Evidence map›Paper›PMID 30470250›Full record

ArticleStem cell research & therapy2018

miR-181b/Notch2 overcome chemoresistance by regulating cancer stem cell-like properties in NSCLC.

Xiaoyuan Wang, Qingwei Meng, Wenbo Qiao, Ruishuang Ma, Weiwei Ju, Jing Hu, Hailing Lu, Jianqi Cui, Zhao Jin, Yanbin Zhao and 1 more

Open access · goldAbstract read
In one paragraph

Article in Stem cell research & therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

50 citing papers in PubMed, 85 citations in OpenAlex.

  1. Article
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  4. Understanding and overcoming multidrug resistance in cancer.Nature reviews. Clinical oncology · 2025
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  6. CouldBiomedicines · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Xiaoyuan WangThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Qingwei MengThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Wenbo QiaoThe Department of Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Ruishuang MaThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Weiwei JuPathology Department, Laboratory of Molecular Medicine, College of Medicine, Eastern Liaodong University, Dandong, Liaoning Province, China.
Jing HuThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Hailing LuThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Jianqi CuiThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Zhao JinThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China.
Yanbin ZhaoThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China. zhaoyanbin1978@sina.com.
Yan WangThe Department of Internal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, China. wangyan86298263@163.com.
Third Affiliated Hospital of Harbin Medical University · CNHarbin Medical University · CNEastern Liaoning University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer stem cells have the ability to self-renew and are resistant to conventional chemotherapy. MicroRNAs (miRNAs) regulate and control the expression and function of many target genes; therefore, miRNA disorders are involved in the pathogenesis of human diseases, such as cancer. However, the effects of miRNA dysregulation on tumour stemness and drug resistance have not been fully elucidated. miR-181b has been reported to be a tumour suppressor miRNA and is associated with drug-resistant non-small cell lung cancer.

methodsCancer stem cell (CSC)-like properties were tested by a cell proliferation assay and flow cytometry; miR-181b expression was measured by real-time PCR; and Notch2 and related proteins were detected by Western blotting and immunohistochemistry. A mouse xenograft model was also established.

resultsIn this study, we found that ectopic miR-181b expression suppressed cancer stem cell properties and enhanced sensitivity to cisplatin (DDP) treatment by directly targeting Notch2. miR-181b could inactivate the Notch2/Hes1 signalling pathway. In addition, tumours from nude mice treated with miR-181b were significantly smaller than tumours from mice treated with control agomir. Decreased miR-181b expression and increased Notch2 expression were observed to have a significant relationship with overall survival (OS) and CSC-like properties in non-small cell lung cancer (NSCLC) patients.

conclusionsThis study elucidates an important role of miR-181b in the regulation of CSC-like properties, suggesting a potential therapeutic target for overcoming drug resistance in NSCLC.

Indexed as

AnimalsCarcinoma, Non-Small-Cell LungCell Line, TumorCisplatinDrug Resistance, NeoplasmFemaleGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMice, NudeMicroRNAsMiddle AgedNeoplastic Stem CellsReceptor, Notch2Signal TransductionCisplatinMicroRNAsMIrn181 microRNA, humanNOTCH2 protein, humanReceptor, Notch2Cancer stem cell-like propertiesChemosensitivityMicroRNA-181bNon-small cell lung cancer (NSCLC)Notch2

Identifiers

PMID30470250
PMCPMC6260863
OpenAlexW2901418239

What OpenQuestion holds

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Registered trials

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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.