Ann Surg Treat Res.  2024 Apr;106(4):195-202. 10.4174/astr.2024.106.4.195.

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

• Yoon KH
• Chu H
• Kim H
• Huh S
• Kim EK
• Kang UB
• Shin HC

• KMID: 2554478
• DOI: http://doi.org/10.4174/astr.2024.106.4.195

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, vasodilatorstimulated 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.

Keyword

Biomarkers; Breast neoplasms; Breast neoplasms

Figure

• 

  Fig. 1 In-depth proteomic profiling of breast cancer plasma. (A) Numbers of plasma proteins identified by DIA MS in breast cancer patients and healthy controls. Total numbers of identified proteins as well as those of known plasma proteins as annotated in the Human Protein Atlas (HPA) database are indicated. (B) Dynamic range of the concentration of plasma proteins identified by DIA MS. Identified proteins with the highest and lowest known blood concentration (ceruloplasmin [CP] and hippocalcin-like protein 1 [HPCAL1], respectively) are indicated. (C) Principal component analysis of the breast cancer and normal plasma proteome. Variance explained by each principal component (PC) is indicated. (D) Bubble chart representing the gene set enrichment analysis results. Names of the representative gene ontology biological processes (GOBPs) and pathways highly enriched by the identified plasma proteome are indicated. (E) Expression heatmap of differentially expressed proteins in breast cancer patients and healthy controls. Numbers of up- and downregulated proteins are indicated. VEGF-A, vascular endothelial growth factor A; VEGFR2, VEGF receptor 2; IGF, insulin-like growth factor; IGFBP, IGF-binding proteins.

• 

  Fig. 2 Expression pattern of selected biomarker proteins in the breast cancer and healthy control samples. CD44, cluster of differentiation 44; EIF2AK3, eukaryotic translation initiation factor 2-α kinase 3; FN1, fibronectin 1; ENO1, α-enolase; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; HSPA8, heat shock protein member 8; ILK, integrin-linked kinase; TIMP1, tissue inhibitor of metalloproteinases-1; VASP, vasodilator-stimulated phosphoprotein; YWHAG, 14-3-3 protein gamma.

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