feature of aggressive breast cancer. Quantitative analysis allowed for better discrimination and more accurate evaluation of low-intensity staining. In conclusion, AMACR protein is expressed in normal breast and its expression seems to increase in invasive carcinomas. We observed stronger AMACR protein expression in high-grade carcinomas when compared with low-grade ones. Quantitative image analysis is a novel way to accurately and reproducibly evaluate immunohistochemistry in breast tissue samples using high-density tissue microarrays.

Adult↗

PubMed2005

Decreased alpha-methylacyl CoA racemase expression in localized prostate cancer is associated with an increased rate of biochemical recurrence and cancer-specific death.

Alpha-methylacyl CoA racemase (AMACR) is overexpressed in prostate cancer relative to benign prostatic tissue. AMACR expression is highest in localized prostate cancer and decreases in metastatic prostate cancer. Herein, we explored the use of AMACR as a biomarker for aggressive prostate cancer. AMACR protein expression was determined by immunohistochemistry using an image analysis system on two localized prostate cancer cohorts consisting of 204 men treated by radical prostatectomy and 188 men followed expectantly. The end points for the cohorts were time to prostate-specific antigen (PSA) failure (i.e., elevation >0.2 ng/mL) and time to prostate cancer death in the watchful waiting cohort. Using a regression tree method, optimal AMACR protein expression cut-points were determined to best differentiate prostate cancer outcome in each of the cohorts separately. Cox proportional hazard models were then employed to examine the effect of the AMACR cut-point on prostate cancer outcome, and adjusted for clinical variables. Lower AMACR tissue expression was associated with worse prostate cancer outcome, independent of clinical variables (hazard ratio, 3.7 for PSA failure; P = 0.018; hazard ratio, 4.1 for prostate cancer death, P = 0.0006). Among those with both low AMACR expression and high Gleason score, the risk of prostate cancer death was 18-fold higher (P = 0.006). The AMACR cut-point developed using prostate cancer-specific death as the end point predicted PSA failures independent of Gleason score, PSA, and margin status. This is the first study to show that AMACR expression is significantly associated with prostate cancer progression and suggests that not all surrogate end points may be optimal to define biomarkers of aggressive prostate cancer.

Biomarkers, Tumor↗

PubMed2004

Mutations in X-linked ichthyosis disrupt the active site structure of estrone/DHEA sulfatase.

X-linked ichthyosis is an inherited genetic disorder of the skin that results from steroid sulfatase (STS) deficiency. Seven critical point mutations have been previously reported for the STS gene, six leading to amino acid substitutions and one to a premature termination of the polypeptide chain. The three-dimensional structure of the full-length human enzyme has been recently determined. Amino acid substitutions due to point mutations in X-linked ichthyosis are mapped onto the three-dimensional structure of human STS. In each case, the substitution appears to cause disruption of the active site architecture or to interfere with the enzyme's putative membrane-associating motifs crucial to the integrity of the catalytic cleft, thereby providing an explanation for the loss of STS activity.

Amino Acid Substitution↗

PubMed2004

Androgen-independent prostate cancer is a heterogeneous group of diseases: lessons from a rapid autopsy program.

Understanding the biology of prostate cancer metastasis has been limited by the lack of tissue for study. We studied the clinical data, distribution of prostate cancer involvement, morphology, immunophenotypes, and gene expression from 30 rapid autopsies of men who died of hormone-refractory prostate cancer. A tissue microarray was constructed and quantitatively evaluated for expression of prostate-specific antigen, androgen receptor, chromogranin, synaptophysin, MIB-1, and alpha-methylacylCoA-racemase markers. Hierarchical clustering of 16 rapid autopsy tumor samples was performed to evaluate the cDNA expression pattern associated with the morphology. Comparisons were made between patients as well as within the same patient. Metastatic hormone-refractory prostate cancer has a heterogeneous morphology, immunophenotype, and genotype, demonstrating that "metastatic disease" is a group of diseases even within the same patient. An appreciation of this heterogeneity is critical to evaluating diagnostic and prognostic biomarkers as well as to designing therapeutic targets for advanced disease.

Aged↗

PubMed2004

Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data.

BACKGROUND: An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. RESULTS: By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples) on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. CONCLUSION: The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta-analyze disparate gene expression data for prognostic signatures of potential clinical use.

Bayes Theorem↗

PubMed2004

Functional significance of a natural allelic variant of human carbonyl reductase 3 (CBR3).

Human carbonyl reductase (CBR) activity accounts for a significant fraction of the metabolism of endogenous and xenobiotic carbonyl compounds. It is possible that genetic polymorphisms in CBR1 and CBR3 are key for the wide interindividual variability in the disposition of CBR drug substrates. We pinpointed a single nucleotide polymorphism in CBR3 (CBR3 V244M) that encodes for a V244 to M244 change. Blacks showed a higher frequency of the M244 allele (q = 0.51, n = 49) than did whites (q = 0.31, n = 70; p = 0.003). In addition, DNA variation panels from 10 ethnic groups presented a wide range of CBR3 V244M genotype distributions. Kinetic experiments with the recombinant CBR3 protein variants and menadione revealed that CBR3 M244 has significantly higher V(max) than does CBR3 V244 (V(max) CBR3 M244 = 40.6 +/- 1.3 micromol/min x mg versus V(max) CBR3 V244 = 19.6 +/- 2.0 micromol/min x mg, p = 0.002). In contrast, both isoforms presented similar K(m) values (K(m) CBR3 M244 = 22.9 +/- 2.9 microM versus K(m) CBR3 V244 = 24.6 +/- 3.2 microM, p = 0.43). Assays with NADP(H) demonstrated a higher V(maxNADP(H)) (1.6-fold) and increased catalytic efficiency (V(maxNADP(H))/K(mNADP(H))) for CBR3 M244 compared with CBR3 V244 (p = 0.013). Comparative three-dimensional analyses based on the structure of the homologous porcine carbonyl reductase suggested that the V244M substitution is positioned in a region critical for interactions with the NADP(H) cofactor. These studies demonstrate that the common CBR3 V244M polymorphism encodes for CBR3 isoforms with distinctive enzymatic properties.

Alcohol Oxidoreductases↗

PubMed2004

Covariate adjustment in the analysis of microarray data from clinical studies.

There is tremendous scientific interest in the analysis of gene expression data in clinical settings, such as oncology. In this paper, we describe the importance of adjusting for confounders and other prognostic factors in order to select for differentially expressed genes for follow-up validation studies. We develop two approaches to the analysis of microarray data in non-randomized clinical settings. The first is an extension of the current significance analysis of microarray procedures, where other covariates are taken into account. The second is a novel covariate-adjusted regression modelling based on the receiver operating characteristic (ROC) curve for the analysis of gene expression data. The ideas are illustrated using data from a prostate cancer molecular profiling study.

Gene Expression Profiling↗

PubMed2004

Nonparametric methods for analyzing replication origins in genomewide data.

Due to the advent of high-throughput genomic technology, it has become possible to monitor cellular activities on a genomewide basis. With these new methods, scientists can begin to address important biological questions. One such question involves the identification of replication origins, which are regions in the chromosomes where DNA replication is initiated. One hypothesis is that their locations are nonrandom throughout the genome. In this article, we analyze data from a recent yeast study in which candidate replication origins were profiled using cDNA microarrays to test this hypothesis. We find no evidence for such clustering.

DNA, Complementary↗

PubMed2004

Altered expression of genes of the Bmp/Smad and Wnt/calcium signaling pathways in the cone-only Nrl-/- mouse retina, revealed by gene profiling using custom cDNA microarrays.

Many mammalian retinas are rod-dominant, and hence our knowledge of cone photoreceptor biology is relatively limited. To gain insights into the molecular differences between rods and cones, we compared the gene expression profile of the rod-dominated retina of wild type mouse with that of the cone-only retina of Nrl(-/-) (Neural retina leucine zipper knockout) mouse. Our analysis, using custom microarrays of eye-expressed genes, provided equivalent data using either direct or reference-based experimental designs, confirmed differential expression of rod- and cone-specific genes in the Nrl(-/-) retina and identified novel genes that could serve as candidates for retinopathies or for functional studies. In addition, we detected altered expression of several genes that encode cell signaling or structural proteins. Prompted by these findings, additional real-time PCR analysis revealed that genes belonging to the Bmp/Smad and Wnt/Ca(2+) signaling pathways are expressed in the mature wild type retina and that their expression is significantly altered in the Nrl(-/-) retina. Chromatin immunoprecipitation analysis of adult retina identified Bmp4 and Smad4, which are down-regulated in the Nrl(-/-) retina, as possible direct transcriptional targets of Nrl. Consistent with these studies, Bmp4 and Smad4 are expressed in the mature rod photoreceptors of mouse retina. Modulation of Bmp4 and/or Smad4 by Nrl may provide a mechanism for integrating diverse cell signaling networks in rods. We hypothesize that Bmp/Smad and Wnt/Ca(2+) pathways participate in cell-cell communication in the mature retina, and expression changes observed in the Nrl(-/-) retina reflect their biased utilization in rod versus cone homeostasis.

Animals↗

PubMed2004

Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression.

Many studies have used DNA microarrays to identify the gene expression signatures of human cancer, yet the critical features of these often unmanageably large signatures remain elusive. To address this, we developed a statistical method, comparative metaprofiling, which identifies and assesses the intersection of multiple gene expression signatures from a diverse collection of microarray data sets. We collected and analyzed 40 published cancer microarray data sets, comprising 38 million gene expression measurements from >3,700 cancer samples. From this, we characterized a common transcriptional profile that is universally activated in most cancer types relative to the normal tissues from which they arose, likely reflecting essential transcriptional features of neoplastic transformation. In addition, we characterized a transcriptional profile that is commonly activated in various types of undifferentiated cancer, suggesting common molecular mechanisms by which cancer cells progress and avoid differentiation. Finally, we validated these transcriptional profiles on independent data sets.

Cell Transformation, Neoplastic↗

PubMed2004

Humoral immune response to alpha-methylacyl-CoA racemase and prostate cancer.

BACKGROUND: Although prostate-specific antigen (PSA) is a prototypic biomarker for prostate cancer, it has poor specificity. Expression of alpha-methylacyl-CoA racemase (AMACR), which is involved in the conversion of R-stereoisomers of branched-chain fatty acids to S-stereoisomers, has been shown to be specifically increased in prostate cancer epithelia. However, attempts to detect AMACR in circulation have not been successful. Hence, we determined whether an immune response to AMACR could be used as a serum biomarker for prostate cancer. METHODS: Sera from patients with biopsy-proven prostate cancer and from control subjects were screened for a humoral immune response to selected tumor antigens, including AMACR, by using protein microarrays (46 patients, 28 control subjects). Humoral immune response to AMACR was then validated using high-throughput immunoblot analysis (151 patients, 259 control subjects) and enzyme-linked immunosorbent assay (ELISA) (54 patients, 55 control subjects). Receiver operating characteristic curves were used to determine the sensitivity and specificity of the immune response to AMACR to detect prostate cancer. RESULTS: Immunoreactivity against AMACR was statistically significantly higher in sera from patients with prostate cancer than in control subjects by all three techniques (P(protein microarray) =.009, P(immunoblot)<.001, P(ELISA) =.011). High-throughput immunoblot analysis revealed that, in subjects with intermediate PSA levels (4-10 ng/mL), the immune response against AMACR was more sensitive and specific than was PSA in distinguishing sera from prostate cancer patients relative to control subjects (sensitivity and specificity of 77.8% and 80.6% versus 45.6% and 50%, respectively; area under the curve of 0.789 versus 0.492; P<.001). CONCLUSION: Assays to detect a humoral immune response against AMACR may have the potential to supplement PSA screening in identifying patients with clinically significant prostate cancer, especially those with intermediate PSA levels.

Adult↗

PubMed2004

Meta-analysis of the association between a serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits.

Anxiety-related personality traits, such as NEO neuroticism and TCI/TPQ harm avoidance, have been shown to have significant genetic components. To date, however, no specific genetic variants that contribute to these traits have been conclusively identified. At least 26 studies have investigated a putative association between a functional serotonin transporter promoter polymorphism (5-HTTLPR) and anxiety-related personality traits. The results of these studies have been inconsistent with some studies finding evidence for an association, and others not. We performed a meta-analysis of all applicable studies investigating this association. In the overall analysis (N = 5,629 subjects), we found suggestive evidence for an association between the 5-HTTLPR short allele (s) and increased anxiety-related personality trait scores (P = 0.087). However, we also found strong evidence for heterogeneity. This heterogeneity is largely explained by substantial variation between the studies in the inventory used. When the analysis was stratified by inventory type, there was a significant association between 5-HTTLPR and NEO neuroticism (P = 0.000016), a non-significant association between 5-HTTLPR and TCI/TPQ harm avoidance (P = 0.166), and no association between 5-HTTLPR and other anxiety-related personality traits (P = 0.944). There was no evidence that these results were either due to publication bias or accounted for by any one single study. We conclude that there is a strong association between the serotonin transporter promoter variant and neuroticism as measured in the NEO personality inventory and that non-replications are largely due to small sample size and the use of different inventories.

Adult↗

PubMed2004

Library on a slide for bacterial comparative genomics.

BACKGROUND: We describe a novel application of microarray technology for comparative genomics of bacteria in which libraries of entire genomes rather than the sequence of a single genome or sets of genes are arrayed on the slide and then probed for the presence or absence of specific genes and/or gene alleles. RESULTS: We first adopted a 96-well high throughput working protocol to efficiently isolate high quality genomic DNA. We then optimized conditions to print genomic DNA onto a glass slide with high density (up to 15000 spots) and to sensitively detect gene targets in each genome spot using fluorescently labeled DNA probe. Finally, we created an E. coli reference collection array and probed it for the presence or absence of the hemolysin (hly) gene using a dual channel non-competing hybridization strategy. Results from the array hybridization matched perfectly with previous tests. CONCLUSIONS: This new form of microarray technology, Library on a Slide, is an efficient way for sharing and utilizing large strain collections in comparative genomic analyses.

Bacterial Typing Techniques↗