Evidence map›Paper›PMID 31623106›Full record

ReviewCancers2019

Proteomic Biomarkers for the Detection of Endometrial Cancer.

Kelechi Njoku, Davide Chiasserini, Anthony D Whetton, Emma J Crosbie

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed
6.4field-weighted citation impact, top 2% 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

49 citing papers in PubMed, 91 citations in OpenAlex.

  1. AKR1B1 and AKR1B10 as Potential Prognostic Biomarkers of Endometrial Cancer.International journal of molecular sciences · 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

4 authors at 2 institutions in 1 country.

Kelechi NjokuDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, 5th Floor Research, St Mary's Hospital, Oxford Road, Manchester M13 9WL, UK. kelechi.njoku@manchester.ac.uk.ORCID 0000-0001-6528-3476
Davide ChiasseriniStoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester M13 9PL, UK. davide.chiasserini@manchester.ac.uk.
Anthony D WhettonStoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Medical and Human Sciences, University of Manchester, Manchester M13 9PL, UK. tony.whetton@manchester.ac.uk.
Emma J CrosbieDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, 5th Floor Research, St Mary's Hospital, Oxford Road, Manchester M13 9WL, UK. emma.crosbie@manchester.ac.uk.ORCID 0000-0003-0284-8630
Manchester Academic Health Science Centre · GBUniversity of Manchester · GB

Funding

Department of Health NIHR-CS-012-009Medical Research Council MR/M008959/1
6 · The paper itself

Abstract

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.

Indexed as

diagnostic biomarkersendometrial cancermass spectrometryproteomics

Identifiers

PMID31623106
PMCPMC6826703
OpenAlexW2981009510

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.