Role of insulin and IGF1 receptors in proliferation of cultured renal proximal tubule cells

We have used a murine proximal tubule cell line (MCT cells) to determine the presence and binding characteristics of insulin and IGF1 receptors and to correlate these parameters with the concentration-response relationships for ligand-induced cellular proliferation. Separate insulin and IGF1 receptors were identified by equilibrium binding assays. Half-maximal displacement of either peptide occurred at 3-10 nM; crossover binding to the alternate receptor occurred with a 10- to 100-fold lower affinity. Peptide effects on cellular proliferation were determined by measuring [3H]thymidine incorporation. Both insulin and IGF1 stimulate thymidine incorporation in a dose-dependent manner with similar increases above the basal level. The estimated half-maximal stimulation (EC50) occurred at 4 nM for IGF1 and 8 nM for insulin. A comparison of the receptor binding affinities with the dose-response relationships for [3H]thymidine incorporation reveals that each growth factor appears to be exerting its effect via binding to its own receptor. Therefore, in this cell line, physiologic concentrations of either insulin or IGF1 can modulate cellular growth. To our knowledge this is the first demonstration of a mitogenic effect which may be modulated by ligand binding to the insulin receptor in proximal tubule epithelia

p21-activated kinase 1: PAK'ed with potential

The p21-activated kinases (PAKs) are central players in growth factor signaling networks and morphogenetic processes that control proliferation, cell polarity, invasion and actin cytoskeleton organization. This raises the possibility that interfering with PAK activity may produce significant anti-tumor activity. In this perspective, we summarize recent data concerning the contribution of the PAK family member, PAK1, in growth factor signaling and tumorigenesis. We further discuss mechanisms by which inhibition of PAK1 can arrest tumor growth and promote cell apoptosis, and the types of cancers in which PAK1 inhibition may hold promise

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

High-resolution analysis of copy number alterations and associated expression changes in ovarian tumors

<p>Abstract</p> <p>Background</p> <p>DNA copy number alterations are frequently observed in ovarian cancer, but it remains a challenge to identify the most relevant alterations and the specific causal genes in those regions.</p> <p>Methods</p> <p>We obtained high-resolution 500K SNP array data for 52 ovarian tumors and identified the most statistically significant minimal genomic regions with the most prevalent and highest-level copy number alterations (recurrent CNAs). Within a region of recurrent CNA, comparison of expression levels in tumors with a given CNA to tumors lacking that CNA and to whole normal ovary samples was used to select genes with CNA-specific expression patterns. A public expression array data set of laser capture micro-dissected (LCM) non-malignant fallopian tube epithelia and LCM ovarian serous adenocarcinoma was used to evaluate the effect of cell-type mixture biases.</p> <p>Results</p> <p>Fourteen recurrent deletions were detected on chromosomes 4, 6, 9, 12, 13, 15, 16, 17, 18, 22 and most prevalently on X and 8. Copy number and expression data suggest several apoptosis mediators as candidate drivers of the 8p deletions. Sixteen recurrent gains were identified on chromosomes 1, 2, 3, 5, 8, 10, 12, 15, 17, 19, and 20, with the most prevalent gains localized to 8q and 3q. Within the 8q amplicon, <it>PVT1</it>, but not <it>MYC</it>, was strongly over-expressed relative to tumors lacking this CNA and showed over-expression relative to normal ovary. Likewise, the cell polarity regulators <it>PRKCI </it>and <it>ECT2 </it>were identified as putative drivers of two distinct amplicons on 3q. Co-occurrence analyses suggested potential synergistic or antagonistic relationships between recurrent CNAs. Genes within regions of recurrent CNA showed an enrichment of Cancer Census genes, particularly when filtered for CNA-specific expression.</p> <p>Conclusion</p> <p>These analyses provide detailed views of ovarian cancer genomic changes and highlight the benefits of using multiple reference sample types for the evaluation of CNA-specific expression changes.</p

Fast index based algorithms and software for matching position specific scoring matrices

BACKGROUND: In biological sequence analysis, position specific scoring matrices (PSSMs) are widely used to represent sequence motifs in nucleotide as well as amino acid sequences. Searching with PSSMs in complete genomes or large sequence databases is a common, but computationally expensive task. RESULTS: We present a new non-heuristic algorithm, called ESAsearch, to efficiently find matches of PSSMs in large databases. Our approach preprocesses the search space, e.g., a complete genome or a set of protein sequences, and builds an enhanced suffix array that is stored on file. This allows the searching of a database with a PSSM in sublinear expected time. Since ESAsearch benefits from small alphabets, we present a variant operating on sequences recoded according to a reduced alphabet. We also address the problem of non-comparable PSSM-scores by developing a method which allows the efficient computation of a matrix similarity threshold for a PSSM, given an E-value or a p-value. Our method is based on dynamic programming and, in contrast to other methods, it employs lazy evaluation of the dynamic programming matrix. We evaluated algorithm ESAsearch with nucleotide PSSMs and with amino acid PSSMs. Compared to the best previous methods, ESAsearch shows speedups of a factor between 17 and 275 for nucleotide PSSMs, and speedups up to factor 1.8 for amino acid PSSMs. Comparisons with the most widely used programs even show speedups by a factor of at least 3.8. Alphabet reduction yields an additional speedup factor of 2 on amino acid sequences compared to results achieved with the 20 symbol standard alphabet. The lazy evaluation method is also much faster than previous methods, with speedups of a factor between 3 and 330. CONCLUSION: Our analysis of ESAsearch reveals sublinear runtime in the expected case, and linear runtime in the worst case for sequences not shorter than | [Formula: see text] |(m )+ m - 1, where m is the length of the PSSM and [Formula: see text] a finite alphabet. In practice, ESAsearch shows superior performance over the most widely used programs, especially for DNA sequences. The new algorithm for accurate on-the-fly calculations of thresholds has the potential to replace formerly used approximation approaches. Beyond the algorithmic contributions, we provide a robust, well documented, and easy to use software package, implementing the ideas and algorithms presented in this manuscript

Identification of Networks of Co-Occurring, Tumor-Related DNA Copy Number Changes Using a Genome-Wide Scoring Approach

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

<p>Abstract</p> <p>Background</p> <p>Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer.</p> <p>Results</p> <p>To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage.</p> <p>Conclusions</p> <p>We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.</p

Identification of Candidate Growth Promoting Genes in Ovarian Cancer through Integrated Copy Number and Expression Analysis

Ovarian cancer is a disease characterised by complex genomic rearrangements but the majority of the genes that are the target of these alterations remain unidentified. Cataloguing these target genes will provide useful insights into the disease etiology and may provide an opportunity to develop novel diagnostic and therapeutic interventions. High resolution genome wide copy number and matching expression data from 68 primary epithelial ovarian carcinomas of various histotypes was integrated to identify genes in regions of most frequent amplification with the strongest correlation with expression and copy number. Regions on chromosomes 3, 7, 8, and 20 were most frequently increased in copy number (>40% of samples). Within these regions, 703/1370 (51%) unique gene expression probesets were differentially expressed when samples with gain were compared to samples without gain. 30% of these differentially expressed probesets also showed a strong positive correlation (r≥0.6) between expression and copy number. We also identified 21 regions of high amplitude copy number gain, in which 32 known protein coding genes showed a strong positive correlation between expression and copy number. Overall, our data validates previously known ovarian cancer genes, such as ERBB2, and also identified novel potential drivers such as MYNN, PUF60 and TPX2

A polymeric nanomedicine diminishes inflammatory events in renal tubular cells

The polyglutamic acid/peptoid 1 (QM56) nanoconjugate inhibits apoptosis by interfering with Apaf-1 binding to procaspase-9. We now describe anti-inflammatory properties of QM56 in mouse kidney and renal cell models. In cultured murine tubular cells, QM56 inhibited the inflammatory response to Tweak, a non-apoptotic stimulus. Tweak induced MCP-1 and Rantes synthesis through JAK2 kinase and NF-kB activation. Similar to JAK2 kinase inhibitors, QM56 inhibited Tweak-induced NF-kB transcriptional activity and chemokine expression, despite failing to inhibit NF-kB-p65 nuclear translocation and NF-kB DNA binding. QM56 prevented JAK2 activation and NF-kB-p65(Ser536) phosphorylation. The anti-inflammatory effect and JAK2 inhibition by QM56 were observed in Apaf-12/2 cells. In murine acute kidney injury, QM56 decreased tubular cell apoptosis and kidney inflammation as measured by downmodulations of MCP-1 and Rantes mRNA expression, immune cell infiltration and activation of the JAK2-dependent inflammatory pathway. In conclusion, QM56 has an anti-inflammatory activity which is independent from its role as inhibitor of Apaf-1 and apoptosis and may have potential therapeutic relevance.This work was supported by grants from the Instituto de Salud Carlos III (www.isciii.es), FIS: PI07/0020, CP08/1083, PS09/00447 and ISCIII-RETICS REDINREN RD 06/0016; Sociedad Española de Nefrología (www.senefro.org). Álvaro Ucero, Sergio Berzal and Carlos Ocaña supported by Fundacion Conchita Rabago (www.fundacionconchitarabago.net), Alberto Ortiz by the Programa de Intensificación de la Actividad Investigadora in the Sistema Nacional de Salud of the Instituto de Salud Carlos III and the Agencia ‘‘Pedro Lain Entralgo’’ of the Comunidad de Madrid and CIFRA S-BIO 0283/2006 www.madrid.org/lainentralgo) and Adrián Ramos, by FIS (Programa Miguel Servet)