A major theme of the program is to develop the foundations for rational application to clinical oncology of the metabolic and physiochemical information obtainable by NMR. To that end, this project will use ex vivo, 31P-, 13C and 1H-NMR spectroscopy to characterize and study the metabolism of a series of 3 animal tumors of varying malignancy (Morris hepatomas 7787, 5123C, and 7777), as well as 2 control tissues (normal and post- partial hepatectomized liver). A unique feature of the study is the use of isolated, arterially perfused solid tumor preparations, analogous to perfused organs. This will permit a variety of NMR experiments not easily performed on either cultured tumor cells or animal tumors in situ. The fundamental issue that this proposal addresses is: Are there NMR detectable markers, or dynamic features of tumor metabolism, which correlate with degree of malignancy or responses to therapy? The specific issued addressed include: 1) Are there NMR detectable markers of tumor metabolism which correlate with the degree of malignancy or responses to therapy. 2) Are there dynamic features of tumor metabolism (ie. responses to changes of metabolic substrates, hormones, etc.) which correlate with the degree of malignancy or responses to therapy. 3) Is the interaction between metabolism and tissue pH different in normal vs. malignant issue? Thus, this study will address fundamental issues in the biology of solid tumors, as well as provide an experimental framework for the eventual application of in vivo NMR measurements to clinical diagnosis and therapeutic monitoring of cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA041078-07
Application #
3772817
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
1993
Total Cost
Indirect Cost
Name
Fox Chase Cancer Center
Department
Type
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19111
Lee, Seung-Cheol; Arias-Mendoza, Fernando; Poptani, Harish et al. (2012) Prediction and Early Detection of Response by NMR Spectroscopy and Imaging. PET Clin 7:119-26
Hultman, Kristi L; Raffo, Anthony J; Grzenda, Adrienne L et al. (2008) Magnetic resonance imaging of major histocompatibility class II expression in the renal medulla using immunotargeted superparamagnetic iron oxide nanoparticles. ACS Nano 2:477-84
Stoyanova, Radka; Querec, Troy D; Brown, Truman R et al. (2004) Normalization of single-channel DNA array data by principal component analysis. Bioinformatics 20:1772-84
Stoyanova, Radka; Nicholls, Andrew W; Nicholson, Jeremy K et al. (2004) Automatic alignment of individual peaks in large high-resolution spectral data sets. J Magn Reson 170:329-35
Stoyanova, Radka; Nicholson, Jeremy K; Lindon, John C et al. (2004) Sample classification based on Bayesian spectral decomposition of metabonomic NMR data sets. Anal Chem 76:3666-74
Sajda, Paul; Du, Shuyan; Brown, Truman R et al. (2004) Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain. IEEE Trans Med Imaging 23:1453-65
Nahum, Alan E; Movsas, Benjamin; Horwitz, Eric M et al. (2003) Incorporating clinical measurements of hypoxia into tumor local control modeling of prostate cancer: implications for the alpha/beta ratio. Int J Radiat Oncol Biol Phys 57:391-401
Stoyanova, R; Brown, T R (2002) NMR spectral quantitation by principal component analysis. III. A generalized procedure for determination of lineshape variations. J Magn Reson 154:163-75
Stoyanova, R; Brown, T R (2001) NMR spectral quantitation by principal component analysis. NMR Biomed 14:271-7
Ochs, M F; Stoyanova, R S; Arias-Mendoza, F et al. (1999) A new method for spectral decomposition using a bilinear Bayesian approach. J Magn Reson 137:161-76

Showing the most recent 10 out of 46 publications