Biomedical subjects

Tim H-M Huang

Publications and source records attributed to Tim H-M Huang.

23 records · Page 2Linked to original sources

PubMed2004

The epigenetics of ovarian cancer drug resistance and resensitization.

Ovarian cancer is the most lethal of all gynecologic neoplasms. Early-stage malignancy is frequently asymptomatic and difficult to detect and thus, by the time of diagnosis, most women have advanced disease. Most of these patients, although initially responsive, eventually develop and succumb to drug-resistant metastases. The success of typical postsurgical regimens, usually a platinum/taxane combination, is limited by primary tumors being intrinsically refractory to treatment and initially responsive tumors becoming refractory to treatment, due to the emergence of drug-resistant tumor cells. This review highlights a prominent role for epigenetics, particularly aberrant DNA methylation and histone acetylation, in both intrinsic and acquired drug-resistance genetic pathways in ovarian cancer. Administration of therapies that reverse epigenetic "silencing" of tumor suppressors and other genes involved in drug response cascades could prove useful in the management of drug-resistant ovarian cancer patients. In this review, we summarize recent advances in the use of methyltransferase and histone deacetylase inhibitors and possible synergistic combinations of these to achieve maximal tumor suppressor gene re-expression. Moreover, when used in combination with conventional chemotherapeutic agents, epigenetic-based therapies may provide a means to resensitize ovarian tumors to the proven cytotoxic activities of conventional chemotherapeutics.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2003

The androgen receptor gene is preferentially hypermethylated in follicular non-Hodgkin's lymphomas.

This investigation examined promoter DNA methylation of the androgen receptor (AR) gene in non-Hodgkin's lymphoma (NHL) representing different stages of B-cell differentiation. Steroid hormones are important endocrine messengers with a broad range of physiological functions, including regulation of B-cell lymphopoiesis. Some of these effects are mediated via specific receptors such as AR that can act as a ligand-dependent transcription factor for other genes. DNA was isolated from 76 NHL specimens representing pregerminal center, germinal center, and postgerminal center states of differentiation. Initial methylation data were obtained from oligonucleotide microarrays and was confirmed and extended using methylation-specific PCR. Methylation of the AR gene promoter was present in a nonrandom pattern. Those tumors derived from pregerminal center or postgerminal center stages showed virtually no methylation and expressed AR mRNA. Cases of germinal center origin, mainly follicular lymphomas and some diffuse large B-cell lymphomas, showed hypermethylation. Studies with NHL cell lines revealed that demethylation or reversal of histone deacetylation partially restored AR expression but reversal of both simultaneously provided a synergistic release from suppression. Promoter methylation of AR occurs in a differentiation stage-selective manner; those cases arising in the germinal center are preferentially methylated. Full re-expression of AR requires both demethylation and reacetylation, a finding that may affect treatment decisions.

Cell Line, Tumor↗

PubMed2003

Analysis of Myc bound loci identified by CpG island arrays shows that Max is essential for Myc-dependent repression.

The c-myc proto-oncogene encodes a transcription factor, c-Myc, which is deregulated and/or overexpressed in many human cancers. Despite c-Myc's importance, the identity of Myc-regulated genes and the mechanism by which Myc regulates these genes remain unclear. By combining chromatin immunoprecipitation with CpG island arrays, we identified 177 human genomic loci that are bound by Myc in vivo. Analyzing a cohort of known and novel Myc target genes showed that Myc-associated protein X, Max, also bound to these regulatory regions. Indeed, Max is bound to these loci in the presence or absence of Myc. The Myc:Max interaction is essential for Myc-dependent transcriptional activation; however, we show that Max bound targets also include Myc-repressed genes. Moreover, we show that the interaction between Myc and Max is essential for gene repression to occur. Taken together, the identification and analysis of Myc bound target genes supports a model whereby Max plays an essential and universal role in the mechanism of Myc-dependent transcriptional regulation.

CpG Islands↗

PubMed2003

Aberrant DNA methylation in ovarian cancer: is there an epigenetic predisposition to drug response?

Epigenetic regulation of gene expression has been observed in a variety of tumor types. We have used microarray technology to evaluate the predisposition of drug response by aberrant methylation in ovarian cancer. Results indicate that loss of gene activity due to hypermethylation potentially confers a predisposition in certain cancer types and is an early event in disease progression. Methylation profiles of ovarian cancer might be useful for early cancer detection and prediction of chemotherapy outcome in a clinical context.

Antineoplastic Agents↗

PubMed2002

Use of CpG island microarrays to identify colorectal tumors with a high degree of concurrent methylation.

We provide a comprehensive description of our microarray-based technique for the simultaneous detection of multiple CpG islands in cancer. Amplicons from tumor and control samples were pools of differentially methylated CpG island fragments hybridized to a panel of approximately 8000 CpG island tags. Data analysis identified 694 CpG island loci hypermethylated in a group of 14 colorectal tumors. The Stanford hierarchical cluster algorithm segregated the tumors into two subgroups, one of which exhibited a high level of concurrent hypermethylation while the other had little or no methylation. This is in agreement with previous observations of a CpG island methylation phenotype present in colorectal tumors. The present study demonstrates that this microarray-based technique is useful in classifying tumors according to their methylation profiles.

Algorithms↗