As a hybrid science that links biological data with techniques for information storage, distribution, and analysis to support multiple areas of scientific research, including biomedicine, Bioinformatics has been driven by the great acceleration in data-generation processes in biology. The NOB for the past years has been collecting and characterizing nearly one thousand gliomas of every grade and histopathological class (oligodendrogliomas, astrocytomas, ependymomas) under a multi-institutional study conceived of. This study is broadly termed the Glioma Molecular Diagnostic Initiative (GMDI), and was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. Moreover, the sample collection is accompanied by careful and prospective clinical data acquisition, allowing an unprecedented wealth of matched molecular and clinical data permitting a wide variety of analyses. The resultant public database (REMBRANDT) is nearly unprecedented, not only in oncology, but in all of molecular medicine and is a testament to what is possible within the intramural program and how it can impact on the overall national cancer research enterprise. On the other hand, realizing that a majority of patients who come to us do not have obtainable fresh frozen tissue we spent over a year developing and optimizing a methodology that allows us to extract high quality DNA from FFPE enabling genomic analyses of these patients. Advances in the molecular analysis of genes, proteins and metabolites have greatly improved our understanding of biological processes and disease, and have increased our ability to monitor treatment response and stratify patients to improve treatment efficacy. Precision medicine facilitated by companion diagnostics is one of the driving forces accelerating the drug development process and improving therapeutic management. Launched in 2016, the NCI Genomic Data Commons (GDC) provides a single source for data from NCI initiatives and cancer research projects, including TCGA and TARGET, and the analytical tools needed to mine them. The new initiated NOB Bioinformatics has extended our bioinformatics and computational analyses efforts to utilize the GDC databases. For example, using the TCGA data effectively doubles the number of GBMs we have to work with and affords us the advantage of formulating computationally derived hypothesis based on one database with the ability to validate those hypotheses on a totally different database. For example, a significant amount of time has been spent by NOB Bioinformatics on the databases to try and understand the biologically basis for the more aggressive phenotype and thus shorter survival of GBMs from older patients compared to those of younger GBMs. To date we have found a very interesting set of differentially expressed genes and miRNAs as well as specific genome wide methylation patterns and specific chromosomal number variants that differentiate older versus younger GBMs. We are in the process of using some of these findings to perform wet lab experiments to better annotate the significance of these findings. Furthermore, in collaborated with NCI ClinOmics program we analyzed and created genomic profiling data from the rare CNS tumors, such as chordomas, and dissected signal transduction pathways, and aided in the design of novel therapeutics. In addition to characterizing the samples from patients enrolled, the NOB Bioinformatics has generated genomic-scale analyses of the many human glioma initiating cells/glioma stem cells (GIC/GSC) lines produced in laboratory. This characterization is both at the primary cell level (including evolution through passages) as well as evaluation of the impact of different treatments (differentiation, animal passages, drug treatment, etc) on the biological behavior of the cells.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Investigator-Initiated Intramural Research Projects (ZIA)
Project #
1ZIABC011784-01
Application #
9556747
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Budget End
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Basic Sciences
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