Dataset Information

Early prediction of response to Vorinostat in an orthotopic rat glioma model.

ABSTRACT: Glioblastoma is the most common primary brain tumor and is uniformly fatal despite aggressive surgical and adjuvant therapy. As survival is short, it is critical to determine the value of therapy early on in treatment. Improved early predictive assessment would allow neuro-oncologists to personalize and adjust or change treatment sooner to maximize the use of efficacious therapy. During carcinogenesis, tumor suppressor genes can be silenced by aberrant histone deacetylation. This epigenetic modification has become an important target for tumor therapy. Suberoylanilide hydroxamic acid (SAHA, Vorinostat, Zolinza) is an orally active, potent inhibitor of histone deacetylase (HDAC) activity. A major shortcoming of the use of HDAC inhibitors in the treatment of patients with brain tumors is the lack of reliable biomarkers to predict and determine response. Histological evaluation may reflect tumor viability following treatment, but is an invasive procedure and impractical for glioblastoma. Another problem is that response to SAHA therapy is associated with tumor redifferentiation and cytostasis rather than tumor size reduction, thus limiting the use of traditional imaging methods. A noninvasive method to assess drug delivery and efficacy is needed. Here, we investigated whether changes in (1)H MRS metabolites could render reliable biomarkers for an early response to SAHA treatment in an orthotopic animal model for glioma. Untreated tumors exhibited significantly elevated alanine and lactate levels and reduced inositol, N-acetylaspartate and creatine levels, typical changes reported in glioblastoma relative to normal brain tissues. The (1)H MRS-detectable metabolites of SAHA-treated tumors were restored to those of normal-like brain tissues. In addition, reduced inositol and N-acetylaspartate were found to be potential biomarkers for mood alteration and depression, which may also be alleviated with SAHA treatment. Our study suggests that (1)H MRS can provide reliable metabolic biomarkers at the earliest stage of SAHA treatment to predict the therapeutic response.

SUBMITTER: Wei L

PROVIDER: S-EPMC3356508 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Early prediction of response to Vorinostat in an orthotopic rat glioma model.

Wei Li L Hong Samuel S Yoon Younghyoun Y Hwang Scott N SN Park Jaekeun C JC Zhang Zhaobin Z Olson Jeffrey J JJ Hu Xiaoping P XP Shim Hyunsuk H

NMR in biomedicine 20120202 9

Glioblastoma is the most common primary brain tumor and is uniformly fatal despite aggressive surgical and adjuvant therapy. As survival is short, it is critical to determine the value of therapy early on in treatment. Improved early predictive assessment would allow neuro-oncologists to personalize and adjust or change treatment sooner to maximize the use of efficacious therapy. During carcinogenesis, tumor suppressor genes can be silenced by aberrant histone deacetylation. This epigenetic modi ...[more]

PMID: 22302519

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Project description:Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities.Implementation of our algorithm on data obtained from an animal (rat) burn injury study identified 281 genes corresponding to 4 unique profiles. Enrichment evaluation upon both gene ontologies and transcription factors, verifies the inflammation-specific character of the selections and the rationalization of the burn-induced inflammatory response. Conducting the transcription network reconstruction and analysis, we have identified transcription factors, including AHR, Octamer Binding Proteins, Kruppel-like Factors, and cell cycle regulators as being highly important to an organism's response to burn response. These transcription factors are notable due to their roles in pathways that play a part in the gross physiological response to burn such as changes in the immune response and inflammation.Our results indicate that our novel selection/classification algorithm has been successful in selecting out genes with play an important role in thermal injury. Additionally, we have demonstrated the value of an integrative approach in identifying possible points of intervention, namely the activation of certain transcription factors that govern the organism's response.

Dataset Information

Early prediction of response to Vorinostat in an orthotopic rat glioma model.

Publications

Early prediction of response to Vorinostat in an orthotopic rat glioma model.

Similar Datasets

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