Polycomb CBX7 Directly Controls Trimethylation of Histone H3 at Lysine 9 at the p16 Locus

BACKGROUND: H3K9 trimethylation (H3K9me3) and binding of PcG repressor complex-1 (PRC1) may play crucial roles in the epigenetic silencing of the p16 gene. However, the mechanism of the initiation of this trimethylation is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we found that upregulating the expression of PRC1 component Cbx7 in gastric cancer cell lines MGC803 and BGC823 led to significantly suppress the expression of genes within the p16-Arf-p15 locus. H3K9me3 formation was observed at the p16 promoter and Regulatory Domain (RD). CBX7 and SUV39H2 binding to these regions were also detectable in the CBX7-stably upregulated cells. CBX7-SUV39H2 complexes were observed within nucleus in bimolecular fluorescence complementation assay (BiFC). Mutations of the chromodomain or deletion of Pc-box abolished the CBX7-binding and H3K9me3 formation, and thus partially repressed the function of CBX7. SiRNA-knockdown of Suv39h2 blocked the repressive effect of CBX7 on p16 transcription. Moreover, we found that expression of CBX7 in gastric carcinoma tissues with p16 methylation was significantly lower than that in their corresponding normal tissues, which showed a negative correlation with transcription of p16 in gastric mucosa. CONCLUSION/SIGNIFICANCE: These results demonstrated for the first time, to our knowledge, that CBX7 could initiate H3K9me3 formation at the p16 promoter

The chaos in calibrating crop models

Calibration, the estimation of model parameters based on fitting the model to experimental data, is among the first steps in many applications of system models and has an important impact on simulated values. Here we propose and illustrate a novel method of developing guidelines for calibration of system models. Our example is calibration of the phenology component of crop models. The approach is based on a multi-model study, where all teams are provided with the same data and asked to return simulations for the same conditions. All teams are asked to document in detail their calibration approach, including choices with respect to criteria for best parameters, choice of parameters to estimate and software. Based on an analysis of the advantages and disadvantages of the various choices, we propose calibration recommendations that cover a comprehensive list of decisions and that are based on actual practices.HighlightsWe propose a new approach to deriving calibration recommendations for system modelsApproach is based on analyzing calibration in multi-model simulation exercisesResulting recommendations are holistic and anchored in actual practiceWe apply the approach to calibration of crop models used to simulate phenologyRecommendations concern: objective function, parameters to estimate, software usedCompeting Interest StatementThe authors have declared no competing interest

Hypermethylation of metallothionein-3 CpG island in gastric carcinoma

The expression of metallothionein (MT)-3 is often markedly reduced in gastric carcinoma (GC). The molecular mechanism of this MT-3 downregulation is unknown. Transcriptional silencing of MT-3 by methylation of CpG island was investigated by nucleotide sequencing and denaturing high performance liquid chromatography (DHPLC) analyses. We found that normal brain tissue and a xenografted GC that expressed MT-3 mRNA had unmethylated regions of the CpG island in intron1 of this gene. On the other hand, gastric cancer cell lines AGS and MKN445, a xenografted GC, and a representative primary gastric cancer that had no expression of MT-3 mRNA demonstrated hypermethylation of the MT-3 intron1 CpG island. Treatment of the gastric cancer cell lines with 5-azacytidine resulted in new expression of MT-3 mRNA in these cells. A quantifying DHPLC assay was developed to determine the methylation status of this specific region of the MT-3 gene. Fifty-eight primary GC and their corresponding normal gastric epithelial tissues, and 34 normal gastric mucosa were analyzed for MT-3 methylation by DHPLC in the region of methylation abnormalities initially identified. Our DHPLC analyses of the methylated MT-3 product demonstrated that the primary gastric cancers have an average methylation percentage of 6.3% per tumor compared with 2.4% in normal gastric tissues (P < 0.05). The MT-3 was not methylated in all of eight P53-positive GCs and hypermethylated in eight of 13 P53-negative cases by immunohistochemistry staining (P = 0.007). In conclusion, the CpG island in the MT-3 intron1 are abnormally hypermethylated in many gastric carcinomas and may account for the downregulation of MT-3 in gastric carcinogenesis

Critical evaluation of Cbx7 downregulation in primary colon carcinomas and its clinical significance in Chinese patients

Background: CBX7 is a Polycomb group protein that shows variable expression changes in various cancers that are often contradictive. A mouse knockout experiment has validated the tumor suppressor role in carcinogenesis. The purpose of this study is to verify the tumor suppressor role of Cbx7 in human colon carcinomas (CC). Methods: Frozen CC and the surgical margin (SM) tissue samples from patients (n = 97) were obtained from the Peking University Cancer Hospital. All patients had follow-up data for at least three years. The level of Cbx7 mRNA and protein was determined by quantitative RT-PCR, immunohistochemistry and Western blot, respectively. The association between Cbx7 mRNA level and clinicopathological characteristics of CC patients was then statistically analyzed. Results: CBX7 expression changes detected through immunohistochemistry and Western blot in 10 pairs of representative CC samples significantly correlated with their corresponding mRNA levels when Alu, but not GAPDH, was used as the endogenous reference control in quantitative RT-PCR. The Alu-normalized Cbx7 mRNA levels were significantly increased in SM tissues when compared with CC tissues or colon biopsies taken from non-cancer patients (Student&apos;s t-test, P &lt; 0.036 or 0.007). Furthermore, decreased levels of Cbx7 mRNA positively correlated with lymph metastasis (P = 0.029). Overall survival (OS) of CC patients classified as Cbx7 expression-low was considerably shorter than those classified as Cbx7 expression-high (Hazard ratio = 2.97, 95% CI [1.68 similar to 5.25]; P &lt; 0.001). Multiple variant analyses showed that the Cbx7 expression-low was an independent predictor of short OS (Hazard ratio = 3.16, 95% CI [1.58-6.30]; P &lt; 0.001). Conclusion: Cbx7 is downregulated in CCs, and Cbx7 expression-low tumors correlated with lymph metastasis and poor overall survival of CC patients.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000351260200001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701OncologySCI(E)[email protected]

Multi-model evaluation of phenology prediction for wheat in Australia

Predicting wheat phenology is important for cultivar selection, for effective crop management and provides a baseline for evaluating the effects of global change. Evaluating how well crop phenology can be predicted is therefore of major interest. Twenty-eight wheat modeling groups participated in this evaluation. Our target population was wheat fields in the major wheat growing regions of Australia under current climatic conditions and with current local management practices. The environments used for calibration and for evaluation were both sampled from this same target population. The calibration and evaluation environments had neither sites nor years in common, so this is a rigorous evaluation of the ability of modeling groups to predict phenology for new sites and weather conditions. Mean absolute error (MAE) for the evaluation environments, averaged over predictions of three phenological stages and over modeling groups, was 9 days, with a range from 6 to 20 days. Predictions using the multi-modeling group mean and median had prediction errors nearly as small as the best modeling group. About two thirds of the modeling groups performed better than a simple but relevant benchmark, which predicts phenology by assuming a constant temperature sum for each development stage. The added complexity of crop models beyond just the effect of temperature was thus justified in most cases. There was substantial variability between modeling groups using the same model structure, which implies that model improvement could be achieved not only by improving model structure, but also by improving parameter values, and in particular by improving calibration techniques.Peer reviewe