OCT 17, 2013 07:00 AM PDT

Advancing Translational Cancer Research through Automated RNASeq Sample Preparation from Archival FFPE Tissue Specimens

98 46 1856

  • Scientific Researcher, Dana-Farber Cancer Institute
      Michaela Bowden received her Ph.D. from Dublin City University in Ireland and went on to complete a Post-Doctoral Research Fellowship at Tufts University. She then spent 4years as a Research Fellow at Novartis Institutes for Biomedical Research, Inc, in Cambridge MA. Dr. Bowden has a strong interdisciplinary skill set with an emphasis on biomarker discovery utilizing cellular and molecular biology techniques. She has previously worked on identifying and evaluating candidate oncogenic biomarkers of small molecule inhibition with a view to elucidating the underlying mechanism of action through analysis of the associated signaling pathways. Dr. Bowden is very interested in molecular characterization of potential prognostic biomarkers of prostate cancer and in developing the molecular approach to utilizing archival FFPE prostate cancer tissues most efficiently.


    RNA-Seq allows the simultaneous observation of gene expression levels, mutations in the coding sequences, splice variants and gene fusions, which are especially important in cancer studies. Archived FFPE collections, which are stored for decades, must be unlocked to discover clinically relevant biomarkers. With the advent of new molecular techniques, specifically targeting FFPE and advances in automation, it is foreseeable that faster, more cost-efficient and reliable tools will facilitate the discovery of clinically relevant biomarkers. This study describes automated RNA isolation from archival FFPE tissue specimens using Agencourt FormaPure Kit and RNA library construction using the Beckman Coulter Biomek FXP. The library preparation method is based on the ScriptSeq RNA sample preparation protocol (Complete Gold low input). The ScriptSeq method is a streamlined, time-saving method that proved amenable to automation with limited optimization required. This automated method is suitable for up to ninety-six library constructions in parallel. As part of this automated method development we assessed; the overall RNA quality of the FFPE sample cohort, the total RNA input amount, SPRI bead-based clean-up strategies and optimization of key preparation steps. Libraries prepped on the Biomek automated platform provide end-users with a more reliable way to generate libraries from precious clinical samples in a faster turnaround time.

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