Genomic landscape of CpG rich elements in human

Background

The studies on CpG islands (CGI) and Alu elements functions, evolution, and distribution in the genome started since the discovery in nineteen eighties (1981, 1986, correspondingly). Their highly skewed genome wide distribution implies the non-random retrotransposition pattern. Besides CGIs in gene promoters, CGIs clusters were observed in the homeobox gene regions and in the macrosatellites, but the whole picture of their distribution specifics was not grasped. Attempts to identify any causative features upon their (genome wide) distribution, such as the DNA context mediated preferred insertion sites of Alu repeats, have been made to ascribe their clusters location.

Methods

Recent emergence of high resolution 3D map of human genome allowed segregating the genome into the large scale chromatin domains of naturally observable nuclear subcompartments, or Topologically Associated Domains (TADs), designated by spatial chromatin distribution. We utilized the chromatin map to elucidate relations between large scale chromatin state and CpG rich elements landscape.In the course of analysis it was confirmed that genes, Alu and CGI clusters maintain obvious, albeit different in strength, preference for open chromatin. For the first time it was clearly shown that the clusters density of the Alu and CGIs monotonically depend on the chromatin accessibility rate. In particular, the highest density of these elements is found in A1 euchromatin regions characterized by a high density of small length genes replicating in the early S-phase. It implies that these elements mediate (CGIs) or are a side element (Alus) of chromatin accessibility.

Results

We elucidated that both methylated and non-methylated CGIs display the affinity to chromatin accessibility. As a part of comparative genomics section, we elucidated that the dog’s genome non-canonical structure, outstanding in mammals for its high CGIs abundance compared to gene number, is explained by the presence of dense tandem CGI extended hotspots (500 kb on average) in subtelomeric and pericentromeric regions with highly skewed CG content, and not by CGIs global distribution pattern shift.

Conclusions

The study underlines the close association of CG-rich elements distribution with the newly introduced large scale chromatin state map, proposing a refined standpoint on interrelation of aforementioned genome elements and the chromatin state. To our expertise, the TAD-associated partition model employed in the study is likely the most substantial one regarding CpG rich clusters distribution among the whole genome chromatin/isochores maps available.

     

Modeling genomic data with type attributes, balancing stability and maintainability

Background

The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern.

Results

We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation.

Conclusion

Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes conserving the accuracy provided by leading binary methylation classification methods.     

Heterogeneity in White Blood Cells Has Potential to Confound DNA Methylation Measurements

Epigenetic studies are commonly conducted on DNA from tissue samples. However, tissues are ensembles of cells that may each have their own epigenetic profile, and therefore inter-individual cellular heterogeneity may compromise these studies. Here, we explore the potential for such confounding on DNA methylation measurement outcomes when using DNA from whole blood. DNA methylation was measured using pyrosequencing-based methodology in whole blood (n = 50–179) and in two white blood cell fractions (n = 20), isolated using density gradient centrifugation, in four CGIs (CpG Islands) located in genes HHEX (10 CpG sites assayed), KCNJ11 (8 CpGs), KCNQ1 (4 CpGs) and PM20D1 (7 CpGs). Cellular heterogeneity (variation in proportional white blood cell counts of neutrophils, lymphocytes, monocytes, eosinophils and basophils, counted by an automated cell counter) explained up to 40% (p<0.0001) of the inter-individual variation in whole blood DNA methylation levels in the HHEX CGI, but not a significant proportion of the variation in the other three CGIs tested. DNA methylation levels in the two cell fractions, polymorphonuclear and mononuclear cells, differed significantly in the HHEX CGI; specifically the average absolute difference ranged between 3.4–15.7 percentage points per CpG site. In the other three CGIs tested, methylation levels in the two fractions did not differ significantly, and/or the difference was more moderate. In the examined CGIs, methylation levels were highly correlated between cell fractions. In summary, our analysis detects region-specific differential DNA methylation between white blood cell subtypes, which can confound the outcome of whole blood DNA methylation measurements. Finally, by demonstrating the high correlation between methylation levels in cell fractions, our results suggest a possibility to use a proportional number of a single white blood cell type to correct for this confounding effect in analyses.     

Insulin Receptor Isoforms A and B as well as Insulin Receptor Substrates-1 and -2 Are Differentially Expressed in Prostate Cancer

Aims/Hypothesis

In different cancers types, insulin receptor isoform composition or insulin receptor substrate (IRS) isoforms are different to healthy tissue. This may be a molecular link to increased cancer risk in diabetes and obesity. Since this is yet unclear for prostate cancer, we investigated IR isoform composition and IRS balance in prostate cancer compared to benign and tumor adjacent benign prostate tissue and brought this into relation to cell proliferation.

Methods

We studied 23 benign prostate samples from radical cystectomy or benign prostatic hyperplasia surgery, 30 samples from benign tissue directly adjacent to prostate cancer foci and 35 cancer samples from different patients. RNA expression levels for insulin receptor isoforms A and B, IRS-1, IRS-2, and IGF-1 receptor were assessed by quantitative real-time RT-PCR. In addition, RNA- and protein expression of the cell cycle regulator p27^Kip1 was quantified by real-time RT-PCR and immunohistochemistry.

Results

Insulin receptor isoform A to B ratio was significantly higher in cancer as well as in tumor adjacent benign prostate tissue compared to purely benign prostates (p<0.05). IRS-1 to IRS-2 ratios were lower in malignant than in benign prostatic tissue (p<0.05). These altered ratios both in cancer and adjacent tissue were significantly associated with reduced p27^Kip1 content (p<0.02). Interestingly, IGF-1 receptor levels were significantly lower in patients with type 2 diabetes (p = 0.0019).

Conclusions/Interpretation

We found significant differences in the insulin signaling cascade between benign prostate tissue and prostate cancer. Histological benign tissue adjacent to cancer showed expression patterns similar to the malignancies. Our findings suggest a role of the insulin signaling pathway in prostate cancer and surrounding tissue and can hence be relevant for both novel diagnostic and therapeutic approaches in this malignancy.     

Human-specific CpG “beacons” identify loci associated with human-specific traits and disease

Regulatory change has long been hypothesized to drive the delineation of the human phenotype from other closely related primates. Here we provide evidence that CpG dinucleotides play a special role in this process. CpGs enable epigenome variability via DNA methylation, and this epigenetic mark functions as a regulatory mechanism. Therefore, species-specific CpGs may influence species-specific regulation. We report non-polymorphic species-specific CpG dinucleotides (termed “CpG beacons”) as a distinct genomic feature associated with CpG island (CGI) evolution, human traits and disease. Using an inter-primate comparison, we identified 21 extreme CpG beacon clusters (≥ 20/kb peaks, empirical p < 1.0 × 10⁻³) in humans, which include associations with four monogenic developmental and neurological disease related genes (Benjamini-Hochberg corrected p = 6.03 × 10⁻³). We also demonstrate that beacon-mediated CpG density gain in CGIs correlates with reduced methylation in these species in orthologous CGIs over time, via human, chimpanzee and macaque MeDIP-seq. Therefore mapping into both the genomic and epigenomic space the identified CpG beacon clusters define points of intersection where a substantial two-way interaction between genetic sequence and epigenetic state has occurred. Taken together, our data support a model for CpG beacons to contribute to CGI evolution from genesis to tissue-specific to constitutively active CGIs.     

Detecting hepatocellular carcinoma in blood

Liquid biopsy is ideal for early diagnosis of cancer and for prognosis upon treatment. Wen et al. describe a methylated CpG tandems amplification and sequencing method to profile hypermethylated CpG islands genome-widely in cell-free DNA, and further identify high performance markers in blood for potential detection of early stage hepatocellular carcinoma.Early diagnosis is key to cancer prevention and treatment. When physiological consequences of cancer are observed it could be too late for the optimal treatment and therapy¹. Traditional biopsy has been widely used for diagnosis; however, it is difficult to frequently perform biopsy. In many cases it is impossible to perform biopsy of solid tumors grown in deep tissues. Cell-free nucleic acids (cfNAs) offer an alternative option. The presence of cfNAs in blood was described in 1948. However, cfNAs such as DNA, mRNA and microRNAs (miRNAs) were not recognized as potential disease biomarkers until recently because of the rapid advance of sequencing technologies^2,3,4. The apoptosis and necrosis of tumor tissues can lead to release of cell-free DNAs (cfDNAs) into the circulating system⁵; these cfDNAs contain crucial genetic and epigenetic information for early diagnosis if sensitive and accurate methods can be developed.Human hepatocellular cancer, one of the most lethal cancers, is characterized by progressive accumulation of epigenetic changes⁶, among which hypermethylation of cancer-associated DNA offers distinct markers for diagnosis. DNA methylation patterns could change throughout the cancer development stages. If the same DNA methylation changes could be monitored in cfDNA released by tumor one could trace the emergence of the cancer, monitor the progression, and predict effects of treatments. Despite these advantages, current cfDNA detection is significantly hampered by the lack of sensitivity because only a very small amount of cfDNA could be obtained from plasma and serum. cfDNA is also heavily fragmented (between 200∼400 bp), adding additional challenges.Faced with these challenges, Wen et al.⁷ invent methylated CpG tandems amplification and sequencing (MCTA-Seq), a method that takes advantage of the fact that CpG tandems are highly enriched in the CpG island-containing promoters of human genome. These CpGs are typically unmethylated but tend to gain hypermethylation in hepatocellular carcinoma (HCC)⁶. The cfDNAs released into circulation carry the same hypermethylation patterns, thereby providing accurate information of the presence of HCC in patients. In their new method, cfDNA is treated with bisulfite, during which non-methylated C (cytosine) is converted to U (uracil) while methylated C remains unaffected. They then use a pair of primers to specifically amplify DNA loci that contain hypermethylated CGCGCGG, a sequence frequently presented in CpG islands and tend to be methylated in cancer tissues. The focus on the CGCGCGG-containing loci may miss other potential markers; however, it offers the sensitivity required for methylation detection in cfDNA. Validation data of MCTA-Seq shows that it is highly reproducible and sensitive, with the detection limit down to as low as 7.5 pg (∼2.5 haploid genome equivalents). Existing biomarkers that are frequently hypermethylated in human cancers⁸, such as VIM, SEPT9, NDRG2 and RASSF1⁸, could be detected with high sensitivity by using MCTA-Seq. The method, although limited by the requirement of the CGCGCGG sequence content, is genome-wide and offers sufficient information about CpG island methylation changes in HCC.Wen et al. applied the new method to detect tumor-specific CGI methylation with plasma samples from HCC patients, cirrhosis patients, and normal individuals. Two types of biomarkers have been identified for early stage HCC diagnosis (Figure 1). Type I markers possess significantly higher methylated CGIs than cancer-free individuals. Type II markers are tissue-specifically methylated CGIs, which tend to be restricted to liver cells under normal circumstances but are released into the blood when malignance occurs. Type II markers dominate in the cfDNA at early stage of HCCs, making them sensitive signs of tumor emergence.Open in a separate windowFigure 1Hypermethylated cfDNA released into the blood can be detected with a new method. Cell-free DNA-containing hypermethylated CpG islands (mCGIs) circulating in the blood of heptocellular carcinoma patients can be detected for early diagnosis. These marker DNAs are released by either tumor cells undergoing apoptosis or necrosis (type I) or adjacent non-cancerous cells affected by tumor growth (type II).The new method and the use of marker combination shown by Wen et al. provide a new strategy for DNA methylation detection from cfDNA. It may have widely applicable potential not only in HCC but also a cohort of other cancer types.     

Nerve Sheath Tumors in Neurofibromatosis Type 1: Assessment of Whole-Body Metabolic Tumor Burden Using F-18-FDG PET/CT

Purpose

To determine the metabolically active whole-body tumor volume (WB-MTV) on F-18-fluorodeoxyglucose positron emission tomography/computed tomography (F-18-FDG PET/CT) in individuals with neurofibromatosis type 1 (NF1) using a three-dimensional (3D) segmentation and computerized volumetry technique, and to compare PET WB-MTV between patients with benign and malignant peripheral nerve sheath tumors (PNSTs).

Patients and Methods

Thirty-six NF1 patients (18 patients with malignant PNSTs and 18 age- and sex-matched controls with benign PNSTs) were examined by F-18-FDG PET/CT. WB-MTV, whole-body total lesion glycolysis (WB-TLG) and a set of semi-quantitative imaging-based parameters were analyzed both on a per-patient and a per-lesion basis.

Results

On a per-lesion basis, malignant PNSTs demonstrated both a significantly higher MTV and TLG than benign PNSTs (p < 0.0001). On a per-patient basis, WB-MTV and WB-TLG were significantly higher in patients with malignant PNSTs compared to patients with benign PNSTs (p < 0.001). ROC analysis showed that MTV and TLG could be used to differentiate between benign and malignant tumors.

Conclusions

WB-MTV and WB-TLG may identify malignant change and may have the potential to provide a basis for investigating molecular biomarkers that correlate with metabolically active disease manifestations. Further evaluation will determine the potential clinical impact of these PET-based parameters in NF1.     

The rs10993994 risk allele for prostate cancer results in clinically relevant changes in microseminoprotein-beta expression in tissue and urine

Background

Microseminoprotein-beta (MSMB) regulates apoptosis and using genome-wide association studies the rs10993994 single nucleotide polymorphism in the MSMB promoter has been linked to an increased risk of developing prostate cancer. The promoter location of the risk allele, and its ability to reduce promoter activity, suggested that the rs10993994 risk allele could result in lowered MSMB in benign tissue leading to increased prostate cancer risk.

Methodology/Principal Findings

MSMB expression in benign and malignant prostate tissue was examined using immunohistochemistry and compared with the rs10993994 genotype. Urinary MSMB concentrations were determined by ELISA and correlated with urinary PSA, the presence or absence of cancer, rs10993994 genotype and age of onset. MSMB levels in prostate tissue and urine were greatly reduced with tumourigenesis. Urinary MSMB was better than urinary PSA at differentiating men with prostate cancer at all Gleason grades. The high risk allele was associated with heterogeneity of MSMB staining and loss of MSMB in both tissue and urine in benign prostate.

Conclusions

These data show that some high risk alleles discovered using genome-wide association studies produce phenotypic effects with potential clinical utility. We provide the first link between a low penetrance polymorphism for prostate cancer and a potential test in human tissue and bodily fluids. There is potential to develop tissue and urinary MSMB for a biomarker of prostate cancer risk, diagnosis and disease monitoring.     

Circulating Methylated XAF1 DNA Indicates Poor Prognosis for Gastric Cancer

Background

Methylated DNA in fluids may be a suitable biomarker for cancer patients. XAF1 has been shown to be frequently down-regulated in human gastric cancer (GC). Here, we investigated if XAF1 methylation in GC could be a useful biomarker.

Methods

Real-time RT-PCR was used to detect XAF1 mRNA expression; immunohistochemistry and western blot were used to examine XAF1 protein expression in GC tissues (n = 202) and their corresponding para-cancerous histological normal tissues (PCHNTs). Real-time methylation specific-PCR was used to investigate XAF1 promoter methylation in the same panel of GC tissues, their PCHNTs and sera.

Results

We confirmed frequent XAF1 down-regulation in both mRNA and protein levels in GC tissues as compared to normal controls and PCHNTs. XAF1 hypermethylation was evidenced in 83.2% (168/202) of GC tissues and 27.2% (55/202) of PCHNTs, while no methylation was detected in the 88 normal controls. The methylation level in GC tissues was significantly higher than that in PCHNTs (p<0.05). The hypermethylation of XAF1 significantly correlated with the down-regulation of XAF1 in GC tissues in both mRNA and protein levels (p<0.001 each). Moreover, we detected high frequency of XAF1 methylation (69.8%, 141 out of 202) in the sera DNAs from the same patients, while the sera DNAs from 88 non-tumor controls were negative for XAF1 methylation. The XAF1 methylation in both GC tissues and in the sera could be a good biomarker for diagnosis of GC (AUC = 0.85 for tissue and AUC = 0.91 for sera) and significantly correlated with poorer prognosis (p<0.001). In addition, after-surgery negative-to-positive transition of XAF1 methylation in sera strongly associated with tumor recurrence.

Conclusions

1) Dysfunction of XAF1 is frequent and is regulated through XAF1 promoter hypermethylation; 2) Detection of circulating methylated XAF1 DNAs in the serum may be a useful biomarker in diagnosis, evaluating patient’s outcome (prognosis and recurrence) for GC patients.     

Development of a Nuclear Morphometric Signature for Prostate Cancer Risk in Negative Biopsies

Background

Our objective was to develop and validate a multi-feature nuclear score based on image analysis of direct DNA staining, and to test its association with field effects and subsequent detection of prostate cancer (PCa) in benign biopsies.

Methods

Tissue sections from 39 prostatectomies were Feulgen-stained and digitally scanned (400×), providing maps of DNA content per pixel. PCa and benign epithelial nuclei were randomly selected for measurement of 52 basic morphometric features. Logistic regression models discriminating benign from PCa nuclei, and benign from malignant nuclear populations, were built and cross-validated by AUC analysis. Nuclear populations were randomly collected <1 mm or >5 mm from cancer foci, and from cancer-free prostates, HGPIN, and PCa Gleason grade 3–5. Nuclei also were collected from negative biopsy subjects who had a subsequent diagnosis of PCa and age-matched cancer-free controls (20 pairs).

Results

A multi-feature nuclear score discriminated cancer from benign cell populations with AUCs of 0.91 and 0.79, respectively, in training and validation sets of patients. In prostatectomy samples, both nuclear- and population-level models revealed cancer-like features in benign nuclei adjacent to PCa, compared to nuclei that were more distant or from PCa-free glands. In negative biopsies, a validated model with 5 variance features yielded significantly higher scores in cases than controls (P = 0.026).

Conclusions

A multifeature nuclear morphometric score, obtained by automated digital analysis, was validated for discrimination of benign from cancer nuclei. This score demonstrated field effects in benign epithelial nuclei at varying distance from PCa lesions, and was associated with subsequent PCa detection in negative biopsies.

Impact

This nuclear score shows promise as a risk predictor among men with negative biopsies and as an intermediate biomarker in Phase II chemoprevention trials. The results also suggest that subvisual disturbances in nuclear structure precede the development of pre-neoplastic lesions.     

The Suppressive Role and Aberrent Promoter Methylation of BTG3 in the Progression of Hepatocellular Carcinoma

Background

BTG3 (B-cell translocation gene 3) has been identified as a tumor suppressor and hypermethylation contributes to its down-regulation in some tumors, but its role in hepatocellular carcinoma (HCC) remain unknown. This study aimed to detect the expression and methylation status of BTG3 in HCC cell lines or tissues, and determine its function in HCC progression.

Methodology

The expression of BTG3 was detected in HCC cell lines and HCC tissue by real-time RT-PCR, Western blot or immunohistochemistry. The promoter methylation status of BTG3 was measured by using methylation-specific PCR in HCC cell lines. A series of assays were performed to evaluate the effect of BTG3 on proliferation, invasion and cell cycle transition in vitro.

Results

BTG3 expression was lower in HCC cell lines than in hepatocyte cell line LO2 (P<0.05). BTG3 was also down-regulated in HCC tissues. Its expression was positively correlated with differentiation and distant metastasis (P<0.05). Patients with lower BTG3 expression had shorter overall survival time (P=0.029). DNA methylation directed repression of BTG3 mRNA expression in HCC cell lines. BTG3 suppressed proliferation, invasion and induces G1/S cycle arrest of HCC cells in vitro.

Conclusion

Down-regulation of BTG3 due to the promoter hypermethylation is closely associated with proliferation, invasion and cell cycle arrest of HCC cells. It may be a novel prognostic biomarker for HCC patients.     

Opposing Roles of Dnmt1 in Early- and Late-Stage Murine Prostate Cancer

Previous studies have shown that tumor progression in the transgenic adenocarcinoma of mouse prostate (TRAMP) model is characterized by global DNA hypomethylation initiated during early-stage disease and locus-specific DNA hypermethylation occurring predominantly in late-stage disease. Here, we utilized Dnmt1 hypomorphic alleles to examine the role of Dnmt1 in normal prostate development and in prostate cancer in TRAMP. Prostate tissue morphology and differentiation status was normal in Dnmt1 hypomorphic mice, despite global DNA hypomethylation. TRAMP; Dnmt1 hypomorphic mice also displayed global DNA hypomethylation, but were characterized by altered tumor phenotype. Specifically, TRAMP; Dnmt1 hypomorphic mice exhibited slightly increased tumor incidence and significantly increased pathological progression at early ages and, conversely, displayed slightly decreased tumor incidence and significantly decreased pathological progression at advanced ages. Remarkably, hypomorphic Dnmt1 expression abrogated local and distant site macrometastases. Thus, Dnmt1 has tumor suppressor activity in early-stage prostate cancer, and oncogenic activity in late stage prostate cancer and metastasis. Consistent with the biological phenotype, epigenomic studies revealed that TRAMP; Dnmt1 hypomorphic mice show dramatically reduced CpG island and promoter DNA hypermethylation in late-stage primary tumors compared to control mice. Taken together, the data reveal a crucial role for Dnmt1 in prostate cancer and suggest that Dnmt1-targeted interventions may have utility specifically for advanced and/or metastatic prostate cancer.Changes in DNA methyltransferase (Dnmt) expression and DNA methylation are observed in human prostate cancer (3, 38, 41). Of particular interest, genes with tumor suppressive function become hypermethylated and silenced, which correlates with the development of specific disease phenotypes (2, 3, 38). Although an association between prostate cancer and alterations in DNA methylation has been established, in vivo models are required to determine whether these changes functionally contribute to the disease. In this context, studies in which pharmacological inhibitors of Dnmts were shown to inhibit prostate cancer in murine models have proven informative (34, 56). However, it remains unknown whether genetic disruption of epigenetic components, such as Dnmts, also impacts prostate cancer development. This is a critical question since the pharmacological inhibitors of Dnmts have pleiotropic effects, including those unrelated to activation of methylation-silenced genes (21, 23, 31). Moreover, no studies to date have examined whether Dnmts or DNA methylation play roles in normal prostate development; this information is vital to fully understanding the effects that inhibiting DNA methylation may have on prostate cancer.Dnmt1 is a maintenance DNA methyltransferase that propagates preexisting DNA methylation patterns in genomic DNA (44). Dnmt1 also is involved in de novo DNA methylation in cancer cells and interacts with other key epigenetic control molecules, including histone-modifying enzymes (11, 19). Murine models have been used to investigate the in vivo functions of Dnmt1. Complete genetic knockout of Dnmt1 is embryonic lethal in mice (29). However, hypomorphic expression of Dnmt1 allows murine development to proceed but causes global DNA hypomethylation and impacts cancer development and progression (7, 14, 28). Specifically, hypomorphic expression of Dnmt1 can lead to the development of lymphoma (14). Furthermore, crossing Dnmt1 hypomorphic mice with murine tumor models alters tumor progression, resulting in either increased or decreased tumor development, depending on the disease stage and tissue site (1, 7, 53). For example, reduced expression of Dnmt1 dramatically decreases intestinal polyp formation in Apc^Min/+ mice, either alone or in combination with 5-aza-2′-deoxycytidine treatment (7, 27). However, it was later noted that reduced expression of Dnmt1 has a dual effect on intestinal cancer in Apc^Min/+ mice, in which the development of early stage intestinal microadenomas is accelerated, whereas the formation of adenomatous polyps is significantly reduced (53). In addition, Apc^Min/+ Dnmt1 hypomorphic mice develop liver cancer associated with the loss of heterozygosity of Apc (53). Similarly, in Dnmt1 hypomorphic mice crossed to Mlh1^−/− mice, a dual effect was noted wherein mice developed fewer intestinal cancers but displayed increased T- and B-cell lymphomas (52). In addition, a recent study demonstrated that hypomorphic Dnmt1 expression is associated with reduced squamous cell carcinoma of the tongue and esophagus, resulting in decreased invasive cancer (1). Taken together, the data suggest that Dnmt1 has diverse effects on cancer development, which are dependent on tissue context and tumor stage.TRAMP is a well-established transgenic prostate cancer model driven by prostate-specific expression of the simian virus 40 (SV40) T/t oncogenes (16). TRAMP mice are characterized by Dnmt mRNA and protein overexpression, altered DNA methylation, and altered gene expression during prostate cancer development (2, 33, 35, 37). Of the three enzymatically active Dnmts, Dnmt1 shows the greatest level of overexpression in TRAMP, and this correlates with Rb inactivation, a key genetic event driving prostate cancer in the model (37). Most critically, global DNA hypomethylation occurs during early and late disease stages, while DNA hypermethylation occurs primarily at late disease stages in TRAMP (35).Here, we utilized Dnmt1 hypomorphic mice and the TRAMP model to assess the role of DNA methylation in both normal prostatic development and prostate cancer. The Dnmt1 hypomorphic mouse model used involves two different hypomorphic alleles (N and R), resulting in four genotypes with progressively reduced DNA methylation (Dnmt1^+/+, Dnmt1^R/+, Dnmt1^N/+, and Dnmt1^N/R) (7, 52). The N allele consists of a PGK-Neo insertion that deletes a portion of exon 4 of Dnmt1, resulting in severely reduced Dnmt1 expression, while the R allele involves a lacO insertion into intron 3 of Dnmt1, which partially reduces Dnmt1 expression (7, 52). Based on our previous work establishing the timing of DNA hypomethylation and DNA hypermethylation in TRAMP, we hypothesized that hypomorphic Dnmt1 expression in TRAMP may have tumor-promoting effects at early disease stages and tumor-inhibitory effects at later stages of prostate cancer progression. Our data are consistent with this hypothesis and, more importantly, reveal a critical and unanticipated role for Dnmt1 in prostate cancer metastasis.     

Characterization of Breast Tumors Using Diffusion Kurtosis Imaging (DKI)

Aim

The aim of this study was to investigate and evaluate the role of magnetic resonance (MR) diffusion kurtosis imaging (DKI) in characterizing breast lesions.

Materials and Methods

One hundred and twenty-four lesions in 103 patients (mean age: 57±14 years) were evaluated by MR DKI performed with 7 b-values of 0, 250, 500, 750, 1,000, 1,500, 2,000 s/mm² and dynamic contrast-enhanced (DCE) MR imaging. Breast lesions were histologically characterized and DKI related parameters—mean diffusivity (MD) and mean kurtosis (MK)—were measured. The MD and MK in normal fibroglandular breast tissue, benign and malignant lesions were compared by One-way analysis of variance (ANOVA) with Tukey''s multiple comparison test. Receiver operating characteristic (ROC) analysis was performed to assess the sensitivity and specificity of MD and MK in the diagnosis of breast lesions.

Results

The benign lesions (n = 42) and malignant lesions (n = 82) had mean diameters of 11.4±3.4 mm and 35.8±20.1 mm, respectively. The MK for malignant lesions (0.88±0.17) was significantly higher than that for benign lesions (0.47±0.14) (P<0.001), and, in contrast, MD for benign lesions (1.97±0.35 (10⁻³ mm²/s)) was higher than that for malignant lesions (1.20±0.31 (10⁻³ mm²/s)) (P<0.001). At a cutoff MD/MK 1.58 (10⁻³ mm²/s)/0.69, sensitivity and specificity of MD/MK for the diagnosis of malignant were 79.3%/84.2% and 92.9%/92.9%, respectively. The area under the curve (AUC) is 0.86/0.92 for MD/MK.

Conclusions

DKI could provide valuable information on the diffusion properties related to tumor microenvironment and increase diagnostic confidence of breast tumors.