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Featured researches published by David Shibata.


Oncogene | 2002

Application of cDNA microarrays to generate a molecular taxonomy capable of distinguishing between colon cancer and normal colon

Tong Tong Zou; Florin M. Selaru; Yan Xu; Valentina Shustova; Jing Yin; Yuriko Mori; David Shibata; Fumiaki Sato; Suma Wang; Andreea Olaru; Elena Deacu; Thomas C. Liu; John M. Abraham; Stephen J. Meltzer

In order to discover global gene expression patterns characterizing subgroups of colon cancer, microarrays were hybridized to labeled RNAs obtained from seventeen colonic specimens (nine carcinomas and eight normal samples). Using a hierarchical agglomerative method, the samples grouped naturally into two major clusters, in perfect concordance with pathological reports (colon cancer versus normal colon). Using a variant of the unpaired t-test, selected genes were ordered according to an index of importance. In order to confirm microarray data, we performed quantitative, real-time reverse transcriptase–polymerase chain reaction (TaqMan RT–PCR) on RNAs from 13 colorectal tumors and 13 normal tissues (seven of which were matched normal-tumor pairs). RT–PCR was performed on the gro1, B-factor, adlican, and endothelin converting enzyme-1 genes and confirmed microarray findings. Two hundred and fifty genes were identified, some of which were previously reported as being involved in colon cancer. We conclude that cDNA microarraying, combined with bioinformatics tools, can accurately classify colon specimens according to current histopathological taxonomy. Moreover, this technology holds promise of providing invaluable insight into specific gene roles in the development and progression of colon cancer. Our data suggests that a large-scale approach may be undertaken with the purpose of identifying biomarkers relevant to cancer progression.


Oncogene | 2002

Global gene expression profiling in Barrett's esophagus and esophageal cancer: a comparative analysis using cDNA microarrays

Florin M. Selaru; Tongtong Zou; Yan Xu; Valentina Shustova; Jing Yin; Yuriko Mori; Fumiako Sato; Suna Wang; Andreea Olaru; David Shibata; Bruce D. Greenwald; Mark J. Krasna; John M. Abraham; Stephen J. Meltzer

In order to identify and contrast global gene expression profiles defining the premalignant syndrome, Barretts esophagus, as well as frank esophageal cancer, we utilized cDNA microarray technology in conjunction with bioinformatics tools. We hybridized microarrays, each containing 8000 cDNA clones, to RNAs extracted from 13 esophageal surgical or endoscopic biopsy specimens (seven Barretts metaplasias and six esophageal carcinomas). Hierarchical cluster analysis was performed on these results and displayed using a color-coded graphic representation (Treeview). The esophageal samples clustered naturally into two principal groups, each possessing unique global gene expression profiles. After retrieving histologic reports for these tissues, we found that one main cluster contained all seven Barretts samples, while the remaining principal cluster comprised the six esophageal cancers. The cancers also clustered according to histopathological subtype. Thus, squamous cell carcinomas (SCCAs) constituted one group, adenocarcinomas (ADCAs) clustered separately, and one signet-ring carcinoma was in its own cluster, distinct from the ADCA cluster. We conclude that cDNA microarrays and bioinformatics show promise in the classification of esophageal malignant and premalignant diseases, and that these methods can be applied to small biopsy samples.


Diseases of The Colon & Rectum | 2002

Surgical Management of Isolated Retroperitoneal Recurrences of Colorectal Carcinoma

David Shibata; Philip B. Paty; Jose G. Guillem; W. Douglas Wong; Alfred M. Cohen

AbstractPURPOSE: Isolated locoregional disease accounts for approximately 20 percent of recurrences after treatment for colorectal cancer. It has been suggested that complete resection of these recurrences can result in increased survival. The value of surgery for isolated retroperitoneal recurrences has not been well defined. We have sought to characterize outcome and survival in patients undergoing resection for isolated retroperitoneal recurrences of colorectal cancer. METHODS: From a prospective database, 25 patients were identified as having undergone surgical exploration with curative intent for isolated retroperitoneal recurrences of colorectal cancer between 1988 and 1999. Variables studied included age, gender, location and size of the tumor, extent of resection, disease-free interval, and morbidity and mortality. Statistical analyses were performed using the log-rank test and Kaplan-Meier estimates, with overall survival as the primary end point. RESULTS: The study population consisted of 25 patients (13 males), with a median age of 55 years and a median follow-up of 29 (range, 1–151) months. The median time to first retroperitoneal recurrence was 23 (range, 3–72) months. Twenty patients underwent resection, whereas five patients were deemed unresectable at the time of operation. The median survival in patients who underwent resection patients was 31 months compared with 3 months in those patients who did not undergo resection (P = 0.0001). Analysis of the entire group demonstrated a disease-free interval of greater than 24 months to be a positive predictor of outcome (median survival, 30 vs. 48 months; P = 0.02). For patients undergoing resection, the presence of positive margins (P = 0.01) and tumor size ≥5 cm (P = 0.008) predicted a worse prognosis. In patients who underwent resection, the two-year and five-year overall survival rates were 60 and 15 percent, respectively. CONCLUSIONS: Patients with isolated retroperitoneal recurrences of colorectal cancer generally have a poor prognosis. However, a longer disease-free interval, complete negative-margin resection, and smaller tumor size are associated with long-term survival in selected patients.


Cancer Research | 2004

An Unsupervised Approach to Identify Molecular Phenotypic Components Influencing Breast Cancer Features

Florin M. Selaru; Jing Yin; Andreea Olaru; Yuriko Mori; Yan Xu; Steven H. Epstein; Fumiaki Sato; Elena Deacu; Suna Wang; Anca Sterian; Amy M. Fulton; John M. Abraham; David Shibata; Claudia R. Baquet; Sanford A. Stass; Stephen J. Meltzer

To discover a biological basis for clinical subgroupings within breast cancers, we applied principal components (PCs) analysis to cDNA microarray data from 36 breast cancers. We correlated the resulting PCs with clinical features. The 35 PCs discovered were ranked in order of their impact on gene expression patterns. Interestingly, PC 7 identified a unique subgroup consisting of estrogen receptor (ER); (+) African-American patients. This group exhibited global molecular phenotypes significantly different from both ER (−) African-American women and ER (+) or ER (−) Caucasian women (P < 0.001). Additional significant PCs included PC 4, correlating with lymph node metastasis (P = 0.04), and PC 10, with tumor stage (stage 2 versus stage 3; P = 0.007). These results provide a molecular phenotypic basis for the existence of a biologically unique subgroup comprising ER (+) breast cancers from African-American patients. Moreover, these findings illustrate the potential of PCs analysis to detect molecular phenotypic bases for relevant clinical or biological features of human tumors in general.


Laboratory Investigation | 2003

Loss of Heterozygosity and Mutational Analyses of the ACTRII Gene Locus in Human Colorectal Tumors

Andreea Olaru; Yuriko Mori; Jing Yin; Suna Wang; Martha C. Kimos; Kellie Perry; Yan Xu; Fumiaki Sato; Florin M. Selaru; Elena Deacu; Anca Sterian; David Shibata; John M. Abraham; Stephen J. Meltzer

The activin type II receptorgene (ACTRII) is mutated in 58.1% of microsatellite-unstable (MSI-H) colorectal cancers and is a close relative of the TGFβ-1 type II receptor, which is known to be involved in both MSI-H and non–MSI-H colorectal carcinogenesis. We therefore sought to determine whether ACTRII was involved in non–MSI-H colorectal cancers. We evaluated ACTRII inactivation by allelic deletion, loss of mRNA expression, or somatic mutation in 51 non–MSI-H colon cancers. Loss of heterozygosity (LOH) at the ACTRII locus (2q23.1) was found in 9 (17.6%) of 51 primary tumors. Loss of ACTRII mRNA expression was seen in one (14.3%) of the seven LOH-positive primary tumors from which total RNA was available. We also performed DNA sequencing analysis of tumors showing LOH. One LOH-positive primary tumor exhibited a novel germline missense sequence alteration (amino acid substitution, 117 Ile to Phe) that was not found in 23 additional normal individuals, implying that this alteration is not a frequent polymorphism. We conclude that ACTRII is probably involved in both non–MSI-H and MSI-H colorectal carcinogenesis, but more frequently in the latter subgroup.


Oncogene | 2003

An LOH and mutational investigation of the ST7 gene locus in human esophageal carcinoma

Suna Wang; Yuriko Mori; Fumiaki Sato; Jing Yin; Yan Xu; Tong Tong Zou; Andreea Olaru; Martha C. Kimos; Kellie Perry; Florin M. Selaru; Elena Deacu; Menghong Sun; Ying Chang Shi; David Shibata; John M. Abraham; Bruce D. Greenwald; Stephen J. Meltzer

Frequent loss of heterozygosity (LOH) on human chromosome 7q31 has been reported in numerous malignancies. Suppressor of tumorigenicity 7 (ST7) has been identified as a candidate tumor suppressor gene in this region. To identify whether 7q31 and genetic alterations of ST7 were involved in human esophageal carcinogenesis, we performed LOH mapping of a 5.4 cM region at 7q31-q35 in 43 primary esophageal carcinomas, as well as mutational analyses of the ST7 gene in tumors with LOH in this region. Of 43 tumors, 12 (28%) showed LOH at 7q31–q35. These included four (22%) of 18 squamous cell carcinomas and eight (32%) of 25 adenocarcinomas. The peak LOH locus was D7S480, lying 4.2 Mb telomeric to ST7 and showing LOH in eight of 37 informative tumors, or 22%. No mutations were found in the entire coding or flanking intronic regions of the ST7 gene among 12 tumors with 7q-LOH. In addition, quantitative RT–PCR analyses of ST7 mRNA expression levels in 11/13 normal-tumor pairs failed to show more than a 50% decrease in tumor ST7 mRNA relative to matched normal tissues. These data suggest that LOH at 7q31–q35 is involved in the origin or progression of at least a subset of esophageal carcinomas, but that ST7 is not the target gene of this somatic event.


Cancer Research | 2002

Artificial Neural Networks and Gene Filtering Distinguish Between Global Gene Expression Profiles of Barrett’s Esophagus and Esophageal Cancer

Yan Xu; Florin M. Selaru; Jing Yin; Tong Tong Zou; Valentina Shustova; Yuriko Mori; Fumiaki Sato; Thomas C. Liu; Andreea Olaru; Suna Wang; Martha C. Kimos; Kellie Perry; Kena Desai; Bruce D. Greenwald; Mark J. Krasna; David Shibata; John M. Abraham; Stephen J. Meltzer


Cancer Research | 2002

Hypermethylation of the p14ARF Gene in Ulcerative Colitis-associated Colorectal Carcinogenesis

Fumiaki Sato; Noam Harpaz; David Shibata; Yan Xu; Jing Yin; Yuriko Mori; Tong Tong Zou; Suna Wang; Kena Desai; Anatoly Leytin; Florin M. Selaru; John M. Abraham; Stephen J. Meltzer


Gastroenterology | 2002

Artificial neural networks distinguish among subtypes of neoplastic colorectal lesions

Florin M. Selaru; Yan Xu; Jing Yin; Tong Zou; Thomas C. Liu; Yuriko Mori; John M. Abraham; Fumiaki Sato; Suna Wang; Charlie Twigg; Andreea Olaru; Valentina Shustova; Anatoly Leytin; Prodromos Hytiroglou; David Shibata; Noam Harpaz; Stephen J. Meltzer


Cancer Research | 2002

Instabilotyping Reveals Unique Mutational Spectra in Microsatellite-Unstable Gastric Cancers

Yuriko Mori; Fumiaki Sato; Florin M. Selaru; Andreea Olaru; Kellie Perry; Martha C. Kimos; Gen Tamura; Nagahide Matsubara; Suna Wang; Yan Xu; Jing Yin; Tong Tong Zou; B A Leggett; Joanne Young; Toshihiro Nukiwa; O. Colin Stine; John M. Abraham; David Shibata; Stephen J. Meltzer

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Yuriko Mori

Johns Hopkins University

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Jing Yin

University of Maryland

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Stephen J. Meltzer

Johns Hopkins University School of Medicine

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John M. Abraham

Johns Hopkins University School of Medicine

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Suna Wang

University of Maryland

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Yan Xu

University of Maryland

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Elena Deacu

University of Maryland

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