alexa Differential expression of miRNAs in colorectal cancer | OMICS International
ISSN: 2572-4126
Journal of Gastrointestinal Cancer and Stromal Tumors
Like us on:
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Differential expression of miRNAs in colorectal cancer

Nihat Dilsiz1*, Ahmet Balik2, Filiz Mutaf3, Cemile Yesil4 and Ersin Borazan2

1Department of Molecular Biology and Genetics, Faculty of Engineering and Natural Sciences, Istanbul Medeniyet University, Istanbul, Turkey

2Department of General Surgery, School of Medicine, Gaziantep University, Gaziantep, Turkey

3Ay-Ka Ltd. Şti, Ankara, Turkey

4Synevo Medical Lab., Pathology Department, Ankara, Turkey

*Corresponding Author:
Nihat Dilsiz
Department of Molecular Biology and Genetics
Faculty of Engineering and Natural Sciences
Istanbul Medeniyet University, Istanbul, Turkey
E-mail: [email protected]

Received date: Mar 27, 2016; Accepted date: May 07, 2016; Published date: May 14, 2016

Citation: Dilsiz N, Balik A, Mutaf F, Yesil C, Borazan E (2016) Differential Expression of miRNAs in Colorectal Cancer. J Gastrointest Cancer Stromal Tumor 1:103. doi:10.4172/2572-4126.1000103

Copyright: © 2016 Dilsiz N et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Journal of Gastrointestinal Cancer and Stromal Tumors

Abstract

Colorectal cancer (CRC) is one of the deadliest diseases in the world and current screening methods are still limited. In past decade, it has been discovered that miRNAs play an important role in every cell process including CRC initiation and progression. The aim of this study was to identify differentially expressed miRNAs in normal colon (CRN) and colorectal cancer (CRC) by using microarray system. This includes discovery of new miRNAs related to CRC. Total RNA was extracted from total 12 tissue samples of 7 patients with colorectal cancer undergoing surgical resection of the colon for studying tumor specific changes in miRNA expression compared to 5 matched as normal tissue samples using the Qiagen miRN easy Kit. MiRNA was polyadenylated by using PolyA Tailing master mix. After Flash Tag Biotin HSR Ligation samples were hybridized, stained and washed. The arrays were finally scanned using AGCC Scan control programmer according to the manufacturer’s protocol of Affymetrix Gene Chip software. It was found that some of miRNAs were found up or down regulated in studied CRC tissues compared to non-tumor tissues. MiR-1201, miR-181a, miR-7, miR-188, miR-552, miR-183, miR-941, U71d, ACA3-2 and miR-34c were over expressed and miR-486, HBII-85-6, miR-550-1, miR-635, miR-10b, miR-550-2, ENSG00000238430 and miR-548a were down regulated in patients with CRC. We have also found that some dysregulated miRNAs, which to our knowledge have not previously been associated with colorectal carcinogenesis. Consequently, the results of this study will increase our understanding of development, progression and earlier detection and personnel treatment of colon cancer. This work was supported by grants from the Turkish Ministry of Development (2009K120780 and 2012K120690).

Keywords

Colon cancer; miRNAs; Microarray; Transcriptomics

Introduction

Colorectal cancer (CRC) is one of the deadliest diseases in the world and it is the second most common cause of cancer-related deaths in women, and the third in men. Although CRC mortality rates have declined in Western population, incidence rate of CRC has been increasing in Asia. Identified risk factors for CRC include: aging, gender, family history, lifestyle, pre-existing conditions such as, lynch syndrome, inflammatory bowel disease. CRC is most of the time asymptomatic until the late stages and can be only diagnosed when the cancer is already metastasized [1].

CRC was used to be considered as a disease caused by genetic mutations. However, it is currently viewed as a complex malignancy including epigenetic abnormalities in addition to genetic mutations. Three different pathogenic pathways have been identified which play role in CRC development: chromosomal instability, microsatellite instability and CpG island methylator phenotype. Chromosomal instability (CI) means deregulation of oncogenes such as, KRAS (functions as a transmitter of key extracellular signals) and TP53 (p53 functions as a key transcriptional regulator in cell cycle regulation) and also tumor suppressor genes. Microsatellite instability (MI) is caused by the inactivation of mismatch repair genes such as, hMLH1, hMSH2, hMSH6, and hPMS2. MI can result in Lynch syndrome and sporadic tumors. The CpG island methylator phenotype is caused by hypermethylation of CpG islands at tumor suppressors gene promotors [2,3].

The most common screening methods for CRC are colonoscopy, flexible sigmoidoscopy, guaiac-based fecal occult blood tests, and fecal immunochemical tests. Having the fact that these methods are still limited by unsatisfactory sensitivity and specificity; researchers have investigated the potential use of miRNAs as diagnostic and prognostic biomarkers for CRC screening [1].

During the past decade, it has been discovered that miRNAs play important roles in cancer initiation, progression and metastasis. Functionally, miRNAs can mediate cell proliferation, cell cycle progression, differentiation, metabolism, apoptosis, invasion to trigger tumor formation and angiogenesis [4].

MiRNA is a ≈ 20 nucleotides long non-protein-coding singlestranded RNA molecule. They are involved in almost all biological pathways, including gene expression, cell cycle regulation, cellular development, proliferation, differentiation and apoptosis [5-9].

MiRNAs are transcribed by RNA polymerase II in nucleus into long primary transcripts of miRNA as hairpins (pri-miRNAs, 1-3 kilobases). Nuclear RNase III enzyme (also called Drosha) cleaves primiRNA into a precursor (pre-miRNA, around ≈ 70 nucleotides in length) hairpin-shaped dsRNA. Pre-miRNAs are then exported from nucleus into cytoplasm by a nuclear export factor, Exportin-5 (XPO5). Then, protein complex of RNase III, Dicer, trims pre-miRNA in the cytoplasm to produce mature double-stranded (miRNA/miRNA complex) miRNA duplexes (≈ 20 nucleotides in length). Next, these two strands of the duplexes are unwounded by helicase, and then combined with RNA-induced silencing complex (RISC) containing an argonaut protein. One strand of the duplex is removed and degraded while the other one (single-stranded miRNA, ssmiRNA) is actively interacts with target mRNA to regulate the expression [6,8-13]. The seed region (6-8 nucleotides) at 5’ ends of miRNAs mainly bind to the 3’-untranslated region (3’-UTR) of their target mRNAs with imperfect sequence complementarity. However, recent studies have reported that miRNAs can also bind to 5’UTR, or open reading frame (ORF) of the target mRNA [8]. By binding to their target mRNA, miRNAs can inhibit expression of proteins from mRNA (suppression of translation) or causing mRNA degradation [12,14-18].

Since miRNAs can function as oncogenic (oncomir) as well as tumor suppressor depending on the function of their target genes, miRNAs are known to play an important role in tumorigenesis. A particular miRNA may be found up regulated in some cancer types as oncogenic function, but down regulated in other cancers, indicative of tumor suppressor function [19]. It is possible that the function of a single miRNA is cell or tissue specific. Recent studies indicate that miRNAs may have more oncogenic than tumor suppressive function in CRC [11,20,21]. 1.900 precursor and 2.600 mature miRNA have been identified up to now and these miRNAs are able to regulate the expression of almost 60% of all protein-coding genes in human genome [6,8,9,14,22-24]. Due to its small size, a single miRNA may act on expression of thousands of mRNAs. However, a single gene can be regulated only by multiple different miRNAs [11,13,23,25]. Therefore, miRNA expression profiles have been shown as potential signatures which are highly tissue specific for the classification, diagnosis and progression of cancer. Early detection of CRC by using miRNAs as diagnostic biomarkers provides the best chance for predictive diagnosis and successful treatment of diseases [1,21,26].

In 2003, it was first reported by Michael that differentially expressed upregulated and downregulated miRNAs were associated with CRC development and progression [27]. Since then more than 100 miRNAs have been shown to be associated with CRC since then. It was also shown that downregulation of let-7a-1 in CRC samples. MiR-34a has been shown to block cell proliferation and it is downregulated in colon cancer cells, whereas miR-31, miR-96, miR-31, miR-135b, and miR-183 were up regulated in CRC cells in the same study [28].

MiRNA associations with specific tumor markers also have been identified. Loss of miR-34 expression has been shown to deteriorate TP53-mediated cell death while overexpression of miR-34 results in apoptosis. MiRNAs also have been exhibited to be associated with regulation of oncogenes and with tumor suppressor genes. MiR-143 and let-7 expression levels have been associated with KRAS2 mutations [21]. Furthermore, miRNA-21 and miRNA-183 were found to be upregulated in CRC and miRNA-143, miRNA-145 and miRNA-497 are down-regulated when compared to healthy subjects as stated by different studies [3,6,7,14,17,21,29-32]. Compared with those in normal tissue, miRNAs expression levels are down-regulated in malignant tissue, only several miRNAs are up regulated; most of them play oncogenic roles [8,15,33]. On the other hand, tumor suppressor’s miRNA-497 and miRNA-378c are mainly downregulated in colorectal cancer [29,30].

The first miRNA mimic entered the clinic for cancer therapy is synthetic miRNA-34 (tumor suppressor) loaded in liposomal nanoparticles [34]. In general, there are two strategies to developing miRNA-based therapeutics either by direct inhibition of the interaction between oncogenic miRNA and mRNA or replacement of target tumor suppressor miRNA genes to restore a loss of function [15]. Oncogenic miRNAs could be therapeutically targeted by repression. A simple method to block oncogenic miRNAs is the use of anti-miRNA oligonucleotides complementary to the sequence of the targeted mature oncogenic miRNAs (antagomirs). These oligonucleotides disrupt miRISC complex and prevent degradation of an mRNA which can then be translated. Another approach to more specifically inhibit the miRNA function is to use of miRNA masks which are complementary to binding sites in 3’UTR of target mRNA. MiRNA replacement therapy aims to substitution of tumor suppressor miRNAs absent or expressed at lower levels by using oligonucleotide mimics containing the same sequence as the mature miRNA. Restoration of silenced tumor suppressor miRNAs might produce beneficial effects on cell migration, invasion and increasing sensitivity to therapeutic agents [6,15,21,35].

Materials and Methods

Ethics statement

This study was approved by the Medical Ethical Committee of the Harran University, Turkey and has been performed in accordance with the ethical principles of the 2008 revised Declaration of Helsinki. The samples were used with written informed consents from patients and the approval of the Turkish Academy of Medical Sciences. Tissue samples (~0.5 cm3) from CRC patients were collected at surgery after the pathologist had confirmed the histopathology at the Hospital of Gaziantep Medical University. Normal tissue adjacent to the cancer tissue was used as control for this study. Subjects were signed by participants in a written informed consent form for this study. None of this CRC patients received chemotherapy or radiotherapy before the surgical resection. Each sample was placed in a cryovial and covered with the RNALater (Applied Biosystems) that prevents fragmentation of the fragile mRNA. Due to small sizes of miRNA (20-22 nt.), miRNA levels are remarkably stable in tissue samples when compared to mRNA. Tissue samples were homogenized in liquid nitrogen by using precellys homogenizer (Bertin) and stored at -86°C for subsequent analysis.

Total RNA isolation and reverse transcription of mature miRNAs

Total RNA containing miRNA was purified from homogenate by using the microRNAsy mini isolation kit (Qiagen) according to manufacturer’s instructions. The purity and concentration of total RNA was assessed by using NanoDrop spectrophotometer p360 (Implen). Total RNA samples were aliquoted and stored at -86°C until used.

Microarray profiling of miRNAs

MiRNA expression was profiled by using GeneChip miRNA 3.0 Array (Affymetrix) for five controls and seven CRC with stage I-IV samples. About 1,000 ng RNA from each sample were labeled by biotin using the FlashTag Biotin HSR RNA labeling kit (Affymetrix). Then, the labeled samples were hybridized with the human probes on the microarray chips for 16 hours at 48°C with a rotation speed of 60 rpm. After hybridization, the probe arrays were washed and stained by using the Fluidics Station 450 according to AGCC Fluidics Control Software. Then the fluorescence on the array was scanned using the Affymetrix® GeneChip® Scanner 3000 with a high resolution 6 g patch. The probe cell intensity files (*CEL files) generated by Affymetrix GeneChip® Command Console® software were transferred into probe level summarization files (*CHP files) using a robust multi-array (RMA) detection algorithm workflow. The *CHP files were further analyzed using Transcriptome Analysis Console (TAC) software, version 3.0, to identify and visualize the differentially expressed genes.

We identified the level of expressed miRNA with statistical significance from a volcano plot filtering between the colorectal cancerous and normal miRNAs from the experiment. Expression data of all probe sets detected by microarray analysis have been deposited in ArrayExpress, E-MTAB-4573.

Results and Discussion

In microarray analysis, we identified 279 aberrantly expressed miRNA genes that either have increased (250 miRNAs), or reduced (29 miRNAs) expression levels as shown in Table 1. We found that MiR-1201, miR-181-a, miR-7, miR-188, miR-552 and miR-183 were highly expressed in colon carcinoma tissues compared with the normal tissues (Table 2a). Among the overexpressed miRNAs, miR-1201 is the highest expressed one in CRC tissues. MiR-181, miR-183, 34a, miR-92, miR-21, miR-431 and miR-487a were identified as on co mirRNA in various tumor tissues [36-39]. MiR-21 has been shown to be overexpressed in many cancer types [18,24,37,39,40]. On the other hand, five miRNAs (miR-451, miR-486, miR-550, miR-635 and miR-10b) had decreased expression significantly in CRC tissue samples compared with the normal samples (Table 2b). These down regulated miRNAs were found to be tumor suppressors in CRC tissues in previous studies [29,30,39,41,42]. MiR-486 was found to be the lowest expressed one CRC tissues compared with the normal tissues. We also found some new aberrant expression miRNAs in colorectal cancer tissues (Tables 1-2b). Finally, we could expect that miRNAs have important role as tumor suppressors or oncogenic factors in the network of carcinogenesis. The genes with similar expression patterns are grouped together and connected by a series of branches (clustering tree or dendrogram). The threshold we used to screen up-regulated or down-regulated miRNAs is fold change ≥2.0 and p valueË‚0.05. The results of hierarchical clustering show aberrantly expressed miRNAs among CRC tissues and normal CR tissues (Figure 1). Principal component analysis was also used to find out the similarities and differences between CRC samples and normal tissues (Figure 2). Total RNA was obtained from tissues of control and CRC and hybridized to Affymetrix GeneChip® miRNA 3.0 Arrays. After normalization, differential miRNA expression data was analyzed by unsupervised hierarchical clustering.

Number Systematic name Tumor Bi-weight Avg
Signal (log2)
Control Bi-weight Avg
Signal (log2)
FoldChange (linear) (Tumor vs. Control) ANOVA p-value
(Tumor vs. Control)
1 hsa-mir-1201 6.65 1.77 29.64 0.000641
2 hsa-miR-181a-star 6.03 1.56 22.21 0.000461
3 hsa-miR-7 6.17 1.77 21.16 0.020387
4 hsa-mir-188 7.05 2.75 19.63 0.001616
5 hsa-mir-552 7.67 3.49 18.11 0.014192
6 hsa-mir-183 8.17 4.02 17.67 0.021005
7 hsa-miR-941 6.36 2.31 16.64 0.000003
8 U71d 6.29 2.33 15.57 0.021340
9 ACA3-2 7.68 3.81 14.67 0.000048
10 hsa-mir-34c 4.74 1.15 12.06 0.000309
11 hsa-miR-7-1-star 5.91 2.34 11.9 0.000627
12 hsa-mir-148a 5.38 1.81 11.9 0.001089
13 hsa-mir-409 6.08 2.54 11.61 0.000224
14 hsa-mir-769 5.19 1.67 11.49 0.000261
15 hsa-mir-331 6.2 2.68 11.43 0.007081
16 hsa-mir-10a 5.75 2.26 11.27 0.017370
17 ACA9 5.55 2.09 11.03 0.000002
18 hsa-mir-181d 8.24 4.81 10.75 0.004900
19 U71d 6.43 3.02 10.58 0.015358
20 hsa-mir-30e 5.55 2.15 10.55 0.047163
21 hsa-mir-455 5.84 2.47 10.36 0.000016
22 hsa-mir-495 5.29 2.01 9.74 0.000285
23 hsa-mir-941-3 5.37 2.11 9.52 0.007112
24 hsa-mir-146b 5.13 1.89 9.44 0.003417
25 hsa-mir-181c 5.51 2.3 9.3 0.003289
26 hsa-mir-299 5.04 1.87 9.03 0.036420
27 ACA9 6.14 2.96 9.02 0.000125
28 hsa-mir-18a 7.04 3.87 9 0.004278
29 hsa-mir-493 5.64 2.52 8.73 0.001531
30 hsa-miR-92a-1-star 5.82 2.73 8.49 0.005380
31 hsa-mir-301a 5.25 2.19 8.34 0.000267
32 ACA6 6.26 3.2 8.32 0.001425
33 HBII-99 8.66 5.61 8.28 0.020411
34 hsa-mir-431 5.44 2.43 8.05 0.000265
35 U70 7.25 4.25 7.99 0.013214
36 hsa-mir-487a 5.34 2.35 7.91 0.000055
37 hsa-mir-505 6.69 3.72 7.85 0.003072
38 ACA34 7.03 4.1 7.65 0.004997
39 hsa-mir-34a 6.1 3.18 7.54 0.000132
40 U65 6.29 3.38 7.5 0.013446
41 hsa-mir-224 7.95 5.06 7.44 0.006594
42 hsa-mir-154 6.18 3.29 7.41 0.014806
43 hsa-mir-181c 7.5 4.63 7.29 0.001522
44 hsa-mir-629 5.61 2.75 7.28 0.033213
45 hsa-mir-542 5.09 2.26 7.1 0.005752
46 hsa-mir-183 6.08 3.29 6.95 0.000749
47 hsa-mir-454 5.22 2.42 6.93 0.000161
48 U71c 4.83 2.07 6.79 0.001399
49 ACA55 5.51 2.74 6.79 0.005687
50 ENSG00000206903 10.38 7.62 6.76 0.005521
51 hsa-miR-181a-2-star 7.28 4.53 6.73 0.019146
52 hsa-mir-654 5.61 2.86 6.72 0.003405
53 hsa-mir-337 6.98 4.25 6.66 0.007153
54 hsa-miR-29b 8.03 5.29 6.66 0.012884
55 hsa-mir-622 4.84 2.11 6.65 0.046174
56 hsa-mir-135b 4.53 1.8 6.64 0.027261
57 U71a 6.63 3.91 6.56 0.011939
58 ACA24 5.95 3.3 6.29 0.000034
59 hsa-mir-429 7.3 4.65 6.26 0.001175
60 hsa-mir-411 5.79 3.15 6.21 0.000330
61 hsa-mir-192 9.41 6.83 5.97 0.013712
62 ACA52 8.2 5.64 5.87 0.010732
63 ACA5 5.05 2.51 5.84 0.000047
64 ENSG00000201199 5.57 3.04 5.8 0.001431
65 U53 7.44 4.9 5.78 0.008812
66 U67 5.21 2.74 5.55 0.000761
67 U71c 4.61 2.14 5.55 0.018617
68 hsa-mir-374b 5.65 3.2 5.46 0.049707
69 ENSG00000201592 5.64 3.21 5.4 0.000223
70 U46 8.64 6.21 5.39 0.020504
71 hsa-let-7i 5.38 2.95 5.38 0.000545
72 hsa-mir-376c 6.83 4.41 5.37 0.002284
73 hsa-mir-485 4.04 1.66 5.21 0.011868
74 ENSG00000207130 10.59 8.22 5.15 0.008658
75 hsa-mir-936 3.92 1.56 5.12 0.000137
76 hsa-mir-377 4.04 1.68 5.12 0.012927
77 hsa-mir-489 5.71 3.35 5.11 0.021337
78 hsa-mir-502 4.25 1.92 5.01 0.003544
79 hsa-mir-941-4 5.76 3.45 4.94 0.034572
80 hsa-mir-34c 4.73 2.44 4.9 0.000645
81 hsa-miR-550-star 6.61 4.34 4.82 0.032494
82 hsa-let-7g 3.66 1.39 4.8 0.000264
83 hsa-mir-361 5.31 3.05 4.77 0.002347
84 hsa-mir-362 3.85 1.6 4.75 0.000054
85 SNORA11B 3.94 1.71 4.69 0.009034
86 ACA66 3.49 1.29 4.58 0.002080
87 hsa-mir-217 3.54 1.35 4.56 0.046813
88 U71b 4.59 2.4 4.55 0.007406
89 hsa-mir-127 4.88 2.7 4.53 0.022632
90 HBII-316 7.19 5.03 4.48 0.023347
91 hsa-mir-370 6.01 3.85 4.47 0.011705
92 U107 5.22 3.07 4.46 0.019918
93 hsa-mir-433 5.7 3.56 4.43 0.004833
94 U103 4.83 2.69 4.4 0.014816
95 ACA10 7.17 5.03 4.39 0.002936
96 hsa-mir-543 4.86 2.73 4.39 0.006302
97 hsa-mir-140 6.87 4.74 4.37 0.024446
98 U46 6.65 4.54 4.34 0.002078
99 hsa-mir-501 7.43 5.31 4.34 0.009283
100 hsa-mir-326 4.34 2.23 4.32 0.000050
101 HBI-100 4.78 2.68 4.28 0.000311
102 hsa-mir-1254 4.86 2.76 4.28 0.001672
103 ACA62 5.54 3.45 4.26 0.001151
104 hsa-mir-196b 6.9 4.86 4.13 0.020518
105 ACA33 6.89 4.84 4.12 0.001894
106 hsa-mir-941-2 5.68 3.64 4.12 0.007328
107 hsa-mir-17 8.91 6.87 4.09 0.000788
108 hsa-mir-147b 3.4 1.4 4.02 0.049155
109 U67 4.25 2.25 3.99 0.017309
110 ACA3-2 9.62 7.63 3.96 0.000053
111 U31 9.14 7.16 3.96 0.002425
112 ACA3 7.61 5.62 3.95 0.005823
113 ACA24 10.34 8.36 3.95 0.011863
114 ACA5 5.73 3.75 3.93 0.000789
115 hsa-mir-299 4.47 2.52 3.87 0.001478
116 HBII-99B 5.39 3.44 3.87 0.008777
117 hsa-mir-96 3.45 1.5 3.87 0.012393
118 hsa-mir-1291 3.91 1.97 3.85 0.002163
119 hsa-mir-425 8.46 6.52 3.82 0.008893
120 ACA26 4.8 2.87 3.8 0.002390
121 hsa-mir-3200 5.02 3.1 3.79 0.011422
122 hsa-miR-3130-5p 3.48 1.58 3.73 0.004953
123 hsa-mir-200a 10.98 9.09 3.7 0.004609
124 ACA31 4.53 2.64 3.7 0.009703
125 ACA17 3.57 1.68 3.69 0.000557
126 ACA16 7.48 5.62 3.64 0.001931
127 hsa-mir-199b 5.25 3.39 3.62 0.004455
128 hsa-mir-221 5.35 3.49 3.62 0.033553
129 hsa-mir-3138 3.82 1.97 3.61 0.035768
130 U58C 6.04 4.2 3.57 0.003545
131 ACA43 5.15 3.32 3.56 0.000473
132 U68 8.18 6.35 3.56 0.007408
133 hsa-mir-21 8.47 6.63 3.56 0.036590
134 U19 6.04 4.21 3.54 0.015532
135 hsa-mir-1201 4.95 3.13 3.53 0.004735
136 hsa-let-7d 3.5 1.71 3.45 0.049116
137 ENSG00000206913 9.34 7.58 3.4 0.000693
138 ACA23 3.48 1.73 3.36 0.000177
139 hsa-miR-103-2-star 3.69 1.94 3.35 0.000714
140 ACA46 3.92 2.19 3.3 0.004512
141 U15B 7.04 5.32 3.3 0.005781
142 ENSG00000206603 3.64 1.93 3.27 0.031852
143 ACA66 3.39 1.69 3.26 0.000431
144 ACA16 4.97 3.27 3.25 0.003536
145 hsa-miR-1285 5.76 4.06 3.25 0.008728
146 hsa-mir-660 8.76 7.07 3.22 0.000667
147 U18A 4.04 2.36 3.22 0.011729
148 hsa-mir-1292 4.7 3.02 3.22 0.020186
149 hsa-miR-24-1-star 3.14 1.46 3.2 0.002881
150 snR38B 5.43 3.77 3.15 0.005555
151 hsa-mir-1183 4.44 2.78 3.15 0.013904
152 HBII-180C 8.22 6.56 3.14 0.010323
153 HBI-6 6.33 4.7 3.1 0.000781
154 hsa-miR-103-as 2.93 1.29 3.1 0.003721
155 hsa-mir-424 3.39 1.76 3.1 0.013516
156 ACA41 9.86 8.24 3.09 0.043374
157 hsa-mir-4317 4.24 2.66 3 0.007898
158 U14B 5.12 3.55 2.98 0.000241
159 hsa-mir-18b 8.01 6.44 2.97 0.048861
160 hsa-mir-1259 4 2.43 2.96 0.005410
161 E2 5.41 3.84 2.95 0.011803
162 U23 3.44 1.91 2.9 0.042505
163 U71b 3.72 2.19 2.89 0.000953
164 14qI-4 3.61 2.09 2.88 0.003175
165 hsa-mir-2276 3.69 2.17 2.87 0.000172
166 U99 6.76 5.24 2.87 0.019247
167 hsa-mir-4257 2.88 1.37 2.86 0.008870
168 ACA34 7.2 5.7 2.83 0.038452
169 v49_ENSG00000206633 3.43 1.93 2.83 0.039065
170 hsa-miR-181b 11.76 10.27 2.8 0.019370
171 ACA15 4.6 3.11 2.8 0.030689
172 ENSG00000238956 7.95 6.47 2.79 0.006921
173 U68 10.87 9.39 2.79 0.009064
174 ENSG00000222489 5.95 4.48 2.77 0.005702
175 hsa-mir-500 9.15 7.69 2.75 0.013823
176 ENSG00000252213 4.59 3.13 2.75 0.013963
177 U48 9.58 8.12 2.75 0.026235
178 U64 4.88 3.43 2.74 0.000422
179 U96b 4.67 3.22 2.74 0.005474
180 ENSG00000200879 8.8 7.35 2.73 0.004711
181 U54 9.23 7.78 2.73 0.006385
182 U27 8.39 6.95 2.71 0.009984
183 U44 11.36 9.92 2.7 0.005082
184 U23 8.9 7.47 2.7 0.039786
185 hsa-mir-532 9.26 7.83 2.69 0.001247
186 ACA67B 3.23 1.8 2.69 0.015256
187 ACA7B 9.29 7.88 2.66 0.011805
188 U60 5.58 4.18 2.65 0.000133
189 U18C 3.27 1.86 2.65 0.001589
190 hsa-mir-148a 9.72 8.31 2.65 0.002850
191 U42B 3.7 2.3 2.64 0.000125
192 ENSG00000207187 7.21 5.81 2.64 0.002058
193 ACA32 5.95 4.55 2.64 0.007992
194 U103B 5.17 3.79 2.61 0.001744
195 U17a 5.01 3.63 2.6 0.001582
196 U106 4.59 3.22 2.6 0.012716
197 snR39B 8.08 6.7 2.6 0.015181
198 hsa-mir-93 3.41 2.04 2.58 0.001656
199 SNORA11B 3.63 2.27 2.56 0.006011
200 14qII-26 4.28 2.93 2.56 0.023833
201 U35A 9.92 8.56 2.56 0.033458
202 ACA2b 3.83 2.48 2.54 0.005727
203 mgU6-53 3.85 2.51 2.53 0.000996
204 snR38A 4.86 3.52 2.53 0.001270
205 ACA18 10.27 8.94 2.52 0.017484
206 SNORA84 4.26 2.93 2.52 0.021507
207 hsa-mir-22 5.96 4.62 2.52 0.034913
208 HBII-180A 9.58 8.25 2.5 0.013371
209 hsa-mir-185 4.1 2.78 2.5 0.023328
210 U46 7.63 6.32 2.49 0.011107
211 hsa-mir-141 9.85 8.55 2.47 0.033946
212 ACA41 4.48 3.18 2.47 0.043068
213 hsa-mir-132 2.56 1.26 2.46 0.013196
214 hsa-mir-493 2.47 1.17 2.46 0.030161
215 hsa-mir-654 3.16 1.87 2.45 0.002769
216 U92 4.26 2.97 2.45 0.003824
217 ACA47 3.02 1.73 2.45 0.013111
218 ACA32 5.71 4.42 2.44 0.016438
219 mgh28S-2411 11.22 9.95 2.42 0.002499
220 hsa-mir-744 2.99 1.72 2.41 0.017194
221 HBI-61 4.28 3.01 2.41 0.025907
222 U13 6.73 5.48 2.38 0.035739
223 ACA50 4.89 3.65 2.37 0.000397
224 hsa-miR-376a 3.39 2.15 2.37 0.029751
225 hsa-mir-612 2.9 1.66 2.36 0.000370
226 hsa-mir-671 3.19 1.95 2.36 0.004397
227 U72 2.43 1.21 2.34 0.007780
228 U18A 4.46 3.27 2.29 0.016004
229 ACA48 8.5 7.31 2.27 0.040439
230 U42B 5.91 4.74 2.24 0.006167
231 U30 11.43 10.27 2.22 0.009547
232 U75 11.24 10.1 2.2 0.003475
233 hsa-mir-421 8.25 7.11 2.2 0.034311
234 U56 10.08 8.95 2.18 0.011403
235 hsa-mir-492 2.79 1.68 2.16 0.019203
236 hsa-mir-182 2.6 1.5 2.15 0.034690
237 HBII-95 2.71 1.62 2.12 0.005868
238 U109 4.11 3.03 2.12 0.009534
239 ACA11 5.71 4.62 2.12 0.023544
240 U36A 6.28 5.2 2.11 0.001139
241 hsa-mir-106b 12.64 11.58 2.1 0.002558
242 hsa-mir-711 2.97 1.9 2.09 0.009272
243 U106 5.36 4.3 2.09 0.041728
244 U47 3.68 2.62 2.08 0.028603
245 ACA53 3.31 2.26 2.07 0.002782
246 hsa-mir-1291 3.42 2.37 2.07 0.008497
247 U58C 8.26 7.23 2.05 0.025618
248 hsa-mir-222 2.56 1.53 2.05 0.030812
249 hsa-mir-212 7.03 6 2.05 0.041135
250 hsa-mir-222 13.12 12.09 2.04 0.014307
251 ENSG00000238807 1.23 2.23 -2.01 0.005883
252 ENSG00000238804 1.08 2.1 -2.02 0.018261
253 ENSG00000238430 1.35 2.38 -2.04 0.013001
254 14qI-1 1.46 2.5 -2.06 0.010180
255 v49_ENSG00000201733 1.36 2.51 -2.22 0.022257
256 ENSG00000239140 1.22 2.38 -2.24 0.023096
257 ENSG00000201619 4.34 5.52 -2.26 0.021703
258 hsa-mir-744 8.21 9.39 -2.27 0.015659
259 hsa-mir-497 9.66 10.86 -2.3 0.021457
260 hsa-mir-4314 1.74 2.95 -2.31 0.012926
261 hsa-mir-3141 8.28 9.5 -2.33 0.029632
262 hsa-mir-631 1.24 2.49 -2.38 0.006627
263 ENSG00000252921 2.81 4.06 -2.38 0.010667
264 ENSG00000252921 1.69 2.98 -2.45 0.033509
265 ENSG00000221345 1.41 2.71 -2.46 0.036777
266 hsa-mir-548x 1 2.3 -2.47 0.002773
267 hsa-mir-1281 7.03 8.42 -2.6 0.025311
268 ENSG00000239080 1.72 3.1 -2.6 0.047346
269 hsa-mir-606 1.29 2.73 -2.72 0.041951
270 ENSG00000238549 1.7 3.15 -2.74 0.003969
271 hsa-miR-548a-3p 2.29 3.8 -2.84 0.037466
272 ENSG00000238430 1.26 2.78 -2.85 0.024357
273 hsa-mir-550-2 2.09 4.04 -3.87 0.000059
274 hsa-mir-10b 9.04 11.05 -4.04 0.002456
275 hsa-mir-635 1.28 3.48 -4.58 0.019899
276 hsa-mir-550-1 4.85 7.12 -4.82 0.001534
277 HBII-85-6 6.54 9.08 -5.83 0.045268
278 hsa-mir-486 8.5 11.05 -5.89 0.024529
279 hsa-mir-451 8.32 11.04 -6.62 0.036823

Table 1: Microarray Analysis: Differentially expressed miRNAs in CRC samples compared with samples of controls in the training and validation sets. Statistical analysis was performed using TAC software one way analysis of variance (ANOVA) was used. The statistical significance level was set at p-value<0.05. Greater than 2-fold changes were analyzed for up/down regulated miRNAs. A total of 279 miRNAs were found to be differentially expressed in the above table.

Number Systematic name Tumor Bi-weight Avg Signal (log2) Control Bi-weight Avg Signal (log2) Fold Change (linear)
1 hsa-mir-1201 6.65 1.77 29.64
2 hsa-miR-181a-star 6.03 1.56 22.21
3 hsa-miR-7 6.17 1.77 21.16
4 hsa-mir-188 7.05 2.75 19.63
5 hsa-mir-552 7.67 3.49 18.11
6 hsa-mir-183 8.17 4.02 17.67
7 hsa-miR-941 6.36 2.31 16.64
8 U71d 6.29 2.33 15.57
9 ACA3-2 7.68 3.81 14.67
10 hsa-mir-34c 4.74 1.15 12.06

Table 2a: The most important significant increase and decrease rates of expression in miRNA transcripts, some upregulated miRNA transcripts.

Number Systematic name Tumor Bi-weight Avg
Signal (log2)
Control Bi-weight Avg Signal (log2) Fold Change (linear)
1 hsa-mir-606 1.29 2.73 -2.72
2 ENSG00000238549 1.7 3.15 -2.74
3 hsa-miR-548a-3p 2.29 3.8 -2.84
4 ENSG00000238430 1.26 2.78 -2.85
5 hsa-mir-550-2 2.09 4.04 -3.87
6 hsa-mir-10b 9.04 11.05 -4.04
7 hsa-mir-635 1.28 3.48 -4.58
8 hsa-mir-550-1 4.85 7.12 -4.82
9 HBII-85-6 6.54 9.08 -5.83
10 hsa-mir-486 8.5 11.05 -5.89

Table 2b: The most important significant increase and decrease rates of expression in miRNA transcripts, some down-regulated miRNA transcripts.

gastrointestinal-cancer-stromal-tumors-hierarchical-clustering

Figure 1: Hierarchical Clustering of Gene Expression.

gastrointestinal-cancer-stromal-tumors-component-analyses

Figure 2: Principle Component Analyses (PCA). Each red dot represents a tumor sample and each blue dot represents control sample. According to the graph tumor and control samples were clustered at different localities.

Each row represents individual miRNA. In hierarchical clustering, genes with similar expression patterns are grouped together and connected by a series of branches (clustering tree or dendrogram). The red colors on the dendrogram indicate expression levels higher than the median. While green colors show expression levels lower than the median.

Conclusion

Our results show that most of miRNAs differentially expressed are up regulated miRNAs in CRC tissues compared to control tissues. Evidences have been accumulating that some miRNAs are overexpressed in CRC cells and might function as inhibitors of different tumor suppressor genes. There are three strategies for miRNA-based therapies are to inhibit oncogenic miRNAs or restoring tumor suppressor miRNAs. The first strategy is to direct inhibition of oncogenic microRNAs and this can be achieved by using singlestranded antisense oligonucleotides (approximately 20-22 nucleotides in long) that act through complementar base-pairing with target miRNAs. The second strategy is tumor suppressor miRNA replacement. This involves reintroducing synthetic miRNA or expression vectors that will produce the miRNA of interest to restore a loss of function. The third strategy is to develop drugs that decrease the levels of oncogenic miRNAs or increase the levels of tumor-suppressor miRNA for cancer prevention [21,43].

The most important challenge is the identification of definitive miRNA signatures for CRC by large and comprehensive profiling studies. This will allow the identification of certain diagnostic and prognostic biomarkers that can help physicians with patient evaluation and also prospective markers for the early therapy [8,12,15,44]. In summary, miRNAs are extremely important regulators of oncogenes and tumor suppressor genes that are responsible for pathologic processes associated with malignant progression. Although the roles of many different miRNA have been identified in various tumors, more study is still needed to fully understand the role of each miRNA and assessing their roles in personalized miRNA targeted cancer therapy [24]. In future cancer therapy, miRNAs may be important in deciding which drugs are selected for a patient and in determination of whether the patient has responded to the drug [23]. In conclusion, further efforts to get more sensitive, fast and effective methods are needed to address the role of miRNAs biomarkers in clinical diagnostic, prognostic and therapy. Finally, miRNAs will emerge as a powerful resource to advance the diagnosis and management of cancer including colorectal cancer.

Acknowledgment

We thank C. Gover for data management.

References

Select your language of interest to view the total content in your interested language
Post your comment

Share This Article

Relevant Topics

Recommended Conferences

  • 2nd World Congress on Embryology and In Vitro Fertilization March 30-31, 2018 Orlando, USA
    March 30-31, 2018 Orlando, USA
  • Annual Physicians Meeting 2018 May 11-12, 2018 Osaka, Japan
    May 11-12, 2018 Osaka, Japan
  • 7th International Conference on Clinical and Medical Case Reports June 01-02, 2018 Osaka, Japan
    October 22-23, 2018 Istanbul, Turkey
  • 7th International Conference on Clinical and Medical Case Reports June 01-02, 2018 Osaka, Japan
    June 01-02, 2018 Osaka, Japan
  • International conference on Fitness and Expo June 04-05, 2018 Baltimore, Maryland, USA
    June 4-5, 2018 Baltimore, USA
  • 4th World Congress and Exhibition on Antibiotics and Antibiotic Resistance June 14-15, 2018 Barcelona, Spain
    April 20-21, 2018 Las Vegas, USA
  • Telemedicine & Medical Informatics July 30- 31, 2018 Melbourne, Australia
    July 30- 31, 2018 Melbourne, Australia
  • Gastroenterology Conference August 20-21, 2018 Rome, Italy
    October 29-30,2018 San Francisco, USA
  • Surgery August 27-28, 2018 Tokyo, Japan
    June 21-23, 2018 Dublin, Ireland Dublin, Ireland
  • Trauma and Reconstructive Surgery Sep 10-11, 2018 Singapore
    Sep 10-11, 2018 Singapore City, Singapore
  • Clinical & Medical Case Reports September 17-18, 2018 | Amsterdam, Netherlands
    September 17-18, 2018 Amsterdam, Netherlands
  • International Conference and Expo on Natural Medicine & Products September 24-25, 2018 Montreal | Quebec | Canada
    September 24-25, 2018 Montreal, USA
  • 6th American Gynecological Surgery Conference September 28-29, 2018 San Antonio | Texas | USA
    September 28-29, 2018 San Antonio, USA
  • Fetal and Maternal Medicine October 15-17, 2018 Osaka, Japan
    October 15-17, 2018 Osaka, Japan
  • 3rd International Conference on Integrative Medicine and Alternative treatments October 22-23, 2018 Boston, USA
    October 22-23, 2018 Boston, USA
  • 3rd International Conference on Internal Medicine and Hospital Medicine October 23-24, 2018 Toronto, Ontario, Canada
    May 21-22, 2018 Osaka, Japan
  • 18th International Conference on Gastroenterology and Endoscopy October 29-30,2018 San Francisco, California, USA
    August 29-30, 2018 Toronto, Canada
  • Cell Therapy and Regenerative Medicine November 9-10, 2018 Atlanta, Georgia, USA
    November 9-10, 2018 Atlanta, USA

Article Usage

  • Total views: 8510
  • [From(publication date):
    December-2016 - Dec 14, 2017]
  • Breakdown by view type
  • HTML page views : 8382
  • PDF downloads : 128

Review summary

  1. Mathew
    Posted on Aug 30 2016 at 6:30 pm
    The author identifies the differential expressed miRNAs in colon cancer using micro array system. The results of this study will increase our understanding of development, progression and earlier detection and personnel treatment of colon cancer. This adds significant data to the scientific field.
 

Post your comment

captcha   Reload  Can't read the image? click here to refresh

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version