An overall goal of this three-year AREA grant application is to enhance the academic and research environment at Miami University by establishing a strong program in NMR- and MS-based metabonomics research for discovery of metabolic biomarkers for human diseases. The specific scientific goal of this research project will be to apply metabolic profiling to discover biomarkers for early detection of pancreatic cancer. More than 85% of lethal human pancreatic tumors originate in the ductal epithelia of the pancreas. Metabolic profiling will be applied to urine and fecal extracts collected from a mouse model for pancreatic cancer that recapitulates the full spectrum of pre-cancerous ductal neoplasias and tumor progression observed in humans. We predict that transformation of ductal epithelial cells during mPanIN initiation will generate a metabolic signature that will be detectable in urine and fecal extracts. Since it is currently not possible to detect human pancreatic cancer at the PanIN stage, we can only test this hypothesis and investigate the earliest metabolic signatures of PanIN initiation using this mouse model. Therefore, achieving the goals outlined in this proposal will only be possible using a mouse model that recapitulates the entire progression of PanIN initiation and tumor progression. In order that this study be most relevant to understanding initiation and progression of human pancreatic cancer, it is necessary to investigate a mouse model that closely reproduces the full spectrum of pre-invasive lesions and tumors that occur in human pancreatic cancer. The best mouse model available, which we will use in this study (Specific Aim #1) is the Pdx1-cre;LSL-KrasG12D transgenic strain, which has been well characterized and recapitulates the full range of pre- invasive pancreatic intraepithelial neoplasias observed in humans. The Pdx1-cre;LSL-KrasG12D strain develops a high incidence of mPanIN's by age 4-6 months and by the age of 6-12 months many of these mPanIN's transform to invasive pancreatic adenocarcinomas. The main goal of this project will be to conduct a 1-year-long longitudinal parallel metabonomics and MRI study to determine if a metabolic profiling biomarker can be discovered for early detection of pancreatic cancer (Specific Aim #4). The success of specific aim #4 will require accurate and reliable interpretation of MRI images of the mouse pancreas. To facilitate this goal, we have outlined a """"""""road mapping"""""""" task to train to interpret MRI and MRJ images in the context of conventional histologies of the mouse pancreas (Specific Aim #3). Finally, given the complexity of the mouse pancreas, and the challenge presented by the fact that the majority of pancreatic tumors originate in the ductal epithelia, we have outlined a task to develop and demonstrate use of novel superparamagnetic antibody contrast agents targeted specifically to the pancreas ductal epithelia to maximize sensitivity and accuracy of detection in MRI images (Specific Aim #2).

Public Health Relevance

Pancreatic cancer kills more than 35,000 individuals in the United States each year, is the fourth leading cause of cancer death in the USA, and is the most lethal form of cancer with about 70% of individuals dying within 4-6 months of initial diagnosis, and the five- year survival rate is less than 5%. The dismal outlook is because pancreatic cancer is usually not detected until it has spread and can no longer be treated by surgery. The best chance for improved survival of pancreatic cancer is early detection, but there are currently no effective biomarkers for early detection. The goal of this proposal is to use a novel technology of metabolic profiling to discover new biomarkers for early detection of pancreatic cancer, which if successful, could improve the survival and quality of life for thousands of Americans each year.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Academic Research Enhancement Awards (AREA) (R15)
Project #
1R15CA152985-01A1
Application #
8101733
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Zhang, Huiming
Project Start
2011-03-01
Project End
2015-02-28
Budget Start
2011-03-01
Budget End
2015-02-28
Support Year
1
Fiscal Year
2011
Total Cost
$426,000
Indirect Cost
Name
Miami University Oxford
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
041065129
City
Oxford
State
OH
Country
United States
Zip Code
45056
Romick-Rosendale, Lindsey E; Legomarcino, Anne; Patel, Neil B et al. (2014) Prolonged antibiotic use induces intestinal injury in mice that is repaired after removing antibiotic pressure: implications for empiric antibiotic therapy. Metabolomics 10:8-20
Shi, Zhanquan; Mirza, Mana; Wang, Bo et al. (2014) Osteopontin-a alters glucose homeostasis in anchorage-independent breast cancer cells. Cancer Lett 344:47-53
Shi, Zhanquan; Wang, Bo; Chihanga, Tafadzwa et al. (2014) Energy metabolism during anchorage-independence. Induction by osteopontin-c. PLoS One 9:e105675
Wang, Bo; Goodpaster, Aaron M; Kennedy, Michael A (2013) Coefficient of Variation, Signal-to-Noise Ratio, and Effects of Normalization in Validation of Biomarkers from NMR-based Metabonomics Studies. Chemometr Intell Lab Syst 128:9-16
Wang, Bo; Shi, Zhanquan; Weber, Georg F et al. (2013) Introduction of a new critical p value correction method for statistical significance analysis of metabonomics data. Anal Bioanal Chem 405:8419-29
Watanabe, Miki; Sheriff, Sulaiman; Lewis, Kenneth B et al. (2012) Metabolic Profiling Comparison of Human Pancreatic Ductal Epithelial Cells and Three Pancreatic Cancer Cell Lines using NMR Based Metabonomics. J Mol Biomark Diagn 3:
Watanabe, Miki; Sheriff, Sulaiman; Lewis, Kenneth B et al. (2012) HMGA-targeted phosphorothioate DNA aptamers increase sensitivity to gemcitabine chemotherapy in human pancreatic cancer cell lines. Cancer Lett 315:18-27
Romick-Rosendale, Lindsey E; Schibler, Kurt R; Kennedy, Michael A (2012) A Potential Biomarker for Acute Kidney Injury in Preterm Infants from Metabolic Profiling. J Mol Biomark Diagn Suppl 3:
Goodpaster, Aaron M; Kennedy, Michael A (2011) Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies. Chemometr Intell Lab Syst 109:162-170
Romick-Rosendale, Lindsey E; Brunner, Hermine I; Bennett, Michael R et al. (2011) Identification of urinary metabolites that distinguish membranous lupus nephritis from proliferative lupus nephritis and focal segmental glomerulosclerosis. Arthritis Res Ther 13:R199