Identification of suitable mRNAs and microRNAs as reference genes for expression analyses in skin cells under sex hormone exposure

Sex-dependent interaction of PTGS2 with miR-146a as risk factor for melanoma and the impact of sex hormones in gene expression in skin cells

Gender disparity in melanoma is a complex issue where sex hormones could be engaged. Differences in genetic variations are important in understanding the mechanisms of sex disparity in melanoma. Post-transcriptional regulation of prostaglandin-endoperoxide synthase (PTGS2) mRNA occurs through a complex interplay of specific trans-acting RNA-binding proteins and microRNAs. MiR-146a is a key player in melanoma, modulating immune responses and tumor microenvironment (TME). Polymorphisms in PTGS2 gene rs20415GC have been associated with an increased risk of melanoma. Epistasis between polymorphisms rs20415GC was investigated by genotyping 453 melanoma patients and 382 control individuals. The effects of testosterone and 17β-estradiol were analyzed in keratinocytes and two melanoma cell lines. The rs2910164GG showed a higher risk in the presence of the genotype rs20417CC in the male population. Testosterone and 17β-estradiol act differently on PTGS2 and miR-146a expression, depending on the cell type. Testosterone augments PTGS2 gene expression in keratinocytes and miR-146a in melanoma cells. While 17β-estradiol only increases miR-146a expression in HaCaT cells. The present study indicates a sex-specific relation between miR-146a and PTGS2 polymorphisms with melanoma cancer risk. Testosterone and 17β-estradiol act differently on the expression of PTGS2 and miR-146a depending on the skin cell type.

Sex and the basal mRNA synthesis machinery

Evolution and change generated an incredible diversity of organisms on this earth. Yet, some processes are so central to life that change is strongly selected against. Synthesis of the eukaryotic messenger RNA is one example. The assemblies that carry out transcription and processing (capping, polyadenylation, and splicing) are so conserved that most genes have recognizable orthologs in yeast and humans. Naturally, most would conclude transcription and processing are identical in both sexes. However, this is an assumption. Men and women vastly differ in their physiologies. The incidence of pathologies, symptom presentation, disease outcome, and therapeutic response in each sex vary enormously. Despite the harm ignorance causes women, biological research has been historically carried out without regard to sex. The male mouse was the default mammal. A cultured cell's sex was considered irrelevant. Attempts to fill this knowledge gap have revealed molecular dissimilarities. For example, the earliest embryonic male and female transcriptomes differ long before fetal sex hormones appear. We used public data to challenge the assumption of sameness by reviewing reports of sex-biased gene expression and gene targeting. We focused on 120 genes encoding nonregulatory proteins involved in mRNA synthesis. Remarkably, genes with recognizable orthologs in yeast and thus LEAST likely to differ, did differ between the sexes. The rapidly growing public databases can be used to compare the expression of any gene in male and female tissues. Appreciating the principles that drive sex differences will enrich our understanding of RNA biology in all humans-men and women. This article is categorized under: RNA in Disease and Development > RNA in Development RNA Evolution and Genomics > Computational Analyses of RNA.

Human Melanoma Cells Differentially Express RNASEL/RNase-L and miR-146a-5p under Sex Hormonal Stimulation

Polymorphisms in the ribonuclease L (RNASEL) coding gene and hsa-miR-146a-5p (miR-146a) have been associated with melanoma in a sex-specific manner. We hypothesized that RNASEL and miR-146a expression could be influenced by sex hormones playing a role in the female advantages observed in melanoma incidence and survival. Thus, we explored the effects of testosterone and 17β-estradiol on RNASEL and miR-146a expression in LM-20 and A375 melanoma cell lines. Direct targeting of miR-146a to the 3′ untranslated region (3′UTR) of RNASEL was examined using a luciferase reporter system. Our results indicate that RNASEL is a direct target of miR-146a in both melanoma cell lines. Trough qPCR and western blot analyses, we explored the effect of miR-146a mimic transfection in the presence of each hormone either on RNASEL mRNA level or on protein expression of RNase-L, the enzyme codified by RNASEL gene. In the presence of testosterone or 17β-estradiol, miR-146a overexpression did not influence RNASEL transcript level in LM-20 cell line, but it slightly induced RNASEL mRNA level in A375 cells. Remarkably, miR-146a overexpression was able to repress the protein level of RNase-L in both LM-20 and A375 cells in the presence of each hormone, as well as to elicit high expression levels of the activated form of the extracellular signal-regulated kinases (ERK)1/2, hence confirming the pro-tumorigenic role of miR-146a overexpression in melanoma. Thereafter, we assessed if the administration of each hormone could affect the endogenous expression of RNASEL and miR-146a genes in LM-20 and A375 cell lines. Testosterone exerted no significant effect on RNASEL gene expression in both cell lines, while 17β-estradiol enhanced RNASEL transcript level at least in LM-20 melanoma cells. Conversely, miR-146a transcript augmented only in the presence of testosterone in either melanoma cell line. Importantly, each hormone acted quite the opposite regarding the RNase-L protein expression, i.e., testosterone significantly decreased RNase-L expression, whereas 17β-estradiol increased it. Overall, the data show that, in melanoma cells treated with 17β-estradiol, RNase-L expression increased likely by transcriptional induction of its gene. Testosterone, instead, decreased RNase-L expression in melanoma cell lines with a post-transcriptional mechanism in which miR-146a could play a role. In conclusion, the pro-tumor activity of androgen hormone in melanoma cells could be exacerbated by both miR-146a increase and RNase-L downregulation. These events may contribute to the worse outcome in male melanoma patients.

Reference gene selection in bovine caruncular epithelial cells under pregnancy-associated hormones exposure

Examination of transcriptional regulation occurring during pregnancy establishment and maintenance requires the identification of endogenous reference genes characterized by high expression stability. Since the expression of some reference genes may be modulated by pregnancy-associated hormones, the goal of our study was to identify suitable reference genes unaffected by hormonal treatment. In our study bovine caruncular epithelial cells were subjected to progesterone, estrogen and prostaglandin F_2α treatment. Ten candidate reference genes (ACTR1A, CNOT11, HDAC1, HPRT1, RPL19, RPS9, SDHA, SUZ12, UXT and ZNF131) were evaluated with the use of four approaches (geNorm, NormFinder, BestKeeper, delta Ct). We found that RPS9 and SUZ12 displayed the highest expression stability in the tested material. Moreover, HPRT1 and SDHA were found inappropriate for RT-qPCR data normalization as they demonstrated the highest expression variability out of all candidates analysed. Hence geNorm calculations shown that the use of just two best-performing genes would be sufficient for obtaining reliable results, we propose that RPS9 and SUZ12 be used as suitable endogenous controls in future studies investigating gene expression in normal and compromised pregnancies.

A Panel of Eight miRNAs Is Deregulated in HTLV-2 Infected PBMCs and BJABGu Cell Line

Despite human T-cell leukemia virus type 1 (HTLV-1) and HTLV-2 being retroviruses closely related at a genomic level, HTLV-2 differs from HTLV-1 in terms of pathogenicity in both single infection and coinfection contexts. Moreover, the HTLV-2 association with clinical outcomes is still debated and several mechanisms underlying HTLV-2 infection remain unexplored as well. Cellular miRNAs are key factors in the post-transcriptional regulation of gene expression and they are known to be potential targets for several pathogens to control the host microenvironment and, in particular, escape immune responses. Here, we identified a HTLV-2-related signature of eight miRNAs (miR-125a-3p, miR-381-3p, miR-502-5p, miR-708-5p, miR-548d-5p, miR-548c-5p, miR-1-3p, and miR-511-5p) in both HTLV-2 infected PBMC and BJABGu cell lines. Altered miRNA expression patterns were correlated with the impairment of Th cell differentiation and signaling pathways driven by cytokines and transcriptional factors such as the Runt-related transcription factor (RUNX) family members. Specifically, we demonstrated that the RUNX2 protein was significantly more expressed in the presence of Tax-2 compared with Tax-1 in an in vitro cell model. To the best of our knowledge, these data represent the first contribution to elucidating the HTLV-2 mediated alteration of host cell miRNA profiles that may impact on HTLV-2 replication and persistent infection.

Selection of reference genes for quantitative analysis of microRNA expression in three different types of cancer

MicroRNAs (miRNAs) are promising biomarkers in cancer research. Quantitative PCR (qPCR), also known as real-time PCR, is the most frequently used technique for measuring miRNA expression levels. The use of this technique, however, requires that expression data be normalized against reference genes. The problem is that a universal internal control for quantitative analysis of miRNA expression by qPCR has yet to be known. The aim of this work was to find the miRNAs with stable expression in the thyroid gland, brain and bone marrow according to NanoString nCounter miRNA quantification data. As a results, the most stably expressed miRNAs were as follows: miR-361-3p, -151a-3p and -29b-3p in the thyroid gland; miR-15a-5p, -194-5p and -532-5p in the brain; miR-140-5p, -148b-3p and -362-5p in bone marrow; and miR-423-5p, -28-5p and -532-5p, no matter what tissue type. These miRNAs represent promising reference genes for miRNA quantification by qPCR.