Biomedical subjects

Phillip Buckhaults

Publications and source records attributed to Phillip Buckhaults.

5 recordsLinked to original sources

PubMed2006

The consensus coding sequences of human breast and colorectal cancers.

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.

Amino Acid Substitution↗

PubMed2006

Gene expression determinants of clinical outcome.

PURPOSE OF REVIEW: Gene expression profiling of human cancers has produced a large amount of information that could aid physicians in making decisions related to the treatment of their patients. A number of recent studies have identified collections of genes and corresponding expression levels that correlate with the physical appearance and clinical behavior of all common human neoplasms. RECENT FINDINGS: This article will discuss emerging trends of study design and approaches to gene expression signature identification. Recently discovered gene expression signatures that correlate with cellular morphology, resistance to chemotherapy, and overall clinical course of disease are discussed. SUMMARY: The prospective evaluation of the predictive value of a number of gene signatures is now appropriate. Newly discovered gene expression signatures that correlate with disease clinical course should be independently evaluated. The timely reporting of both positive and negative results from such validation attempts will be crucial to the advancement of molecular pathology.

Drug Resistance, Neoplasm↗

PubMed2004

Identification of a binding partner for the endothelial cell surface proteins TEM7 and TEM7R.

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.

Alternative Splicing↗

PubMed2004

Serum macrophage inhibitory cytokine 1 as a marker of pancreatic and other periampullary cancers.

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.

Adenocarcinoma↗

PubMed2003

Identifying tumor origin using a gene expression-based classification map.

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.

Adenocarcinoma↗