Biomedical subjects

Adam Margolin

Publications and source records attributed to Adam Margolin.

4 recordsLinked to original sources

PubMed2006

NOTCH1 directly regulates c-MYC and activates a feed-forward-loop transcriptional network promoting leukemic cell growth.

The NOTCH1 signaling pathway directly links extracellular signals with transcriptional responses in the cell nucleus and plays a critical role during T cell development and in the pathogenesis over 50% of human T cell lymphoblastic leukemia (T-ALL) cases. However, little is known about the transcriptional programs activated by NOTCH1. Using an integrative systems biology approach we show that NOTCH1 controls a feed-forward-loop transcriptional network that promotes cell growth. Inhibition of NOTCH1 signaling in T-ALL cells led to a reduction in cell size and elicited a gene expression signature dominated by down-regulated biosynthetic pathway genes. By integrating gene expression array and ChIP-on-chip data, we show that NOTCH1 directly activates multiple biosynthetic routes and induces c-MYC gene expression. Reverse engineering of regulatory networks from expression profiles showed that NOTCH1 and c-MYC govern two directly interconnected transcriptional programs containing common target genes that together regulate the growth of primary T-ALL cells. These results identify c-MYC as an essential mediator of NOTCH1 signaling and integrate NOTCH1 activation with oncogenic signaling pathways upstream of c-MYC.

Cell Line↗

PubMed2006

Transcriptional regulatory networks downstream of TAL1/SCL in T-cell acute lymphoblastic leukemia.

Aberrant expression of 1 or more transcription factor oncogenes is a critical component of the molecular pathogenesis of human T-cell acute lymphoblastic leukemia (T-ALL); however, oncogenic transcriptional programs downstream of T-ALL oncogenes are mostly unknown. TAL1/SCL is a basic helix-loop-helix (bHLH) transcription factor oncogene aberrantly expressed in 60% of human T-ALLs. We used chromatin immunoprecipitation (ChIP) on chip to identify 71 direct transcriptional targets of TAL1/SCL. Promoters occupied by TAL1 were also frequently bound by the class I bHLH proteins E2A and HEB, suggesting that TAL1/E2A as well as TAL1/HEB heterodimers play a role in transformation of T-cell precursors. Using RNA interference, we demonstrated that TAL1 is required for the maintenance of the leukemic phenotype in Jurkat cells and showed that TAL1 binding can be associated with either repression or activation of genes whose promoters occupied by TAL1, E2A, and HEB. In addition, oligonucleotide microarray analysis of RNA from 47 primary T-ALL samples showed specific expression signatures involving TAL1 targets in TAL1-expressing compared with -nonexpressing human T-ALLs. Our results indicate that TAL1 may act as a bifunctional transcriptional regulator (activator and repressor) at the top of a complex regulatory network that disrupts normal T-cell homeostasis and contributes to leukemogenesis.

Basic Helix-Loop-Helix Proteins↗

PubMed2005

High-resolution detection and mapping of genomic DNA alterations in neuroblastoma.

We used array-based comparative genomic hybridization (aCGH) to measure genomic copy number alterations (CNAs) in 42 neuroblastoma cell lines with known 1p36.3, 2p24 (MYCN), 11q23, and 17q23 allelic status. All cell lines showed CNAs, with an average of 22.0% of the genome of each sample showing evidence of gain (11.6%) or loss (10.4%). MYCN amplification was detected in 81% of cell lines, but other regions with high-level genomic amplification were observed only rarely. Gain of 17q material was present in 75% of the samples, and four discrete genomic regions at 17q23.2-17q25.3 were defined. Novel regions of gain were identified, including a 2.6-Mb subtelomeric region at 5p that includes the telomerase reverse transcriptase gene (TERT), which was found in 45% of the cell lines. Hemizygous deletions were noted at 1p36.23-1p36.32 and 11q23.3-11q25 in 60% and 36%, respectively, of the samples, with other frequent (>25%) regions of deletion localized to 1p32.1, 3p21.31-3p22.1, 5q35.2-5q35.3, 7q31.2, 7q34, 9q22.3-9q24.1, 10q26.11-10q26.12, 16q23.1-16q24.3, 18q21.32-18q23, and 20p11.21-20p11.23. A smallest region of overlap (SRO) for CNAs was mapped across all experiments and in each case was consistent with or refined the published data. A single cell line showed a homozygous deletion at 3p22.3, which was verified, and this location was refined by FISH and PCR. There was outstanding concordance of aCGH with PCR-based CNA detection methods. Several potential cooperating loci were identified, including deletion of 11q23-25, which was highly associated with both regional gain and loss at multiple chromosomal loci but was inversely correlated with the deletion of 1p36. Taking all of this together indicates that aCGH can accurately measure CNAs in the neuroblastoma genome and facilitate gene discovery efforts by high-throughput refinement of candidate loci.

Cell Line, Tumor↗

PubMed2003

1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis.

Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, widespread utilization of a CGH has been limited by the lack of well characterized, high-resolution clone sets optimized for consistent performance in aCGH assays and specifically designed analytic software. We have assembled a set of approximately 4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at approximately 1-Mb resolution across the genome, which includes direct coverage of approximately 400 known cancer genes. This aCGH-optimized clone set was compiled from five existing sets, experimentally refined, and supplemented for higher resolution and enhancing mapping capabilities. This clone set is associated with a public online resource containing detailed clone mapping data, protocols for the construction and use of arrays, and a suite of analytical software tools designed specifically for aCGH analysis. These resources should greatly facilitate the use of aCGH in gene discovery.

Cell Line, Tumor↗