Optimizing PCR assays for DNA based cancer diagnostics

Ali Bashir, Qing Lu, Dennis Carson, Benjamin Raphael, Yu Tsueng Liu, Vineet Bafna

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Somatically acquired DNA rearrangements are characteristic of many cancers. The use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal DNA. Detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. Here, we present an algorithm for designing PCR primers and oligonucleotide probes to assay for these variant rearrangements. Specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant DNA over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. Our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. Simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. Additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection. We applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the CDKN2A locus. The CDKN2A deletion has highly variable boundaries across many cancers. We successfully detect the breakpoint in all cell-lines, even when the regionhas undergone multiple rearrangements. These results point to the development of a successful protocol for early diagnosis and monitoring of cancer.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 13th Annual International Conference, RECOMB 2009, Proceedings
Number of pages16
StatePublished - 2009
Externally publishedYes
Event13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009 - Tucson, AZ, United States
Duration: May 18 2009May 21 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5541 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009
Country/TerritoryUnited States
CityTucson, AZ

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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