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¹H NMR based serum metabolic profiles associated with pathological progression of pancreatic islet β cell tumor in Rip1-Tag2 mice.

Yang Y, Liu Y, Zheng L, Zhang Q, Gu Q, Wang L, Wang L - Int. J. Biol. Sci. (2015)

Bottom Line: Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells.In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism.The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.

View Article: PubMed Central - PubMed

Affiliation: 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China ; 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China.

ABSTRACT
Pancreatic islet β cell tumor is the most common islet cell tumor. A well-characterized tumor progression in Rip1-Tag2 mice undergoes five stages, involving normal, hyperplasia, angiogenic islets, tumorigenesis and invasive carcinoma. (1)H NMR based metabonomics was applied to identify potential biomarkers for monitoring pancreatic islet β cell tumor progression in Rip1-Tag2 mice. Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells. At angiogenic islets stage, the up-regulated glycolysis, disturbed choline and phospholipid metabolism composed the metabolic signature. In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism. All the changes were aggravated at invasive carcinoma stage, coupled with notable changes in alanine, glutamate and glycine. Moreover, the distinct metabolic phenotype was found associated with the implanting of SV40 large T antigen in Rip1-Tag2 mice. The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.

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OPLS-DA analysis results of sera 1H CPMG NMR data in Rip1-Tag2 mice at 3 weeks (●), 8 weeks (◆), 10 weeks (■) and 14 weeks (▲). A, scores plots; B, coefficient-coded loadings plots. A1, B1: 8 weeks vs 3 weeks, R2X=68.5%, Q2Y=57.3%; A2, B2: 10 weeks vs 3 weeks, R2X=76.1%, Q2Y=69.3%; A3, B3: 14 weeks vs 3 weeks, R2X=89.5%, Q2Y=80.7%.
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Figure 5: OPLS-DA analysis results of sera 1H CPMG NMR data in Rip1-Tag2 mice at 3 weeks (●), 8 weeks (◆), 10 weeks (■) and 14 weeks (▲). A, scores plots; B, coefficient-coded loadings plots. A1, B1: 8 weeks vs 3 weeks, R2X=68.5%, Q2Y=57.3%; A2, B2: 10 weeks vs 3 weeks, R2X=76.1%, Q2Y=69.3%; A3, B3: 14 weeks vs 3 weeks, R2X=89.5%, Q2Y=80.7%.

Mentions: In this research, OPLS-DA models were built among the samples at different stages to find the potential biomarkers characterizing the histopathological progression. Scores and loadings line plots coded with coefficients were presented. The metabolites with significant contribution to the differentiation between two groups were hot colored. We didn't perform multivariate analysis on the spectra data at 5 weeks because of the metabolic similarity with the ones at 3 week. Fig. 5A1 showed the distinct grouping cluster between samples at 3 weeks and the ones at 8 weeks, which revealed the obvious sera metabolic changes in Rip1-Tag2 mice at angiogenic islets stage. It was found that lactate was up-regulated, while acetate, dimethylamine, taurine, glucose and myo-inositol were decreased in the serum samples at 8 weeks (Fig. 5B1). The same OPLS-DA strategy was also used to the metabonome between 3 weeks and 10 weeks, which showed the clear differentiation between them. In addition to the metabolites changes mentioned above, a series of new metabolites with notable changes appeared at the early stage of tumor, including alanine, methionine, citrate and choline. The variation trend of metabolites contributing to the favorable classification between 3 weeks and 14 weeks (Fig. 5B3) were generally in consistent with the changes at 10 weeks, except the changes of glutamate and glycine at 14 weeks. It was noted from the scores plots that the differentiation from the samples at 14 weeks became greater with the aggravation of pathological progression, which indicated that more important metabolites variations appeared with tumor development. The statistical analysis results were showed in table 2. It was observed that changes in lactate, dimethylamine and myo-inositol started to change with statistical significance at 8 weeks, when angiogenic islets emerged. The significantly increased methionine, citrate, choline, and the decreased acetate, taurine and glucose firstly appeared at the early stage of pancreatic islet β cell tumor. Therefore, these metabolites could be regarded as potential biomarkers of tumorigenesis. Moreover, the emerging of statistically elevated alanine and glutamate, as well as the decreased glycine were metabolic characteristics for invasive carcinoma in Rip1-Tag2 mice.


¹H NMR based serum metabolic profiles associated with pathological progression of pancreatic islet β cell tumor in Rip1-Tag2 mice.

Yang Y, Liu Y, Zheng L, Zhang Q, Gu Q, Wang L, Wang L - Int. J. Biol. Sci. (2015)

OPLS-DA analysis results of sera 1H CPMG NMR data in Rip1-Tag2 mice at 3 weeks (●), 8 weeks (◆), 10 weeks (■) and 14 weeks (▲). A, scores plots; B, coefficient-coded loadings plots. A1, B1: 8 weeks vs 3 weeks, R2X=68.5%, Q2Y=57.3%; A2, B2: 10 weeks vs 3 weeks, R2X=76.1%, Q2Y=69.3%; A3, B3: 14 weeks vs 3 weeks, R2X=89.5%, Q2Y=80.7%.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4400390&req=5

Figure 5: OPLS-DA analysis results of sera 1H CPMG NMR data in Rip1-Tag2 mice at 3 weeks (●), 8 weeks (◆), 10 weeks (■) and 14 weeks (▲). A, scores plots; B, coefficient-coded loadings plots. A1, B1: 8 weeks vs 3 weeks, R2X=68.5%, Q2Y=57.3%; A2, B2: 10 weeks vs 3 weeks, R2X=76.1%, Q2Y=69.3%; A3, B3: 14 weeks vs 3 weeks, R2X=89.5%, Q2Y=80.7%.
Mentions: In this research, OPLS-DA models were built among the samples at different stages to find the potential biomarkers characterizing the histopathological progression. Scores and loadings line plots coded with coefficients were presented. The metabolites with significant contribution to the differentiation between two groups were hot colored. We didn't perform multivariate analysis on the spectra data at 5 weeks because of the metabolic similarity with the ones at 3 week. Fig. 5A1 showed the distinct grouping cluster between samples at 3 weeks and the ones at 8 weeks, which revealed the obvious sera metabolic changes in Rip1-Tag2 mice at angiogenic islets stage. It was found that lactate was up-regulated, while acetate, dimethylamine, taurine, glucose and myo-inositol were decreased in the serum samples at 8 weeks (Fig. 5B1). The same OPLS-DA strategy was also used to the metabonome between 3 weeks and 10 weeks, which showed the clear differentiation between them. In addition to the metabolites changes mentioned above, a series of new metabolites with notable changes appeared at the early stage of tumor, including alanine, methionine, citrate and choline. The variation trend of metabolites contributing to the favorable classification between 3 weeks and 14 weeks (Fig. 5B3) were generally in consistent with the changes at 10 weeks, except the changes of glutamate and glycine at 14 weeks. It was noted from the scores plots that the differentiation from the samples at 14 weeks became greater with the aggravation of pathological progression, which indicated that more important metabolites variations appeared with tumor development. The statistical analysis results were showed in table 2. It was observed that changes in lactate, dimethylamine and myo-inositol started to change with statistical significance at 8 weeks, when angiogenic islets emerged. The significantly increased methionine, citrate, choline, and the decreased acetate, taurine and glucose firstly appeared at the early stage of pancreatic islet β cell tumor. Therefore, these metabolites could be regarded as potential biomarkers of tumorigenesis. Moreover, the emerging of statistically elevated alanine and glutamate, as well as the decreased glycine were metabolic characteristics for invasive carcinoma in Rip1-Tag2 mice.

Bottom Line: Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells.In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism.The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.

View Article: PubMed Central - PubMed

Affiliation: 1. School of Basic Course, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China ; 2. Vascular Biology Research Institute, Guangdong Pharmaceutical University, Guangzhou, 510006, PR China.

ABSTRACT
Pancreatic islet β cell tumor is the most common islet cell tumor. A well-characterized tumor progression in Rip1-Tag2 mice undergoes five stages, involving normal, hyperplasia, angiogenic islets, tumorigenesis and invasive carcinoma. (1)H NMR based metabonomics was applied to identify potential biomarkers for monitoring pancreatic islet β cell tumor progression in Rip1-Tag2 mice. Multivariate analysis results showed the serum metabonome at hyperplasia stage shared the similar characteristics with the ones at normal stage as a result of slight proliferation of pancreatic islet β cells. At angiogenic islets stage, the up-regulated glycolysis, disturbed choline and phospholipid metabolism composed the metabolic signature. In addition to the changes mentioned above, several metabolites were identified as early biomarkers for tumorigenesis, including increased methionine, citrate and choline, and reduced acetate, taurine and glucose, which suggested the activated energy and amino acid metabolism. All the changes were aggravated at invasive carcinoma stage, coupled with notable changes in alanine, glutamate and glycine. Moreover, the distinct metabolic phenotype was found associated with the implanting of SV40 large T antigen in Rip1-Tag2 mice. The combined metabolic and multivariate statistics approach provides a robust method for screening the biomarkers of disease progression and examining the association between gene and metabolism.

Show MeSH
Related in: MedlinePlus