Evidence map›Paper›PMID 25182173›Full record

ArticleScientific reports2014

Identification and characterization of novel serum microRNA candidates from deep sequencing in cervical cancer patients.

Li Juan, Hong-li Tong, Pengjun Zhang, Guanghong Guo, Zi Wang, Xinyu Wen, Zhennan Dong, Ya-ping Tian

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Li Juan1] Department of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853 [2].
Hong-li Tong1] Department of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853 [2].
Pengjun Zhang1] Department of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853 [2].
Guanghong GuoDepartment of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853.
Zi WangDepartment of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853.
Xinyu WenDepartment of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853.
Zhennan DongDepartment of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853.
Ya-ping TianDepartment of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing, China, 100853.
Chinese PLA General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small non-coding microRNAs (miRNAs) are involved in cancer development and progression, and serum profiles of cervical cancer patients may be useful for identifying novel miRNAs. We performed deep sequencing on serum pools of cervical cancer patients and healthy controls with 3 replicates and constructed a small RNA library. We used MIREAP to predict novel miRNAs and identified 2 putative novel miRNAs between serum pools of cervical cancer patients and healthy controls after filtering out pseudo-pre-miRNAs using Triplet-SVM analysis. The 2 putative novel miRNAs were validated by real time PCR and were significantly decreased in cervical cancer patients compared with healthy controls. One novel miRNA had an area under curve (AUC) of 0.921 (95% CI: 0.883, 0.959) with a sensitivity of 85.7% and a specificity of 88.2% when discriminating between cervical cancer patients and healthy controls. Our results suggest that characterizing serum profiles of cervical cancers by Solexa sequencing may be a good method for identifying novel miRNAs and that the validated novel miRNAs described here may be cervical cancer-associated biomarkers.

Indexed as

Base SequenceBiomarkers, TumorCase-Control StudiesFemaleHigh-Throughput Nucleotide SequencingHumansMicroRNAsMiddle AgedMolecular Sequence DataUterine Cervical NeoplasmsBiomarkers, TumorMicroRNAs

Identifiers

PMID25182173
PMCPMC4152751
OpenAlexW2017931686

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.