Category: clinically Small Molecule

This strongly suggests the existence of variant influencing the variability of DNA Epoxomicin methylation levels at the SLC19A2 gene. How the rs970740 T/C genetic variation affects SLC19A2 DNA methylation remains an open question. This could be through the creation of a transcription factor binding site, the modification of the local CpG sites distribution, or more complex phenomena. The SLC19A2 gene codes for a thiamine transporter protein that has been associated with human anemia syndrome. Our results suggest that genetically determined DNA methylation sensitive mechanisms are involved in this disease susceptibility. Several conclusions could be drawn from this work. First, three identified CpG sites were found to be strongly associated with the plasma variability of two quantitative biomarkers of the coagulation cascade, supporting the potential of genome-wide DNA methylation data to identify epigenetic marks associated with biological phenotypes involved in thrombotic disorders. Nonetheless, this works highlights the need for careful analyses of associations between genetic variants, biological phenotypes, and methylation at CpG sites to avoid false inference on functional variant, in particular due to LD extending over large genomic distances. Integrating MWAS, GWAS and biological data from the same individuals, as illustrated here, is key to elucidating these relationships. Second, if such cautions are taken, DNA methylation data can help to dissect the functional mechanisms associated with known disease-causing SNPs. Several limitations must be acknowledged. First, the design of our study may not be optimal. As we did not have access to a casecontrol study for VT with genome-wide DNA methylation data, we adopted a ‘case-only’ approach for our discovery stage. Such approach has been shown to be a valid alternative to detect gene6 environment or gene 6 gene interactions. We here used this strategy with the aim of identifying epigenetic factors that interact with the FV Leiden mutation to modulate the risk of VT. Since, in our replication study, 45 carriers were VT patients and the remaining 8 carriers were healthy individuals, we also looked into this dataset for specific methylation patterns associated with VT but the low sample size precludes from identifying any significant association. Second, because homozygosity for FV Leiden mutation was an exclusion criteria for the MARTHA study and no homozygote was observed in the F5L-families, our analysis only included heterozygous carriers which may have reduced our power to identify CpG sites under the strong influence of the mutation. Third, while extremely dense, the used Illumina array does not cover all sites of the genome that could be subject to DNA methylation, we cannot exclude that some relevant methylation association has been missed. Fourth, the sample size of our discovery study was large enough to detect, at the genome-wide level of 1.29 1027, a 0.05 increase in the methylation b-value. Whether an increase of smaller magnitude in DNA methylation marks detected in whole blood could be biologically relevant remains an open question. Whole blood DNA methylation levels reflect the average levels resulting from the epigenetic state.
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The analysis of BORIS expression demonstrated that we successfully enriched the cell population that expressed BORIS mRNA. In our experiments we used NCCIT cell line, classified as germ-cell tumor or GSK2118436 embryonic cancer cells. Due to its higher BORIS expression compared to the other tumor cell lines, the NCCIT cell line provides a good model for our studies, especially for the feasibility of isolation of BORIS positive cells by MB technology. In normal human cells, telomerase is generally absent in somatic cells but remains active in germ cells, progenitor cells and some adult stem cells. It has been shown that telomerase is reactivated in a majority of tumors and in clinical studies its reactivation is associated with poor outcomes of different tumors. In addition, current literature supports the evidence that CSCs express telomerase and its inhibition suppresses the self-renewal of CSCs. All these discoveries, together with our observations, indicate that BORIS could play an important and direct role in tumor malignancies by up-regulation of the hTERT telomerase gene. Consistent with this, we notably observed that the BORIS-positive/hTERT-high isolated cells expressed also high levels of the most important stem cell markers. The embryonic carcinoma cells that we investigated, indeed, provide a good model system to study the stem cell concept of cancer. They are stem cells derived from a teratocarcinoma and are also the malignant transformed embryonic stem cells. They show gene expression profiles close to those of human embryonic stem cells. Therefore, we analyzed the association of BORIS-positive/hTERT-high cells with the expression of the key-regulator genes of embryonic cells and with some of the most known specific markers of CSCs. CSCs are cancer cells characterized by stem cell properties and represent a small population of tumor cells that drives tumor development, progression, metastasis and drug resistance. Interestingly, a correlation of the isolated BORISpositive/hTERT-high cells with high expression of stem cell markers was observed. These findings were confirmed by BORIS silencing studies. Stable BORIS knockdown NCCIT-derived cells were generated by an efficient system of inducible-shRNA lentivirus. After BORIS silencing, a significant decrease of hTERT expression was observed, as well as a down-regulation of telomerase activity, which is strictly regulated by hTERT gene transcription. CTCF expression was also decreased. This is consistent with our previous results and confirms a role of BORIS in the transcriptional regulation of CTCF. This correlation between CTCF and BORIS was not observed in the expression analysis of the isolated BORIS-positive cells. This discrepancy could be due to the different experimental conditions. Indeed, in the expression analysis of the isolated BORIS-positive cells, CTCF was analyzed at steady state, while in BORIS silencing studies what we observed is the result of cellular and genetic modifications. Importantly, after BORIS knockdown a decrease of expression of stem cell and CSC marker genes was also observed. These results highlight the importance of BORIS in malignant disease and its possible critical role on cancer growth and progression.

If cancer drugs behave as classifiers for colon cancers, they will likely behave as classifiers in other organs. Analyzing cells originating from different tissues is therefore not likely to affect the principle of this study. Another limitation of this study is that we VE-821 1232410-49-9 measured markers in different tissue contexts. Unlike the Quake dataset, the Gray dataset measured expression of cultured cell lines rather than expression levels in primary single cells. Additionally, because this dataset did not include healthy cells, we had to demonstrate our approach by targeting one subtype of breast cancer versus another, rather than cancerous versus healthy cells. More rigorous analyses based upon treatment of single-cell or minimally amplified clones as well as relevant classification analyses will have to wait for more extensive experimental data to become available. An important question that this study highlights is whether experiments with tumor cell populations capture as much relevant information as experiments with individual cells. Cell line gene expression levels reflect a population average rather than the expression of individual cells. It is possible that small numbers of drug-resistant cells with distinct marker profiles may not be detectable when the whole tumor cell population is analyzed together. For example, small populations of cells within a tumor have been shown to drive the evolution and drug resistance of some types of cancer. But although single cell data is preferable, it presents challenges of its own. Even genetically identical single cells can differ phenotypically in a number of ways including epigenetic state, protein and gene expression and morphologic state, and these states can change with time. Thus, nongenetic heterogeneity across single cells may complicate classification analyses. These factors underscore the need to measure a diverse set of markers from single cells in order to target cancer effectively. Our statistical analyses have some similarity to other cancer studies that used statistical approaches in conjunction with large datasets. The Friend group, for example, used machine learning to predict prognosis and phenotypes in breast cancer. This resembles our strategy in that they use gene expression to make predictions about cancer. Other groups have used machine learning to distinguish between sub-types of cancer. They typically combine microarray data with such algorithms to distinguish between types of cancer. This resembles our strategy to optimally discriminate between cancer sub-types. The Golub group used machine learning to classify cell lines as belonging to a drug-resistant or drug-sensitive class based upon gene expression whereas the Gray group related certain signaling networks to drug response. More recently, a large consortium predicted cancer drug sensitivity using gene expression. These studies have a similar goal of modeling drug responses.

GLPG0187 is currently in phase Ib clinical trial for patients with a variety of solid tumors. The effect of blocking integrin receptors by GLPG0187 were similar to effects of knockdown of ITGAV in prostate cancer cells. These data indicate that ITGAV is functionally involved in the migratory, mesenchymal cellular phenotype of prostate cancer cells. Moreover, ITGAV is important for the acquisition of prostate cancer cells with a metastasis-initiating capacity. Inhibition of av integrin might also have therapeutic potential in bladder cancer, since ITGAV is significantly overexpressed in bladder tumors compared to normal urothelium and a trend is observed of stage and grade-dependent increase in ITGAV expression. In the present study we determined the effect of functional inactivation of ITGAV on migration, EMT and stemness in bladder cancer using the human bladder carcinoma cell line UM-UC-3 and the human papilloma cell line RT-4. Functional inactivation of ITGAV in bladder cancer leads to a less malignant phenotype as illustrated by significantly impaired migration, EMT response, clonogenicity and a reduction in the size of the stem/progenitor pool. In line with these in vitro observations, knockdown of ITGAV or LY2109761 TGF-beta inhibitor treatment with GLPG0187 significantly inhibited metastasis and secondary tumor growth. These data indicate that ITGAV inhibition represents a novel, promising strategy for the prevention and/or treatment of bladder cancer growth and metastasis. Low survival rates of metastatic bladder cancer emphasize the need for a drug that can prevent and/or treat metastatic cancer. A promising approach that has been explored for these means in breast, melanoma and prostate cancer is the targeting of av integrins, which has been shown to reduce tumor growth, metastasis and angiogenesis. In this study, the role of ITGAV, which are highly expressed in bladder carcinomas, and its potential as a drug target in bladder cancer were investigated both by treatment with the ITGAV integrin-inhibitor GLPG0187 and knockdown of ITGAV. RT-4 and UM-UC-3luc2 cells were investigated to determine whether av integrin targeted therapies could be beneficial for these different grades of bladder tumors. The rationale for targeting of ITGAV is their involvement in cell proliferation, migration, invasion, survival and angiogenesis, which are essential processes for primary tumor growth and metastasis formation. These processes are induced via activation of focal adhesion kinase and srcfamily kinases, that activate the ERK/MAPK, NF-kB and AKT/PKB pathways. Modulating adherence to the extracellular matrix by changing the affinity of integrins for their ECM ligands, is important for the motility of cancer cells. Both GLPG0187 treatment and knockdown of ITGAV resulted in loss of adhesion, resembling loss of adherence to the ECM, which might have an inhibitory effect on cell motility and migration.

Accumulating evidence suggests that cholesterol and cholesterol related proteins are involved in the pathogenesis of AD in humans and AD mouse models. Although the LDLR has been shown to have a major role in cholesterol and ApoE homeostasis in the periphery its role in the CNS remains unclear. Some LDLR polymorphisms showed a sex-dependent increased risk for developing AD in humans. In LDLR deficient mice, lack of LDLR increases brain ApoE but has no effect on hippocampal or CSF cholesterol. A number of studies using AD mice have provided evidence that the family of proteins involved in cholesterol metabolism as the ABCA1, the ApoA1, the SR-BI and the LDLR are involved in the pathogenesis of the AD-like phenotype in the mouse brain. Previous studies using different AD mouse models that were LDLR deficient resulted in conflicting data on the effect of LDLR deficiency on the amyloid related phenotype of the mice. Lack of LDLR had no effect on amyloid deposition in the brain in a study using a huAPP transgenic mouse while an analogous study using another huAPP transgenic mouse showed a significant increase in amyloid deposition. A recent study where LDLR was overexpressed in the brains of APP transgenic mice resulted in a significant decrease of amyloid plaque formation, thus establishing an important role for LDLR in the amyloid related pathology in the mouse brain. ApoE is a major risk factor in the pathogenesis of AD in the human population. We speculate that the type and position of the alteration may not noticeably interfere with the kinase domain structure. Alternatively, this polymorphism may be balanced by second-site mutations. For example, an altered site may have a biologically relevant negative effect on SUB conformation. However, it is conceivable that a second-site mutation in for example, a direct interactor of SUB may result in a protein that can still interact with the altered SUB protein and thus compensate for the principally deleterious effect. It is presently unclear if, and how often, this possibility actually occurs in the case of SUB in wild-type accessions. A different scenario, where accumulation of genetic incompatibilities between accessions can lead to reproductive isolation, has been described for SRF3. Genome sequencing has led to the discovery of myriads of new open reading frames from microbial, plant and animal systems whose cellular and biochemical functions are often unknown. Analysis of such proteins generally involves their expression in heterologous hosts, followed by their purification and biochemical characterization.