Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues.

Svitlana Tyekucheva, Neil E Martin, Edward C Stack, Wei Wei, Vinod Vathipadiekal, Levi Waldron, Michelangelo Fiorentino, Rosina T Lis, Meir J Stampfer, Massimo Loda, Giovanni Parmigiani, Lorelei A Mucci, Michael Birrer

Journal: The Journal of molecular diagnostics : JMD 2016;17(4):374-81

PMID: 25937617

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Abstract

Archival formalin-fixed, paraffin-embedded (FFPE) tissue specimens represent a readily available but largely untapped resource for gene expression profiling-based biomarker discovery. Several technologies have been proposed to cope with the bias from RNA cross-linking and degradation associated with archival specimens to generate data comparable with RNA from fresh-frozen materials. Direct comparison studies of these RNA expression platforms remain rare. We compared two commercially available platforms for RNA expression profiling of archival FFPE specimens from clinical studies of prostate and ovarian cancer: the Affymetrix Human Gene 1.0ST Array following whole-transcriptome amplification using the NuGen WT-Ovation FFPE System V2, and the NanoString nCounter without amplification. For each assay, we profiled 7 prostate and 11 ovarian cancer specimens, with a block age of 4 to 21 years. Both platforms produced gene expression profiles with high sensitivity and reproducibility through technical repeats from FFPE materials. Sensitivity and reproducibility remained high across block age within each cohort. A strong concordance was shown for the transcript expression values for genes detected by both platforms. We showed the biological validity of specific gene signatures generated by both platforms for both cohorts. Our study supports the feasibility of gene expression profiling and large-scale signature validation on archival prostate and ovarian tumor specimens using commercial platforms. These approaches have the potential to aid precision medicine with biomarker discovery and validation.

Address: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts. Electronic address: [email protected].; Department of Radiation Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts.; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts.; Center for Cancer Research, Massachusetts General Hospital, Boston, Massachusetts.; City University of New York School of Public Health, Hunter College, New York, New York.; Pathology Unit, Addarii Institute, S. Orsola-Malpighi Hospital, Bologna, Italy.; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts; Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts.; Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts; Center for Molecular Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts; Broad Institute, Cambridge, Massachusetts; Division of Cancer Studies, King's College London, London, United Kingdom.; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts; Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts.

DOI: 10.1016/j.jmoldx.2015.02.002