Systematic analysis of transcribed loci in ENCODE regions using RACE sequencing reveals extensive transcription in the human genome

RACE sequencing of ENCODE regions shows that much of the human genome is represented in poly(A)+ RNA

Activation of Nrf2 by Sulforaphane Inhibits High Glucose-Induced Progression of Pancreatic Cancer via AMPK Dependent Signaling

Background/Aims: Sulforaphane (SFN) is known for its potent bioactive properties, such as anti-inflammatory and anti-tumor effects. However, its anti-tumor effect on pancreatic cancer is still poorly understood. In the present study, we explored the therapeutic potential of SFN for pancreatic cancer and disclosed the underlying mechanism. Methods: Panc-1 and MiaPaca-2 cell lines were used in vitro. The biological function of SFN in pancreatic cancer was measured using EdU staining, colony formation, apoptosis, migration and invasion assays. Reactive oxygen species (ROS) production was measured using 2’-7’-Dichlorofluorescein diacetate (DCF-DA) fluorometric analysis. Western blotting and immunofluorescence were used to measure the protein levels of p-AMPK and epithelial-mesenchymal transition (EMT) pathway-related proteins, and cellular translocation of nuclear factor erythroid 2-related factor 2 (Nrf2). Nude mice and transgenic pancreatic cancer mouse model were used to measure the therapeutic potential of SFN on pancreatic cancer. Results: SFN can inhibit pancreatic cancer cell growth， promote apoptosis, curb colony formation and temper the migratory and invasion ability of pancreatic cancer cells. Mechanistically, excessive ROS production induced by SFN activated AMPK signaling and promoted the translocation of Nrf2, resulting in cell viability inhibition of pancreatic cancer. Pretreatment with compound C, a small molecular inhibitor of AMPK signaling, reversed the subcellular translocation of Nrf2 and rescued cell invasion ability. With nude mice and pancreatic cancer transgenic mouse, we identified SFN could inhibit tumor progression, with smaller tumor size and slower tumor progression in SFN treatment group. Conclusion: Our study not only elucidates the mechanism of SFN-induced inhibition of pancreatic cancer in both normal and high glucose condition, but also testifies the dual-role of ROS in pancreatic cancer progression. Collectively, our research suggests that SFN may serve as a potential therapeutic choice for pancreatic cancer

Hubungan IL-10 Dengan Serum Kreatinin Dan Terjadinya Komplikasi Pada Preeklampsia Perawatan Konservatif

Tujuan: mengetahui hubungan penurunan IL-10 dengan terjadinya peningkatan serum kreatinin (SK) dan terjadinya komplikasi preeklampsia.Bahan dan Metode: penelitian ini merupakan analitik observasional yang dilakukan pada 30 wanita preeklampsia berat tipe dini yang dilakukan perawatan konservatif. Dilakukan pemeriksaan IL-10 pada serum darah dengan metode ELISA sebelum perawatan konservatif dan kemudian dinilai luaran maternal (SK dan komplikasi preeklampsia)Hasil: didapatkan rerata kadar IL-10 pada preeklampsia tipe dini 0,71 ± 0,66 pg/mL, rerata luaran SK 0,83 ± 0,29, terjadinya komplikasi 9 kasus (edema paru, impending eklampsia, sindroma HELLP). Tidak didapatkan hubungan antara IL-10 dengan peningkatan serum kreatinin (p = 0,483) dan komplikasi preeklampsia (p = 0,828).Simpulan: IL-10 bukan merupakan faktor prediktif untuk luaran maternal pada preeklampsia perawatan konservatif

Functional Promoter -31G>C Variant in Survivin Gene Is Associated with Risk and Progression of Renal Cell Cancer in a Chinese Population

BACKGROUND: Survivin is an inhibitor of apoptosis protein and is involved in the occurrence and progression of human malignancies. Recently, a functional polymorphism (-31G>C, rs9904341) in the promoter of survivin has been shown to influence its expression and confer susceptibility to different types of cancer. The present study was aimed to investigate whether the polymorphism also influences susceptibility and progression of renal cell cancer (RCC) in a Chinese population. METHODS: We genotyped this polymorphism using the TaqMan assay in a case-control study comprised of 710 RCC patients and 760 controls. The logistic regression was used to assess the genetic association with occurrence and progression of RCC. RESULTS: Compared with the genotypes containing G allele (GG and GC), we found a statistically significant increased occurrence of RCC associated with the CC genotype [P = 0.006, adjusted odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08-1.76]. The polymorphism was associated with risk of developing advanced stage (OR = 2.02, 95%CI = 1.34-3.07) and moderately differentiated (OR = 1.75; 95%CI = 1.20-2.54) RCC. Furthermore, the patients carrying the CC genotype had a significantly greater prevalence of high clinical stage disease (P(trend) = 0.003). Similar results were also observed when we restricted the analysis to clear cell RCC, a major histological type of RCC. CONCLUSIONS: Our results suggest that the functional -31G>C polymorphism in the promoter of survivin may influence the susceptibility and progression of RCC in the Chinese population. Large population-based prospective studies are required to validate our findings

The DNA Repair Gene APE1 T1349G Polymorphism and Risk of Gastric Cancer in a Chinese Population

Background: Apurinic/apyrimidinic endonuclease 1 (APE1) has a central role in the repair of apurinic apyrimidic sites through both its endonuclease and its phosphodiesterase activities. A common APE1 polymorphism, T1349G (rs3136820), was previously shown to be associated with the risk of cancers. Objective: We hypothesized that the APE1 T1349G polymorphism is also associated with risk of gastric cancer. Methods: In a hospital-based case-control study of 338 case patients with newly diagnosed gastric cancer and 362 cancerfree controls frequency-matched by age and sex, we genotyped the T1349G polymorphism and assessed its associations with risk of gastric cancer. Results: Compared with the APE1 TT genotype, individuals with the variant TG/GG genotypes had a significantly increased risk of gastric cancer (odds ratio = 1.69, 95 % confidence interval = 1.19–2.40), which was more pronounced among subgroups of aged #60 years, male, ever smokers, and ever drinkers. Further analyses revealed that the variant genotypes were associated with an increased risk for diffuse-type, low depth of tumor infiltration (T1 and T2), and lymph node metastasis gastric cancer. Conclusions: The APE1 T1349G polymorphism may be a marker for the development of gastric cancer in the Chinese population. Larger studies are required to validate these findings in diverse populations

A genetic study and meta-analysis of the genetic predisposition of prostate cancer in a Chinese population.

Prostate cancer predisposition has been extensively investigated in European populations, but there have been few studies of other ethnic groups. To investigate prostate cancer susceptibility in the under-investigated Chinese population, we performed single-nucleotide polymorphism (SNP) array analysis on a cohort of Chinese cases and controls and then meta-analysis with data from the existing Chinese prostate cancer genome-wide association study (GWAS). Genotyping 211,155 SNPs in 495 cases and 640 controls of Chinese ancestry identified several new suggestive Chinese prostate cancer predisposition loci. However, none of them reached genome-wide significance level either by meta-analysis or replication study. The meta-analysis with the Chinese GWAS data revealed that four 8q24 loci are the main contributors to Chinese prostate cancer risk and the risk alleles from three of them exist at much higher frequencies in Chinese than European populations. We also found that several predisposition loci reported in Western populations have different effect on Chinese men. Therefore, this first extensive single-nucleotide polymorphism study of Chinese prostate cancer in comparison with European population indicates that four loci on 8q24 contribute to a great risk of prostate cancer in a considerable large proportion of Chinese men. Based on those four loci, the top 10% of the population have six- or two-fold prostate cancer risk compared with men of the bottom 10% or median risk respectively, which may facilitate the design of prostate cancer genetic risk screening and prevention in Chinese men. These findings also provide additional insights into the etiology and pathogenesis of prostate cancer.This work was conducted on behalf of the CHIPGECS and The PRACTICAL consortia (see Supplementary Consortia). We acknowledge the contribution of doctors, nurses and postgraduate research students at the CHIPGENCS sample collecting centers. We thank Orchid and Rosetrees for funding support. This work was also supported by National Natural Science foundation of China for funding support to H Zhang (Grant No: 30671793 and 81072377), N Feng (Grant No: 81272831), X Zhang (Grant No: 30572139, 30872924 and 81072095), S Zhao (Grant No: 81072092 and 81328017), Y Yu (Grant No: 81172448) and Program for New Century Excellent Talents in University from Department of Education of China (NCET-08-0223) and the National High Technology Research and Development Program of China (863 Program 2012AA021101) to X Zhang.This is the final version of the article. It first appeared from Impact Journals via http://dx.doi.org/10.18632/oncotarget.725

Detection of copy number variation from array intensity and sequencing read depth using a stepwise Bayesian model

Abstract Background Copy number variants (CNVs) have been demonstrated to occur at a high frequency and are now widely believed to make a significant contribution to the phenotypic variation in human populations. Array-based comparative genomic hybridization (array-CGH) and newly developed read-depth approach through ultrahigh throughput genomic sequencing both provide rapid, robust, and comprehensive methods to identify CNVs on a whole-genome scale. Results We developed a Bayesian statistical analysis algorithm for the detection of CNVs from both types of genomic data. The algorithm can analyze such data obtained from PCR-based bacterial artificial chromosome arrays, high-density oligonucleotide arrays, and more recently developed high-throughput DNA sequencing. Treating parameters--e.g., the number of CNVs, the position of each CNV, and the data noise level--that define the underlying data generating process as random variables, our approach derives the posterior distribution of the genomic CNV structure given the observed data. Sampling from the posterior distribution using a Markov chain Monte Carlo method, we get not only best estimates for these unknown parameters but also Bayesian credible intervals for the estimates. We illustrate the characteristics of our algorithm by applying it to both synthetic and experimental data sets in comparison to other segmentation algorithms. Conclusions In particular, the synthetic data comparison shows that our method is more sensitive than other approaches at low false positive rates. Furthermore, given its Bayesian origin, our method can also be seen as a technique to refine CNVs identified by fast point-estimate methods and also as a framework to integrate array-CGH and sequencing data with other CNV-related biological knowledge, all through informative priors.</p

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead