Evidence map›Paper›PMID 25826415›Full record

ArticleRNA biology2015

Systematic analysis of berberine-induced signaling pathway between miRNA clusters and mRNAs and identification of mir-99a ∼ 125b cluster function by seed-targeting inhibitors in multiple myeloma cells.

Maoxiao Feng, Xiaochuang Luo, Chunming Gu, Yumin Li, Xuejiao Zhu, Jia Fei

Open access · bronzeAbstract read
In one paragraph

Article in RNA biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
5.9field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 44 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Maoxiao Fenga Department of Biochemistry and Molecular Biology; Medical College of Jinan University ; Guangzhou , China.
Xiaochuang Luo
Chunming Gu
Yumin Li
Xuejiao Zhu
Jia Fei
Jinan University · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBerberine (BBR) is a natural alkaloid derived from a traditional Chinese herbal medicine. However, the exact mechanisms underlying the different effects of berberine on MM cells have not been fully elucidated.

methodsA systematic analysis assay integrated common signaling pathways modulated by the 3 miRNA clusters and mRNAs in MM cells after BBR treatment. The role of the mir-99a ∼ 125b cluster, an important oncomir in MM, was identified by comparing the effects of t-anti-mirs with complete complementary antisense locked nucleic acids (LNAs) against mature mir-125b (anti-mir-125b).

resultsThree miRNAs clusters (miR-99a ∼ 125b, miR-17 ∼ 92 and miR-106 ∼ 25) were significantly down-regulated in BBR-treated MM cells and are involved in multiple cancer-related signaling pathways. Furthermore, the top 5 differentially regulated genes, RAC1, NFκB1, MYC, JUN and CCND1 might play key roles in the progression of MM. Systematic integration revealed that 3 common signaling pathways (TP53, Erb and MAPK) link the 3 miRNA clusters and the 5 key mRNAs. Meanwhile, both BBR and seed-targeting t-anti-mir-99a ∼ 125b cluster LNAs significantly induced apoptosis, G2-phase cell cycle arrest and colony inhibition.

conclusionsour results suggest that BBR suppresses multiple myeloma cells, partly by down-regulating the 3 miRNA clusters and many mRNAs, possibly through TP53, Erb and MAPK signaling pathways. The mir-99a ∼ 125b cluster might be a novel target for MM treatment. These findings provide new mechanistic insight into the anticancer effects of certain traditional Chinese herbal medicine compounds.

Indexed as

AlkaloidsBerberineCell Line, TumorG2 Phase Cell Cycle CheckpointsHumansMicroRNAsMultiple MyelomaOligoribonucleotides, AntisenseRNA, MessengerSignal TransductionAlkaloidsBerberineMicroRNAsMIRN125 microRNA, humanMIRN99 microRNA, humanOligoribonucleotides, AntisenseRNA, Messengerberberinebioinformaticsmir-99a∼125b clustermultiple myelomaseed sequencesignaling pathway

Identifiers

PMID25826415
PMCPMC4615191
OpenAlexW1504570937

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.