Evidence map›Paper›PMID 38586559›Full record

ArticleAnnals of surgical treatment and research2024

Comparative profiling by data-independent acquisition mass spectrometry reveals featured plasma proteins in breast cancer: a pilot study.

Kyung-Hwak Yoon, Hyosub Chu, Hyeonji Kim, Sunghyun Huh, Eun-Kyu Kim, Un-Beom Kang, Hee-Chul Shin

Abstract read
In one paragraph

Article in Annals of surgical treatment and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Kyung-Hwak YoonDepartment of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.ORCID https://orcid.org/0000-0002-6206-7767
Hyosub ChuBertis R&D Division, Bertis Inc., Seongnam, Korea.ORCID https://orcid.org/0000-0002-8536-7500
Hyeonji KimBertis R&D Division, Bertis Inc., Seongnam, Korea.ORCID https://orcid.org/0009-0004-4311-243X
Sunghyun HuhBertis R&D Division, Bertis Inc., Seongnam, Korea.ORCID https://orcid.org/0000-0002-1885-419X
Eun-Kyu KimDepartment of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.ORCID https://orcid.org/0000-0003-1318-0939
Un-Beom KangBertis R&D Division, Bertis Inc., Seongnam, Korea.ORCID https://orcid.org/0000-0002-9246-4237
Hee-Chul ShinDepartment of Surgery, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.ORCID https://orcid.org/0000-0001-6512-2218

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Breast cancer is known to be influenced by genetic and environmental factors, and several susceptibility genes have been discovered. Still, the majority of genetic contributors remain unknown. We aimed to analyze the plasma proteome of breast cancer patients in comparison to healthy individuals to identify differences in protein expression profiles and discover novel biomarkers. Methods: This pilot study was conducted using bioresources from Seoul National University Bundang Hospital's Human Bioresource Center. Serum samples from 10 breast cancer patients and 10 healthy controls were obtained. Liquid chromatography-mass spectrometry analysis was performed to identify differentially expressed proteins. Results: We identified 891 proteins; 805 were expressed in the breast cancer group and 882 in the control group. Gene set enrichment and differential expression analysis identified 30 upregulated and 100 downregulated proteins in breast cancer. Among these, 10 proteins were selected as potential biomarkers. Three proteins were upregulated in breast cancer patients, including cluster of differentiation 44, eukaryotic translation initiation factor 2-α kinase 3, and fibronectin 1. Seven proteins downregulated in breast cancer patients were also selected: glyceraldehyde-3-phosphate dehydrogenase, α-enolase, heat shock protein member 8, integrin-linked kinase, tissue inhibitor of metalloproteinases-1, vasodilator-stimulated phosphoprotein, and 14-3-3 protein gamma. All proteins had been previously reported to be related to tumor development and progression. Conclusion: The findings suggest that plasma proteome profiling can reveal potential diagnostic biomarkers for breast cancer and may contribute to early detection and personalized treatment strategies. A further validation study with a larger sample cohort of breast cancer patients is planned.

Indexed as

BiomarkersBreast neoplasmsProteomics

Identifiers

PMID38586559
PMCPMC10995839

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.