Project description:TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method.
Project description:TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method. TK6 cells were exposed to various perturbations and then the transcriptome profiles were collected at 4 hours to assemble a reference database to generate a Genotoxic / Nongenotoxic classifier using the nearest shrunken centroids method.
Project description:Direct and indirect- acting genotoxic carcinogens at 3 dose levels i.e., low, medium and high with and without S9 metabolic mix, were exposed to TK6 cells along with control TK6 cell cultures in- vitro. Total RNA was isolated and hybridized to illumina microarrays to assess the effects of carcinogens on genomewide gene expression in TK6 cells.
Project description:Gene expression of TK6 cells transduced with an oncoretrovirus expressing MDR1 (TK6MDR1) was compared to untransduced TK6 cells and to TK6 cell transduced with an oncoretrovirus expressing the Neomycin resistance gene (TK6neo). Two biological replicates of each were generated and the expression profiles were determined using Affymetrix Human Genome U133 Plus2.0 GeneChip microarrays. Comparisons between the sample groups allow the identification of genes with expression dependent on the MDR1 overexpression.
Project description:We performed whole genome profiling in order to determine the landscape of genetic alterations assoicated with a subset of CLL that is characterized by deletions in 17p The number of copy number alterations predicted shorter time to treatment among patients untreated at sampling. Chromosome 3p, 4p, and 9p were frequently deleted in del(17p) CLL and strongly associated with shorter OS. We conclude that del(17p) has a unique genomic profile characterized typically by TP53 mutation with novel CNAs and novel drivers, with increasing genomic complexity of any type associated with worse overall survival.
Project description:Transcriptional profiling of squamous cell carcinoma of oral tongue, comparing p53 NS+ and p53 NS- tumors. Goal was to determine differentially expressed genes between them based on global gene expression.
Project description:Transcriptomic signatures, or biomarkers, of toxicity can facilitate rapid mechanistic analysis of chemicals using high-content transcriptomic data and identification of potential hazards to human health. We developed an 81-gene transcriptomic biomarker, named TGx-HDACi, to detect histone deacetylase inhibitors (HDACi) in TK6 human lymphoblastoid cells after 4 hours of chemical exposure. This work leveraged an established transcriptomic biomarker of DNA damage, TGx-DDI, which was developed by Heng Hong Li et al. (2015); TGx-DDI contains 63 genes and can distinguish between DNA damage-inducing (DDI) and non-DDI agents after 4 hours of exposure in TK6 cells. TGx-HDACi was derived from Templated Oligo-Sequencing (TempO-Seq) whole transcriptome gene expression profiles of 20 reference compounds, consisting of 10 HDACi and 10 non-HDACi compounds. Fourteen of the TGx-HDACi reference compounds are also part of the 28-compound reference set for TGx-DDI. The nearest shrunken centroid (NSC) method was applied to the gene expression profiles and 81 genes were identified that accurately identified HDACi compounds in the NSC probability analysis. The classification performance of TGx-HDACi was validated using an additional set of 11 test compounds (4 HDACi and 7 non-HDACi). Thus far, TGx-HDACi has demonstrated 100% accuracy. The availability of TGx-HDACi increases the diversity of tools that can facilitate mode of action analysis of toxicants using gene expression profiling.
Project description:Gene expression biomarkers are now available for application in the identification of genotoxic hazards. The TGx-DDI transcriptomic biomarker can accurately distinguish DDI from non-DDI exposures based on changes in the expression of 64 biomarker genes. The bioamarker was originally derived from DNA microarray gene expression profiles of TK6 human lymphoblastoid cells post 4-hour exposure to 28 reference DDI and non-DDI agents [Li et al. 2015]. To broaden the applicability of TGx-DDI, the biomarker was tested using quantitative RT-PCR (qPCR), which is accessible to most molecular biology laboratories. To assess the classification capability of the biomarker using qPCR, a custom 96-well TaqMan qPCR array (TGx-DDI qPCR array) was constructed using the 64 biomarker genes. TK6 cells were exposed to each of the 28 reference agents and their vehicle controls for 4 hours and the expression level of the TGx-DDI genes were profiled using the TaqMan arrays. This study provides reference qPCR expression profiles of the TGx-DDI biomarker for DDI chemical classification using qPCR.
