Mutational profiling of pancreatic cancer holds major promise for early detection, prognosis and therapeutic management of this disease. However, as with many other cancers, while reliable screening methods for germline or prevalent somatic mutations already exist, detection of low-prevalence somatic mutations in heterogeneous, multifocal pancreatic cancers with stromal contamination, or in bodily fluids remains problematic. Thus, for a substantial fraction of clinical pancreatic cancer samples, the new powerful mutation detection technologies "lose steam" and their advantages cannot be exploited. We developed co-amplification at lower denaturation temperature polymerase chain reaction (COLD-PCR), a new form of PCR that amplifies preferentially the "minority alleles" from mixtures of wild-type and mutation-containing sequences, irrespective of where the mutation lies, providing a 10-100-fold enrichment of the mutated sequences during PCR. Because PCR comprises the ubiquitous first step in genetic analysis, COLD-PCR provides a general platform to improve sensitivity for essentially all diagnostic assays. In this application we propose to develop further, optimize and adapt COLD-PCR for increasing the sensitivity of two established mutation detection methods, such that they can be applied for reliable identification of clinically-relevant, somatic mutations in heterogeneous, multifocal pancreatic cancers: matrix assisted laser desorption ionization-time of flight (MALDI-TOF) for known mutations, and single molecule sequencing for high-throughput sequencing of somatic mutations. The combination of COLD-PCR with these two technologies, each tackling a different aspect of mutation detection, will boost the sensitivity of patient- specific mutational profiling, and is suited for application to pancreatic cancer. A comprehensive list of genes mutated in pancreatic cancers will be compiled and COLD-PCR will be adapted for parallel screening of somatic mutations in pancreatic surgical specimens and plasma samples using the selected technologies. In the forthcoming era of molecular medicine, clinical decisions will increasingly rely on molecular tumor profiling, and the reliability of identifying somatic mutations in diverse clinical specimens must be high. This application tackles the problem of molecular analysis in heterogeneous cancers. We focus the new technology on pancreatic cancer, a heterogeneous cancer that currently has very low cure rates and for which molecular biomarkers can make a difference.