Impact of Genomics Platform and Statistical Filtering on Transcriptional Benchmark Doses (BMD) and Multiple Approaches for Selection of Chemical Point of Departure (PoD).

Many regulatory agencies are exploring ways to integrate toxicogenomic data into their chemical risk assessments. The major challenge lies in determining how to distill the complex data produced by high-content, multi-dose gene expression studies into quantitative information. It has been proposed that benchmark dose (BMD) values derived from toxicogenomics data be used as point of departure (PoD) values in chemical risk assessments. However, there is limited information regarding which genomics platforms are most suitable and how to select appropriate PoD values. In this study, we compared BMD values modeled from RNA sequencing-, microarray-, and qPCR-derived gene expression data from a single study, and explored multiple approaches for selecting a single PoD from these data. The strategies evaluated include several that do not require prior mechanistic knowledge of the compound for selection of the PoD, thus providing approaches for assessing data-poor chemicals. We used RNA extracted from the livers of female mice exposed to non-carcinogenic (0, 2 mg/kg/day, mkd) and carcinogenic (4, 8 mkd) doses of furan for 21 days. We show that transcriptional BMD values were consistent across technologies and highly predictive of the two-year cancer bioassay-based PoD. We also demonstrate that filtering data based on statistically significant changes in gene expression prior to BMD modeling creates more conservative BMD values. Taken together, this case study on mice exposed to furan demonstrates that high-content toxicogenomics studies produce robust data for BMD modelling that are minimally affected by inter-technology variability and highly predictive of cancer-based PoD doses.

Mining the Archives: A Cross-Platform Analysis of Gene Expression Profiles in Archival Formalin-Fixed Paraffin-Embedded Tissues.

Formalin-fixed paraffin-embedded (FFPE) tissue samples represent a potentially invaluable resource for transcriptomic research. However, use of FFPE samples in genomic studies has been limited by technical challenges resulting from nucleic acid degradation. Here we evaluated gene expression profiles derived from fresh-frozen (FRO) and FFPE mouse liver tissues preserved in formalin for different amounts of time using 2 DNA microarray protocols and 2 whole-transcriptome sequencing (RNA-seq) library preparation methodologies. The ribo-depletion protocol outperformed the other methods by having the highest correlations of differentially expressed genes (DEGs), and best overlap of pathways, between FRO and FFPE groups. The effect of sample time in formalin (18 h or 3 weeks) on gene expression profiles indicated that test article treatment, not preservation method, was the main driver of gene expression profiles. Meta- and pathway analyses indicated that biological responses were generally consistent for 18 h and 3 week FFPE samples compared with FRO samples. However, clear erosion of signal intensity with time in formalin was evident, and DEG numbers differed by platform and preservation method. Lastly, we investigated the effect of time in paraffin on genomic profiles. Ribo-depletion RNA-seq analysis of 8-, 19-, and 26-year-old control blocks resulted in comparable quality metrics, including expected distributions of mapped reads to exonic, untranslated region, intronic, and ribosomal fractions of the transcriptome. Overall, our results indicate that FFPE samples are appropriate for use in genomic studies in which frozen samples are not available, and that ribo-depletion RNA-seq is the preferred method for this type of analysis in archival and long-aged FFPE samples.