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MiRNA expression profiles in gastric diffuse large B cell lymphoma

ABSTRACT: Background: Gastric diffuse large B-cell lymphoma (DLBCL) is often associated with Helicobacter pylori (H. pylori) infection. Early-stage gastric DLBCLs could be treated with H. pylori eradication therapy (HPET), and are classified into a sensitive group and a resistant group. Methods: Genome-wide miRNA and mRNA profiles were performed on gastric DLBCLs that had been treated with HPET. MicroRNAs and mRNAs preferentially associated with resistance or sensitivity to HPET were identified. Pathway enrichment and a miR-centered bioinformatic approach were also used. The candidate markers were further evaluated with a luciferase assay and Western blotting in BJAB or U2932 lymphoma cell lines of B-cell origin. These markers were verified in an independent series, and clinical and pathological correlations were established. Results: Genome-wide miRNA and mRNA profiles showed that the resistant group had higher levels of miR-155 and lower levels of DEPTOR (an inhibitor of mTOR) than the sensitive group. BJAB cells transfected with miR-155 also had lower DEPTOR and higher mTOR levels. Therefore, miR-155-mediated inhibition of DEPTOR with secondary activation of mTOR was a potential marker for resistance HPET. In contrast, pathway enrichment analysis showed that Toll-like receptor 5 (TLR5), the receptor for bacterial flagellin, was a potential marker for sensitivity to HPET. In an independent series, stronger expression of pS6K1 (a direct target of mTOR) was associated with the resistant group, and morphologic evidence of active gastritis was associated with the sensitive group. Conclusions: These findings showed that miR-155 and TLR5 were markers for resistance and sensitivity to HPET. Furthermore, histological evaluation of active gastritis might be used as a surrogate marker to predict responsiveness to HPET in gastric DLBCL. These data also suggested the possibility that mTOR inhibitors might be used in gastric DLBCLs resistant to HPET.

ORGANISM(S): Homo sapiens

PROVIDER: GSE182361 | GEO | 2022/02/09

REPOSITORIES: GEO

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Project description:Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high prevalence and resistance make it difficult to tackle. A graph neural network-based deep learning model, employing different training sets of 13,638 molecules for pre-training and fine-tuning through rigorous iterative learning processes, was aided in predicting and exploring novel molecules against H. pylori. A positively predicted novel berberine (BBR) derivative 8 with 3,13-disubstituted alkene exhibited a potency against all tested drug-susceptible and resistant H. pylori strains with minimum inhibitory concentrations (MICs) of 0.25–0.5 μg/mL. Strikingly, pharmacokinetic studies demonstrated an ideal gastric retention of 8, with the stomach concentration significantly higher than its MIC value at 24 h post dose. Oral administration of 8 and proton pump inhibitor omeprazole (OPZ) showed a 2.2-log reduction in the gastric bacterial burden compared with the control group, which is comparable to the triple-therapy, namely OPZ + amoxicillin (AMX) + clarithromycin (CLA), and partially restored the diversity of the intestinal flora as well as the abundance of probiotics. A combination of OPZ + AMX + CLA + 8 could further decrease the bacteria load (2.8-log reduction). More importantly, the mono-therapy of 8 showed comparable eradicative efficacies compared with both triple-therapy (OPZ + AMX + CLA) and the quadruple-therapy (OPZ + AMX + CLA + bismuth citrate) groups. SecA and BamD, playing a major role in outer membrane protein (OMP) transport and assembling, were identified and verified as the direct targets of 8 by employing the chemoproteomics technique. The treatment of 8 induced the death of H. pylori caused by OMP deficiency, and the subsequent reduced adhesion to gastric epithelial cells. In summary, by targeting the relatively conserved OMPs transport and assembling system, 8 has the potential to be developed as a novel anti-H. pylori candidate, especially for the eradication of drug-resistant strains. The deep learning model established in this study might provide a reliable prediction tool for future anti-H. pylori candidate discovery.

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MiRNA expression profiles in gastric diffuse large B cell lymphoma

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