Person: Stiles, Charles
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Publication Molecular imaging of drug transit through the blood-brain barrier with MALDI mass spectrometry imaging
(Nature Publishing Group, 2013) Liu, Xiaohui; Ide, Jennifer L.; Norton, Isaiah Hakim; Marchionni, Mark A.; Ebling, Maritza C.; Wang, Lan; Davis, Erin; Sauvageot, Claire M.; Kesari, Santosh; Kellersberger, Katherine A.; Easterling, Michael L.; Santagata, Sandro; Stuart, Darrin D.; Alberta, John; Agar, Jeffrey N.; Stiles, Charles; Agar, Nathalie Y. R.Drug transit through the blood-brain barrier (BBB) is essential for therapeutic responses in malignant glioma. Conventional methods for assessment of BBB penetrance require synthesis of isotopically labeled drug derivatives. Here, we report a new methodology using matrix assisted laser desorption ionization mass spectrometry imaging (MALDI MSI) to visualize drug penetration in brain tissue without molecular labeling. In studies summarized here, we first validate heme as a simple and robust MALDI MSI marker for the lumen of blood vessels in the brain. We go on to provide three examples of how MALDI MSI can provide chemical and biological insights into BBB penetrance and metabolism of small molecule signal transduction inhibitors in the brain – insights that would be difficult or impossible to extract by use of radiolabeled compounds.
Publication Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples
(Public Library of Science, 2009) Campbell, Catarina D.; Kehoe, Sarah M.; Hatton, Charles; Niu, Lili; Yao, Keluo; Hanna, Megan; Mondal, Chandrani; Luongo, Lauren; Baker, Alissa C.; Philips, Juliet; Goff, Deborah J.; Rubin, Mark A.; Corso, Gianni; Roviello, Franco; MacConaill, Laura; Bass, Adam; Davis, Matt; Emery, Caroline Margaret; Fiorentino, Michelangelo; Polyak, Kornelia; Chan, Jennifer; Wang, Yufang; Fletcher, Jonathan; Santagata, Sandro; Shivdasani, Ramesh; Kieran, Mark W.; Ligon, Keith; Stiles, Charles; Hahn, William; Meyerson, Matthew; Garraway, Levi; Jones, ChrisBackground: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. Methodology: We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. Conclusions: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents.