Biomedical subjects

Dominic Sinibaldi

Publications and source records attributed to Dominic Sinibaldi.

3 recordsLinked to original sources

PubMed2002

Inhibition of Bcr-Abl kinase activity by PD180970 blocks constitutive activation of Stat5 and growth of CML cells.

Chronic myelogenous leukemia (CML) is a myeloproliferative disease characterized by the BCR-ABL genetic translocation and constitutive activation of the Abl tyrosine kinase. Among members of the Signal Transducers and Activators of Transcription (STAT) family of transcription factors, Stat5 is activated by the Bcr-Abl kinase and is implicated in the pathogenesis of CML. We recently identified PD180970 as a new and highly potent inhibitor of Bcr-Abl kinase. In this study, we show that blocking Bcr-Abl kinase activity using PD180970 in the human K562 CML cell line resulted in inhibition of Stat5 DNA-binding activity with an IC(50) of 5 nM. Furthermore, abrogation of Abl kinase-mediated Stat5 activation suppressed cell proliferation and induced apoptosis in K562 cells, but not in the Bcr-Abl-negative myeloid cell lines, HEL 92.1.7 and HL-60. Dominant-negative Stat5 protein expressed from a vaccinia virus vector also induced apoptosis of K562 cells, consistent with earlier studies that demonstrated an essential role of Stat5 signaling in growth and survival of CML cells. RNA and protein analyses revealed several candidate target genes of Stat5, including Bcl-x, Mcl-1, c-Myc and cyclin D2, which were down-regulated after treatment with PD180970. In addition, PD180970 inhibited Stat5 DNA-binding activity in cultured primary leukemic cells derived from CML patients. To detect activated Stat5 in CML patient specimens, we developed an immunocytochemical assay that can be used as a molecular end-point assay to monitor inhibition of Bcr-Abl signaling. Moreover, PD180970 blocked Stat5 signaling and induced apoptosis of STI-571 (Gleevec, Imatinib)-resistant Bcr-Abl-positive cells. Together, these results suggest that the mechanism of action of PD180970 involves inhibition of Bcr-Abl-mediated Stat5 signaling and provide further evidence that compounds in this structural class may represent potential therapeutic agents for CML.

Apoptosis↗

PubMed2002

Constitutive Stat3 activity up-regulates VEGF expression and tumor angiogenesis.

Non-receptor and receptor tyrosine kinases, such as Src and EGF receptor (EGFR), are major inducers of vascular endothelial growth factor (VEGF), one of the most potent mediators of angiogenesis. While tyrosine kinases signal through multiple pathways, signal transducer and activation of transcription 3 (Stat3) is a point of convergence for many of these and is constitutively activated with high frequency in a wide range of cancer cells. Here, we show that VEGF expression correlates with Stat3 activity in diverse human cancer cell lines. An activated Stat3 mutant (Stat3C) up-regulates VEGF expression and stimulates tumor angiogenesis. Stat3C-induced VEGF up-regulation is abrogated when a Stat3-binding site in the VEGF promoter is mutated. Furthermore, interrupting Stat3 signaling with dominant-negative Stat3 protein or Stat3 antisense oligonucleotide in tumor cells down-regulates VEGF expression. Consistent with an important role of Stat3 in VEGF up-regulation induced by various oncogenic tyrosine kinases, v-Src-mediated VEGF expression is inhibited when Stat3 signaling is blocked. Moreover, chromatin immunoprecipitation assays indicate that Stat3 protein binds to the VEGF promoter in vivo and mutation of a Stat3-binding site in the VEGF promoter abrogates v-Src-induced VEGF promoter activity. These studies provide evidence that the VEGF gene is regulated directly by Stat3 protein, and indicate that Stat3 represents a common molecular target for blocking angiogenesis induced by multiple signaling pathways in human cancers.

3T3 Cells↗

PubMed2002

A simple method to improve probe set estimates from oligonucleotide arrays.

A popular commercially available oligonucleotide microarray technology employs sets of 25 base pair oligonucleotide probes for measurement of gene expression levels. A mathematical algorithm is required to compute an estimate of gene expression from the multiple probes. Previously proposed methods for summarizing gene expression data have either been substantially ad hoc or have relied on model assumptions that may be easily violated. Here we present a new algorithm for calculating gene expression from probe sets. Our approach is functionally related to leave-one-out cross-validation, a non-parametric statistical technique that is often applied in limited data situations. We illustrate this approach using data from our study seeking a molecular fingerprint of STAT3 regulated genes for early detection of human cancer.

Algorithms↗