Evidence map›Paper›PMID 19740432›Full record

ArticleJournal of experimental & clinical cancer research : CR2009

Mining novel biomarkers for prognosis of gastric cancer with serum proteomics.

Fu-Ming Qiu, Jie-Kai Yu, Yi-Ding Chen, Qi-Feng Jin, Mei-Hua Sui, Jian Huang

Open access · goldAbstract read
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

12 citing papers in PubMed, 25 citations in OpenAlex.

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  7. Serum profiling by mass spectrometry combined with bioinformatics for the biomarkers discovery in diffuse large B-cell lymphoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015
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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

6 authors at 3 institutions in 2 countries.

Fu-Ming QiuDepartment of Oncology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, PR China. qiufuming@yahoo.com.cn
Jie-Kai Yu
Yi-Ding Chen
Qi-Feng Jin
Mei-Hua Sui
Jian Huang
Second Affiliated Hospital of Zhejiang University · CNZhejiang University · CNMedical University of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough gastric cancer (GC) remains the second cause of cancer-related death, useful biomarkers for prognosis are still unavailable. We present here the attempt of mining novel biomarkers for GC prognosis by using serum proteomics.

methodsSera from 43 GC patients and 41 controls with gastritis as Group 1 and 11 GC patients as Group 2 was successively detected by Surface Enhanced Laser Desorption/ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) with Q10 chip. Peaks were acquired by Ciphergen ProteinChip Software 3.2.0 and analyzed by Zhejiang University-ProteinChip Data Analysis System (ZJU-PDAS). CEA level were evaluated by chemiluminescence immunoassay.

resultsAfter median follow-up periods of 33 months, Group 1 with 4 GC patients lost was divided into 20 good-prognosis GC patients (overall survival more than 24 months) and 19 poor-prognosis GC patients (no more than 24 months). The established prognosis pattern consisted of 5 novel prognosis biomarkers with 84.2% sensitivity and 85.0% specificity, which were significantly higher than those of carcinoembryonic antigen (CEA) and TNM stage. We also tested prognosis pattern blindly in Group 2 with 66.7% sensitivity and 80.0% specificity. Moreover, we found that 4474-Da peak elevated significantly in GC and was associated with advanced stage (III+IV) and short survival (p < 0.03).

conclusionWe have identified a number of novel biomarkers for prognosis prediction of GC by using SELDI-TOF-MS combined with sophisticated bioinformatics. Particularly, elevated expression of 4474-Da peak showed very promising to be developed into a novel biomarker associated with biologically aggressive features of GC.

Indexed as

Area Under CurveBiomarkers, TumorCarcinoembryonic AntigenHumansLuminescenceNeoplasm StagingPrognosisProtein Array AnalysisProteomicsReproducibility of ResultsROC CurveSensitivity and SpecificitySpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationStomach NeoplasmsBiomarkers, TumorCarcinoembryonic Antigen

Identifiers

PMID19740432
PMCPMC2753349
OpenAlexW2128952020

What OpenQuestion holds

Textmetadata
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.