[Promoter methylation of ID4. A marker for recurrence-free survival in human breast cancer]

Quantitative Detection of ID4 Gene Aberrant Methylation in the Differentiation of Myelodysplastic Syndrome from Aplastic Anemia

BACKGROUND

The diagnosis of myelodysplastic syndrome (MDS), especially hypoplastic MDS, and MDS with low blast counts or normal karyotype may be problematic. This study characterized ID4 gene methylation in patients with MDS and aplastic anemia (AA).

METHODS

The methylation status of ID4 was analyzed by bisulfite sequencing polymerase chain reaction (PCR) and quantitative real-time methylation-specific PCR (MethyLight PCR) in 100 patients with MDS and 31 patients with AA.

RESULTS

The MDS group had a higher ID4 gene methylation positivity rate (22.22%) and higher methylation levels (0.21 [0-3.79]) than the AA group (P < 0.05). Furthermore, there were significant differences between the hypoplastic MDS and AA groups, the MDS with low blast count and the AA groups, and the MDS with normal karyotype and the AA groups. The combination of genetic and epigenetic markers was used in much more patients with MDS (62.5% [35/56]) than the use of genetic markers only (51.79% [29/56]).

CONCLUSIONS

These results showed that the detection of ID4 methylation positivity rates and levels could be a useful biomarker for MDS diagnosis.

Inhibitor of DNA binding 4 functions as a tumor suppressor and is targetable by 5-aza-2'-deoxycytosine with potential therapeutic significance in Burkitt's lymphoma

Epigenetic gene silencing due to promoter methylation is observed in human neoplasia, including lymphoma and certain cancer types. One important target for gene methylation analysis in non-Hodgkin lymphoma (NHL) is inhibitor of DNA binding 4 (ID4). The present study aimed to investigate the gene methylation status of ID4, the expression of ID4 protein and the effect of demethylating agent 5-aza-2'-deoxycytosine (CdR) in the Raji human Burkitt's lymphoma cell line in vitro. Following assessment of the inhibition of Raji cell growth by various concentrations of CdR, the effects of CdR on the expression of ID4 protein were assessed using the immunocytochemical streptavidin-peroxidase method and semi-quantitative analysis, while apoptosis and cell cycle were determined by flow cytometry. The ID4 gene methylation status of Raji cells was tested using methylation-specific polymerase chain reaction analysis. ID4 was methylated and its protein expression was low in the control group, while ID4 was partly or completely demethylated and its protein expression was upregulated in Raji cells treated with CdR. In addition, CdR induced apoptosis and cell cycle arrest in Raji cells in a dose- and time-dependent manner. These results demonstrated that ID4 is hypermethylated and its protein expression is low in Burkitt's lymphoma cells, while CdR reversed the abnormal DNA methylation and induced re-expression of ID4 protein. Hypermethylation of ID4 promotes the proliferation of Burkitt's lymphoma cells; ID4 may function as a tumor suppressor and can be targeted with demethylating compounds such as CdR for the treatment of Burkitt's lymphoma.

Clinical implications of the quantitative detection of ID4 gene methylation in myelodysplastic syndrome

Background

Myelodysplastic syndrome (MDS) eventually transforms into acute leukemia (AL) in about 30% of patients. Hypermethylation of the inhibitor of DNA binding 4 (ID4) gene may play an important role in the initiation and development of MDS and AL. The aim of this study was to quantitatively assess ID4 gene methylation in MDS and to establish if it could be an effective method of evaluating MDS disease progression.

Methods

We examined 142 bone marrow samples from MDS patients, healthy donors and MDS-AL patients using bisulfite sequencing PCR and quantitative real-time methylation-specific PCR. The ID4 methylation rates and levels were assessed.

Results

ID4 methylation occurred in 27 patients (27/100). ID4 gene methylation was more frequent and at higher levels in patients with advanced disease stages and in high-risk subgroups according to WHO (P < 0.001, P < 0.001, respectively) and International Prognostic Scoring System (IPSS) (P = 0.002, P = 0.007, respectively) classifications. ID4 methylation levels changed during disease progression. Both methylation rates and methylation levels were significantly different between healthy donor, MDS patients and patients with MDS-AL (P < 0.001, P < 0.001, respectively). Multivariate analysis indicated that the level of ID4 methylation was an independent factor influencing overall survival. Patients with MDS showed decreased survival time with increased ID4 methylation levels (P = 0.011, hazard ratio (HR) = 2.371). Patients with ID4 methylation had shorter survival time than those without ID4 methylation (P = 0.008).

Conclusions

Our findings suggest that ID4 gene methylation might be a new biomarker for MDS monitoring and the detection of minimal residual disease.

Bone morphogenetic protein type I receptor antagonists decrease growth and induce cell death of lung cancer cell lines

Bone morphogenetic proteins (BMPs) are highly conserved morphogens that are essential for normal development. BMP-2 is highly expressed in the majority of non-small cell lung carcinomas (NSCLC) but not in normal lung tissue or benign lung tumors. The effects of the BMP signaling cascade on the growth and survival of cancer cells is poorly understood. We show that BMP signaling is basally active in lung cancer cell lines, which can be effectively inhibited with selective antagonists of the BMP type I receptors. Lung cancer cell lines express alk2, alk3, and alk6 and inhibition of a single BMP receptor was not sufficient to decrease signaling. Inhibition of more than one type I receptor was required to decrease BMP signaling in lung cancer cell lines. BMP receptor antagonists and silencing of BMP type I receptors with siRNA induced cell death, inhibited cell growth, and caused a significant decrease in the expression of inhibitor of differentiation (Id1, Id2, and Id3) family members, which are known to regulate cell growth and survival in many types of cancers. BMP receptor antagonists also decreased clonogenic cell growth. Knockdown of Id3 significantly decreased cell growth and induced cell death of lung cancer cells. H1299 cells stably overexpressing Id3 were resistant to growth suppression and induction of cell death induced by the BMP antagonist DMH2. These studies suggest that BMP signaling promotes cell growth and survival of lung cancer cells, which is mediated through its regulation of Id family members. Selective antagonists of the BMP type I receptors represents a potential means to pharmacologically treat NSCLC and other carcinomas with an activated BMP signaling cascade.

Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles

Background

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS).

Methodology/Principal Findings

We implemented a multivariate Cox Lasso model and median time-to-event prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).

Conclusions/Significance

We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients.