Genome-wide analysis of DNA copy number alterations and loss of heterozygosity in intracranial germ cell tumors.

BACKGROUNDS: Intracranial germ cell tumors (GCTs) are rare and heterogeneous with very little is known about their pathogenesis and underlying genetic abnormalities. PROCEDURES: In order to identify candidate genes and pathways which are involved in the pathogenesis of these tumors, we have profiled 62 intracranial GCTs for DNA copy number alterations (CNAs) and loss of heterozygosity (LOH) by using single nucleotide polymorphism (SNP) array and quantitative real time PCR (qPCR). RESULTS: Initially 27 cases of tumor tissues with matched blood samples were fully analyzed by SNP microarray and qPCR. Statistical analysis using the genomic identification of significant targets in cancer (GISTIC) tool identified 10 regions of significant copy number gain and 11 regions of significant copy number loss. While overall pattern of genomic aberration was similar between germinoma and nongerminomatous germ cell tumors (NGGCTs), a few subtype-specific peak regions were identified. Analysis by SNP array and qPCR was replicated using an independent cohort of 35 cases. CONCLUSIONS: Frequent aberrations of CCND2 (12p13) and RB1 (13q14) suggest that Cyclin/CDK-RB-E2F pathway might play a critical role in the pathogenesis of intracranial GCTs. Frequent gain of PRDM14 (8q13) implies that transcriptional regulation of primordial germ cell specification might be an important factor in the development of this tumor.

Immunodepletion plasma proteomics by tripleTOF 5600 and Orbitrap elite/LTQ-Orbitrap Velos/Q exactive mass spectrometers.

Plasma proteomic experiments performed rapidly and economically using several of the latest high-resolution mass spectrometers were compared. Four quantitative hyperfractionated plasma proteomics experiments were analyzed in replicates by two AB SCIEX TripleTOF 5600 and three Thermo Scientific Orbitrap (Elite/LTQ-Orbitrap Velos/Q Exactive) instruments. Each experiment compared two iTRAQ isobaric-labeled immunodepleted plasma proteomes, provided as 30 labeled peptide fractions, and 480 LC-MS/MS runs delivered >250 GB of data in 2 months. Several analysis algorithms were compared. At 1% false discovery rate, the relative comparative findings concluded that the Thermo Scientific Q Exactive Mass Spectrometer resulted in the highest number of identified proteins and unique sequences with iTRAQ quantitation. The confidence of iTRAQ fold-change for each protein is dependent on the overall ion statistics (Mascot Protein Score) attainable by each instrument. The benchmarking also suggested how to further improve the mass spectrometry parameters and HPLC conditions. Our findings highlight the special challenges presented by the low abundance peptide ions of iTRAQ plasma proteome because the dynamic range of plasma protein abundance is uniquely high compared with cell lysates, necessitating high instrument sensitivity.

Histone induced platelet aggregation is inhibited by normal albumin.

INTRODUCTION: Histones are small, nuclear proteins that serve to package DNA. Recent reports suggest that extracellular histones, including histone H4, may contribute to the pathogenesis of sepsis; they promote platelet aggregation and thrombosis when released into the circulation during inflammation or cell death. The mechanisms by which the body minimizes the deleterious effects of circulating histones are unclear. Because histones can bind to plasma proteins, including albumin, we hypothesized that normal albumin can prevent histones from activating platelets. MATERIALS AND METHODS: Platelets and platelet-free plasma were obtained from healthy, adult subjects. The dose-dependent effects of histone H4 on platelet aggregation were studied by optical aggregometry. The effects of native and albumin-depleted plasma (prepared by affinity chromatography) on histone-induced platelet aggregation were also assessed. The effects of normal and surface-neutralized albumin (through modification of carboxyl groups) on histone-induced platelet activation and aggregation were evaluated using flow cytometry and aggregometry. RESULTS: Histone H4 induced platelet aggregation in a dose-dependent manner. This histone-induced platelet aggregation was inhibited by both plasma and human serum albumin in a dose-dependent fashion. Furthermore, depletion of albumin from plasma reduced its ability to inhibit aggregation. Finally, surface neutralization of albumin decreased its ability to inhibit histone-induced activation and aggregation. DISCUSSION: These data suggest that normal albumin serves a role in preventing histone-induced platelet aggregation in a charge-dependent manner.

Curcumin modulates DNA methylation in colorectal cancer cells.

AIM: Recent evidence suggests that several dietary polyphenols may exert their chemopreventive effect through epigenetic modifications. Curcumin is one of the most widely studied dietary chemopreventive agents for colon cancer prevention, however, its effects on epigenetic alterations, particularly DNA methylation, remain unclear. Using systematic genome-wide approaches, we aimed to elucidate the effect of curcumin on DNA methylation alterations in colorectal cancer cells. MATERIALS AND METHODS: To evaluate the effect of curcumin on DNA methylation, three CRC cell lines, HCT116, HT29 and RKO, were treated with curcumin. 5-aza-2'-deoxycytidine (5-aza-CdR) and trichostatin A treated cells were used as positive and negative controls for DNA methylation changes, respectively. Methylation status of LINE-1 repeat elements, DNA promoter methylation microarrays and gene expression arrays were used to assess global methylation and gene expression changes. Validation was performed using independent microarrays, quantitative bisulfite pyrosequencing, and qPCR. RESULTS: As expected, genome-wide methylation microarrays revealed significant DNA hypomethylation in 5-aza-CdR-treated cells (mean ß-values of 0.12), however, non-significant changes in mean ß-values were observed in curcumin-treated cells. In comparison to mock-treated cells, curcumin-induced DNA methylation alterations occurred in a time-dependent manner. In contrast to the generalized, non-specific global hypomethylation observed with 5-aza-CdR, curcumin treatment resulted in methylation changes at selected, partially-methylated loci, instead of fully-methylated CpG sites. DNA methylation alterations were supported by corresponding changes in gene expression at both up- and down-regulated genes in various CRC cell lines. CONCLUSIONS: Our data provide previously unrecognized evidence for curcumin-mediated DNA methylation alterations as a potential mechanism of colon cancer chemoprevention. In contrast to non-specific global hypomethylation induced by 5-aza-CdR, curcumin-induced methylation changes occurred only in a subset of partially-methylated genes, which provides additional mechanistic insights into the potent chemopreventive effect of this dietary nutraceutical.

Boswellic acid induces epigenetic alterations by modulating DNA methylation in colorectal cancer cells.

Accumulating evidence suggests that chemopreventive effects of some dietary polyphenols may in part be mediated by their ability to influence epigenetic mechanisms in cancer cells. Boswellic acids, derived from the plant Boswellia serrata, have long been used for the treatment of various inflammatory diseases due to their potent anti-inflammatory activities. Recent preclinical studies have also suggested that this compound has anti-cancer potential against various malignancies. However, the precise molecular mechanisms underlying their anti-cancer effects remain elusive. Herein, we report that boswellic acids modulate DNA methylation status of several tumor suppressor genes in colorectal cancer (CRC) cells. We treated RKO, SW48 and SW480 CRC cell lines with the active principle present in boswellic acids, acetyl-keto-ß-boswellic acid (AKBA). Using genome-wide DNA methylation and gene expression microarray analyses, we discovered that AKBA induced a modest genome-wide demethylation that permitted simultaneous re-activation of the corresponding tumor suppressor genes. The quantitative methylation-specific PCR and RT-PCR validated the gene demethylation and re-expression in several putative tumor suppressor genes including SAMD14 and SMPD3. Furthermore, AKBA inhibited DNMT activity in CRC cells. Taken together, these results lend further support to the growing notion that anti-cancer effect of boswellic acids may in part be due to its ability to demethylate and reactivate methylation-silenced tumor suppressor genes. These results suggest that not only boswellic acid might be a promising epigenetic modulator in the chemoprevention and treatment of CRC, but also provide a rationale for future investigations on the usefulness of such botanicals for epigenetic therapy in other human malignancies.

De novo constitutional MLH1 epimutations confer early-onset colorectal cancer in two new sporadic Lynch syndrome cases, with derivation of the epimutation on the paternal allele in one.

Lynch syndrome is an autosomal dominant cancer predisposition syndrome classically caused by germline mutations of the mismatch repair genes, MLH1, MSH2, MSH6 and PMS2. Constitutional epimutations of the MLH1 gene, characterized by soma-wide methylation of a single allele of the promoter and allelic transcriptional silencing, have been identified in a subset of Lynch syndrome cases lacking a sequence mutation in MLH1. We report two individuals with no family history of colorectal cancer who developed that disease at age 18 and 20 years. In both cases, cancer had arisen because of the de novo occurrence of a constitutional MLH1 epimutation and somatic loss-of-heterozygosity of the functional allele in the tumors. We show for the first time that the epimutation in one case arose on the paternally inherited allele. Analysis of 13 tumors from seven individuals with constitutional MLH1 epimutations showed eight tumors had lost the second MLH1 allele, two tumors had a novel pathogenic missense mutation and three had retained heterozygosity. Only 1 of 12 tumors demonstrated the BRAF V600E mutation and 3 of 11 tumors harbored a mutation in KRAS. The finding that epimutations can originate on the paternal allele provides important new insights into the mechanism of origin of epimutations. It is clear that the second hit in MLH1 epimutation-associated tumors typically has a genetic not epigenetic basis. Individuals with mismatch repair-deficient cancers without the BRAF V600E mutation are candidates for germline screening for sequence or methylation changes in MLH1.

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data.

BACKGROUND: Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. RESULTS: We developed a recursive support vector machine (R-SVM) algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE), paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5%- approximately 20% improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. R-SVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. CONCLUSION: The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features.