Suppression of tumor growth via IGFBP3 depletion as a potential treatment in glioma.

OBJECTIVE: Despite intensive medical treatment, patients with glioblastoma (grade IV glioma [GBM]) have a low 5-year survival rate of 5.5%. In this study, the authors tried to improve currently used therapies by identification of a therapeutic target, IGFBP3, for glioma treatment. METHODS: IGFBP3 RNA expression in 135 patients newly diagnosed with glioma was correlated with clinicopathological factors. Immunohistochemical analysis was performed to determine IGFBP3 protein expression in glioma specimens. The effect of IGFBP3 depletion on cell proliferation was examined using IGFBP3 knockdown glioma cells. Intracranial infusion of IGFBP3 siRNAs was performed to evaluate the effect of IGFBP3 depletion in mouse intracranial xenograft models. RESULTS: We demonstrated higher IGFBP3 expression in GBM than in tumor margin and grade II glioma. IGFBP3 expression was not only positively correlated with tumor grades but also associated with tumor histology and IDH1/2 mutation status. Additionally, higher IGFBP3 expression predicted shorter overall survival in glioma and GBM proneural subgroup patients. In vitro cell culture studies suggested IGFBP3 knockdown suppressed cell proliferation and induced cell cycle G2/M arrest as well as apoptosis in glioma cells. Also, accumulation of DNA double-strand breaks and γH2AX was observed in IGFBP3 knockdown cells. IGFBP3 knockdown delayed in vivo tumor growth in mouse subcutaneous xenograft models. Furthermore, convection-enhanced delivery of IGFBP3 siRNA to mouse brain suppressed intracranial tumor growth and prolonged survival of tumor-bearing mice. CONCLUSIONS: Our findings suggest IGFBP3 predicts poor outcome of glioma patients and is a potential therapeutic target for which depletion of its expression suppresses tumor growth through inducing apoptosis and accumulation of DNA damage in glioma cells.

The skin microbiome of wound scars and unaffected skin in patients with moderate to severe burns in the subacute phase.

Although studies on skin microbiome of acute and chronic wounds abound, evidence on newly built microbial communities of subacute wounds remains scant. To characterize the skin microbiome of recently healed (scarred) burn wounds in relation to unaffected skin surfaces, we collected weekly swabs from patients with moderate to severe burns in the 3rd postburn month for 4 weeks in 2015. We performed skin type (moist, dry, and oily)-matched comparisons within six burn patients (43 pairs of swabs) and with 13 skin-healthy, control patients (22 pairs of samples) using 16S ribosomal RNA gene sequencing results. Results of comparative microbiome analysis showed that, there were no substantial variations in the microbial abundance (all p > 0.05) or composition (all p > 0.01, adjusted for multiple comparisons) between samples obtained from wound scars and those from unaffected surfaces of burn patients. Nor did we find significant temporal dynamics in microbial richness or diversity in burn samples (all p ≥ 0.05). However, samples from burn patients harbored more Firmicutes (median: 25.6%, interquartile range [IQR]: 14.3%-52.8%) than those of control patients (14.9%, IQR: 6.7%-27.0%; p: 0.016), even after adjusting for host age, sex, and skin type-matching (p: 0.026). The number of observed bacterial operational taxonomic units at the genus level was reduced in burn patients (median: 62, IRQ: 32-85) as compared to control patients (median: 128, IQR: 112-136; age-, skin type-adjusted p < 0.01). Meanwhile, estimates of community diversity and evenness for surveyed body sites of burn patients were higher than those of control patients (all adjusted p ≤ 0.05). With a much-reduced bacterial burden and a relative overgrowth of Staphylococcus spp., the skin microbiota of burn patients remained dysbiotic in the subacute phase as compared to that of skin-normal patients.

The rs16906252:C>T SNP is not associated with increased overall survival or temozolomide response in a Han-Chinese glioma cohort.

The methylation status of O-6-methylguanine-DNA methyltransferase (MGMT) is associated with the prognosis in gliomas and in other cancers. Recent studies showed that rs16906252, an SNP in the MGMT promoter, is associated with promoter methylation and is a predictor of the overall survival time (OST) and the response to temozolomide (TMZ) treatment. However, these findings haven't been systematically investigated in the Han-Chinese population. We analyzed the relevance between rs16906252 polymorphisms, the MGMT methylation status, and the OST in 72 Han-Chinese gliomas patients. The MGMT promoter methylation was measured by bisulfite conversion followed by pyro-sequencing, while rs16906252 was measured by restriction endonuclease digestion. Contrary to the previous findings, we found no association between rs16906252 genotypes and promoter methylation on MGMT. The lower-grade glioma (LGGs) patients carrying the C allele with rs16906252 showed a surprisingly better OST (P = 0.04). Furthermore, the LGG patients carrying hypo-methylated MGMT promoter and rs16906252 T allele showed significantly poorer prognosis. The prognostic benefit of MGMT promoter methylation and genotypes on gliomas patients is marginal. A new molecular stratified patient grouping of LGGs is potentially associated with poorer OST. Active MGMT might have a protective role in LGG tumors, enabling evolution to severe malignancy.

RNASEQR--a streamlined and accurate RNA-seq sequence analysis program.

Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.

The largest prospective warfarin-treated cohort supports genetic forecasting.

Genetic variants of cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose, but the effect of other genes has not been fully elucidated. We genotyped 183 polymorphisms in 29 candidate genes in 1496 Swedish patients starting warfarin treatment, and tested for association with response. CYP2C9*2 and *3 explained 12% (P = 6.63 x 10(-34)) of the variation in warfarin dose, while a single VKORC1 SNP explained 30% (P = 9.82 x 10(-100)). No SNP outside the CYP2C gene cluster and VKORC1 regions was significantly associated with dose after correction for multiple testing. During initiation of therapy, homozygosity for CYP2C9 and VKORC1 variant alleles increased the risk of over-anticoagulation, hazard ratios 21.84 (95% CI 9.46; 50.42) and 4.56 (95% CI 2.85; 7.30), respectively. One of 8 patients with CYP2C9*3/*3 (12.5%) experienced severe bleeding during the first month compared with 0.27% of other patients (P = .066). A multiple regression model using the predictors CYP2C9, VKORC1, age, sex, and druginteractions explained 59% of the variance in warfarin dose, and 53% in an independent sample of 181 Swedish individuals. In conclusion, CYP2C9 and VKORC1 significantly influenced warfarin dose and predicted individuals predisposed to unstable anticoagulation. Our results strongly support that initiation of warfarin guided by pharmacogenetics would improve clinical outcome.

Association of warfarin dose with genes involved in its action and metabolism.

We report an extensive study of variability in genes encoding proteins that are believed to be involved in the action and biotransformation of warfarin. Warfarin is a commonly prescribed anticoagulant that is difficult to use because of the wide interindividual variation in dose requirements, the narrow therapeutic range and the risk of serious bleeding. We genotyped 201 patients for polymorphisms in 29 genes in the warfarin interactive pathways and tested them for association with dose requirement. In our study, polymorphisms in or flanking the genes VKORC1, CYP2C9, CYP2C18, CYP2C19, PROC, APOE, EPHX1, CALU, GGCX and ORM1-ORM2 and haplotypes of VKORC1, CYP2C9, CYP2C8, CYP2C19, PROC, F7, GGCX, PROZ, F9, NR1I2 and ORM1-ORM2 were associated with dose (P < 0.05). VKORC1, CYP2C9, CYP2C18 and CYP2C19 were significant after experiment-wise correction for multiple testing (P < 0.000175), however, the association of CYP2C18 and CYP2C19 was fully explained by linkage disequilibrium with CYP2C9*2 and/or *3. PROC and APOE were both significantly associated with dose after correction within each gene. A multiple regression model with VKORC1, CYP2C9, PROC and the non-genetic predictors age, bodyweight, drug interactions and indication for treatment jointly accounted for 62% of variance in warfarin dose. Weaker associations observed for other genes could explain up to approximately 10% additional dose variance, but require testing and validation in an independent and larger data set. Translation of this knowledge into clinical guidelines for warfarin prescription will be likely to have a major impact on the safety and efficacy of warfarin.

Single nucleotide polymorphism mapping using genome-wide unique sequences.

As more and more genomic DNAs are sequenced to characterize human genetic variations, the demand for a very fast and accurate method to genomically position these DNA sequences is high. We have developed a new mapping method that does not require sequence alignment. In this method, we first identified DNA fragments of 15 bp in length that are unique in the human genome and then used them to position single nucleotide polymorphism (SNP) sequences. By use of four desktop personal computers with AMD K7 (1 GHz) processors, our new method mapped more than 1.6 million SNP sequences in 20 hr and achieved a very good agreement with mapping results from alignment-based methods.