Quantitation of microRNA‑92a in colorectal adenocarcinoma and its precancerous lesions: Co‑utilization of in situ hybridization and spectral imaging

Lao,I   Weng; Cui,Fengyun; Zhu,Hongguang

doi:10.3892/ol.2014.2813

Quantitation of microRNA‑92a in colorectal adenocarcinoma and its precancerous lesions: Co‑utilization of in situ hybridization and spectral imaging

Authors:
- I Weng Lao
- Fengyun Cui
- Hongguang Zhu
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Affiliations: Department of Pathology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, P.R. China
Published online on: December 18, 2014 https://doi.org/10.3892/ol.2014.2813
Pages: 1109-1115
Copyright: © Lao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The expression level of microRNA (miR)‑92a has been proven to increase during the development of colorectal adenocarcinoma (CA) and has been verified at the cellular, plasma and fecal levels by various quantitative methods. However, a method to quantitate the expression level using tissue sections has not been established. To do this, in situ hybridization (ISH) and multispectral imaging microscopy (MSI) were introduced to quantitate miR‑92a expression on the microscopic level. ISH of miR‑92a was first performed on 34 tissue samples of CA and adenomas with high‑grade and low‑grade intraepithelial neoplasms, while 31 paralesional normal tissue samples were defined as the control. Subsequently, a MSI technique was applied to quantitate the hybridization signal in terms of optical density (OD) at the visible wavelength. A t‑test with unequal variance was used to examine the statistical significance between the groups. Despite all 34 tissue sections demonstrating at least partial positivity of miR‑92a expression following ISH, visual grading was inconclusive. As such, the signal of ISH was transformed in terms of OD and further analyzed by employing the MSI system. A statistically significant difference was observed between the expression levels of miR‑92a in CA and the paralesional normal controls. By contrast, a poor correlation was revealed between visual and spectral grading. The co‑utilization of ISH and MSI generated a legible observation in the expression level of miR‑92a, revealing the dynamic change in miR‑92a expression in the progression of the disease and providing important information for further functional investigation.

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1	Wienholds E, Kloosterman WP, Miska E, et al: MicroRNA expression in zebrafish embryonic development. Science. 309:310–311. 2005. View Article : Google Scholar : PubMed/NCBI
2	Zhang B and Farwell MA: microRNAs: a new emerging class of players for disease diagnostics and gene therapy. J Cell Mol Med. 12:3–21. 2008. View Article : Google Scholar
3	Lu J, Getz G, Miska EA, et al: MicroRNA expression profiles classify human cancers. Nature. 435:834–838. 2005. View Article : Google Scholar : PubMed/NCBI
4	Yang L, Belaguli N and Berger DH: MicroRNA and colorectal cancer. World J Surg. 33:638–646. 2009. View Article : Google Scholar : PubMed/NCBI
5	Guiot Y and Rahier J: The effects of varying key steps in the non-radioactive in situ hybridization protocol: a quantitative study. Histochem J. 27:60–68. 1995. View Article : Google Scholar : PubMed/NCBI
6	Levsky JM and Singer RH: Fluorescence in situ hybridization: past, present and future. J Cell Sci. 116:2833–2838. 2003. View Article : Google Scholar : PubMed/NCBI
7	Levenson RM: Spectral imaging perspective on cytomics. Cytometry A. 69:592–600. 2006. View Article : Google Scholar : PubMed/NCBI
8	Barber PR, Vojnovic B, Atkin G, Daley FM, et al: Applications of cost-effective spectral imaging microscopy in cancer research. J Phys D Appl Phys. 36:1729–1738. 2003. View Article : Google Scholar
9	Farkas DL, Du C, Fisher GW, et al: Non-invasive image acquisition and advanced processing in optical bioimaging. Comput Med Imaging and Graph. 22:89–102. 1998. View Article : Google Scholar
10	Levenson R, Beechem J and McNamara G: Spectral imaging in preclinical research and clinical pathology. Stud Health Technol Inform. 185:43–75. 2013.PubMed/NCBI
11	Atkin G, Barber PR, Vojnovic B, et al: Correlation of spectral imaging and visual grading for the quantification of thymidylate synthase protein expression in rectal cancer. Hum Pathol. 36:1302–1308. 2005. View Article : Google Scholar : PubMed/NCBI
12	Slaby O, Svoboda M, Michalek J and Vyzula R: MicroRNAs in colorectal cancer: translation of molecular biology into clinical application. Mol Cancer. 8:1022009. View Article : Google Scholar : PubMed/NCBI
13	Ahmed FE, Jeffries CD, Vos PW, et al: Diagnostic microRNA markers for screening sporadic human colon cancer and active ulcerative colitis in stool and tissue. Cancer Genomics Proteomics. 6:281–295. 2009.PubMed/NCBI
14	Wang S, Wang L, Bayaxi N, et al: A microRNA panel to discriminate carcinomas from high-grade intraepithelial neoplasms in colonoscopy biopsy tissue. Gut. 62:280–289. 2013. View Article : Google Scholar
15	Liang Y, Ridzon D, Wong L and Chen C: Characterization of microRNA expression profiles in normal human tissues. BMC Genomics. 8:1662007. View Article : Google Scholar : PubMed/NCBI
16	Jørgensen S, Baker A, Møller S and Nielsen BS: Robust one-day in situ hybridization protocol for detection of microRNAs in paraffin samples using LNA probes. Methods. 52:375–381. 2010. View Article : Google Scholar : PubMed/NCBI
17	Nuovo GJ, Elton TS, Nana-Sinkam P, et al: A methodology for the combined in situ analyses of the precursor and mature forms of microRNAs and correlation with their putative targets. Nat Protoc. 4:107–115. 2009. View Article : Google Scholar : PubMed/NCBI
18	Zhang Q, He XJ, Liu YJ, Ma LP and Pan XY: Profiling of microRNAs in mouse brain with real-time PCR array. Beijing Da Xue Xue Bao. 41:152–157. 2009.(In Chinese). PubMed/NCBI
19	Chugh P, Tamburro K and Dittmer DP: Profiling of pre-micro RNAs and microRNAs using quantitative real-time PCR (qPCR) arrays. J Vis Exp. 3:22102010.
20	Mansfield JR: Cellular context in epigenetics: quantitative multicolor imaging and automated per-cell analysis of miRNAs and their putative targets. Methods. 52:271–280. 2010. View Article : Google Scholar : PubMed/NCBI
21	Ryoo SR, Lee J, Yeo J, et al: Quantitative and multiplexed microRNA sensing in living cells based on peptide nucleic acid and nano graphene oxide (PANGO). ACS Nano. 7:5882–5891. 2013. View Article : Google Scholar : PubMed/NCBI
22	Huang Z, Huang D, Ni S, et al: Plasma microRNAs are promising novel biomarkers for early detection of colorectal cancer. Int J Cancer. 127:118–126. 2010. View Article : Google Scholar
23	Ng EK, Chong WW, Jin H, et al: Differential expression of microRNAs in plasma of patients with colorectal cancer: a potential marker for colorectal cancer screening. Gut. 58:1375–1381. 2009. View Article : Google Scholar : PubMed/NCBI
24	Link A, Balaguer F, Shen Y, et al: Fecal MicroRNAs as novel biomarkers for colon cancer screening. Cancer Epidemiol Biomarkers Prev. 19:1766–1774. 2010. View Article : Google Scholar : PubMed/NCBI
25	Kloosterman WP, Wienholds E, de Bruijn E, Kauppinen S and Plasterk RH: In situ detection of miRNAs in animal embryos using LNA-modified oligonucleotide probes. Nat Methods. 3:27–29. 2006. View Article : Google Scholar
26	Stenvang J, Silahtaroglu AN, Lindow M, Elmen J and Kauppinen S: The utility of LNA in microRNA-based cancer diagnostics and therapeutics. Semin Cancer Biol. 18:89–102. 2008. View Article : Google Scholar : PubMed/NCBI
27	Hara M, Yamada S and Hirata K: Nonradioactive In Situ Hybridization: Recent Techniques and Applications. Endocr Pathol. 9:21–29. 1998. View Article : Google Scholar
28	Crabb ID, Hughes SS, Hicks DG, et al: Nonradioactive in situ hybridization using digoxigenin-labeled oligonucleotides. Applications to musculoskeletal tissues. Am J Pathol. 141:579–589. 1992.PubMed/NCBI
29	Ornberg RL, Woerner BM and Edwards DA: Analysis of stained objects in histological sections by spectral imaging and differential absorption. J Histochem Cytochem. 47:1307–1314. 1999. View Article : Google Scholar : PubMed/NCBI
30	Levenson RM and Hoyt CC: Spectral imaging and microscopy. Am Lab. 32:26–34. 2000.
31	Kavvadias V, Epitropou G, Georgiou N, et al: A novel endoscopic spectral imaging platform integrating k-means clustering for early and non-invasive diagnosis of endometrial pathology. Conf Proc IEEE Eng Med Biol Soc. 2013:4442–4445. 2013.PubMed/NCBI
32	Seidal T, Balaton AJ and Battifora H: Interpretation and quantification of immunostains. Am J Surg Pathol. 25:1204–1207. 2001. View Article : Google Scholar : PubMed/NCBI