Mutational load distribution analysis yields metrics reflecting genetic instability during pancreatic carcinogenesis

Gemma Tarafa, David Tuck, Daniela Ladner, Mark Topazian, Randall Brand, Carolyn Deters, Victor Moreno, Gabriel Capella, Henry Lynch, Paul Lizardi, Jose Costa

Research output: Contribution to journalArticle

14 Scopus citations


Considering carcinogenesis as a microevolutionary process, best described in the context of metapopulation dynamics, provides the basis for theoretical and empirical studies that indicate it is possible to estimate the relative contribution of genetic instability and selection to the process of tumor formation. We show that mutational load distribution analysis (MLDA) of DNA found in pancreatic fluids yields biometrics that reflect the interplay of instability, selection, accident, and gene function that determines the eventual emergence of a tumor. An in silico simulation of carcinogenesis indicates that MLDA may be a suitable tool for early detection of pancreatic cancer. We also present evidence indicating that, when performed serially in individuals harboring a p16 germ-line mutation bestowing a high risk for pancreatic cancer, MLDA may be an effective tool for the longitudinal assessment of risk and early detection of pancreatic cancer.

Original languageEnglish (US)
Pages (from-to)4306-4311
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number11
StatePublished - Mar 18 2008



  • Biomarkers
  • Cancer
  • Early detection
  • Microevolution
  • Modeling

ASJC Scopus subject areas

  • General

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