Search PubMed for publications by Dr Buckhaults
The genomic landscapes of human breast and
colorectal cancers.
Wood LD, Parsons DW, Jones S, Lin J, Sjöblom T, Leary RJ, Shen D, Boca SM,
Barber T, Ptak J, Silliman N, Szabo S, Dezso Z, Ustyanksky V, Nikolskaya T,
Nikolsky Y, Karchin R, Wilson PA, Kaminker JS, Zhang Z, Croshaw R, Willis J,
Dawson D, Shipitsin M, Willson JK, Sukumar S, Polyak K, Park BH, Pethiyagoda CL,
Pant PV, Ballinger DG, Sparks AB, Hartigan J, Smith DR, Suh E, Papadopoulos N,
Buckhaults P, Markowitz SD, Parmigiani G, Kinzler KW, Velculescu VE, Vogelstein
B.
Science. 2007 Nov 16;318(5853):1108-13.
Human cancer is caused by the accumulation of mutations in oncogenes and tumor
suppressor genes. To catalog the genetic changes that occur during tumorigenesis,
we isolated DNA from 11 breast and 11 colorectal tumors and determined the
sequences of the genes in the Reference Sequence database in these samples.
Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we
conclude that the genomic landscapes of breast and colorectal cancers are
composed of a handful of commonly mutated gene "mountains" and a much larger
number of gene "hills" that are mutated at low frequency. We describe
statistical and bioinformatic tools that may help identify mutations with a role
in tumorigenesis. These results have implications for understanding the nature
and heterogeneity of human cancers and for using personal genomics for tumor
diagnosis and therapy.
The consensus coding sequences of human breast and colorectal cancers.
Sjöblom T, Jones S, Wood LD, Parsons DW, Lin J, Barber TD, Mandelker D, Leary
RJ, Ptak J, Silliman N, Szabo S, Buckhaults P, Farrell C, Meeh P, Markowitz SD,
Willis J, Dawson D, Willson JK, Gazdar AF, Hartigan J, Wu L, Liu C, Parmigiani
G, Park BH, Bachman KE, Papadopoulos N, Vogelstein B, Kinzler KW, Velculescu VE.
Science. 2006 Oct 13;314(5797):268-74
The elucidation of the human genome sequence has made it possible to identify
genetic alterations in cancers in unprecedented detail. To begin a systematic
analysis of such alterations, we determined the sequence of well-annotated human
protein-coding genes in two common tumor types. Analysis of 13,023 genes in 11
breast and 11 colorectal cancers revealed that individual tumors accumulate an
average of approximately 90 mutant genes but that only a subset of these
contribute to the neoplastic process. Using stringent criteria to delineate this
subset, we identified 189 genes (average of 11 per tumor) that were mutated at
significant frequency. The vast majority of these genes were not known to be
genetically altered in tumors and are predicted to affect a wide range of
cellular functions, including transcription, adhesion, and invasion. These data
define the genetic landscape of two human cancer types, provide new targets for
diagnostic and therapeutic intervention, and open fertile avenues for basic
research in tumor biology.
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.
For more publications, click
here |
