Selecting suitable reference genes for qPCR normalization: a comprehensive analysis in MCF-7 breast cancer cell line

Identifying the stability of housekeeping genes to be used for the quantitative real-time PCR normalization in retinal tissue of streptozotocin-induced diabetic rats

AIM

To investigate the stability of the seven housekeeping genes: beta-actin (ActB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18s ribosomal unit 5 (18s), cyclophilin A (CycA), hypoxanthine-guanine phosphoribosyl transferase (HPRT), ribosomal protein large P0 (36B4) and terminal uridylyl transferase 1 (U6) in the diabetic retinal tissue of rat model.

METHODS

The expression of these seven genes in rat retinal tissues was determined using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) in two groups; normal control rats and streptozotocin-induced diabetic rats. The stability analysis of gene expression was investigated using geNorm, NormFinder, BestKeeper, and comparative delta-Ct (ΔCt) algorithms.

RESULTS

The 36B4 gene was stably expressed in the retinal tissues of normal control animals; however, it was less stable in diabetic retinas. The 18s gene was expressed consistently in both normal control and diabetic rats' retinal tissue. That this gene was the best reference for data normalisation in RT-qPCR studies that used the retinal tissue of streptozotocin-induced diabetic rats. Furthermore, there was no ideal gene stably expressed for use in all experimental settings.

CONCLUSION

Identifying relevant genes is a need for achieving RT-qPCR validity and reliability and must be appropriately achieved based on a specific experimental setting.

Translational Utility of Organoid Models for Biomedical Research on Gastrointestinal Diseases

Organoid models have recently been utilized to study 3D human-derived tissue systems to uncover tissue architecture and adult stem cell biology. Patient-derived organoids unambiguously provide the most suitable in vitro system to study disease biology with the actual genetic background. With the advent of much improved and innovative approaches, patient-derived organoids can potentially be used in regenerative medicine. Various human tissues were explored to develop organoids due to their multifold advantage over the conventional in vitro cell line culture approach and in vivo models. Gastrointestinal (GI) tissues have been widely studied to establish organoids and organ-on-chip for screening drugs, nutraceuticals, and other small molecules having therapeutic potential. The function of channel proteins, transporters, and transmembrane proteins was also explained. The successful application of genome editing in organoids using the CRISPR-Cas approach has been reported recently. GI diseases such as Celiac disease (CeD), Inflammatory bowel disease (IBD), and common GI cancers have been investigated using several patient-derived organoid models. Recent advancements on organoid bio-banking and 3D bio-printing contributed significantly in personalized disease management and therapeutics. This article reviews the available literature on investigations and translational applications of patient-derived GI organoid models, notably on elucidating gut-microbial interaction and epigenetic modifications.

Advanced breast cancer diagnosis: Multiplex RT-qPCR for precise typing and angiogenesis profiling

Breast cancer (BC) remains the foremost cause of cancer-related mortality, with an estimated 2.3 million new cases anticipated globally. The timely diagnosis of BC is pivotal for effective treatment. Currently, BC diagnosis predominantly relies on Immunohistochemistry (IHC), a method known for its sluggishness, expense, and dependence on proficient pathologists for confident cancer typing. In this study, we introduce a novel approach to enhance the accuracy, speed, and cost-effectiveness of BC diagnosis. We employ multiplex Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) with touch-down methods, which consistently yield significantly lower Cycle Threshold (CT) values. The study evaluates gene expression profiles of HER2, PGR, ESR, and Ki67 genes across 61 samples representing four BC subtypes, using RPL13A as the endogenous control gene. The results demonstrate that our method offers remarkable precision, nearly equivalent to IHC, in detecting gene expressions vital for BC diagnosis and subtyping. Moreover, we explore the gene expression of Hif1A, ANG, and VEGFR genes involved in angiogenesis, shedding light on the metastatic potential of the tested BC tumours. Notably, numerous samples exhibit elevated levels of Hif1A and VEGFR, indicating their potential as valuable biomarkers for assessing metastatic status. Collectively, our RT-qPCR methodology emerges as a powerful diagnostic tool for swiftly identifying BC subtypes and can be complemented with other essential tumorigenic biomarker assessments, such as angiogenesis, to further refine cancer characterisation and inform personalised therapeutic strategies for BC patients. This innovation holds the promise of revolutionising BC diagnosis and treatment, offering expedited and reliable insights for improved patient care.

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

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.

Identification of optimal reference genes for gene expression normalization in human osteosarcoma cell lines under proliferative conditions

The molecular pathogenesis and therapeutic target research studies on osteosarcoma (OS) have developed well during the last few years using various OS cell lines with reverse transcription quantitative polymerase chain reaction (RT-qPCR). However, the identification of suitable reference genes of RT-qPCR for OS cell lines has not been reported. Here, we conducted the normalization research of 12 reference genes (GAPDH, ACTB, 18S, B2M, ALAS1, GUSB, HPRT1, HMBS, PPIA, PUM1, RPL29, and TBP) for gene expression analysis in four kinds of human OS cell lines (U2OS, Saos-2, HOS, and MG-63) to improve the investigation of molecular mechanisms and the accuracy of diagnosis and prognostic molecular targets of OS. The gene expression stability and applicability of the 12 reference gene candidates were determined using geNorm, NormFinder, and BestKeeper software. The results indicated that PUM1 and the combination of PPIA + ALAS1 were recommended as the optimal reference gene in these four different sources of human OS cell lines under proliferative conditions. The present study identified the most suitable reference genes and reference gene combinations for OS cell lines under proliferative conditions in order to use in gene expression profile analysis. A reliable standardized method has the potential to improve the understanding of the biological mechanisms underlying OS in the future.

Identification and Validation of Common Reference Genes for Normalization of Esophageal Squamous Cell Carcinoma Gene Expression Profiles

Esophageal squamous cell carcinoma (ESCC) is one of the subtypes of esophageal cancer with Chinese characteristics, and its five-year survival rate is less than 20%. Early diagnosis is beneficial to improving the survival rate of ESCC significantly. Quantitative Real-Time Polymerase Chain Reaction is a high-throughput technique that can quantify tumor-related genes for early diagnosis. Its accuracy largely depends on the stability of the reference gene. There is no systematic scientific basis to demonstrate which reference gene expression is stable in ESCC and no consensus on the selection of internal reference. Therefore, this research used four software programs (The comparative delta-Ct method, GeNorm, NormFinder, and BestKeeper) to evaluate the expression stability of eight candidate reference genes commonly used in other tumor tissues and generated a comprehensive analysis by RefFinder. Randomly selected transcriptome sequencing analysis confirmed the SPP1 gene is closely related to ESCC. It was found that the expression trend of SPP1 obtained by RPS18 and PPIA as internal reference genes were the same as that of sequencing. The results show that RPS18 and PPIA are stable reference genes, and PPIA + RPS18 are a suitable reference gene combination. This is a reference gene report that combines transcriptome sequencing analysis and only focuses on ESCC, which makes the quantification more precise, systematic, and standardized, and promotes gene regulation research and the early diagnosis of ESCC in the future.

Uncovering the stability status of the reputed reference genes in breast and hepatic cancer cell lines

Accurate and reliable relative gene expression analysis via the Reverse Transcription-quantitative Real Time PCR (RT-qPCR) method strongly depends on employing several stable reference genes as normalizers. Utilization of the reference genes without analyzing their expression stability under each experimental condition causes RT-qPCR analysis error as well as false output. Similar to cancerous tissues, cancer cell lines also exhibit various gene expression profiles. It is crucial to recognize stable reference genes for well-known cancer cell lines to minimize RT-qPCR analysis error. In this study, we showed the expression level and investigated the expression stability of eight common reference genes that are ACTB, YWHAZ, HPRT1, RNA18S, TBP, GAPDH, UBC, and B2M, in two sets of cancerous cell lines. One set contains MCF7, SKBR3, and MDA-MB231 as breast cancer cell lines. Another set includes three hepatic cancer cell lines, including Huh7, HepG2, and PLC-PRF5. Three excel-based softwares comprising geNorm, BestKeeper, and NormFinder, and an online tool, namely RefFinder were used for stability analysis. Although all four algorithms did not show the same stability ranking of nominee genes, the overall results showed B2M and ACTB as the least stable reference genes for the studied breast cancer cell lines. While TBP had the lowest expression stability in the three hepatic cancer cell lines. Moreover, YWHAZ, UBC, and GAPDH showed the highest stability in breast cancer cell lines. Besides that, a panel of five nominees, including ACTB, HPRT1, UBC, YWHAZ, and B2M showed higher stability than others in hepatic cancer cell lines. We believe that our results would help researchers to find and to select the best combination of the reference genes for their own experiments involving the studied breast and hepatic cancer cell lines. To further analyze the reference genes stability for each experimental condition, we suggest researchers to consider the provided stability ranking emphasizing the unstable reference genes.

Identification of Novel Endogenous Controls for qPCR Normalization in SK-BR-3 Breast Cancer Cell Line

Normalization of gene expression using internal controls or reference genes (RGs) has been the method of choice for standardizing the technical variations in reverse transcription quantitative polymerase chain reactions (RT-qPCR). Conventionally, ACTB and GAPDH have been used as reference genes despite evidence from literature discouraging their use. Hence, in the present study we identified and investigated novel reference genes in SK-BR-3, an HER2-enriched breast cancer cell line. Transcriptomic data of 82 HER2-E breast cancer samples from TCGA database were analyzed to identify twelve novel genes with stable expression. Additionally, thirteen RGs from the literature were analyzed. The expression variations of the candidate genes were studied over five successive passages (p) in two parallel cultures S1 and S2 and in acute and chronic hypoxia using various algorithms. Finally, the most stable RGs were selected and validated for normalization of the expression of three genes of interest (GOIs) in normoxia and hypoxia. Our results indicate that HSP90AB1, DAD1, PFN1 and PUM1 can be used in any combination of three (triplets) for optimizing intra- and inter-assay gene expression differences in the SK-BR-3 cell line. Additionally, we discourage the use of conventional RGs (ACTB, GAPDH, RPL13A, RNA18S and RNA28S) as internal controls for RT-qPCR in SK-BR-3 cell line.

Antibacterial, Antioxidant and Melanogenesis Inhibitory Activity of Auraptene, a Coumarin from Ferula szowitsiana Root

The auraptene is a geranyloxyn coumarin found in the Ferula species. The plant is endemic in Central Asia and it is used as a medicinal food in Iran. This research aimed to evaluate the antibacterial, antioxidant, and anti-melanogenic properties of auraptene, a coumarin from Ferula szowitsiana root. The results revealed that auraptene possessed antibacterial activity with minimum inhibitory and minimum bactericidal concentrations ranged from 2.5 up to 10 mg/ml against human pathogenic bacteria (Escherichia coli, Salmonella typhimurium, Salmonella paratyphi, Clostridium perfringens, Staphylococcus aureus). The nitric oxide scavenging activity (IC₅₀: 670.9 µg/ml) showed its moderate antioxidant potential. Similarly, the results of ferric thiocyanate and thiobarbituric acid assays reconfirmed the moderate antioxidant activity of auraptene and indicated the percentage inhibitions of hydroxyl radicals to be 31.87 and 14%, respectively. The cell-based antioxidant evaluation confirmed the antioxidant activity of auraptene through up-regulation of the antioxidant-related genes including superoxide dismutase, catalase, and glutathione peroxidase in the human foreskin fibroblast (HFF). The auraptene has also displayed the anti-melanogenic activity through direct tyrosinase enzyme inhibition (IC₅₀ of 29.7 µg/ml) and could modulate the expression of major melanogenesis-related genes including tyrosinase, tyrosinase-related protein 1, and dopachrome tautomerase in the murine melanoma cell line. The auraptene from Ferula szowitsiana root exhibited antibacterial, antioxidant, and melanogenesis inhibitory activities.

Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues

Failure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity—a network topology metric—also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.