A methodology for utilization of predictive genomic signatures in FFPE samples

Jennifer A Freedman,Christina K Augustine,Joseph R Nevins,William T Barry,David S Hsu,Zhengzheng Wei,Kirsten C Holshausen,Katherine A Tsamis,Angelica M Selim,Holly K Dressman,Douglas S Tyler

doi:10.1186/1755-8794-4-58

Jennifer A Freedman, Christina K Augustine + Show 9 more

Open Access

https://doi.org/10.1186/1755-8794-4-58

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Abstract

BackgroundGene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, thus potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential.MethodsPatterns of pathway activity in matched fresh-frozen and FFPE xenograft tumor samples were generated using the MessageAmp Premier methodology in combination with assays using Affymetrix arrays. Results generated were compared with those obtained from fresh-frozen samples using a standard Affymetrix assay. In addition, gene expression data from patient matched fresh-frozen and FFPE melanomas were also utilized to evaluate the consistency of predictions of oncogenic signaling pathway status.ResultsSignificant correlation was observed between pathway activity predictions from paired fresh-frozen and FFPE xenograft tumor samples. In addition, significant concordance of pathway activity predictions was also observed between patient matched fresh-frozen and FFPE melanomas.ConclusionsReliable and consistent predictions of oncogenic pathway activities can be obtained from FFPE tumor tissue samples. The ability to reliably utilize FFPE patient tumor tissue samples for genomic analyses will lead to a better understanding of the biology of disease progression and, in the clinical setting, will provide tools to guide the choice of therapeutics to those most likely to be effective in treating a patient's disease.

Highlights

Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, potentially identifying therapeutic options for subgroups of patients
Studies have generated predictive models from FFPE tissues, including a genomic profile of nontumoral liver tissue surrounding hepatocellular carcinoma that correlates with survival and of primary extremity soft tissue sarcoma that correlates with metastatic recurrence [7,8]
Given the need to develop tools that can be applied in a clinical setting, we have focused on developing the capability to apply these same pathway analyses to more readily available FFPE tissue samples

Summary

Introduction

Gene expression signatures developed to measure the activity of oncogenic signaling pathways have been used to dissect the heterogeneity of tumor samples and to predict sensitivity to various cancer drugs that target components of the relevant pathways, potentially identifying therapeutic options for subgroups of patients. To facilitate broad use, including in a clinical setting, the ability to generate data from formalin-fixed, paraffin-embedded (FFPE) tissues is essential. While the majority of studies have made use of fresh tissue samples so as to optimize the measurement of gene expression, an ability to generate reliable and consistent data from formalinfixed, paraffin-embedded (FFPE) tissue samples has several advantages. With respect to human tumors, concordance has been found between gene expression profiles from fresh-frozen and FFPE colonic epithelial cells isolated by laser capture microdissection [3]. Concordance has been observed between unsupervised hierarchical clusters of gene expression data and tumor type of FFPE carcinomas and the tissue of origin of 3 unknown carcinomas has been elucidated [9]

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