Biomedical subjects

Nicholas D Socci

Publications and source records attributed to Nicholas D Socci.

28 records · Page 2Linked to original sources

PubMed2003

Cytokine-induced patterns of gene expression in skeletal muscle tissue.

Tumor necrosis factor alpha (TNF-alpha) and other cytokines induce a state of negative energy balance leading to the breakdown of skeletal muscle. Leptin, another member of the cytokine superfamily, also induces a state of negative energy balance but does not alter lean body mass. The transcription profile of skeletal muscle was compared in animals treated with TNF-alpha or leptin or in animals pair-fed over a 7-day time course using 11,000-gene microarrays (Affymetrix, Santa Clara, CA). Ten clusters of skeletal muscle genes were identified, each of which showed significantly different expression between TNF-alpha treatment and pair feeding. Studies comparing leptin treatment and pair feeding revealed that both activate nearly identical programs of gene expression in skeletal muscle. These data indicate that the effects of leptin on skeletal muscle are markedly different from those of TNF-alpha and that the effects of leptin on skeletal muscle can be largely ascribed to its anorectic effects. Subtle differences between leptin and pair feeding were evident only after 7 days of treatment. In general, pair feeding altered gene expression after the 7-day treatment, whereas leptin did not. The effects of TNF-alpha on skeletal muscle are distinct from those of pair feeding, a result consistent with its known catabolic effects on this tissue. Analyses of the data from food-restricted animals also identified a set of transcriptional changes associated with this state. Further studies of many newly identified leptin-, TNF-alpha-, and starvation-regulated genes and the apparent coordinate regulation of these clusters may reveal important insights into the different effects of cytokines on skeletal muscle.

Animals↗

PubMed2003

A study of accuracy and precision in oligonucleotide arrays: extracting more signal at large concentrations.

MOTIVATION: Despite the success and popularity of oligonucleotide arrays as a high-throughput technique for measuring mRNA expression levels, quantitative calibration studies have until now been limited. The main reason is that suitable data was not available. However, calibration data recently produced by Affymetrix now permits detailed studies of the intensity dependent sensitivity. Given a certain transcript concentration, it is of particular interest to know whether current analysis methods are capable of detecting differential expression ratios of 2 or higher. RESULTS: Using the calibration data, we demonstrate that while current techniques are capable of detecting changes in the low to mid concentration range, the situation is noticeably worse for high concentrations. In this regime, expression changes as large as 4 fold are severely biased, and changes of 2 are often undetectable. Such effects are mainly the consequence of the sequence specific binding properties of probes, and not the result of optical saturation in the fluorescence measurements. GeneChips are manufactured such that each transcript is probed by a set of sequences with a wide affinity range. We show that this property can be used to design a method capable of reducing the high intensity bias. The idea behind our methods is to transfer the weight of a measurement to a subset of probes with optimal linear response at a given concentration, which can be achieved using local embedding techniques. AVAILABILITY: Program source code will be sent electronically upon request.

Algorithms↗

PubMed2003

Gene discovery in bladder cancer progression using cDNA microarrays.

To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression.

Aged↗

PubMed2003

Oncogenic Ras and Akt signaling contribute to glioblastoma formation by differential recruitment of existing mRNAs to polysomes.

In order to determine the global effects of oncogenic Ras and Akt signaling pathways on translational efficiencies, we compared the gene expression profiles of total cellular mRNA and mRNA associated with polysomes. We found that the immediate effect of Ras and Akt signaling blockade on transcription was relatively modest; however, the profile of mRNA associated with polysomes was substantially altered. These observations indicate that the immediate effect of Ras and Akt signaling regulates the recruitment of specific mRNAs to ribosomes to a far greater extent than they regulate the production of mRNAs by transcriptional effects. The mRNAs most affected are those encoding proteins that regulate growth, transcription regulation, cell to cell interactions, and morphology. These data support a model whereby Ras and Akt signaling primarily lead to cellular transformation by altering the transcriptome and producing a radical shift in the composition of mRNAs associated with actively translating polysomes.

Animals↗

PubMed2003

SMASHing regulatory sites in DNA by human-mouse sequence comparisons.

Regulatory sequence elements provide important clues to understanding and predicting gene expression. Although the binding sites for hundreds of transcription factors are known, there has been no systematic attempt to incorporate this information in the annotation of the human genome. Cross species sequence comparisons are critical to a meaningful annotation of regulatory elements since they generally reside in conserved non-coding regions. To take advantage of the recently completed drafts of the mouse and human genomes for annotating transcription factor binding sites, we developed SMASH, a computational pipeline that identifies thousands of orthologous human/ mouse proteins, maps them to genomic sequences, extracts and compares upstream regions and annotates putative regulatory elements in conserved, non-coding, upstream regions. Our current dataset consists of approximately 2,500 human/mouse gene pairs. Transcription start sites were estimated by mapping quasi-full length cDNA sequences. SMASH uses a novel probabilistic method to identify putative conserved binding sites that takes into account the competition between transcription factors for binding DNA. SMASH presents the results via a genome browser web interface which displays the predicted regulatory information together with the current annotations for the human genome. Our results are validated by comparison to previously published experimental data. SMASH results compare favorably to other existing computational approaches.

Algorithms↗

PubMed2002

Molecular profiling of bladder cancer using cDNA microarrays: defining histogenesis and biological phenotypes.

This study was designed to characterize the expression profiles of nine bladder cancer cell lines (T24, J82, 5637, HT1376, RT4, SCaBER, TCCSUP, UMUC-3, and HT1197) using cDNA microarrays (8976 genes and expressed sequence tags). Novel targets involved in bladder cancer progression of potential clinical relevance were validated by immunohistochemistry using tissue microarrays of primary bladder tumors (n = 193 cases). Hierarchical clustering classified uroepithelial cells based on their histopathogenesis and cell cycle alterations. Keratin 10 and caveolin-1 transcripts were more abundant in tumor cells from squamous and invasive origin. Their combined expression was shown to stratify bladder tumors and define squamous differentiation. To assess the robustness of the clustering analysis, a bootstrap resampling technique was used. This grouped tumor cell lines based on their biological properties, including cell cycle and cell adhesion features. E-cadherin, zyxin, and moesin were identified as genes differentially expressed in these clusters and related to the p53, RB, and INK4A status of the cell lines. Loss of these adhesion molecules was associated with stage and grade in primary tumors (P < 0.05), and moesin expression was also associated with survival (P = 0.01). Deregulation of cell cycle and apoptotic pathways, such as mutations or altered expression of p53, pRB, and INK4A (p16), is necessary for uroepithelial transformation. However, it appears that deregulation of cell adhesion is a common event associated with tumor progression in uroepithelial neoplasms.

Biomarkers, Tumor↗

PubMed2002

Role for stearoyl-CoA desaturase-1 in leptin-mediated weight loss.

Leptin elicits a metabolic response that cannot be explained by its anorectic effects alone. To examine the mechanism underlying leptin's metabolic actions, we used transcription profiling to identify leptin-regulated genes in ob/ob liver. Leptin was found to specifically repress RNA levels and enzymatic activity of hepatic stearoyl-CoA desaturase-1 (SCD-1), which catalyzes the biosynthesis of monounsaturated fatty acids. Mice lacking SCD-1 were lean and hypermetabolic. ob/ob mice with mutations in SCD-1 were significantly less obese than ob/ob controls and had markedly increased energy expenditure. ob/ob mice with mutations in SCD-1 had histologically normal livers with significantly reduced triglyceride storage and VLDL (very low density lipoprotein) production. These findings suggest that down-regulation of SCD-1 is an important component of leptin's metabolic actions.

Animals↗

PubMed2002

Specific and nonspecific collapse in protein folding funnels.

Experiments with fast folding proteins are beginning to address the relationship between collapse and folding. We investigate how different scenarios for folding can arise depending on whether the folding and collapse transitions are concurrent or whether a nonspecific collapse precedes folding. Many earlier studies have focused on the limit in which collapse is fast compared to the folding time; in this work we focus on the opposite limit where, at the folding temperature, collapse and folding occur simultaneously. Real proteins exist in both of these limits. The folding mechanism varies substantially in these two regimes. In the regime of concurrent folding and collapse, nonspecific collapse now occurs at a temperature below the folding temperature (but slightly above the glass transition temperature).

Amino Acid Sequence↗

PubMed2002

Gene expression profiling of osteoclast differentiation by combined suppression subtractive hybridization (SSH) and cDNA microarray analysis.

Bone homeostasis is maintained by the balanced action of bone-forming osteoblasts and bone-resorbing osteoclasts. Multinucleated, mature osteoclasts develop from hematopoietic stem cells via the monocyte-macrophage lineage, which also give rise to macrophages and dendritic cells. Despite their distinct physiologic roles in bone and the immune system, these cell types share many molecular and biochemical features. To provide insights into how osteoclasts differentiate and function to control bone metabolism, we employed a systematic approach to profile patterns of osteoclast-specific gene expression by combining suppression subtractive hybridization (SSH) and cDNA microarray analysis. Here we examined how gene expression profiles of mature osteoclast differ from macrophage or dendritic cells, how gene expression profiles change during osteoclast differentiation, and how Mitf, a transcription factor critical for osteoclast maturation, affects the gene expression profile. This approach revealed a set of genes coordinately regulated for osteoclast function, some of which have previously been implicated in several bone diseases in humans.

Animals↗

PubMed2002

The evolution of DNA regulatory regions for proteo-gamma bacteria by interspecies comparisons.

The comparison of homologous noncoding DNA for organisms a suitable evolutionary distance apart is a powerful tool for the identification of cis regulatory elements for transcription and translation and for the study of how they assemble into functional modules. We have fit the three parameters of an affine global probabilistic alignment algorithm to establish the background mutation rate of noncoding sequence between E. coli and a series of gamma proteobacteria ranging from Salmonella to Vibrio. The lower bound we find to the neutral mutation rate is sufficiently high, even for Salmonella, that most of the conservation of noncoding sequence is indicative of selective pressures rather than of insufficient time to evolve. We then use a local version of the alignment algorithm combined with our inferred background mutation rate to assign a significance to the degree of local sequence conservation between orthologous genes, and thereby deduce a probability profile for the upstream regulatory region of all E. coli protein-coding genes. We recover 75%-85% (depending on significance level) of all regulatory sites from a standard compilation for E. coli, and 66%-85% of sigma sites. We also trace the evolution of known regulatory sites and the groups associated with a given transcription factor. Furthermore, we find that approximately one-third of paralogous gene pairs in E. coli have a significant degree of correlation in their regulatory sequence. Finally, we demonstrate an inverse correlation between the rate of evolution of transcription factors and the number of genes they regulate. Our predictions are available at http://www.physics.rockefeller.edu/([tilde-see text])siggia.

Algorithms↗