| Literature DB >> 29203780 |
Farah J Nassar1, Rabih Talhouk1, Nathalie K Zgheib2, Arafat Tfayli3, Maya El Sabban4, Nagi S El Saghir3, Fouad Boulos5, Mark N Jabbour5, Claude Chalala6, Rose-Mary Boustany7,8,9, Humam Kadara8, Zhou Zhang10,11, Yinan Zheng10,12, Brian Joyce10,13, Lifang Hou10,14,15, Ali Bazarbachi3, George Calin16, Rihab Nasr17.
Abstract
Breast cancer (BC) has a higher incidence in young Lebanese woman as compared to the West. We assessed the microRNA (miRNA) microarray profile of tissues derived from Lebanese patients with early BC and performed mRNA-miRNA integration analysis. 173 miRNAs were significantly dysregulated in 45 BC versus 17 normal adjacent breast tissues, including 74 with a fold change more than two of which 17 were never reported before in cancer. Integration analysis of mRNA-miRNA microarray data revealed a potential role of 51 dysregulated miRNA regulating 719 tumor suppressive or oncogenic mRNA associated with increased proliferation and decreased migration and invasion. We then performed a comparative miRNA microarray profile analysis of BC tissue between these 45 Lebanese and 197 matched American BC patients. Notably, Lebanese BC patients had 21 exclusively dysregulated miRNA (e.g. miR-31, 362-3p, and 663) and 4 miRNA with different expression manner compared to American patients (e.g. miR-1288-star and 324-3p). Some of these differences could reflect variation in patient age at diagnosis or ethnic variation affecting miRNA epigenetic regulation or sequence of miRNA precursors. Our data provide a basis for genetic/epigenetic investigations to explore the role of miRNA in early stage BC in young women, including ethnic specific differences.Entities:
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Year: 2017 PMID: 29203780 PMCID: PMC5715135 DOI: 10.1038/s41598-017-16978-y
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Clinical and pathological characteristics of Lebanese breast cancer tissues used in microarray and RT-qPCR.
| Patient Characteristics | Assay Type | |
|---|---|---|
| Microarray | RT-qPCR | |
| N(%) | N(%) | |
| Normal | 17 (27.4) | 10 (33.3) |
| Tumor | 45 (72.6) | 20 (66.7) |
|
| ||
| ≤40 years | 19 (42.2) | 6 (30) |
| >40 years | 26 (57.8) | 14 (70) |
|
| ||
| Premenopausal | 27 (60) | 10 (50) |
| Postmenopausal | 18 (40) | 10 (50) |
|
| ||
| Negative | 0 (0) | 0 (0) |
| Positive | 45 (100) | 20 (100) |
|
| ||
| Negative | 1 (2.2) | 0 (0) |
| Positive | 44 (97.8) | 20 (100) |
|
| ||
| Negative | 34 (75.5) | 15 (75) |
| Positive | 11 (24.5) | 5 (25) |
|
| ||
| No | 19 (45.2) | 9 (45) |
| Yes | 23 (54.8) | 11 (55) |
|
| ||
| T1: ≤2 cm | 19 (42.2) | 7 (35) |
| T2: >2 cm but ≤5 cm | 21 (46.7) | 10 (50) |
| T3: >5 cm | 4 (8.9) | 3 (15) |
| T4: any size with direct extension to chest wall and/or to skin | 1 (2.2) | 0 (0) |
|
| ||
| G1: Well differentiated | 7 (15.6) | 2 (10) |
| G2: Moderately differentiated | 20 (44.4) | 12 (60) |
| G3–G4: Poorly differentiated | 18 (40) | 6 (30) |
Figure 1Heatmap of differentially expressed miRNA in tumor versus normal adjacent breast tissues taken from Lebanese patients. (Fold Change >2 and adjusted p-value < 0.05). Each row represents a differentially expressed miRNA and each column represents one of the 62 samples. The color key shown at the top left illustrates the relative expression level of a miRNA across all samples. A total of 74 miRNA were differentially expressed with separate clustering of tumor and normal adjacent tissues.
Figure 2Volcano plot representing log2 fold change as a function of the adjusted p-value for miRNA expression in tumor versus normal adjacent breast tissues from Lebanese patients. The arrows highlight the upregulated and downregulated miRNA with the highest fold change.
Figure 3Validation of 6 significantly upregulated (a) and 4 significantly downregulated (b) miRNAs as per microarray results in tumor vs normal adjacent tissues. These dotplots show the fold change of miRNA expression in 20 tumor breast tissues normalized to the average of 10 normal adjacent breast tissues with RNU6B used as an endogenous control. The plot represents the mean with the standard error of mean as error bars. *Denotes p < 0.05 for tumor versus normal adjacent tissues using Wilcoxon’s signed-rank sum test.
Figure 4Filtration method for mRNA targets of the 74 differentially expressed miRNAs in tumor vs normal adjacent tissues from Lebanese patients using IPA. 13202 mRNA targets were predicted as potential targets of 74 dysregulated miRNA in Lebanese samples. The predicted miRNA targets decreased to 1047 mRNAs after miRNA-mRNA integration, and then to 907 mRNAs when specifying breast tissue. mRNAs were filtered to 719 when choosing an inverse correlation of mRNA and miRNA expression. 719 mRNA are involved in decreasing cell movement, invasion, and metastasis as well as increasing proliferation, growth and cell cycle progression.
Figure 5Ingenuity pathway analysis (IPA) of predicted cellular and molecular functions of all 1294 differentially expressed mRNA in tumor versus normal adjacent breast tissues. The most often predicted cellular function was cellular growth and proliferation. The p-value measures the probability of random association between mRNA and a related function.
Figure 6Significant functional networks of mRNA selected upon mRNA-miRNA integration analysis. Dysregulated mRNA in Lebanese population are mainly involved in cell movement, cell cycle progression, cell proliferation and growth as predicted by IPA.
Figure 7Canonical pathway of molecular mechanisms of cancer from IPA showing dysregulated mRNA targets along with their potential differentially expressed miRNA regulators found in Lebanese samples. Red denotes increased expression and green decreased expression. Note: CCND1 is upregulated while CCND2 is downregulated but both are represented as Cyclin D.