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Biomarker Description

TGx-DDI Biomarker Description

  • Developed in human TK6 cells
  • The gene set was derived from TK6 cells exposed to a training set of prototypical DNA damage-inducing agents and chemicals with a clean genetic toxicology profile (28 chemicals: 13 DNA damage-inducing, 15 non DNA-damage inducing)
  • Comprised of 64 gene probes
  • Critical to have intact p53 response as many of the genes are regulated by p53
  • Measures early responses to DNA damage-inducing agents and classifies agents as DNA damage-inducing (DDI) or non-DNA damage-inducing (NDDI)
  • For direct-acting chemicals (i.e., not requiring metabolic activation), recommend 4 hours of exposure and immediate sampling in TK6 cells
  • Demonstrated to work in the presence of various types of rat microsomal liver S9, but recommend keeping %S9 as low as possible
  • For chemicals requiring metabolic activation, recommend 4 hours of exposure in presence of S9 following by 3-4 hours of recovery period
  • Dose-optimization protocols described in Li et al., 2015 and Buick et al., 2015
  • Recommended positive control: X-ray, cisplatin, benzo(a)pyrene
  • Developed on the Agilent Whole Genome microarray platform. This platform is expected to work best with datasets generated from Agilent microarrays.

Things to know about using the classifier

  • This classifier supports the following platforms:
    • Agilent Human Genome 8X60K
      • one dye
      • two dyes
      • dye-swapped
    • Affymetrix Human Genome U133 Plus 2.0 array
    • Generic arrays (must use log2 transformed data for a single chemical and dose)
    • Batch data (must use log2 transformed data for multiple chemicals and/or doses)
  • Data must be in the following formats based on the platform selected:
    • Agilent: delimited text file (.txt)
    • Affymetrix: CEL file
    • Generic: delimited text file (.txt)
    • Batch data: Excel (.xlsx)
  • Probe IDs for Generic and Batch data files should be converted to Agilent IDs. This can be achieved using a web based tool such as the Gene ID Conversion Tool from DAVID Bioinformatics Resources
  • Data in the Results table remain available up to 72 hours or until removed

Classification Process

The TGx-DDI Biomarker tool for data analysis and classification is described in detail by Jackson et al., 2017. Briefly, the probability that the test data profile matches the profile of either the DDI or NDDI reference compounds is determined. The analysis applies the Nearest Shrunken Centroids (NSC) method with a 90% probability cut-off for class membership along with the statistical and bioinformatics tools described by Tibshirani et al., 2002. The classification tool assigns a positive DDI call when the probability is > 0.9 that the test data match the DDI reference data. When the probability is > 0.9 that the test data match the NDDI reference data, a NDDI call is made. If neither probability is > 0.9, the classification call is Inconclusive (INC). Results from principal component analyses (PCA) and hierarchical clustering are also presented to aid the user in the interpretation of the results. The prcomp function in R is used for PCA analysis and the R function hclust is used for hierarchical clustering by Euclidean distances with average linkage. Principle components are estimated using only the training data set.

prcomp
principle components function in R
hclust
hierarchical clustering function in R