Evidence map›Paper›PMID 26251261›Full record

ArticleExperimental & molecular medicine2015

Prognostic role of genetic biomarkers in clinical progression of prostate cancer.

Maria Jesus Alvarez-Cubero, Luis Javier Martinez-Gonzalez, Maria Saiz, Pedro Carmona-Saez, Juan Carlos Alvarez, Manrique Pascual-Geler, Jose Antonio Lorente, Jose Manuel Cozar

Open access · goldAbstract read
In one paragraph

Article in Experimental & molecular medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Association of selectedPathology oncology research : POR · 2026
    Article
  3. Article
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  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Oxidative stress in prostate hyperplasia and carcinogenesis.Journal of experimental & clinical cancer research : CR · 2016
    Review
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  13. 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

8 authors at 3 institutions in 1 country.

Maria Jesus Alvarez-Cubero1] Laboratory of Genetic Identification, Faculty of Medicine, Legal Medicine and Toxicology Department, University of Granada, Granada, Spain [2] GENYO (Pfizer-University of Granada-Andalusian Government Centre for Genomics and Oncological Research), Granada, Spain.
Luis Javier Martinez-GonzalezGENYO (Pfizer-University of Granada-Andalusian Government Centre for Genomics and Oncological Research), Granada, Spain.
Maria SaizLaboratory of Genetic Identification, Faculty of Medicine, Legal Medicine and Toxicology Department, University of Granada, Granada, Spain.
Pedro Carmona-SaezGENYO (Pfizer-University of Granada-Andalusian Government Centre for Genomics and Oncological Research), Granada, Spain.
Juan Carlos AlvarezLaboratory of Genetic Identification, Faculty of Medicine, Legal Medicine and Toxicology Department, University of Granada, Granada, Spain.
Manrique Pascual-GelerService of Urology, University Hospital Virgen de las Nieves, Granada, Spain.
Jose Antonio Lorente1] Laboratory of Genetic Identification, Faculty of Medicine, Legal Medicine and Toxicology Department, University of Granada, Granada, Spain [2] GENYO (Pfizer-University of Granada-Andalusian Government Centre for Genomics and Oncological Research), Granada, Spain.
Jose Manuel CozarService of Urology, University Hospital Virgen de las Nieves, Granada, Spain.
Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research · ESUniversidad de Granada · ESHospital Universitario Virgen de las Nieves · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to analyze the use of 12 single-nucleotide polymorphisms in genes ELAC2, RNASEL and MSR1 as biomarkers for prostate cancer (PCa) detection and progression, as well as perform a genetic classification of high-risk patients. A cohort of 451 men (235 patients and 216 controls) was studied. We calculated means of regression analysis using clinical values (stage, prostate-specific antigen, Gleason score and progression) in patients and controls at the basal stage and after a follow-up of 72 months. Significantly different allele frequencies between patients and controls were observed for rs1904577 and rs918 (MSR1 gene) and for rs17552022 and rs5030739 (ELAC2). We found evidence of increased risk for PCa in rs486907 and rs2127565 in variants AA and CC, respectively. In addition, rs627928 (TT-GT), rs486907 (AG) and rs3747531 (CG-CC) were associated with low tumor aggressiveness. Some had a weak linkage, such as rs1904577 and rs2127565, rs4792311 and rs17552022, and rs1904577 and rs918. Our study provides the proof-of-principle that some of the genetic variants (such as rs486907, rs627928 and rs2127565) in genes RNASEL, MSR1 and ELAC2 can be used as predictors of aggressiveness and progression of PCa. In the future, clinical use of these biomarkers, in combination with current ones, could potentially reduce the rate of unnecessary biopsies and specific treatments.

Indexed as

Polymorphism, Single NucleotideAgedAged, 80 and overCohort StudiesDisease ProgressionEndoribonucleasesGene FrequencyGenetic MarkersGenetic Predisposition to DiseaseHumansMaleMiddle AgedNeoplasm ProteinsPrognosisProstateProstatic Neoplasms2-5A-dependent ribonucleaseELAC2 protein, humanEndoribonucleasesGenetic MarkersMSR1 protein, humanNeoplasm ProteinsScavenger Receptors, Class A

Identifiers

PMID26251261
PMCPMC4558485
OpenAlexW1893562964

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.