Evidence map›Paper›PMID 29286311›Full record

ArticleProteomes2017

Comparative Proteomics Analysis of Urine Reveals Down-Regulation of Acute Phase Response Signaling and LXR/RXR Activation Pathways in Prostate Cancer.

Katarina Davalieva, Sanja Kiprijanovska, Ivana Maleva Kostovska, Sotir Stavridis, Oliver Stankov, Selim Komina, Gordana Petrusevska, Momir Polenakovic

Open access · goldAbstract read
In one paragraph

Article in Proteomes, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

33 citing papers in PubMed, 58 citations in OpenAlex.

  1. Trial
  2. High-Throughput Proteomic and Glycoproteomic Analyses in Benign Prostatic Hyperplasia.Journal of the American Society for Mass Spectrometry · 2026
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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 3 institutions in 3 countries.

Katarina DavalievaResearch Centre for Genetic Engineering and Biotechnology "Georgi D Efremov", Macedonian Academy of Sciences and Arts, Skopje, Krste Misirkov 2, 1000 Skopje, Macedonia. katarina@manu.edu.mk.
Sanja KiprijanovskaResearch Centre for Genetic Engineering and Biotechnology "Georgi D Efremov", Macedonian Academy of Sciences and Arts, Skopje, Krste Misirkov 2, 1000 Skopje, Macedonia. skiprijanovska@manu.edu.mk.
Ivana Maleva KostovskaResearch Centre for Genetic Engineering and Biotechnology "Georgi D Efremov", Macedonian Academy of Sciences and Arts, Skopje, Krste Misirkov 2, 1000 Skopje, Macedonia. maleva_i@manu.edu.mk.
Sotir StavridisUniversity Clinic for Urology, University Clinical Centre "Mother Theresa", 1000 Skopje, Macedonia. sotir.stavridis@medf.ukim.edu.mk.
Oliver StankovUniversity Clinic for Urology, University Clinical Centre "Mother Theresa", 1000 Skopje, Macedonia. oliver.stankov@medf.ukim.edu.mk.
Selim KominaInstitute of Pathology, Medical Faculty, University "St. Cyril and Methodius", 1000 Skopje, Macedonia. s_komina@yahoo.com.
Gordana PetrusevskaInstitute of Pathology, Medical Faculty, University "St. Cyril and Methodius", 1000 Skopje, Macedonia. gordanap61@yahoo.com.
Momir PolenakovicResearch Centre for Genetic Engineering and Biotechnology "Georgi D Efremov", Macedonian Academy of Sciences and Arts, Skopje, Krste Misirkov 2, 1000 Skopje, Macedonia. momir@manu.edu.mk.
Macedonian Academy of Sciences and Arts · MKSs. Cyril and Methodius University in Skopje · MKUniversity Clinic of Traumatology · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detecting prostate cancer (PCa) using non-invasive diagnostic markers still remains a challenge. The aim of this study was the identification of urine proteins that are sufficiently sensitive and specific to detect PCa in the early stages. Comparative proteomics profiling of urine from patients with PCa, benign prostate hyperplasia, bladder cancer, and renal cancer, coupled with bioinformatics analysis, were performed. Statistically significant difference in abundance showed 20 and 85 proteins in the 2-D DIGE/MS and label-free LC-MS/MS experiments, respectively. In silico analysis indicated activation, binding, and cell movement of subset of immune cells as the top affected cellular functions in PCa, together with the down-regulation of Acute Phase Response Signaling and Liver X Receptor/ Retinoid X Receptor (LXR/RXR) activation pathways. The most promising biomarkers were 35, altered in PCa when compared to more than one group. Half of these have confirmed localization in normal or PCa tissues. Twenty proteins (CD14, AHSG, ENO1, ANXA1, CLU, COL6A1, C3, FGA, FGG, HPX, PTGDS, S100A9, LMAN2, ITIH4, ACTA2, GRN, HBB, PEBP1, CTSB, SPP1) are oncogenes, tumor suppressors, and multifunctional proteins with highly confirmed involvement in PCa, while 9 (AZU1, IGHG1, RNASE2, PZP, REG1A, AMY1A, AMY2A, ACTG2, COL18A1) have been associated with different cancers, but not with PCa so far, and may represent novel findings. LC-MS/MS data are available via ProteomeXchange with identifier PXD008407.

Indexed as

2-D DIGE/MSLC-MS/MSnon-invasive biomarkerprostate cancerproteomicsurine

Identifiers

PMID29286311
PMCPMC5874760
OpenAlexW2779085518

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.