Urine proteome changes in rats subcutaneously inoculated with approximately ten tumor cells

Wei, Jing; Meng, Wenqi; Gao, Youhe

doi:10.7717/peerj.7717

“…We also compared the urinary differential proteins in the CUMS model to those in 15 other models, including a clinical model of autism [62] and a variety of animal models of Alzheimer's disease [11], Parkinson's disease [12], myocarditis [63] , chronic pancreatitis [64], unilateral ureteral obstruction model [65], astrocytoma [66], liver fibrosis [67] , pulmonary fibrosis [68] , glomerulosclerosis [69] , a model involving the injection of 10 tumor cells [70], the Walker-256 intracerebral tumor model [71], the Walker-256 liver tumor model [72], the Walker-256 subcutaneous model [73] and the Walker-256 lung metastasis model [74]. The comparison results are presented in Table S6.…”

Section: Discussionmentioning

confidence: 99%

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Huan

¹

,

Wei

²

,

Su

³

et al. 2021

Journal of Pharmaceutical and Biomedical Analysis

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Background. Major depressive disorder (MDD) is a prevalent complex psychiatric disorder with a high prevalence rate. Because MDD is a systemic multifactorial disorder involving complex interactions and disturbances of various molecular pathways, there are no effective biomarkers for clinical diagnosis. Urine is not subjected to homeostatic control, allowing it to reflect the sensitive and comprehensive changes that occur in various diseases. In this study, we examined the urine proteome changes in a CUMS mouse model of MDD. Methods. Male C57BL/6 mice were subjected to chronic unpredictable mild stress for 5 weeks. The tail suspension test (TST) and sucrose consumption test (SCT) were then applied to evaluate depression-like behaviors. The urine proteomes on day 0 and day 36 in the CUMS group were profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Results. A total of 45 differential proteins were identified, 24 of which have been associated with the pathogenic mechanisms of MDD, while 10 proteins have been previously suggested as MDD biomarkers. There was an average of two differential proteins that were identified through 1048574 random combination statistical analyses, indicating that at least 95% of the differential proteins were reliable and not the result of random combination. The differential proteins were mainly associated with blood coagulation, inflammatory responses and central nervous system development. Conclusions. Our preliminary results indicated that the urine proteome can reflect changes associated with MDD in the CUMS model, which provides potential clues for the diagnosis of clinical MDD patients.

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“…We also compared the urinary differential proteins in the CUMS model to those in 15 other models, including a clinical model of autism [62] and a variety of animal models of Alzheimer's disease [11], Parkinson's disease [12], myocarditis [63] , chronic pancreatitis [64], unilateral ureteral obstruction model [65], astrocytoma [66], liver fibrosis [67] , pulmonary fibrosis [68] , glomerulosclerosis [69] , a model involving the injection of 10 tumor cells [70], the Walker-256 intracerebral tumor model [71], the Walker-256 liver tumor model [72], the Walker-256 subcutaneous model [73] and the Walker-256 lung metastasis model [74]. The comparison results are presented in Table S6.…”

Section: Discussionmentioning

confidence: 99%

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Huan

¹

,

Wei

²

,

Su

³

et al. 2020

Preprint

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Background. Major depressive disorder (MDD) is a prevalent complex psychiatric disorder with a high prevalence rate. Because MDD is a systemic multifactorial disorder involving complex interactions and disturbances of various molecular pathways, there are no effective biomarkers for clinical diagnosis. Urine is not subjected to homeostatic control, allowing it to reflect the sensitive and comprehensive changes that occur in various diseases. In this study, we examined the urine proteome changes in a CUMS mouse model of MDD. Methods. Male C57BL/6 mice were subjected to chronic unpredictable mild stress for 5 weeks. The tail suspension test (TST) and sucrose consumption test (SCT) were then applied to evaluate depression-like behaviors. The urine proteomes on day 0 and day 36 in the CUMS group were profiled by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Results. A total of 45 differential proteins were identified, 24 of which have been associated with the pathogenic mechanisms of MDD, while 10 proteins have been previously suggested as MDD biomarkers. There was an average of two differential proteins that were identified through 1048574 random combination statistical analyses, indicating that at least 95% of the differential proteins were reliable and not the result of random combination. The differential proteins were mainly associated with blood coagulation, inflammatory responses and central nervous system development. Conclusions. Our preliminary results indicated that the urine proteome can reflect changes associated with MDD in the CUMS model, which provides potential clues for the diagnosis of clinical MDD patients.

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“…For analysis, 1 µg of peptide from each sample was loaded into a trap column (75 µm × 2 cm, 3 µm, C18, 100 Å) at a flow rate of 0.25 μL/min and separated with a reversed-phase analytical column (75 µm × 250 mm, 2 µm, C18, 100 Å). The peptides were eluted with a gradient extending from 5 to 30% buffer B (0.1% formic acid in 80% acetonitrile) for 60 min and were then analyzed with an Orbitrap Fusion Lumos Tribrid Mass Spectrometer (Thermo Fisher Scientific) 17 . To obtain MS data, survey MS scans were acquired in the Orbitrap using a range of 350-1,550 m/z with the resolution set to 120,000.…”

Section: Lc-ms/ms Analysismentioning

confidence: 99%

Early urinary protein changes during tumor formation in a NuTu-19 tail vein injection rat model

Wei

¹

,

Ni

²

,

Meng

³

et al. 2020

Sci Rep

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Early detection of cancer is essential for effective intervention. Urine has been used to reflect early changes in various tumor-bearing models. However, urine has not been used to predict whether tumors will form in animal models. In this study, a cancer model was established by tail vein injection of 2 million NuTu-19 tumor cells. Urine samples were randomly selected from tumor-forming and non-tumor-forming rats on day 0/12/27/39/52 and were analyzed by label-free and parallel reaction monitoring targeted proteomic quantitative analyses. In tumor-forming rats, differential proteins were associated with tumor cell migration, TGF-β signaling and the STAT3 pathway. A total of 9 urinary proteins showed significant changes in the early phase of lung tumor formation in all eight tumor-bearing rats. Differential proteins in non-tumor-forming rats were associated with glutathione biosynthesis, IL-12 signaling and vitamin metabolism. A total of 12 urinary proteins changed significantly in the early phase in all seven non-tumor-forming rats. Our small-scale pilot study indicated that (1) the urinary proteome reflects early changes during lung tumor formation and that (2) the urinary proteome can distinguish early tumor-forming rats from non-tumor-forming rats. The lungs are common sites for cancer metastasis because of their specific immunologically permissive environment 1. Therefore, various cancers, such as breast cancer, skin melanoma, colorectal cancer, sarcoma and pancreatic cancer, metastasize more easily to the lungs than to other tissues 2. Lung metastasis is a lethal determinant in many cancers 3. The prognosis of patients with malignant lung tumors is very poor, with a low 5-year survival rate, and immunotherapy and chemotherapy have had limited success in reversing lung cancer progression 4,5. Therefore, there is an urgent need to identify biomarkers for the early detection of lung tumors and even for the prediction of whether tumors will form in the lungs. The discovery of such biomarkers will enable the development of effective therapies for metastatic lung cancer patients. Urine, as the filtrate of the blood, does not need to remain stable in composition; therefore, it is an ideal biomarker source, accumulating molecules that reflect all changes throughout the body, possibly even early and small pathological changes 6,7. Urinary proteomics analysis has already been applied for the clinical detection of lung cancer in patients 8,9. However, the urinary proteome is easily affected by various factors, such as age, sex, diet and medication, especially in the context of clinical urine samples 7. Experiments using animal models will help to minimize these influential factors and will establish the direct relationships between diseases and corresponding changes in urinary proteins 10. In addition, the exact starting point and the entire tumor progression period can be controlled in animal model studies, making it possible to collect urine samples in early stages. In our previous studies, we used urinary proteomes...

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Urine proteome changes in rats subcutaneously inoculated with approximately ten tumor cells

Cited by 9 publications

References 36 publications

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Early urinary protein changes during tumor formation in a NuTu-19 tail vein injection rat model

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