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Molecular Screening for Nigericin Treatment in Pancreatic Cancer by High-Throughput RNA Sequencing.

ABSTRACT: Objectives: Nigericin, an antibiotic derived from Streptomyces hygroscopicus, has been proved to exhibit promising anti-cancer effects on a variety of cancers. Our previous study investigated the potential anti-cancer properties in pancreatic cancer (PC), and demonstrated that nigericin could inhibit the cell viabilities in concentration- and time-dependent manners via differentially expressed circular RNAs (circRNAs). However, the knowledge of nigericin associated with long non-coding RNA (lncRNA) and mRNA in pancreatic cancer (PC) has not been studied. This study is to elucidate the underlying mechanism from the perspective of lncRNA and mRNA. Methods: The continuously varying molecules (lncRNAs and mRNAs) were comprehensively screened by high-throughput RNA sequencing. Results: Our data showed that 76 lncRNAs and 172 mRNAs were common differentially expressed in the nigericin anti-cancer process. Subsequently, the bioinformatics analyses, including Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, coding and non-coding co-expression network, cis- and trans-regulation predictions and protein-protein interaction (PPI) network, were applied to annotate the potential regulatory mechanisms among these coding and non-coding RNAs during the nigericin anti-cancer process. Conclusions: These findings provided new insight into the molecular mechanism of nigericin toward cancer cells, and suggested a possible clinical application in PC.

SUBMITTER: Xu Z

PROVIDER: S-EPMC7411259 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Only a subset of radically-resected pancreatic ductal adenocarcinoma (PDAC) patients benefit from chemotherapy, and identification of novel prognostic factors is warranted. Recently miRNAs emerged as diagnostic biomarkers and innovative therapeutic targets, while high-throughput arrays are opening new opportunities to evaluate whether they can also predict clinical outcome. The present study evaluated whether comprehensive miRNA expression profiling correlated with overall survival (OS) in resected PDAC patients. Methodology/Principal Findings: High-resolution miRNA profiles were obtained with the Toray’s 3D-GeneTM miRNA chip, detecting more than 1200 types of human miRNA. RNA was isolated from paraffin-embedded primary tumors of 26 radically resected stage-pT3N1 homogeneously treated patients (adjuvant gemcitabine 1000mg/m2/day, days-1/8/15, every 28days), carefully selected according to their outcome (OS<12 vs. OS>30 months, i.e. short/long-OS). Highly stringent statistics included t-test, distance matrix with Spearman-ranked correlation, and iterative approaches. Unsupervised hierarchical analysis revealed that PDAC specimens clustered according to their short/long-OS classification, while the feature selection algorithm RELIEF identified the top-4 discriminating miRNAs between the two groups. These miRNAs target more than 1500 transcripts, including 169 targeted by two or more of these miRNAs. MiR-211 emerged as the best discriminating miRNA, with significantly higher expression in long- vs. short-OS patients. The expression of this miRNA was subsequently assessed by quantitative-PCR in an independent cohort of laser microdissected tumors from 60 resected stage-pT3N1 PDAC patients treated with the same gemcitabine regimen. Patients with low miR-211 expression according to median value had a significantly shorter median OS (14.8, 95%CI=13.1-16.5, vs. 25.7 months, 95%CI=16.2-35.1, log-rank P=0.004). Multivariate analysis demonstrated that low miR-211 expression was an independent factor of poor prognosis (hazard ratio 2.3, P=0.03) after adjusting for all the factors influencing outcome. 19 samples, duplicated gene spots

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Molecular Screening for Nigericin Treatment in Pancreatic Cancer by High-Throughput RNA Sequencing.

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