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Gregory N Fuller

Publications and source records attributed to Gregory N Fuller.

63 records · Page 4Linked to original sources
PubMed2002

Toward better early-phase brain tumor clinical trials: a reappraisal of current methods and proposals for future strategies.

Although no optimal treatment is currently available for malignant brain tumors, as the molecular mechanisms underlying brain tumor development have been delineated, new chemotherapeutic agents that act directly on specific molecular targets have become available. Defining a specific molecular target raises the possibility that the molecular effects of a given agent can be analyzed in patients in a clinical trial. Specifically, whereas standard phase I and II clinical trials classically determine the safety and efficacy of agents by using indirect global end points, these new biological agents afford the opportunity to incorporate molecular end points into phase I and II clinical trials to determine whether the agent under investigation is actually doing what it was intended to do. This work presents avenues for improving current brain tumor clinical trial designs based on the molecular specificity of new agents and the unique features of brain tumors. Specifically, the authors recommend brain-applicable phase I and II clinical trial strategies that take advantage of the targeted nature of new agents to maximize information about their efficacy, toxicity, and molecular effects.

Brain Neoplasms↗
PubMed2002

Necrosis and glioblastoma: a friend or a foe? A review and a hypothesis.

OBJECTIVE: Two main forms of cell death are encountered in biology: apoptosis (i.e., programmed cell death) and necrosis (i.e., accidental cell death). Because necrosis and apoptosis can lead to cell removal, one might intuit that they are both desirable in cancer treatment. However, in the setting of glioblastoma multiforme, a malignant brain tumor for which the presence of necrosis is an important diagnostic feature, clinical studies indicate that as the degree of necrosis advances, the patient's prognosis worsens. Despite the apparent importance of this form of cell death, the mechanism of development of necrosis in glioblastomas remains unelucidated. The purpose of this article is to try to resolve this dilemma by hypothesizing the mechanism of necrosis formation in these tumors. METHODS: On the basis of an extensive review of the literature, we present a hypothesis for the mechanism of necrosis formation in glioblastoma multiforme. RESULTS: One of the many possible pathways leading to necrosis formation may involve increased tumor cell secretion of tumor necrosis factor. Procoagulation and antiapoptotic mechanisms resulting from certain pathways could prevent the completion of tumor necrosis factor-induced apoptosis and could promote necrosis as the final mode of cell death. Such a hypothesis would explain the inverse correlation that exists between tumor necrosis and the survival of patients with glioblastomas, because the hypoxia that results from procoagulation selects for tumor cells that are more aggressive and more resistant to apoptosis-inducing therapies. CONCLUSION: A complete understanding of the series of events surrounding necrosis development in glioblastomas that is evidence-based is likely to provide targets for future therapies. On the basis of the potential mechanisms of development of necrosis described in this article, we postulate that effective therapies may have to be directed against the pathways that result in the formation of necrosis.

Apoptosis↗
PubMed2002

Sacrococcygeal ganglioneuroma.

Ganglioneuromas are benign slow-growing masses that can be treated with complete surgical extirpation without any adjuvant therapy. Such lesions involving the sacrococcygeal region are exceedingly rare. The authors present the case of a 70-year-old woman with a sacrococcygeal ganglioneuroma treated by total en bloc resection. This patient also had a previous coccygeal fracture. To the authors' knowledge, there are no other reports of ganglioneuroma in association with a history of trauma.

Aged↗
PubMed2002

Insulin-like growth factor binding protein 2: gene expression microarrays and the hypothesis-generation paradigm.

A major goal of modern medicine is to identify key genes and their products that are altered in the diseased state and to elucidate the molecular mechanisms underlying disease development, progression, and resistance to therapy. This is a daunting task given the exceptionally high complexity of the human genome. The paradigm for research has historically been hypothesis-driven despite the fact that the hypotheses under scrutiny often rest on tenuous subjective grounds or are derived from and dependent on chance observation. The imminent deciphering of the complete human genome, coupled with recent advances in high-throughput bioanalytical technology, has made possible a new paradigm in which data-based hypothesis-generation is the initial step in the investigative process, followed by hypothesis-testing. Genomics technologies are the primary source of the new hypothesis-generating capabilities that are now empowering biomedical researchers. The synergistic interaction between contemporary genomics technologies and the hypothesis-generation paradigm is well-illustrated by the discovery and subsequent ongoing study of the role of insulin-like growth factor binding protein 2 (IGFBP2) in human glioma biology. Using gene expression microarray technology, the IGFBP2 gene was recently found to be highly and differentially overexpressed in the most advanced grade of human glioma, glioblastoma. Based on this discovery, subsequent functional studies were initiated that suggest that IGFBP2 overexpression may contribute to the invasive nature of glioblastoma, and that IGFBP2 may exert its function via a newly identified novel binding protein. The IGFBP2 story is but one example of the power and potential of the new molecular methodologies that are transforming modern diagnostic and investigative neuropathology.

Brain Neoplasms↗
PubMed2002

Tissue microarrays: applications in neuropathology research, diagnosis, and education.

Tissue microarrays (TMAs) are composite paraffin blocks constructed by extracting cylindrical tissue core "biopsies" from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be composited into a single paraffin block. Tissue microarrays permit high-volume simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and utilization of limited and irreplaceable archival tissue samples. This versatile technique facilitates retrospective and prospective human tissue studies, animal tissue studies, and cell line cytospin cell block studies. In this review, we present the technical aspects of TMA construction and sectioning, validation aspects of the technique, TMA advantages and limitations, and a sampling of the broad range of TMA uses in modern neuropathologic clinical diagnosis, research, and education. A specific illustration of the most widely employed and increasingly important TMA application is also presented: confirmation via TMA-based immunohistochemistry of the differential expression of a marker (IGFBP2) initially identified by gene expression profiling to be overexpressed in glioblastoma.

Animals↗
PubMed2002

Molecular classification of human diffuse gliomas by multidimensional scaling analysis of gene expression profiles parallels morphology-based classification, correlates with survival, and reveals clinically-relevant novel glioma subsets.

There are several currently employed classification systems for diffuse gliomas that sort tumors based on histological features. Contemporary molecular techniques, however, offer the promise of improved tumor classification and resultant patient stratification for treatment and prognosis. In particular, gene expression profiling has shown exceptional promise for providing an alternative and more objective molecular approach to glioma classification. In this study, we used cDNA array technology to profile the gene expression of 30 primary human glioma tissue samples comprising 4 different glioma subtypes as defined by current World Health Organization (WHO 2000) criteria: glioblastoma (GM, WHO grade IV), anaplastic astrocytoma (AA, WHO grade III), anaplastic oligodendroglioma (AO, WHO grade III), and oligodendroglioma (OL, WHO grade II). Gene expression data alone were used to group the tumors using multidimensional scaling, which is an unsupervised statistical method. Results show that impressive separation of the 4 glioma subtypes can be achieved solely on the basis of molecular data. In addition, a subcluster of 3 glioblastomas was identified as distinct from other GMs and from the oligodendroglial tumors. These 3 patients have shown extended survival compared to other GMs in the study. Survival analysis of the full data set revealed a good correlation with the molecular classification. Results of this proof-of-principle study demonstrate that molecular profiling alone can recapitulate conventional histologic classification and grading with high fidelity. In addition, results show that the molecular approach to tumor classification can generate clinically meaningful patient stratification, and, more importantly, is an efficient class-discovery tool for human gliomas, permitting the identification of previously unrecognized, clinically relevant tumor subsets.

Algorithms↗
PubMed2002

Genetic modeling of glioma formation in mice.

In addition to the histological features that define gliomas, mutations and other alterations in gene expression and signal transduction are classically found in these tumors. Some of these alterations are likely to be the effects of the neoplastic phenotype, while others may be causative agents essential to the etiologic origin of the disease. The determination of whether specific genetic alterations, either individually or in combination, can serve as the etiology of gliomas requires modeling in animals with the fulfillment of Koch's postulates. Animal modeling studies not only provide information on the potential causes of glioma formation, they also identify novel candidate targets for therapy and provide tumor-bearing animals for preclinical trials. Recently, remarkable strides have been made in the generation of mouse models of the diffuse gliomas that provide unparalleled opportunities for advancing our knowledge of the etiology, maintenance, and treatment of this lethal class of tumors.

Animals↗
PubMed2002

Identification of combination gene sets for glioma classification.

One goal for the gene expression profiling of cancer tissues is to identify signature genes that robustly distinguish different types or grades of tumors. Such signature genes would ideally provide a molecular basis for classification and also yield insight into the molecular events underlying different cancer phenotypes. This study applies a recently developed algorithm to identify not only single classifier genes but also gene sets (combinations) for use as glioma classifiers. Classifier genes identified by this algorithm are shown to be strong features by conservatively and collectively considering the misclassification errors of the feature sets. Applying this approach to a test set of 25 patients, we have identified the best single genes and two- to three-gene combinations for distinguishing four types of glioma: (a) oligodendroglioma; (b) anaplastic oligodendroglioma; (c) anaplastic astrocytoma; and (d) glioblastoma multiforme. Some of the identified genes, such as insulin-like growth factor-binding protein 2, have been confirmed to be associated with one of the tumor types. Using combinations of genes, the classification error rate can be significantly lowered. In many instances, neither of the individual genes of a two-gene set performs well as an accurate classifier, but the combination of the two genes forms a robust classifier with a small error rate. Two-gene and three-gene combinations thus provide robust classifiers possessing the potential to translate expression microarray results into diagnostic histopathological assays for clinical utilization.

Algorithms↗