We reported that resveratrol decreased DNA methyltransferase (DNMT) 1 and 3b expression in vitro and demethylates tumor suppressor RASSF-1a in women at increased breast cancer risk. We investigated the effects of resveratrol on DNMT and miRNA expression in normal and tumor mammary tissue in a rodent model of estrogen dependent mammary carcinoma. Eighty-nine female ACI rats received estradiol plus: low dose (lo) resveratrol, high dose (hi) resveratrol, 5-aza-2-deoxycytidine (Aza), a known inhibitor of DNMTs, or control (no additional treatment). After 21 wk of treatment, animals were sacrificed and mammary glands harvested. Matched tumor/normal tissues were available from 36 rats. DMNT3b (but not DNMT1) differed in tumor vs. normal tissue after lo (P = .04) and hi (P = .007) resveratrol and Aza treatment. With hi resveratrol, DNMT3b decreased in tumor but increased normal tissue. Hi resveratrol increased miR21, -129, -204, and -489 >twofold in tumor and decreased the same miRs in normal tissue 10-50% compared to control. There was an inverse association between DNMT3b and miR129, -204, and -489 in normal and/or tumor tissue. Treatment with resveratrol differentially influences tumor vs. normal tissue DNMT3b and miRNA expression. This mechanism of action of resveratrol to influence mammary carcinogenesis warrants further investigation.
The fast development of next-generation sequencing technology presents a major computational challenge for data processing and analysis. A fast algorithm, de Bruijn graph has been successfully used for genome DNA de novo assembly; nevertheless, its performance for transcriptome assembly is unclear. In this study, we used both simulated and real RNA-Seq data, from either artificial RNA templates or human transcripts, to evaluate five de novo assemblers, ABySS, Mira, Trinity, Velvet and Oases. Of these assemblers, ABySS, Trinity, Velvet and Oases are all based on de Bruijn graph, and Mira uses an overlap graph algorithm. Various numbers of RNA short reads were selected from the External RNA Control Consortium (ERCC) data and human chromosome 22. A number of statistics were then calculated for the resulting contigs from each assembler. Each experiment was repeated multiple times to obtain the mean statistics and standard error estimate. Trinity had relative good performance for both ERCC and human data, but it may not consistently generate full length transcripts. ABySS was the fastest method but its assembly quality was low. Mira gave a good rate for mapping its contigs onto human chromosome 22, but its computational speed is not satisfactory. Our results suggest that transcript assembly remains a challenge problem for bioinformatics society. Therefore, a novel assembler is in need for assembling transcriptome data generated by next generation sequencing technique.
Cadmium (Cd2+) is a known nephrotoxin causing tubular necrosis during acute exposure and potentially contributing to renal failure in chronic long-term exposure. To investigate changes in global gene expression elicited by cadmium, an in-vitro exposure system was developed from cultures of human renal epithelial cells derived from cortical tissue obtained from nephrectomies. These cultures exhibit many of the qualities of proximal tubule cells. Using these cells, a study was performed to determine the cadmium-induced global gene expression changes after short-term (1 day, 9, 27, and 45 μM) and long-term cadmium exposure (13 days, 4.5, 9, and 27 μM). These studies revealed fundamental differences in the types of genes expressed during each of these time points. The obtained data was further analyzed using regression to identify cadmium toxicity responsive genes. Regression analysis showed 403 genes were induced and 522 genes were repressed by Cd2+ within 1 day, and 366 and 517 genes were induced and repressed, respectively, after 13 days. We developed a gene set enrichment analysis method to identify the cadmium induced pathways that are unique in comparison to traditional approaches. The perturbation of global gene expression by various Cd2+ concentrations and multiple time points enabled us to study the transcriptional dynamics and gene interaction using a mutual information-based network model. The most prominent network module consisted of INHBA, KIF20A, DNAJA4, AKAP12, ZFAND2A, AKR1B10, SCL7A11, and AKR1C1.
Breast cancer that develops during or shortly after pregnancy is frequently more aggressive than cancer diagnosed at other times in a woman's life. To better understand the patterns of cancer-related protein expression in the breasts of lactating women, we determined the differences in total and individual protein expression in milk based on (a) three time points during lactation (early, mid, and late), (b) length of lactation, and (c) parity. Breastmilk was collected from 72 healthy lactating women within 10 days of starting lactation (transitional [T]), 2 months after lactation started, and during breast weaning (W). Sixteen proteins whose expression is altered in breast cancer (11 kallikreins [KLKs], basic fibroblast growth factor [bFGF], YKL-40, neutrophil gelatinase-associated lipocalin, and transforming growth factor [TGF] β1 and β2) were evaluated. The concentration of total milk protein decreased over time (p<0.01 at 2 months and W compared with T). After we controlled for total protein, KLK6 and TGFβ2 significantly increased, and bFGF decreased from T to W. Neither length of nursing nor parity significantly influenced individual protein expression at the W time point. On the other hand, length of nursing did influence the difference in KLK6, -7, and -8 expression between the W and T time points. Total milk protein concentration is lower in the mid and late phases of nursing. Biomarker differences between T and W milk samples in KLK6, TGFβ2, and bFGF are consistent with a protective effect of nursing.
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