Global microRNA profiling of well-differentiated small intestinal neuroendocrine tumors

Abstract

Well-differentiated small intestinal neuroendocrine tumors are rare malignancies. They arise from enterochromaffin cells and very little is known about differential microRNA (miRNA) expression. The aim of this study was to identify the miRNA profile of well-differentiated small intestinal neuroendocrine tumors, which may have a critical role in tumor development, progression and potentially develop miRNAs as novel clinical biomarkers. Specimens from two test groups, 24 small intestinal neuroendocrine tumor specimens at different stages of malignancy, are included in this study. Total RNA from the first test group, five primary tumors, five mesentery metastases and five liver metastases was hybridized onto the Affymetrix Genechip miRNA arrays to perform a genome-wide profile. The results were validated by using quantitative real-time PCR (QRT-PCR) and northern blot analyses. We then expanded the investigation to laser capture microdissected small intestinal neuroendocrine tumor cells and immuno-laser capture microdissected normal enterochromaffin cells of the first test group. Furthermore, a second test group, three primary tumors, three mesentery metastases and three liver metastases, was included in the study. Thus, two independent test groups validated the data by QRT-PCR. Moreover, we characterized nine miRNAs, five (miR-96, -182, -183, -196a and -200a), which are upregulated during tumor progression, whereas four (miR-31, -129-5p, -133a and -215) are downregulated. Several online software programs were used to predict potential miRNA target genes to map a number of putative target genes for the aberrantly regulated miRNAs, through an advanced and novel bioinformatics analysis. Our findings provide information about pivotal miRNAs, which may lead to further insights into tumorigenesis, progression mechanisms and novel therapeutic targets recognition.

Figure 1

Representative 33 differentially expressed microRNAs (miRNAs) from frozen well-differentiated small intestinal neuroendocrine tumor specimens by using genome-wide Affymetrix miRNA arrays. (a) In all, 33 differentially expressed miRNAs were detected from mesentery metastases (M) and liver metastases (L) compared with primary tumors (P). Out of 33 miRNAs, 9 were selected for further analysis and they are marked by a red asterisk. Deregulated miRNAs expression is plotted in yellow (up) and in blue (down). (b) A cluster of 33 differentially expressed miRNAs from five P (P1–5), five M (M1–5) and five L (L1–5) is shown as an example. Out of 10 metastatic samples, 9 were clustered together (indicated by the blue triangle in the figure) with a singular exception of sample M2. MiRNAs were clustered according to Pearson's correlation distance as indicated in the figure.

Figure 2

Quantitative real-time PCR (QRT-PCR) analysis validated the expression of the nine selected microRNA (miRNAs) from the first group of specimens. Total RNA was isolated from frozen specimens of three primary tumors (P), three mesentery metastases (M) and three liver metastases (L) to run QRT-PCR analysis. (a) Upregulated miRNA expression in metastatic disease compared with primary tumors. (b) Downregulated miRNA expression in metastatic disease compared with primary tumors. Results were plotted using the 2^−ΔΔCt method with RNU48 expression (set to 1) from each individual sample for normalization. Plotted results are mean±s.d. for triplicate wells. Significance was calculated by one-way analysis of variance (ANOVA) followed by Bonferroni test. *P<0.05, **P<0.01 and ***P<0.001.

Figure 3

Northern blot analysis validated miR-31, -133a, -182 and -183 expression. Total RNA was isolated from frozen well-differentiated small intestinal neuroendocrine tumor specimens, which were primary tumor (P), mesentery metastasis (M) and liver metastasis (L). (a) Specific ³²P-labeled probes were hybridized to total RNA. (b) The fold changes were calculated as the ratio of mesentery metastasis versus primary tumor and liver metastasis versus primary tumor. RNU48 was used as an internal control to standardize the calculation of fold change.

Figure 4

Quantitative real-time PCR (QRT-PCR) analysis validated the expression of nine selected microRNAs (miRNAs) from the first test group. Total RNA was isolated from microdissected tumor cells and microdissected normal enterochromaffin cells. Analysis was run using three normal enterochromaffin cell, three primary tumor, three mesentery metastasis and three liver metastasis samples. (a) Upregulated miRNA expression in tumor cells compared with normal enterochromaffin cells. (b) Downregulated miRNA expression in tumor cells compared with normal enterochromaffin cells. Results were plotted using the 2^−ΔΔCt method with RNU48 expression (set to 1) from each individual sample for normalization. Plotted results are mean±s.d. for triplicate wells. Significance was calculated by one-way analysis of variance (ANOVA) followed by Bonferroni test. *P<0.05, **P<0.01 and ***P<0.001.

Figure 5

Quantitative real-time PCR (QRT-PCR) analysis validated the expression of nine selected microRNAs (miRNAs) from the second test group. Total RNA was isolated from microdissected tumor cells and microdissected normal enterochromaffin cells. Analysis was run using three normal enterochromaffin cell, three primary tumor, three mesentery metastasis and three liver metastasis samples. (a) Upregulated miRNA expression in tumor cells compared with normal enterochromaffin cells. (b) Downregulated miRNA expression in tumor cells compared with normal enterochromaffin cells. Results were plotted using the 2^−ΔΔCt method with RNU48 expression (set to 1) from each individual sample for normalization. Plotted results are mean±s.d. for triplicate wells. Significance was calculated by one-way analysis of variance (ANOVA) followed by Bonferroni test. *P<0.05, **P<0.01 and ***P<0.001.