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PHILLIP J. BUCKHAULTS, PhD
Nanda
A, Buckhaults P, Seaman S, Agrawal N, Boutin P, Shankara S,
Nacht M, Teicher B, Stampfl J, Singh S, Vogelstein B,
Kinzler KW, St Croix B. Identification of a binding partner
for the endothelial cell surface proteins TEM7 and TEM7R.
Cancer Res. 2004 Dec 1;64(23):8507-11
Tumor endothelial marker 7 (TEM7) was
recently identified as an mRNA transcript overexpressed in
the blood vessels of human solid tumors. Here, we identify
several new variants of TEM7, derived by alternative
splicing, that are predicted to be intracellular (TEM7-I),
secreted (TEM7-S), or on the cell surface membrane (TEM7-M)
of tumor endothelium. Using new antibodies against the TEM7
protein, we confirmed the predicted expression of TEM7 on
the cell surface and demonstrated that TEM7-M protein, like
its mRNA, is overexpressed on the endothelium of various
tumor types. We then used an affinity purification strategy
to search for TEM7-binding proteins and identified cortactin
as a protein capable of binding to the extracellular region
of both TEM7 and its closest homologue, TEM7-related
(TEM7R), which is also expressed in tumor endothelium. The
binding domain of cortactin was mapped to a unique
nine-amino acid region in its plexin-like domain. These
studies establish the overexpression of TEM7 protein in
tumor endothelium and provide new opportunities for the
delivery of therapeutic and imaging agents to the vessels of
solid tumors.
Koopmann J, Buckhaults P, Brown DA,
Zahurak ML, Sato N, Fukushima N, Sokoll LJ, Chan DW, Yeo CJ,
Hruban RH, Breit SN, Kinzler KW, Vogelstein B, Goggins M.
Serum macrophage inhibitory cytokine 1 as a marker of
pancreatic and other periampullary cancers. Clin Cancer Res.
2004 Apr 1;10(7):2386-92
PURPOSE: Patients with pancreatic ductal
adenocarcinoma usually present with advanced-stage disease
and a dismal prognosis. One effective strategy likely to
improve the morbidity and mortality from pancreatic cancer
would be the identification of accurate, noninvasive
diagnostic markers that would enable earlier diagnosis of
symptomatic patients and earlier detection of cancer in
asymptomatic individuals at high risk for developing
pancreatic cancer. In this study, we evaluated serum
macrophage inhibitory cytokine-1 (MIC-1) as a marker of
pancreatic cancer. EXPERIMENTAL DESIGN: MIC-1 expression in
primary pancreatic cancers, intraductal papillary mucinous
neoplasms, and pancreatic cancer cell lines was determined
using the National Center for Biotechnology Information
serial analysis of gene expression database, oligonucleotide
microarrays analysis, in situ hybridization, and
immunohistochemistry. Serum MIC-1 levels were determined by
ELISA in 80 patients with pancreatic adenocarcinomas, in 30
patients with ampullary and cholangiocellular carcinomas, in
42 patients with benign pancreatic tumors, in 76 patients
with chronic pancreatitis, and in 97 healthy control
subjects. The diagnostic performance of serum MIC-1 as a
marker of pancreatic cancer was compared with that of serum
CA19-9. RESULTS: Oligonucleotide microarray and serial
analysis of gene expression data demonstrated that MIC-1 RNA
levels were higher in primary pancreatic cancers,
intraductal papillary mucinous neoplasms, and pancreatic
cancer cell lines than in nonneoplastic pancreatic ductal
epithelium. MIC-1 expression was localized to the malignant
epithelium in pancreatic adenocarcinomas by in situ
hybridization. MIC-1 protein was expressed in 14 of 16
primary pancreatic adenocarcinomas (88%) by
immunohistochemistry and was also expressed in some
pancreata affected by pancreatitis but not in normal
pancreas. Serum MIC-1 levels were significantly higher in
patients with pancreatic ductal adenocarcinoma (mean +/- SD,
2428 +/- 2324 pg/ml) and in patients with ampullary and
cholangiocellular carcinomas (2123 +/- 2387 pg/ml) than in
those with benign pancreatic neoplasms (940 +/- 469 pg/ml),
chronic pancreatitis (1364 +/- 1236 pg/ml), or in healthy
controls (546 +/- 262 pg/ml). An elevated serum MIC-1
(defined as 2 SD above the mean for healthy controls)
performed as well as CA19-9 (area under the receiver
operating characteristic curve, 0.81 and 0.77,
respectively), and the combination of MIC-1 and CA19-9
significantly improved diagnostic accuracy (P < 0.05; area
under the receiver operating characteristic curve, 0.87;
sensitivity, 70%; specificity, 85%). CONCLUSION: Serum MIC-1
measurement can aid in the diagnosis of pancreatic
adenocarcinoma.
Buckhaults P, Zhang Z, Chen YC, Wang
TL, St Croix B, Saha S, Bardelli A, Morin PJ, Polyak K,
Hruban RH, Velculescu VE, Shih IeM. Identifying tumor origin
using a gene expression-based classification map. Cancer
Res. 2003 Jul 15;63(14):4144-9 (Cover article)
Identifying the primary site in cases of
metastatic carcinoma of unknown origin has profound clinical
importance in managing cancer patients. Although
transcriptional profiling promises molecular solutions to
this clinical challenge, simpler and more reliable methods
for this purpose are needed. A training set of 11 serial
analysis of gene expression (SAGE) libraries was analyzed
using a combination of supervised and unsupervised
computational methods to select a small group of candidate
genes with maximal power to discriminate carcinomas of
different tissue origins. Quantitative real-time PCR was
used to measure their expression levels in an independent
validation set of 62 samples of ovarian, breast, colon, and
pancreatic adenocarcinomas and normal ovarian surface
epithelial controls. The diagnostic power of this set of
genes was evaluated using unsupervised cluster analysis
methods. From the training set of 21,321 unique SAGE
transcript tags derived from 11 libraries, five genes were
identified with expression patterns that distinguished four
types of adenocarcinomas. Quantitative real-time PCR
expression data obtained from the validation set clustered
tumor samples in an unsupervised manner, generating a
self-organized map with distinctive tumor site-specific
domains. Eighty-one percent (50 of 62) of the carcinomas
were correctly allocated in their corresponding diagnostic
regions. Metastases clustered tightly with their
corresponding primary tumors. A classification map
diagnostic of tumor types was generated based on expression
patterns of five genes selected from the SAGE database. This
expression map analysis may provide a reliable and practical
approach to determine tumor type in cases of metastatic
carcinoma of clinically unknown origin.
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