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Mathematically universal and biologically consistent astrocytoma genotype encodes for transformation and predicts survival phenotype.
Aiello, Katherine A; Ponnapalli, Sri Priya; Alter, Orly.
Afiliación
  • Aiello KA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112, USA.
  • Ponnapalli SP; Department of Bioengineering, University of Utah, Salt Lake City, Utah 84112, USA.
  • Alter O; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112, USA.
APL Bioeng ; 2(3)2018 Sep.
Article en En | MEDLINE | ID: mdl-30397684
DNA alterations have been observed in astrocytoma for decades. A copy-number genotype predictive of a survival phenotype was only discovered by using the generalized singular value decomposition (GSVD) formulated as a comparative spectral decomposition. Here, we use the GSVD to compare whole-genome sequencing (WGS) profiles of patient-matched astrocytoma and normal DNA. First, the GSVD uncovers a genome-wide pattern of copy-number alterations, which is bounded by patterns recently uncovered by the GSVDs of microarray-profiled patient-matched glioblastoma (GBM) and, separately, lower-grade astrocytoma and normal genomes. Like the microarray patterns, the WGS pattern is correlated with an approximately one-year median survival time. By filling in gaps in the microarray patterns, the WGS pattern reveals that this biologically consistent genotype encodes for transformation via the Notch together with the Ras and Shh pathways. Second, like the GSVDs of the microarray profiles, the GSVD of the WGS profiles separates the tumor-exclusive pattern from normal copy-number variations and experimental inconsistencies. These include the WGS technology-specific effects of guaninecytosine content variations across the genomes that are correlated with experimental batches. Third, by identifying the biologically consistent phenotype among the WGS-profiled tumors, the GBM pattern proves to be a technology-independent predictor of survival and response to chemotherapy and radiation, statistically better than the patient's age and tumor's grade, the best other indicators, and MGMT promoter methylation and IDH1 mutation. We conclude that by using the complex structure of the data, comparative spectral decompositions underlie a mathematically universal description of the genotype-phenotype relations in cancer that other methods miss.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: APL Bioeng Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: APL Bioeng Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos