The influence of DNA repair on neurological degeneration, cachexia, skin cancer and internal neoplasms: autopsy report of four xeroderma pigmentosum patients (XP-A, XP-C and XP-D).

BACKGROUND: To investigate the association of DNA nucleotide excision repair (NER) defects with neurological degeneration, cachexia and cancer, we performed autopsies on 4 adult xeroderma pigmentosum (XP) patients with different clinical features and defects in NER complementation groups XP-A, XP-C or XP-D. RESULTS: The XP-A (XP12BE) and XP-D (XP18BE) patients exhibited progressive neurological deterioration with sensorineural hearing loss. The clinical spectrum encompassed severe cachexia in the XP-A (XP12BE) patient, numerous skin cancers in the XP-A and two XP-C (XP24BE and XP1BE) patients and only few skin cancers in the XP-D patient. Two XP-C patients developed internal neoplasms including glioblastoma in XP24BE and uterine adenocarcinoma in XP1BE. At autopsy, the brains of the 44 yr XP-A and the 45 yr XP-D patients were profoundly atrophic and characterized microscopically by diffuse neuronal loss, myelin pallor and gliosis. Unlike the XP-A patient, the XP-D patient had a thickened calvarium, and the brain showed vacuolization of the neuropil in the cerebrum, cerebellum and brainstem, and patchy Purkinje cell loss. Axonal neuropathy and chronic denervation atrophy of the skeletal muscles were observed in the XP-A patient, but not in the XP-D patient. CONCLUSIONS: These clinical manifestations and autopsy findings indicate advanced involvement of the central and peripheral nervous system. Despite similar defects in DNA repair, different clinicopathological phenotypes are seen in the four cases, and therefore distinct patterns of neurodegeneration characterize XP-D, XP-A and XP-C patients.

Unsupervised analysis of transcriptomic profiles reveals six glioma subtypes.

Gliomas are the most common type of primary brain tumors in adults and a significant cause of cancer-related mortality. Defining glioma subtypes based on objective genetic and molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications based on gene expression data have been attempted in the past with varying success and with only some concordance between studies, possibly due to inherent bias that can be introduced through the use of analytic methodologies that make a priori selection of genes before classification. To overcome this potential source of bias, we have applied two unsupervised machine learning methods to genome-wide gene expression profiles of 159 gliomas, thereby establishing a robust glioma classification model relying only on the molecular data. The model predicts for two major groups of gliomas (oligodendroglioma-rich and glioblastoma-rich groups) separable into six hierarchically nested subtypes. We then identified six sets of classifiers that can be used to assign any given glioma to the corresponding subtype and validated these classifiers using both internal (189 additional independent samples) and two external data sets (341 patients). Application of the classification system to the external glioma data sets allowed us to identify previously unrecognized prognostic groups within previously published data and within The Cancer Genome Atlas glioblastoma samples and the different biological pathways associated with the different glioma subtypes offering a potential clue to the pathogenesis and possibly therapeutic targets for tumors within each subtype.

Microarray-based, high-throughput gene expression profiling of microRNAs.

MicroRNAs (miRNAs) are small regulatory RNAs that serve fundamental biological roles across eukaryotic species. We describe a new method for high-throughput miRNA detection. The technique is termed the RNA-primed, array-based Klenow enzyme (RAKE) assay, because it involves on-slide application of the Klenow fragment of DNA polymerase I to extend unmodified miRNAs hybridized to immobilized DNA probes. We used RAKE to study human cell lines and brain tumors. We show that the RAKE assay is sensitive and specific for miRNAs and is ideally suited for rapid expression profiling of all known miRNAs. RAKE offers unique advantages for specificity over northern blots or other microarray-based expression profiling platforms. Furthermore, we demonstrate that miRNAs can be isolated and profiled from formalin-fixed paraffin-embedded tissue, which opens up new opportunities for analyses of small RNAs from archival human tissue. The RAKE assay is theoretically versatile and may be used for other applications, such as viral gene profiling.