Journal: Toxicological Sciences

Article Title: In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals

doi: 10.1093/toxsci/kfac127

Figure Lengend Snippet: Comparison of estrogen receptor alpha (ERα) bioactivity and transcriptomic points of departure (tPODs) derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to bisphenol A and 15 alternative chemicals at a range of concentrations (0.0005–100 µM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also postfiltered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene benchmark concentration (BMC) (shown in µM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC.

Article Snippet: Data were processed as described below and reads were aligned to the BioSpyder TempO-Seq Human Whole Transcriptome probe set (22 537 probes over 19 687 genes) using their purpose-built pipeline.

Techniques: Comparison, Derivative Assay, Concentration Assay, Biomarker Discovery

Journal: Toxicological Sciences

Article Title: In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals

doi: 10.1093/toxsci/kfac127

Figure Lengend Snippet: Comparison of ERα bioactivity and tPODs derived from the whole transcriptome analysis in MCF-7 cells ( n = 3–4 per concentration) exposed to BPA and 15 alternative chemicals at a range of concentrations (0.0005–100 μM) for 48 h. ERα prediction is based on at least one concentration yielding an agonist or antagonist call. For tPOD derivation, data were prefiltered using the Williams trend test ( p ≤ .05) and a fold-change of ≥1.5 or ≤1.5. Data were also post-filtered with the following settings in BMDExpress v2.3: Best BMD/BMDL <20, Best BMDU/BMD <20, Best BMDU/BMDL <40, and Best fitPvalue >.1. tPODs representing the 25th rank ordered gene BMC (shown in μM), the median gene BMC for the lowest pathway (at least 3 genes and 5% of pathway) as well as the median gene BMC for the ERα biomarker gene set are shown in the table and in the top panel. The chemicals are shown in decreasing order of potency based on tPODS from the 25th gene BMC. 25th gene, ERα biomarker, lowest median pathway.

Article Snippet: Data were processed as described below and reads were aligned to the BioSpyder TempO-Seq Human Whole Transcriptome probe set (22 537 probes over 19 687 genes) using their purpose-built pipeline.

Techniques: Comparison, Derivative Assay, Concentration Assay, Biomarker Discovery

Journal: Discover Oncology

Article Title: Comparison of targeted next generation sequencing assays in non-small cell lung cancer patients

doi: 10.1007/s12672-024-01640-7

Figure Lengend Snippet: Concordance analysis in the commonly covered regions by both assays. A. Frequency of NSCLC tumors with mutations identified by either one or both methods (concordant mutations). B. Venn diagram indicating the number of variants identified by either assay. 34 variants were commonly identified by both assays, while one extra variant was identified by the N MEDICOVER Genetics custom tumor profile assay (the KRAS G13C variant was detect below threshold level at VAF < 5% with the IonAmliseq and thus was excluded). C. Distribution of variant allele frequencies (VAF) for the concordant mutations identified by each assay. D. Variability of mutation detection and VAF for NGS data originating from different sections for the same FFPE biopsy

Article Snippet: The IonAmliseq assay covers hotspot regions of 22 genes while the MEDICOVER Genetics custom tumor profile assay covers hotspots and other exonic regions of 49 genes.

Techniques: Variant Assay, Mutagenesis

Journal: Discover Oncology

Article Title: Comparison of targeted next generation sequencing assays in non-small cell lung cancer patients

doi: 10.1007/s12672-024-01640-7

Figure Lengend Snippet: Description of the assays and experimental strategy used. A. List of genes covered in the two assays used for molecular profiling of NSCLC tumor specimens. The IonAmliseq assay covers hotspot regions of 22 genes while the MEDICOVER Genetics custom tumor profile assay covers hotspots and other exonic regions of 49 genes. With red are the genes commonly covered by both assays. B. Venn diagram showing the size of the genomic area covered by both assays as well as their overlapping genomic coverage. C. Experimental strategy followed: FFPE specimens from 51 patients diagnosed with NSCLC were subjected to sectioning. For 39 patients, adequate amount of DNA was extracted from the same set of sections and sent to two labs for subsequent analysis with the Ion Ampliseq and the MEDICOVER assays. For 12 patients DNA derived from different sections of the same FFPE block was sent to the two labs for downstream processing. A total of 39 patients met QC parameters and proceeded to NGS. Available sequencing data were used for concordance analysis and estimation of the molecular profile of each tumor sample

Article Snippet: The IonAmliseq assay covers hotspot regions of 22 genes while the MEDICOVER Genetics custom tumor profile assay covers hotspots and other exonic regions of 49 genes.

Techniques: Derivative Assay, Blocking Assay, Sequencing