Digital PCR analysis of tumor-specific mutations from peripheral blood in ER positive breast cancer samples

Atocha Romero
Hospital Universitario Puerta de Hierro, Spain

Abstract
Background: Digital polymerase chain reaction (dPCR) is a new technology that enables detection and quantification of tumor-specific mutations in circulating plasma DNA. Detecting tumor-specific mutations in circulating plasma DNA may potentially be useful to select systemic therapies for solid tumors as well as to monitor treatment outcome. The aim of our study is to evaluate the feasibility of QuantStudio® 3D Digital PCR System for detecting and quantifying PIK3CA mutations from plasma of breast cancer patients.
Methods: 49 Formalin-fixed paraffin-embedded (FFPE) stage IV tumor samples were screened for PIK3CA mutations using cobas® 4800 System (Roche Molecular Diagnostics). Plasma samples were analyzed by digital PCR using Rare Mutation Assays for E542K, E545K and H1047R on QuantStudio® 3D Digital PCR System (Life Technologies). We compared the tumor markers CA 15-3 and CEA with the PIK3CA mutation quantification in circulating free DNA (cfDNA) from plasma.
Results: Of the 49 ER positive breast cancer tumors analyzed, 20 harbored a mutation in PIK3CA. Regarding tumor mutation status, the proportion of observed agreement between COBAS and digital PCR was 100%. However, a moderate agreement was found between FFPE samples and ctDNA, which might be due to the heterogeneity of metastasic disease. Circulating tumor DNA was successfully detected in 12 of plasma samples. The sensitivity of digital PCR assay allowed for the detection of a mutant allele fraction of lower than 1% (detection level guaranteed by Life Technologies). In 9 women with PIK3CA somatic mutation, circulating tumor DNA and tumor markers CA15-3 and CEA were quantified in a total 29 serial plasma samples. Overall, the level of PIK3CA mutations correlated with the amount of tumors markers.
Conclusions: The methodology presented in this study is a feasible approach for PIK3CA mutation detection and quantification in blood derived samples.

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