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Identifying metabolomic risk factors for pancreatic cancer

Principal Investigator
Name
Rachael Stolzenberg-Solomon
Degrees
Ph.D., M.P.H., R.D.
Institution
NCI, DCEG, NEB
Position Title
Senior Investigator
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
2012-0066
Initial CDAS Request Approval
Sep 5, 2012
Title
Identifying metabolomic risk factors for pancreatic cancer
Summary
Metabolomics is a high throughput method that involves the quantitative and qualitative study of a large number (e.g. 500-1000) of small molecules (typically less than 1000 Daltons) in a biofluid. A metabolomic profile represents the collection of metabolites within a biological system and it reflects environmental and genetic factors, as well as, the gut microflora which may play an important role in diet and metabolism. These profiles have proven to be robust indicators of disease status. We hypothesize that metabolites and metabolomic profiles will be associated with pancreatic cancer risk. We propose performing a nested case-control study using prediagnostic serum samples from 300 incident pancreatic cancer cases and 300 matched controls within the intervention arm of PLCO study. Our three specific aims are to: 1) identify metabolites associated with pancreatic cancer risk. 2) identify groups of metabolites that connect known risk factors, such as insulin resistance, with pancreatic cancer. 3) test whether unique metabolic profiles identified from the pancreatic ductal adenocarcinoma (PDA) mouse model are associated with early (pre-invasive) and late stage (invasive) pancreatic carcinogenesis in humans. Serum samples will be analyzed by liquid chromatography mass spectrometry (LC-MS/MS: +ESI and -ESI)) and gas chromatography mass spectrometry (GCMS) at Metabolon, Inc. Metabolon identifies known and unknown metabolites in serum. Presently Metabolon has identified 472 metabolites within super- and sub-pathways. As this technology advances additional metabolites not presently identified may be added. The findings from this project could provide a major advance in our understanding of potentially modifiable pancreatic cancer risk factors and their underlying pathophysiology and mechanisms.
Aims

1. To identify metabolites associated with pancreatic cancer risk. We will conduct an association study, using a non-targeted approach, to identify serum metabolites associated with pancreatic cancer. We hypothesize unique metabolites and metabolic profiles will be associated with pancreatic cancer.

2. To identify groups of metabolites that connect known risk factors, such as insulin resistance, with pancreatic cancer. Previous studies have identified metabolomic profiles that characterize insulin resistance and diabetes, as well as obesity. Using the metabolite data in Aim 1, we will conduct a targeted analysis of metabolites that characterize exposures and risk of pancreatic cancer. We hypothesize that metabolomic profiles that characterize insulin resistance and other exposures will be associated with pancreatic cancer.

3. To test whether unique metabolic profiles identified from the pancreatic ductal adenocarcinoma (PDA) mouse model are associated with early (pre-invasive) and late stage (invasive) pancreatic carcinogenesis in humans. Using the metabolite data from Aim 1, we will conduct a targeted analysis to examine the association between unique metabolomic profiles identified from PDA mouse studies conducted at Dr. Oteys laboratory in the Department of Cell and Molecular Physiology, at the University of North Carolina, School of Medicine. We hypothesize that the same metabolites that predict early and late stage pancreatic adenocarcinoma in mice will also predict human pancreatic adenocarcinoma.

Secondary aims: Measure the risk of pancreatic cancer attributable to nutritional and other poorly measured exposures and to identify metabolites that mediate exposure-cancer associations. Many nutritional and lifestyle exposures, such as physical activity, and consumption of fat, meat and energy, are poorly measured by questionnaires used in large epidemiological studies of cancer. Therefore, it has been equally difficult to quantify their true effects on cancer risk. The hope is that the profiles will provide a more accurate assessment of exposure than those currently used in epidemiological studies and, therefore, increase our power to detect associations. These analyses will then be extended to determine whether any subset of the exposure related metabolites show stronger associations with cancer. We hypothesize that metabolomic profiles that characterize insulin resistance, physical activity, obesity, and consumption of fat, meat, and energy will be associated with pancreatic cancer.

Collaborators

Carol Otey (Department of Cell and Molecular Physiology, UNC)
Joshua Sampson (DCEG, BB)
Steve Moore (DCEG, NEB)
Rachael Stolzenberg-Solomon (NCI)

Approved Addenda This project has one or more approved addenda.
  • Identifying metabolomic risk factors for pancreatic cancer
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