Pleiotrophin enhances clonal growth and long-term expansion of human embryonic stem cells.

To identify additional growth factors for optimizing propagation of human embryonic stem cells (hESCs), we mined publicly available data sets for the transcriptomes of murine and human ESCs and feeder cells, thereby generating a list of growth factors and complementary receptors. We identified the major pathways previously reported to be important, as well as several new ones. One pathway is the Pleiotrophin (PTN)-Pleiotrophin receptor (PTPRZ1) axis. Murine fibroblasts secrete Ptn, whereas hESCs expressed PTPRZ1, which is downregulated upon differentiation. Depletion of PTPRZ1 resulted in decreased colony formation and lower recovery of hESCs. Supplementation of chemically defined medium for feeder-free propagation of hESCs with PTN allowed higher recovery of hESCs without loss of pluripotency. PTN-PTPRZ1 functions here predominantly via an antiapoptotic effect mediated in part by the activation of Akt. These findings reveal the underlying importance of PTN in hESC survival and its usefulness in the clonal manipulation and large-scale propagation of hESCs. Disclosure of potential conflicts of interest is found at the end of this article.

iHAP--integrated haplotype analysis pipeline for characterizing the haplotype structure of genes.

BACKGROUND: The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations. RESULTS: To facilitate analysis of HapMap data for characterizing the haplotype structure of genes or any chromosomal regions, we have developed an integrated web-based resource, iHAP. In addition to incorporating genotype and haplotype data from the International HapMap Project and gene information from the UCSC Genome Browser Database, iHAP also provides capabilities for inferring haplotype blocks and selecting tag SNPs that are representative of haplotype patterns. These include block partitioning algorithms, block definitions, tag SNP definitions, as well as SNPs to be "force included" as tags. Based on the parameters defined at the input stage, iHAP performs on-the-fly analysis and displays the result graphically as a webpage. To facilitate analysis, intermediate and final result files can be downloaded. CONCLUSION: The iHAP resource, available at http://ihap.bii.a-star.edu.sg, provides a convenient yet flexible approach for the user community to analyze HapMap data and identify candidate targets for genotyping studies.

Meta-analysis of genetic polymorphisms and gastric cancer risk: variability in associations according to race.

The goal of this study was to consolidate information on genetic risk factors for gastric cancer. An additional aim was to investigate the influence of race on these genetic risk associations. Relevant studies were identified from PubMed and references of retrieved articles. Meta-analysis techniques were used to summarise associations between genetic polymorphisms and gastric cancer. A total of 203 relevant studies were identified, assessing 225 polymorphisms across 95 genes. Subgroup analysis indicated that Chinese, Japanese and Korean data were consistent and could be pooled. However, 6 of 13 polymorphisms (ACE I/D, CCND1 870G>A, CDH1 -160C>A, IL1B -511C>T, IL4 -590C>T, IL10 -592A>C) displayed conflicting effects between Asian and Caucasian populations, three of which (ACE I/D, CCND1 870G>A, IL1B -511C>T) had significantly different odds ratios between the two racial groups. In total, 37 polymorphisms across 27 genes were found to be significantly associated with gastric cancer in Asians, and 12 polymorphisms across 11 genes in Caucasians. Consolidated panels of polymorphisms associated with gastric cancer risk were identified in Asians and Caucasians. The results caution against the assumption that genetic risk factors are consistent between races.

Gastric Cancer (Biomarkers) Knowledgebase (GCBKB): A Curated and Fully Integrated Knowledgebase of Putative Biomarkers Related to Gastric Cancer.

The Gastric Cancer (Biomarkers) Knowledgebase (GCBKB) (http://biomarkers.bii.a-star.edu.sg/background/gastricCancerBiomarkersKb.php) is a curated and fully integrated knowledgebase that provides data relating to putative biomarkers that may be used in the diagnosis and prognosis of gastric cancer. It is freely available to all users. The data contained in the knowledgebase was derived from a large literature source and the putative biomarkers therein have been annotated with data from the public domain. The knowledgebase is maintained by a curation team who update the data from a defined source. As well as mining data from the literature, the knowledgebase will also be populated with unpublished experimental data from investigators working in the gastric cancer biomarker discovery field. Users can perform searches to identify potential markers defined by experiment type, tissue type and disease state. Search results may be saved, manipulated and retrieved at a later date. As far as the authors are aware this is the first open access database dedicated to the discovery and investigation of gastric cancer biomarkers.