Identification of novel protein biomarkers from the blood and urine for the early diagnosis of bladder cancer via proximity extension analysis
Background Bladder cancer (BC) is a very common urinary tract malignancy that has a high incidence and lethality. In this study, we identified BC biomarkers and described a new noninvasive detection method using serum and urine samples for the early detection of BC. Methods Serum and urine samples were retrospectively collected from patients with BC (n = 99) and healthy controls (HC) (n = 50), and the expression levels of 92 inflammation-related proteins were examined via the proximity extension analysis (PEA) technique. Differential protein expression was then evaluated by univariate analysis (p < 0.05). The expression of the selected potential marker was further verified in BC and adjacent tissues by immunohistochemistry (IHC) and single-cell sequencing. A model was constructed to differentiate BC from HC by LASSO regression and compared to the detection capability of FISH. Results The univariate analysis revealed significant differences in the expression levels of 40 proteins in the serum (p < 0.05) and 17 proteins in the urine (p < 0.05) between BC patients and HC. Six proteins (AREG, RET, WFDC2, FGFBP1, ESM-1, and PVRL4) were selected as potential BC biomarkers, and their expression was evaluated at the protein and transcriptome levels by IHC and single-cell sequencing, respectively. A diagnostic model (a signature) consisting of 14 protein markers (11 in serum and three in urine) was also established using LASSO regression to distinguish between BC patients and HC (area under the curve = 0.91, PPV = 0.91, sensitivity = 0.87, and specificity = 0.82). Our model showed better diagnostic efficacy than FISH, especially for early-stage, small, and low-grade BC. Conclusion Using the PEA method, we identified a panel of potential protein markers in the serum and urine of BC patients. These proteins are associated with the development of BC. A total of 14 of these proteins can be used to detect early-stage, small, low-grade BC. Thus, these markers are promising for clinical translation to improve the prognosis of BC patients. Graphical Abstract.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
Journal of translational medicine - 22(2024), 1 vom: 26. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kong, Tong [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Biomarkers |
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| Anmerkungen: |
© The Author(s) 2024 |
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| doi: |
10.1186/s12967-024-04951-z |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR055309887 |
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| 520 | |a Background Bladder cancer (BC) is a very common urinary tract malignancy that has a high incidence and lethality. In this study, we identified BC biomarkers and described a new noninvasive detection method using serum and urine samples for the early detection of BC. Methods Serum and urine samples were retrospectively collected from patients with BC (n = 99) and healthy controls (HC) (n = 50), and the expression levels of 92 inflammation-related proteins were examined via the proximity extension analysis (PEA) technique. Differential protein expression was then evaluated by univariate analysis (p < 0.05). The expression of the selected potential marker was further verified in BC and adjacent tissues by immunohistochemistry (IHC) and single-cell sequencing. A model was constructed to differentiate BC from HC by LASSO regression and compared to the detection capability of FISH. Results The univariate analysis revealed significant differences in the expression levels of 40 proteins in the serum (p < 0.05) and 17 proteins in the urine (p < 0.05) between BC patients and HC. Six proteins (AREG, RET, WFDC2, FGFBP1, ESM-1, and PVRL4) were selected as potential BC biomarkers, and their expression was evaluated at the protein and transcriptome levels by IHC and single-cell sequencing, respectively. A diagnostic model (a signature) consisting of 14 protein markers (11 in serum and three in urine) was also established using LASSO regression to distinguish between BC patients and HC (area under the curve = 0.91, PPV = 0.91, sensitivity = 0.87, and specificity = 0.82). Our model showed better diagnostic efficacy than FISH, especially for early-stage, small, and low-grade BC. Conclusion Using the PEA method, we identified a panel of potential protein markers in the serum and urine of BC patients. These proteins are associated with the development of BC. A total of 14 of these proteins can be used to detect early-stage, small, low-grade BC. Thus, these markers are promising for clinical translation to improve the prognosis of BC patients. Graphical Abstract | ||
| 650 | 4 | |a Bladder cancer |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Diagnostic model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Biomarkers |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Diagnosis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Prognosis proximity extension assay (PEA) |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Qu, Yang |4 aut | |
| 700 | 1 | |a Zhao, Taowa |4 aut | |
| 700 | 1 | |a Niu, Zitong |4 aut | |
| 700 | 1 | |a Lv, Xiuyi |4 aut | |
| 700 | 1 | |a Wang, Yiting |4 aut | |
| 700 | 1 | |a Ding, Qiaojiao |4 aut | |
| 700 | 1 | |a Wei, Pengyao |4 aut | |
| 700 | 1 | |a Fu, Jun |4 aut | |
| 700 | 1 | |a Wang, Liang |4 aut | |
| 700 | 1 | |a Gao, Jing |4 aut | |
| 700 | 1 | |a Zhou, Cheng |4 aut | |
| 700 | 1 | |a Wang, Suying |4 aut | |
| 700 | 1 | |a Jiang, Junhui |4 aut | |
| 700 | 1 | |a Zheng, Jianping |0 (orcid)0000-0001-6014-5197 |4 aut | |
| 700 | 1 | |a Wang, Kaizhe |0 (orcid)0000-0003-0331-6847 |4 aut | |
| 700 | 1 | |a Wu, Kerong |0 (orcid)0000-0003-3023-9904 |4 aut | |
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