||5R03CA094746-02 Interpret this number
||Ut Md Anderson Cancer Ctr
||Metabolic Polymorphisms and Survival From Brain Tumors
DESCRIPTION (provided by applicant):
The outcome for patients with primary malignant brain tumors is poor. Radiotherapy and chemotherapy have improved the outcome, especially in the chemotherapy-sensitive group of tumors such as anaplastic astrocytoma and anaplastic oligodendroglioma. Yet it is not possible to identify the patients who will benefit from such treatments in advance. Inherited variability in metabolism of therapeutic agents is suggested to be responsible, in part for individual differences in response to cancer treatment. Overall purpose of the proposed study is to investigate the role of genetic polymorphisms in the glutathione s-transferase (GST) enzyme family in predicting survival in 305 patients with anaplastic astrocytoma, anaplastic oligodendroglioma and anaplastic oligoastrocytoma, treated at the University of Texas MD Anderson Cancer Center between 1994 and 2004. We hypothesize that patients with inherent low GST activity have reduced clearance of reactive agents of chemo- and radiotherapy and are more likely to have a better treatment effect at the tumor site. Further, we predict that individuals with low activity GST genotypes will have increased survival time when compared to those with inherently high GST activity. We will determine the frequencies of GSTM1, GSTT1, and GSTP1 polymorphisms in 350 cases by polymerase chain reaction and restriction fragment length polymorphisms. We will review medical records of the 350 patients and abstract information on outcome, treatment and clinically significant adverse events related to radiotherapy and, chemotherapy that required delaying or cessation of treatment. To assess if GST polymorphisms are associated with outcome in patients with primary malignant brain tumor we will perform Kaplan-Meier and Cox proportional hazard analyses. To explore whether metabolic polymorphisms of the GST enzyme family are correlated with occurrence of adverse effects secondary to chemotherapy we will use logistic regression, Kaplan-Meier and Cox proportional hazard analyses. Based on the results of the proposed study, in the future chemotherapy regimens can be tailored according to individual patient's metabolic enzyme profile. Thus, patients who can tolerate higher doses of chemotherapy can be treated more efficiently, suffering from less side effects and potentially may have a better outcome.
Last Updated: August 24, 2012