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1.
Neuroscience ; 309: 224-32, 2015 Nov 19.
Article in English | MEDLINE | ID: mdl-26086545

ABSTRACT

Cancer therapies can be associated with significant central nervous system (CNS) toxicity. While radiation-induced brain damage has been long recognized both in pediatric and adult cancer patients, CNS toxicity from chemotherapy has only recently been acknowledged. Clinical studies suggest that the most frequent neurotoxic adverse effects associated with chemotherapy include memory and learning deficits, alterations of attention, concentration, processing speed and executive function. Preclinical studies have started to shed light on how chemotherapy targets the CNS both on cellular and molecular levels to disrupt neural function and brain plasticity. Potential mechanisms include direct cellular toxicity, alterations in cellular metabolism, oxidative stress, and induction of pro-inflammatory processes with subsequent disruption of normal cellular and neurological function. Damage to neural progenitor cell populations within germinal zones of the adult CNS has been identified as one of the key mechanisms by which chemotherapy might exert long-lasting and progressive neurotoxic effects. Based on the important role of the hippocampus for maintenance of brain plasticity throughout life, several experimental studies have focused on the study of chemotherapy effects on hippocampal neurogenesis and associated learning and memory. An increasing body of literature from both animal studies and neuroimaging studies in cancer patients suggests a possible relationship between chemotherapy induced hippocampal damage and the spectrum of neurocognitive deficits and mood alterations observed in cancer patients. This review aims to briefly summarize current preclinical and neuroimaging studies that are providing a potential link between the neurotoxic effects of chemotherapy and hippocampal dysfunction, highlighting challenges and future directions in this field of investigation.


Subject(s)
Antineoplastic Agents/toxicity , Cognition Disorders/chemically induced , Hippocampus/drug effects , Animals , Cognition Disorders/pathology , Hippocampus/pathology , Humans , Memory/drug effects , Neurogenesis/drug effects , Organ Size
2.
Neurology ; 77(13): 1287-94, 2011 Sep 27.
Article in English | MEDLINE | ID: mdl-21917775

ABSTRACT

OBJECTIVE: To characterize Alexander disease (AxD) phenotypes and determine correlations with age at onset (AAO) and genetic mutation. AxD is an astrogliopathy usually characterized on MRI by leukodystrophy and caused by glial fibrillary acidic protein (GFAP) mutations. METHODS: We present 30 new cases of AxD and reviewed 185 previously reported cases. We conducted Wilcoxon rank sum tests to identify variables scaling with AAO, survival analysis to identify predictors of mortality, and χ(2) tests to assess the effects of common GFAP mutations. Finally, we performed latent class analysis (LCA) to statistically define AxD subtypes. RESULTS: LCA identified 2 classes of AxD. Type I is characterized by early onset, seizures, macrocephaly, motor delay, encephalopathy, failure to thrive, paroxysmal deterioration, and typical MRI features. Type II is characterized by later onset, autonomic dysfunction, ocular movement abnormalities, bulbar symptoms, and atypical MRI features. Survival analysis predicted a nearly 2-fold increase in mortality among patients with type I AxD relative to those with type II. R79 and R239 GFAP mutations were most common (16.6% and 20.3% of all cases, respectively). These common mutations predicted distinct clinical outcomes, with R239 predicting the most aggressive course. CONCLUSIONS: AAO and the GFAP mutation site are important clinical predictors in AxD, with clear correlations to defined patterns of phenotypic expression. We propose revised AxD subtypes, type I and type II, based on analysis of statistically defined patient groups.


Subject(s)
Alexander Disease/classification , Alexander Disease/genetics , Glial Fibrillary Acidic Protein/genetics , Mutation/genetics , Adolescent , Adult , Age Factors , Age of Onset , Alexander Disease/mortality , Bayes Theorem , DNA Mutational Analysis , Exons/genetics , Female , Humans , Logistic Models , Male , Retrospective Studies , Survival Analysis , Young Adult
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