This study examined DNA methylation associated with acute lymphoblastic leukemia (ALL) and showed that selected molecular targets can be pharmacologically modulated to reverse gene silencing. A CpG island (CGI) microarray containing more than 3,400 unique clones that span all human chromosomes was used for large-scale discovery experiments and led to 262 unique CGI loci being statistically identified as methylated in ALL lymphoblasts. The methylation status of 10 clones encompassing 11 genes (DCC, DLC-1, DDX51, KCNK2, LRP1B, NKX6-1, NOPE, PCDHGA12, RPIB9, ABCB1, and SLC2A14) identified as differentially methylated between ALL patients and controls was independently verified. Consequently, the methylation status of DDX51 was found to differentiate patients with B-and T-ALL subtypes (P = 0.011, Fisher's exact test). Next, the relationship between methylation and expression of these genes was examined in ALL cell lines (NALM-6 and Jurkat) before and after treatments with 5-aza-2-deoxycytidine and trichostatin A. More than a 10-fold increase in mRNA expression was observed for two previously identified tumor suppressor genes (DLC-1 and DCC) and also for RPIB9 and PCDHGA12. Although the mechanisms that lead to the CGI methylation of these genes are unknown, bisulfite sequencing of the promoter of RPIB9 suggests that expression is inhibited by methylation within SP1 and AP2 transcription factor binding motifs. Finally, specific chromosomal methylation hotspots were found to be associated with ALL. This study sets the stage for acquiring a better biological understanding of ALL and for the identification of epigenetic biomarkers useful for differential diagnosis, therapeutic monitoring, and the detection of leukemic relapse. [Cancer Res 2007;67(6):2617-25]

Non-Hodgkin's lymphoma (NHL) is a group of malignancies of the immune system with variable clinical behaviors and diverse molecular features. Despite the progress made in classification of NHLs based on classical methods, molecular classifications are a work in progress. Toward this goal, we used an arraybased technique called differential methylation hybridization (DMH) to study small B-cell lymphoma (SBCL) subtypes. A total of 43 genomic DMH experiments were performed. From these results, several statistical methods were used to generate a set of differentially methylated genes for further validation. Methylation of LHX2, POU3F3, HOXC10, NRP2, PRKCE, RAMP, MLLT2, NKX6.1, LRP1B and ARF4 was validated in cell lines and patient samples and demonstrated subtype-related preferential methylation patterns. For LHX2 and LRP1B, bisulfite sequencing, real-time reverse transcriptase-polymerase chain reaction and induction of gene expression following treatment with the demethylating agent, 5 0 -aza-2 0 -deoxycytidine, were confirmed. This new epigenetic information is helping to define molecular portraits of distinct subtypes of SBCL that are not recognized by current classification systems and provides valuable potential insights into the biology of these tumors.

Non-Hodgkin's lymphoma (NHL) is a group of malignancies with heterogeneous genetic and epigenetic alterations. Discovery of molecular markers that better define NHL should improve diagnosis, prognosis and understanding of the biology. We developed a CpG island DNA microarray for discovery of aberrant methylation targets in cancer, and now apply this method to examine NHL cell lines and primary tumors. This methylation profiling revealed differential patterns in six cell lines originating from different subtypes of NHL. We identified 30 hypermethylated genes in these cell lines and independently confirmed 10 of them. Methylation of 6 of these genes was then further examined in 75 primary NHL specimens composed of four subtypes representing different stages of maturation. Each gene (DLC-1, PCDHGB7, CYP27B1, EFNA5, CCND1 and RARbeta2) was frequently hypermethylated in these NHLs (87, 78, 61, 53, 40 and 38%, respectively), but not in benign follicular hyperplasia. Although some genes such as DLC-1 and PCDHGB7 were methylated in the vast majority of NHLs, others were differentially methylated in specific subtypes. The methylation of the candidate tumor suppressor gene DLC-1 was detected in a high proportion of primary tumor and plasma DNA samples by using quantitative methylation-specific PCR analysis. This promoter hypermethylation inversely correlated with DLC-1 gene expression in primary NHL samples. Thus, this CpG island microarray is a powerful discovery tool to identify novel methylated genes for further studies of their relevant molecular pathways in NHLs and identification of potential epigenetic biomarkers of disease.

Fuzzy set methods have been used to model and manage uncertainty in various aspects of image processing, pattern recognition, and computer vision. High-level computer vision applications hold a great potential for fuzzy set theory because of its links to natural language. Linguistic scene description, a language-based interpretation of regions and their relationships, is one such application that is starting to bear the fruits of fuzzy set theoretic involvement. In this paper, we are expanding on two earlier endeavors. We introduce new families of fuzzy directional relations that rely on the computation of histograms of forces. These families preserve important relative position properties. They provide inputs to a fuzzy rule base that produces logical linguistic descriptions along with assessments as to the validity of the descriptions. Each linguistic output uses hedges from a dictionary of about 30 adverbs and other terms that can be tailored to individual users. Excellent results from several synthetic and real image examples show the applicability of this approach.

Aims B-cell chronic lymphocytic leukemia (CLL) is a heterogeneous malignancy that clinically ranges from indolent to rapidly progressive. CLL, like other cancers, can be affected by epigenetic alterations. Materials & methods A microarray discovery-based study was initiated to determine DNA methylation in CLL cases with a range of CD38 expression (1–92%). Results Many loci were either methylated or unmethylated across all CD38 levels, but differential methylation was also observed for some genes. Genomic sequencing of DLEU7 confirmed extensive cytosine methylation preferentially in patient samples with low CD38 expression, whereas NRP2, SFRP2 and ADAM12 were more commonly methylated in those with high CD38 expression. Conclusion This study demonstrates that CLL is affected by CpG island methylation in some genes that segregate with CD38 expression levels, while most others show similar methylation patterns across all levels. The CpG island methylation in certain functional gene groups and pathway-associated genes that are known to be deregulated in CLL provides additional insights into the CLL methylome and epigenetic contribution to cellular dysfunction. It will now be useful to investigate the effectiveness of epigenetic therapeutic reversal of these alterations to develop effective treatments for the disease.