| Literature DB >> 23469001 |
Francesca Simonato1, Laura Ventura, Nicola Sartori, Rocco Cappellesso, Matteo Fassan, Lill-Tove Busund, Ambrogio Fassina.
Abstract
MicroRNAs' dysregulation and profiling have been demonstrated to be clinically relevant in urothelial carcinoma (UC). Urine cytology is commonly used as the mainstay non-invasive test for secondary prevention and follow-up of UC patients. Ancillary tools are needed to support cytopathologists in the diagnosis of low-grade UC. The feasibility and reliability of microRNAs profiling by qRT-PCR analysis (miR-145 and miR-205) in archival routine urine cytology smears (affected by fixation/staining [Papanicolau] and room temperature storage) was tested in a series of 15 non-neoplastic and 10 UC urine specimens. Only samples with >5,000 urothelial cells and with <50% of inflammatory cells/red blood cells clusters were considered. Overall, a satisfactory amount of total RNA was obtained from all the considered samples (mean 1.27±1.43 µg, range 0.06-4.60 µg). Twenty nanograms of total RNA have been calculated to be the minimal total RNA concentration for reliable and reproducible miRNAs expression profiling analysis of archival cytological smears (slope= -3.4084; R-squared=0.99; efficiency=1.94). miR-145 and miR-205 were significantly downregulated in UC samples in comparison to non-tumor controls. These findings demonstrate that urine archival cytology smears are suitable for obtaining high-quality RNA to be used in microRNAs expression profiling. Further studies should investigate if miRNAs profiling can be successfully translated into clinical practice as diagnostic or prognostic markers.Entities:
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Year: 2013 PMID: 23469001 PMCID: PMC3585351 DOI: 10.1371/journal.pone.0057490
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Selection of the cytology specimens.
Only cases with >5,000 well-preserved and well-visualized urothelial cells (as observed in 10 fields at 4x magnification) were selected. Cases largely constituted by red blood cells or inflammatory cells were excluded.
Cytological and molecular features of the 25 cytology samples.
| Sample | Type | RNA yield (µg) | A260/A280 ratio | Cellularity | Cell types | |
| Cancer | Inflammatory | |||||
| 1 | NT | 1.28 | 1.74 | H | – | 5% |
| 2 | NT | 1.52 | 1.80 | H | – | 10% |
| 3 | NT | 0.88 | 1.01 | L | – | – |
| 4 | NT | 2.60 | 1.96 | H | – | – |
| 5 | NT | 2.92 | 2.30 | H | – | 5% |
| 6 | NT | 4.60 | 2.24 | H | – | 30% |
| 7 | NT | 4.44 | 2.25 | H | – | 20% |
| 8 | NT | 0.08 | 1.90 | L | – | 10% |
| 9 | NT | 0.29 | 2.80 | L | – | – |
| 10 | NT | 0.06 | 1.92 | L | – | – |
| 11 | NT | 2.21 | 2.01 | H | – | – |
| 12 | NT | 1.04 | 1.71 | H | – | 15% |
| 13 | NT | 1.32 | 1.94 | H | – | 10% |
| 14 | NT | 1.15 | 1.71 | H | – | 5% |
| 15 | NT | 0.94 | 1.74 | L | – | 5% |
| 16 | T | 0.17 | 2.22 | L | 40% | 10% |
| 17 | T | 0.11 | 2.25 | L | 30% | 20% |
| 18 | T | 0.25 | 2.25 | L | 50% | 5% |
| 19 | T | 0.16 | 2.00 | L | 35% | 15% |
| 20 | T | 0.13 | 2.24 | L | 70% | 10% |
| 21 | T | 0.25 | 2.01 | L | 60% | 10% |
| 22 | T | 4.20 | 1.88 | H | 50% | 5% |
| 23 | T | 0.16 | 1.68 | L | 30% | 15% |
| 24 | T | 0.48 | 1.66 | L | 40% | 20% |
| 25 | T | 0.62 | 1.71 | H | 50% | 10% |
Note: NT = non-tumor; T = tumor; H = >10,000 cells; L = >5,000 and <10,000 cells.
RNA amount cut-off values for qRT-PCR analysis using archival cytology smears.
| Material | Gene | RNA amount cut-off | Slope | R-squared | Efficiency |
| Cell lines | RNA U6B | 1 ng | −3.561 | 0.99 | 1.81 |
| miR-205 | 5 ng | −3.649 | 0.91 | 1.75 | |
| Non-tumor urine smears | RNA U6B | 10 ng | −2.966 | 0.99 | 2.37 |
| miR-205 | 20 ng | −3.408 | 0.99 | 1.94 |
Figure 2Identification of the minimal RNA quantity to obtain an adequate qRT-PCR reaction from cytology specimens.
(A) The relationship between Ct and ldose for the two cell lines (BxPc3 and Capan-1) was analyzed as covariance (ANCOVA) model and the minimal RNA quantity was identified in terms of the estimated slope. For RNU6B, the ANCOVA analysis (R2 = 0.99) revealed that the slope of the relationship between ldose and Ct is the same in the two cells lines (p = 0.55) and it is equal to −3.73 (±0.07, p<0.0001), with efficiency e = 1.70. The estimated models are Ct = 27.65–3.55*ldose for BxPc3 and Ct = 24.97–3.55*ldose for Capan-1. (B) For miR-205 ANCOVA analysis (R2 = 0.98) revealed that the slope of the relationship between ldose and Ct is the same in the two cell lines and is equal to −4.00 (±0.12, p<0.000), with efficiency e = 1.50. The estimated model is Ct = 29.09–3.64*ldose both for BxPc3 and Capan-1. (C) To estimate the relationship between Ct and ldose on the 15 non-neoplastic patients, we used linear mixed effect models including a random effect for the subject. (D) The minimal RNA quantity was selected in terms of the fixed effect slope. For miR-205, when considering all the dilutions, the LME analysis (R2 = 0.92) revealed that the fixed effect slope of the relationship between ldose and Ct is −1.73 (±0.13, p<0.000), with efficiency e = 4.78.
Figure 3Total RNA extracted from archival urine cytology smears is suitable for miRNA expression profiling.
Box plots show differences in miRNAs expression between non-tumor (NT) and low grade urothelial carcinoma samples (T). *p<0.05.