Research Interests
The goal of our laboratory is to elucidate the molecular events associated with the progression of colon cancer, with particular focus on changes in gene expression that occur during transitions between stages of significantly different probabilities of good clinical outcome. Two such transitions are of great interest, and the necessary reagents are now available to us for study. First, we seek to identify alterations in gene expression that are diagnostic for the transition from node-negative (T3N0M0) to node-positive (T3N2M0), two states with very significantly different clinical courses and treatment regimens. Once identified, these diagnostic genes will then be assessed for their predictive value in a retrospective analysis of a large set of tumors for which node status and outcome data is available. The gene expression signature will allow for a rapid and more sensitive identification of node-positive tumors, and elucidate the molecular mechanism of the transition between these two clinically important biological states. Second, we seek to identify alterations in gene expression signature that accompany loss of heterozygosity along chromosomal arms 8p and 18q, and to use this data to identify tumor suppressors located in these regions. Patients with mismatch repair proficient tumors that have retained both arms have a 100% 5-year survival rate, while those patients with LOH at both locations have only a 40% 5-year survival rate. LOH at these two locations is therefore a more accurate prognostic indicator than is histopathologic grade. However, LOH is tedious and technically demanding, and not practical for clinical deployment. Measurements of the expression levels of a small, highly informative subset of genes is a reasonable surrogate, and will allow for the identification of high-risk early stage tumors for which adjuvant therapy should be indicated. SAGE is a method of gene expression analysis that will allow the identification of unknown genes. Our analysis of alterations in expression of tumors with and without LOH may reveal unknown genes mapping to previously identified minimally lost regions, which are candidate tumor suppressor genes to be evaluated for mutations.
Recent Publications
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.
Sjòblom 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.
|
