Evidence map›Paper›PMID 41241913›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Urinary Micropeptides: Integrative In Silico Profiling and LC-MS/MS Analysis for Prostate Cancer Biomarker Discovery.

Rita Ferreira, Rui Vitorino

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Rita FerreiraLAQV-REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal.
Rui VitorinoDepartment of Medical Sciences, Institute of Biomedicine-IBIMED, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal. rvitorino@ua.pt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Micropeptides encoded by small open reading frames (sORFs) represent a newly recognized class of biomolecules involved in important cellular functions such as metabolism, signal transduction and homeostasis. In the past, these peptides have been overlooked due to annotation and technical challenges. Recent advances in high-throughput techniques such as ribosome profiling, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics tools have enabled the systematic identification and characterization of these peptides. In prostate cancer (PCa), urinary micropeptides have been shown to be promising noninvasive biomarkers, as the prostate is located close to the urinary tract and urine can be easily collected. In this chapter, we discuss the methods used to detect micropeptides, incorporating in silico predictions, LC-MS/MS-based proteomic analyzes, and metabolic pathway enrichment approaches. We highlight the recent discoveries of micropeptides with differential expression in PCa and their potential as diagnostic and prognostic biomarkers. These findings highlight the importance of micropeptide research and pave the way for new strategies in PCa diagnosis and personalized medicine.

Indexed as

Biomarkers, TumorPeptidesProstatic NeoplasmsProteomicsTandem Mass SpectrometryChromatography, LiquidComputational BiologyComputer SimulationHumansLiquid Chromatography-Mass SpectrometryMaleMicropeptidesBiomarkers, TumorMicropeptidesPeptidesMicropeptidesNoncoding RNAProteomicssORFsSystems biologyTherapeutic targets

Identifiers

What OpenQuestion holds

Textmetadata
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.