Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling

Brzeszczyńska, Joanna; Brzeszczyński, Filip; Samuel, Kay; Morgan, Katie; Morley, Steven D.; Plevris, John; Hayes, Peter

doi:10.3390/cells9030770

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…Murine and human genespecific primers were as follows: rat Ercc2: 5 -ATGGGCTGCTGGTCTACTTC-3 (F), 5 -TCCAGTGGATAAGCCCGTTG-3 (R); rat Glyceraldehyde-3-phosphate dehydrogenase (Gapdh): 5 -ATGGGAGTTGCTGTTGAAGTC-3 (F), 5 -CCGAGGGCCCACTAAAGG-3 (R); human ERCC2: 5 -CCTACATGCGGGAGCTCAAA-3 (F), 5 -CAGCGGATATGCTCTCTGGT-3 (R); human GAPDH: 5 -GACAGTCAGCCGCATCTTCT-3 (F), 5 -GCGCCCAATACGACCAAA-TC-3 (R). As reference genes used for the normalization of RT-qPCR data can sometimes vary under different experimental conditions [34], we verified that Ct values of human GAPDH and murine Gapdh expression were stable in our experiments.…”

Section: Rna Analysessupporting

confidence: 71%

Deacetylase Plus Bromodomain Inhibition Downregulates ERCC2 and Suppresses the Growth of Metastatic Colon Cancer Cells

Kapoor

Gustafson

Zhang

et al. 2021

Cancers

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There is growing evidence that DNA repair factors have clinical value for cancer treatment. Nucleotide excision repair (NER) proteins, including excision repair cross-complementation group 2 (ERCC2), play a critical role in maintaining genome integrity. Here, we examined ERCC2 expression following epigenetic combination drug treatment. Attention was drawn to ERCC2 for three reasons. First, from online databases, colorectal cancer (CRC) patients exhibited significantly reduced survival when ERCC2 was overexpressed in colon tumors. Second, ERCC2 was the most highly downregulated RNA transcript in human colon cancer cells and rat tumors after treatment with the histone deacetylase 3 (HDAC3) inhibitor sulforaphane (SFN) plus JQ1, which is an inhibitor of the bromodomain and extraterminal domain (BET) family. Third, as reported here, RNA-sequencing of polyposis in rat colon (Pirc) polyps following treatment of rats with JQ1 plus 6-methylsulfinylhexyl isothiocyanate (6-SFN) identified Ercc2 as the most highly downregulated gene. The current work also defined promising second-generation epigenetic drug combinations with enhanced synergy and efficacy, especially in metastasis-lineage colon cancer cells cultured as 3D spheroids and xenografts. This investigation adds to the growing interest in combination approaches that target epigenetic ‘readers’, ‘writers’, and ‘erasers’ that are deregulated in cancer and other pathologies, providing new avenues for precision oncology and cancer interception.

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Section: Rna Analysessupporting

confidence: 71%

Deacetylase Plus Bromodomain Inhibition Downregulates ERCC2 and Suppresses the Growth of Metastatic Colon Cancer Cells

Kapoor

Gustafson

Zhang

et al. 2021

Cancers

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“…Many studies have shown that there is no single reference gene that could be effectively used in the RT-qPCR in all species or under all experimental conditions ( Suzuki et al, 2000 ; Zhou et al, 2018 ). For example, Brzeszczyńska et al (2020) proved that the classical reference gene in HepaRG cells such as GAPDH was altered by drug treatment. Vorachek et al (2013) found that the commonly used reference genes, PGK1 , ACTB , and B2M for neutrophils were not reliable reference genes under different conditions.…”

Section: Discussionmentioning

confidence: 99%

Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data

Wen

Yang

Dong³

et al. 2022

Front. Genet.

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Many studies in recent years have demonstrated that some messenger RNA (mRNA) in platelets can be used as biomarkers for the diagnosis of pan-cancer. The quantitative real-time polymerase chain reaction (RT-qPCR) molecular technique is most commonly used to determine mRNA expression changes in platelets. Accurate and reliable relative RT-qPCR is highly dependent on reliable reference genes. However, there is no study to validate the reference gene in platelets for pan-cancer. Given that the expression of some commonly used reference genes is altered in certain conditions, selecting and verifying the most suitable reference gene for pan-cancer in platelets is necessary to diagnose early stage cancer. This study performed bioinformatics and functional analysis from the RNA-seq of platelets data set (GSE68086). We generated 95 candidate reference genes after the primary bioinformatics step. Seven reference genes (YWHAZ, GNAS, GAPDH, OAZ1, PTMA, B2M, and ACTB) were screened out among the 95 candidate reference genes from the data set of the platelets’ transcriptome of pan-cancer and 73 commonly known reference genes. These candidate reference genes were verified by another platelets expression data set (GSE89843). Then, we used RT-qPCR to confirm the expression levels of these seven genes in pan-cancer patients and healthy individuals. These RT-qPCR results were analyzed using the internal stability analysis software programs (the comparative Delta CT method, geNorm, NormFinder, and BestKeeper) to rank the candidate genes in the order of decreasing stability. By contrast, the GAPDH gene was stably and constitutively expressed at high levels in all the tested samples. Therefore, GAPDH was recommended as the most suitable reference gene for platelet transcript analysis. In conclusion, our result may play an essential part in establishing a molecular diagnostic platform based on the platelets to diagnose pan-cancer.

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“…Data generated within this study are included in the manuscript and Supplementary Materials . Studies obtained through the systematic review of published literature and analyzed within this study are quoted in the References section [ 16 , 22 , 45 , 47 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 ,…”

mentioning

confidence: 99%

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

et al. 2023

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In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed “housekeeping” genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.

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Validation of Reference Genes for Gene Expression Studies by RT-qPCR in HepaRG Cells during Toxicity Testing and Disease Modelling

Cited by 5 publications

References 43 publications

Deacetylase Plus Bromodomain Inhibition Downregulates ERCC2 and Suppresses the Growth of Metastatic Colon Cancer Cells

Deacetylase Plus Bromodomain Inhibition Downregulates ERCC2 and Suppresses the Growth of Metastatic Colon Cancer Cells

Selection and Validation of Reference Genes for Pan-Cancer in Platelets Based on RNA-Sequence Data

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

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