Universal Toxicity Gene Signatures for Early Identification of Drug-Induced Tissue Injuries in Rats

Toxicol Sci. 2021 May 27;181(2):148-159. doi: 10.1093/toxsci/kfab038.

Abstract

A new safety testing paradigm that relies on gene expression biomarker panels was developed to easily and quickly identify drug-induced injuries across tissues in rats prior to drug candidate selection. Here, we describe the development, qualification, and implementation of gene expression signatures that diagnose tissue degeneration/necrosis for use in early rat safety studies. Approximately 400 differentially expressed genes were first identified that were consistently regulated across 4 prioritized tissues (liver, kidney, heart, and skeletal muscle), following injuries induced by known toxicants. Hundred of these "universal" genes were chosen for quantitative PCR, and the most consistent and robustly responding transcripts selected, resulting in a final 22-gene set from which unique sets of 12 genes were chosen as optimal for each tissue. The approach was extended across 4 additional tissues (pancreas, gastrointestinal tract, bladder, and testes) where toxicities are less common. Mathematical algorithms were generated to convert each tissue's 12-gene expression values to a single metric, scaled between 0 and 1, and a positive threshold set. For liver, kidney, heart, and skeletal muscle, this was established using a training set of 22 compounds and performance determined by testing a set of approximately 100 additional compounds, resulting in 74%-94% sensitivity and 94%-100% specificity for liver, kidney, and skeletal muscle, and 54%-62% sensitivity and 95%-98% specificity for heart. Similar performance was observed across a set of 15 studies for pancreas, gastrointestinal tract, bladder, and testes. Bundled together, we have incorporated these tissue signatures into a 4-day rat study, providing a rapid assessment of commonly seen compound liabilities to guide selection of lead candidates without the necessity to perform time-consuming histopathologic analyses.

Keywords: algorithms; degeneration; heart; kidney; liver; necrosis; skeletal muscle.

MeSH terms

  • Animals
  • Gene Expression Profiling*
  • Liver
  • Pharmaceutical Preparations*
  • Rats
  • Risk Assessment
  • Transcriptome

Substances

  • Pharmaceutical Preparations