Combining magnetic resonance spectroscopy and molecular genomics offers better accuracy in brain tumor typing and prediction of survival than either methodology alone (Journal article)

Astrakas, L./ Blekas, K./ Constantinou, C./ Andronesi, O. C./ Mindrinos, M. N./ Likas, A. C./ Rahme, L. G./ Black, P. M./ Marcus, K. J./ Tzika, A. A.

Recent advents in magnetic resonance spectroscopy (MRS) techniques permit subsequent microarray analysis over the entire human transcriptome in the same tissue biopsies. However, extracting information from such immense quantities of data is limited by difficulties in recognizing and evaluating the relevant patterns of apparent gene expression in the context of the existing knowledge of phenotypes by histopathology. Using a quantitative approach derived from a knowledge base of pathology findings, we present a novel methodology used to process genome-wide transcription and MRS data. This methodology was tested to examine metabolite and genome-wide profiles in MRS and RNA in 55 biopsies from human subjects with brain tumors with similar to 100% certainty. With the guidance of histopathology and clinical outcome, 15 genes with the assistance of 15 MRS metabolites were able to be distinguished by tumor categories and the prediction of survival was better than when either method was used alone. This new method, combining MRS, genomics, statistics and biological content, improves the typing and understanding of the complexity of human brain tumors, and assists in the search for novel tumor biomarkers. It is an important step for novel drug development, it generates testable hypotheses regarding neoplasia and promises to guide human brain tumor therapy provided improved in vivo methods for monitoring response to therapy are developed.
Institution and School/Department of submitter: Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής
Keywords: brain/central nervous system cancers,tumor biomarkers,ex vivo high-resolution magic angle spinning magnetic resonance spectroscopy,support vector machines,genomics,gene-expression data,support vector machines,nervous-system cancers,renal-cell carcinoma,short echo time,h-1 mr spectra,in-vivo,binding-protein,biochemical-characterization,myocardial-infarction
ISSN: 1019-6439
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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