| Literature DB >> 28560185 |
Pauline Floch1, Caroline Capdevielle1, Cathy Staedel2, Julien Izotte1, Elodie Sifré1, Amandine M Laur1, Alban Giese1, Victoria Korolik3, Pierre Dubus1, Francis Mégraud1, Philippe Lehours1.
Abstract
Helicobacter pylori infection is considered as an excellent model of chronic inflammation-induced tumor development. Our project focuses on gastric MALT lymphoma (GML) related to H. pylori infection and mediated by the chronic inflammatory process initiated by the infection. Recently, microRNAs (miRNAs) have emerged as a new class of gene regulators, which play key roles in inflammation and carcinogenesis acting as oncogenes or tumor suppressors. Their precise characterization in the development of inflammation and their contribution in regulating host cells responses to infection by H. pylori have been little explored. Our goal was to analyze the changes in miRNAs in a GML mouse model using BALB/c mice thymectomized at day 3 post-birth (d3Tx model) and to clarify their implication in GML pathogenesis. PCR array followed by RT-qPCR identified five miRNAs (miR-21a, miR-135b, miR-142a, miR-150, miR-155) overexpressed in the stomachs of GML-developing d3Tx mice infected by H. pylori. The analysis of their putative targets allowed us to identify TP53INP1, an anti-proliferative and pro-apoptotic protein, as a common target of 4 of the 5 up-regulated miRNAs. We postulate that these miRNAs may act in synergy to promote the development of GML. miR-142a was also overexpressed in mouse sera samples and therefore could serve as a diagnostic marker. In situ hybridization on gastric samples with miR-142a revealed a global up-regulation of this miRNA by the tumor microenvironment at the lymphoma stage. Dysregulation of miR-21a, miR-135b, miR-142a, miR-150, miR-155 could play a critical role in the pathogenesis of GML and might offer potential applications as therapeutic targets and novel biomarkers for this disease.Entities:
Keywords: Helicobacter pylori; MALT lymphoma; TP53INP1; apoptosis; microRNAs
Mesh:
Substances:
Year: 2017 PMID: 28560185 PMCID: PMC5432547 DOI: 10.3389/fcimb.2017.00185
Source DB: PubMed Journal: Front Cell Infect Microbiol ISSN: 2235-2988 Impact factor: 5.293
Deregulated miRNAs in infected d3Tx mice compared to NI d3Tx mice.
| miR-135b | 4.655 | 15.614 |
| miR-142a | 1.216 | 12.410 |
| miR-150 | 2.062 | 10.776 |
| miR-19a | −1.914 | 8.495 |
| miR-153 | −1.915 | 5.541 |
| miR-17 | −1.531 | 5.483 |
| miR-340 | −1.208 | 5.095 |
| miR-155 | 7.301 | 4.801 |
| miR-135a | 1.276 | 4.695 |
| miR-19b | −2.615 | 4.654 |
| miR-140 | −1.482 | 4.595 |
| miR-190a | −1.393 | 4.407 |
| let-7c-2 | −1.367 | 3.950 |
| miR-101a | −2.974 | 3.757 |
| miR-21a | 2.415 | 3.735 |
| miR-342 | 1.06 | 3.571 |
| miR-376c | −2.209 | 3.252 |
| miR-18a | −1.213 | 3.171 |
| miR-126a | −1.620 | 3.077 |
| let-7b | 1.294 | −3.064 |
| miR-323 | −1.323 | −3.232 |
| miR-125a | −1.309 | −3.320 |
| miR-615 | 2.212 | −3.347 |
| miR-320 | 1.666 | −3.454 |
| miR-375 | −1.172 | −3.490 |
| miR-382 | −1.759 | −3.565 |
| miR-193b | −1.182 | −4.116 |
| miR-762 | −1.556 | −4.502 |
| miR-1224 | −1.665 | −5.071 |
| miR-494 | −2.229 | −5.181 |
| miR-802 | −3.937 | −5.374 |
| miR-217 | −1.824 | −17.816 |
| miR-216a | −1.093 | −41.184 |
PCR array 1 was performed with a pool of miRNAs from frozen gastric biopsies from 4 infected and 3 NI d3Tx mice. PCR array 2 was performed with a pool of miRNAs from paraffin-embedded gastric tissues from 2 infected and 2 NI d3Tx mice. miRNAs regulated in common between the two runs of PCR arrays are highlighted in gray.
Figure 1Relative expression levels of miR-21a, miR-135b, miR-142a, miR150, and miR-155 in . Expression levels quantified by RT-qPCR for infected NTx (n = 19) and d3Tx (n = 19) mice groups were normalized in comparison to expression levels for NI NTx (n = 7) and NI d3Tx (n = 7) control groups, respectively. SNORD72 was used to normalize miRNA expression levels. The results were similar to those obtained with RNU6. Data are plotted as bar graphs displaying the mean ± standard deviation for each group, **p < 0.01, ***p < 0.001.
Figure 2Western blot analysis of TP3INP1 (A) Example of Western-blot analysis of TP3INP1 in four GML-developing, Helicobacter pylori infected d3Tx mice compared to four infected d3Tx mice showing no gastric inflammation. Corresponding Sypro Ruby staining are shown on the side. Weak of no visible TP53INP1 was found in GML-developing mice compare to control. (B) Quantification of Western-blot analysis of TP3INP1 in GML-developing, Helicobacter pylori infected d3Tx mice (n = 4) compared to infected d3Tx mice (n = 4) showing no inflammation (inflammatory scores = 0) or lymphoid infiltration (lymphoid infiltration = 0). Intensity of Sypro Ruby staining (total protein staining) was used for normalization. The production of TP53INP1 decreased in GML-developing mice compared to that observed in control mice. Data are plotted as bar graphs displaying the mean ± standard deviation for each group, *p < 0.05.
Figure 3Relative expression levels of interest miRNAs in . Expression levels in sera quantified by RT-qPCR for NI infected d3Tx mice group (n = 12) were normalized in comparison to NI d3Tx (n = 7) control group expression levels. miR-16a was used to normalize miRNA expression levels. Graphic representation as box plots, with the box representing 50% of values around the median (horizontal line) and the whiskers representing the minimum and maximum of all the data, ***p < 0.001. NS = non-significant.
Figure 4Potential action network of predicted targets of miRNAs overexpressed in GML mice stomachs. The five overexpressed miRNAs (in yellow) inhibit the expression of various targets such as TP53INP1. Activation of a signaling pathway is represented by blue arrows and inhibition by red arrows. Validated targets are in yellow and non-validated targets in gray.