Evidence map›Paper›PMID 26945985›Full record

ArticleJournal of cancer research and clinical oncology2016

Proteomic study of benign and malignant pleural effusion.

Hongqing Li, Zhonghao Tang, Huili Zhu, Haiyan Ge, Shilei Cui, Weiping Jiang

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cancer research and clinical oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. The application of high-throughput proteomics in cytopathology.Journal of pathology and translational medicine · 2022
    Review
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  8. Performance of the UroVysionCancer medicine · 2018
    Article
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

6 authors at 2 institutions in 1 country.

Hongqing LiDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Zhonghao TangDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Huili ZhuDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China. zhuhuili001@126.com.
Haiyan GeDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Shilei CuiDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Weiping JiangDepartment of Respiratory Medicine, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China.
Huadong Hospital · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion. PURPOSE: This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model.

methodsWe chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker.

resultsA GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion.

conclusionsThis model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

Indexed as

ProteomicsAdultAgedAmino Acid SequenceBiomarkersFemaleHumansMaleMiddle AgedNeoplasm ProteinsPleural EffusionReproducibility of ResultsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationBiomarkersNeoplasm ProteinsBiomarkerLung adenocarcinomaMagnetic beadMalignant pleural effusionMatrix-assisted laser desorption/ionization time-of-flight mass spectrometryProteomic

Identifiers

PMID26945985
PMCPMC11818992
OpenAlexW2296605604

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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.