Evidence map›Paper›PMID 25233230›Full record

ArticlePloS one2014

The C-terminal fragment of prostate-specific antigen, a 2331 Da peptide, as a new urinary pathognomonic biomarker candidate for diagnosing prostate cancer.

Kenji Nakayama, Takahiro Inoue, Sadanori Sekiya, Naoki Terada, Yu Miyazaki, Takayuki Goto, Shigeki Kajihara, Shin-Ichiro Kawabata, Shinichi Iwamoto, Kuniko Ikawa and 4 more

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Approaches to urinary detection of prostate cancer.Prostate cancer and prostatic diseases · 2019
    Review
  5. Article
  6. Review
  7. Effect ofInternational journal of clinical and experimental pathology · 2017
    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

14 authors.

Kenji NakayamaDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Takahiro InoueDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Sadanori SekiyaKoichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Nakagyou-ku, Kyoto, Japan.
Naoki TeradaDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Yu MiyazakiDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Takayuki GotoDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.
Shigeki KajiharaKoichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Nakagyou-ku, Kyoto, Japan.
Shin-Ichiro KawabataKoichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Nakagyou-ku, Kyoto, Japan.
Shinichi IwamotoKoichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Nakagyou-ku, Kyoto, Japan.
Kuniko IkawaDepartment of Clinical Laboratory, Kyoto University Hospital, Sakyo-ku, Kyoto, Japan.
Junko OosagaDepartment of Clinical Laboratory, Kyoto University Hospital, Sakyo-ku, Kyoto, Japan.
Hiroaki TsujiDepartment of Clinical Laboratory, Kyoto University Hospital, Sakyo-ku, Kyoto, Japan.
Koichi TanakaKoichi Tanaka Laboratory of Advanced Science and Technology, Shimadzu Corporation, Nakagyou-ku, Kyoto, Japan.
Osamu OgawaDepartment of Urology, Graduate School of Medicine, Kyoto University, Sakyo-ku, Kyoto, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesProstate cancer (PCa) is one of the most common cancers and leading cause of cancer-related deaths in men. Mass screening has been carried out since the 1990s using prostate-specific antigen (PSA) levels in the serum as a PCa biomarker. However, although PSA is an excellent organ-specific marker, it is not a cancer-specific marker. Therefore, the aim of this study was to discover new biomarkers for the diagnosis of PCa. MATERIALS AND

methodsWe focused on urine samples voided following prostate massage (digital rectal examination [DRE]) and conducted a peptidomic analysis of these samples using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS(n)). Urinary biomaterials were concentrated and desalted using CM-Sepharose prior to the following analyses being performed by MALDI-TOF/MS(n): 1) differential analyses of mass spectra; 2) determination of amino acid sequences; and 3) quantitative analyses using a stable isotope-labeled internal standard.

resultsMultivariate analysis of the MALDI-TOF/MS mass spectra of urinary extracts revealed a 2331 Da peptide in urine samples following DRE. This peptide was identified as a C-terminal PSA fragment composed of 19 amino acid residues. Moreover, quantitative analysis of the relationship between isotope-labeled synthetic and intact peptides using MALDI-TOF/MS revealed that this peptide may be a new pathognomonic biomarker candidate that can differentiate PCa patients from non-cancer subjects.

conclusionThe results of the present study indicate that the 2331 Da peptide fragment of PSA may become a new pathognomonic biomarker for the diagnosis of PCa. A further large-scale investigation is currently underway to assess the possibility of using this peptide in the early detection of PCa.

Indexed as

AgedAged, 80 and overAgingAmino Acid SequenceBiomarkers, TumorDigital Rectal ExaminationHumansMaleMiddle AgedPeptide FragmentsProstate-Specific AntigenProstatic NeoplasmsSequence Analysis, ProteinSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationBiomarkers, TumorPeptide FragmentsProstate-Specific Antigen

Identifiers

PMID25233230
PMCPMC4169392

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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.