Polycystic kidney disease is a complex clinical entity which comprises a group of genetic diseases that leads to renal cyst development. We evaluated the most suitable housekeeping genes for microRNA expression by RT-qPCR analyses of kidney tissues in Pkd1-deficient mouse models from a panel of five candidates genes (miR-20a, miR-25, miR-26a, miR-191 and U6) and 3 target genes (miR-17, miR-21 and let-7a) using samples from kidneys of cystic mice (Pkd1flox/flox:Nestincre, CY), non-cystic controls (Pkd1flox/flox, NC), Pkd1-haploinsufficient (Pkd1+/−, HT), wild-type controls (Pkd1+/+, WT), severely cystic mice (Pkd1V/V, SC), wild-type controls (CO). The stability of the candidate genes was investigated using NormFinder, GeNorm, BestKeeper, DataAssist, and RefFinder software packages and the comparative ΔCt method. The analyses identified miR-26a as the most stable housekeeping gene for all kidney samples, miR-20a for CY and NC, miR-20a and miR-26a for HT and WT, and miR-25 and miR-26a for SC and CO. Expression of miR-21 was upregulated in SC compared to CO and trends of miR-21 upregulation and let-7a downregulation in CY and HT compared to its control kidneys, when normalized by different combinations of miR-20a, miR-25 and miR-26a. Our findings established miR-20a, miR-25, and miR-26a as the best housekeeping genes for miRNA expression analyses by RT-qPCR in kidney tissues of Pkd1-deficient mouse models.

Aim: To analyze gene expression and copy number of five miRNAs ( miR-1204, miR-1205, miR-1206, miR-1207 and miR-1208) localized in this chromosome region in gastric cancer (GC). Materials & methods: 65 paired neoplastic and non-neoplastic specimens collected from GC patients and 20 non-neoplastic gastric tissues from cancer-free individuals were included in this study. The expression levels of the five miRNAs were accessed by real time qPCR and were correlated. Results:  MiR-1207-3p, miR-1205, miR-1207-5p and miR-1208 were upregulated in approximately 50% of GC tumors in relation to those of adjacent non-neoplastic tissues. MiR-1205 expression was associated with gain of gene copies and was upregulated in adjacent non-neoplastic samples relative to external controls. Conclusion: The coexpression of the 8q24 miRNAs indicated the role of miR-1205 in the initiation of gastric cancer development.

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BackgroundReal-time PCR remains currently the gold standard method for gene expression studies. Identification of the best reference gene is a key point in performing high quality qPCR, providing strong support for results, as well as performing as a source of bias when inappropriately chosen. Mesangial cells and podocytes, as essential cell lines to study diabetic kidney disease (DKD) physiopathology, demand accurate analysis of the reference genes used so far to enhance validity of gene expression studies, especially regarding high glucose (HG) and DKD treatments, with angiotensin II receptor blockers (e.g. Losartan) being the most commonly used. This study aimed to evaluate the suitability and define the most stable reference gene for mesangial cells and podocytes studies of an in vitro DKD model of disease and its treatment.MethodsFive software packages (RefFinder, NormFinder, GeNorm, Bestkeeper, and DataAssist) and the comparative ΔCt method were selected to analyze six different candidate genes: HPRT, ACTB, PGAM-1, GAPDH, PPIA, and B2M. RNA was extracted and cDNA was synthesized from immortalized mouse mesangial cells and podocytes cultured in 4 groups: control (n=5; 5mM glucose), mannitol (n=5; 30mM, as osmotic control), HG (n=5; 30mM glucose), and HG + losartan (n=5; 30mM glucose and 10-4 mM of losartan). Real-time PCR was performed according to MIQE guidelines.ResultsWe identified that the use of 2 genes is the best combination for qPCR normalization for both mesangial cell and podocytes. For mesangial cells, the combination of HPRT and ACTB presented higher stability values. For podocytes, HPRT and GAPDH showed the best results.ConclusionThis analysis provides support for the use of HPRT and ACTB as reference genes in mouse mesangial cell studies of gene expression via real-time PCR technique, while for podocytes, HPRT and GAPDH should be chosen.

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Sepsis contributes to the high prevalence of acute kidney injury (AKI), which mainly occurs in hospitalized patients. The delay in AKI detection is a risk factor for death and chronicity; thus, early diagnosis is essential for initiating proper treatment strategies. Although serum creatinine is used as biomarker, it is increased in plasma serum creatinine only at late stages of AKI. MicroRNAs (miRNAs), a class of noncoding RNAs responsible for gene regulation, can be found in biological fluids within vesicles such as exosomes and may be promising tools for the early detection of AKI. We aimed to identify potential blood miRNAs that can be used as early biomarkers of sepsis-induced AKI in rats. Adult male Wistar rats received a single dose of lipopolysaccharide (LPS). The earliest significant increase in serum creatinine was detected 4 h after LPS administration. To evaluate whether miRNAs could act as early biomarkers, blood samples were collected before and 2 h after LPS infusion. Serum NGAL levels were used as a comparative marker. Serum miRNAs were derived from exosomes, and their expression were evaluated by the PCR array. miR-181a-5p and miR-23b-3p showed higher expression in LPS-treated rats than in the control animals (p < 0.05). Bioinformatics analysis showed that both miRNAs target molecules associated with transcription factors that regulate genes related to proinflammatory cytokines. Considering that LPS activates transcription factors that lead to the production of proinflammatory cytokines, possible premature changes in the serum levels of miR-181a-5p and miR-23b-3p may be used to identify sepsis-induced AKI earlier.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most common inherited renal disorder, characterized by renal cyst development leading to end-stage renal disease. Although the appropriate choice of suitable reference is critical for quantitative RNA analysis, no comparison of frequently used “housekeeping” genes is available. Here, we determined the validity of 7 candidate housekeeping genes (Actb, Actg1, B2m, Gapdh, Hprt, Pgam1 and Ppia) in kidney tissues from mouse models orthologous to ADPKD, including a cystic mice (CY) 10–12 weeks old (Pkd1flox/flox:Nestincre/Pkd1flox/−:Nestincre, n = 10) and non-cystic (NC) controls (Pkd1flox/flox/Pkd1flox/-, n = 10), Pkd1-haploinsufficient (HT) mice (Pkd1+/−, n = 6) and wild-type (WT) controls (Pkd1+/+, n = 6) and a severely cystic (SC) mice 15 days old (Pkd1V/V, n = 7) and their controls (CO, n = 5). Gene expression data were analyzed using six distinct statistical softwares. The estimation of the ideal number of genes suggested the use of Ppia alone as sufficient, although not ideal, to analyze groups altogether. Actb, Hprt and Ppia expression profiles were correlated in all samples. Ppia was identified as the most stable housekeeping gene, while Gapdh was the least stable for all kidney samples. Stat3 expression level was consistent with upregulation in SC compared to CO when normalized by Ppia expression. In conclusion, present findings identified Ppia as the best housekeeping gene for CY + NC and SC + CO groups, while Hprt was the best for the HT + WT group.

Despite the advancements in cancer treatments, gastric cancer is still one of the leading causes of death worldwide. In this context, it is of great interest to discover new and more effective ways of treating this disease. Accumulated evidences have demonstrated the amplification of 8q24.21 region in gastric tumors. Furthermore, this is the region where the widely known MYC oncogene and different microRNAs are located. MYC deregulation is key in tumorigenesis in various types of tissues, once it is associated with cell proliferation, survival, and drug resistance. microRNAs are a class of noncoding RNAs that negatively regulate the protein translation, and which deregulation is related with gastric cancer development. However, little is understood about the interactions between microRNAs and MYC. Here, we overview the MYC role and its relationship with the microRNAs network in gastric cancer aiming to identify potential targets useful to be used in clinic, not only as biomarkers, but also as molecules for development of promising therapies.