Liposoluble Vitamins E and A in Human Renal Cortex and Renal Cell Carcinomas

Nikiforova, N. V.; Kirpatovskiy, V.I.; Darenkov, A F; Chumakov, Alexey M.; Sevrukov, E.A.; Darenkov, S P

doi:10.1159/000188518

Cited by 9 publications

(6 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To the best of knowledge, our study is the first one that discovered the upregulation of vitamin E metabolism in bladder caners, which may be caused by inflammation secondary to tumors. Concerning the renal cell carcinoma, Catchpole et al observed that an increased level of α-tocopherol in RCC tumor tissues compared with the normal renal cortex tissue, consistent with the findings of Nikiforova etc 26,33 . Besides, analysing the 66 invasive ovarian carcinomas and 9 borderline tumor tissues by gas chromatography/time-of-flight mass spectrometry, Denkert etc.…”

Section: Discussionsupporting

confidence: 64%

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Wang

Liu

et al. 2019

Preprint

View full text Add to dashboard Cite

Purpose To discover biomarker panels that could distinguish cancers(BC & RCC) from healthy controls(HCs) and bladder cancers(BC) from renal cell carcinoma(RCC), regardless of whether with hematuria. Methods Totallys, 403 participants were enrolled in our study, with 146 BC patients(77 without hematuria and 69 with hematuria), 115 RCC patients (94 without hematuria and 21 with hematuria) and 142 gender- and age- matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. Results The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the cancers from the HCs(the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel consisiting of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N'-formylkynurenine could differentiate BC from RCC without hematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with hematuria(AUC was 0.913). Pathway analyses revealed there existed alterd lipid and purine metabolism between cancers and HCs, together with disordered amino acid and purine metablism between BC and RCC with hematuria. Conclusions The UPLC-MS urine metabolomic analyses could not only differentiate the cancers from HCs but also discriminate the BC from RCC. Besides, pathway analyses could demonstrate the deeper metabolic mechanism of BC and RCC.

show abstract

Section: Discussionsupporting

confidence: 64%

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Wang

Liu

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 64%

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Wang

Liu

et al. 2019

Preprint

View full text Add to dashboard Cite

Background: To discover biomarker panels that could distinguish cancers(BC & RCC) from healthy controls(HCs) and bladder cancers(BC) from renal cell carcinoma(RCC), regardless of whether with hematuria. Methods: Totallys, 403 participants were enrolled in our study, with 146 BC patients(77 without hematuria and 69 with hematuria), 115 RCC patients (94 without hematuria and 21 with hematuria) and 142 gender- and age- matched HCs. Their midstream urine samples were collected and analysed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarker panels and altered metabolic pathways. Results: The panel of α-CEHC, β-cortolone, deoxyinosine, flunisolide, 11b,17a,21-trihydroxypreg-nenolone and glycerol tripropanoate could distinguish the cancers from the HCs(the AUC was 0.950) and the external validation also displayed a good predictive ability (the AUC was 0.867). The panel consisiting of 4-ethoxymethylphenol, prostaglandin F2b, thromboxane B3, hydroxybutyrylcarnitine, 3-hydroxyphloretin and N'-formylkynurenine could differentiate BC from RCC without hematuria. The AUC was 0.829 in the discovering group and 0.76 in the external validation. The metabolite panel comprising 1-hydroxy-2-oxopropyl tetrahydropterin, 1-acetoxy-2-hydroxy-16-heptadecyn-4-one, 1,2-dehydrosalsolinol and L-tyrosine could significantly discriminate BC from RCC with hematuria(AUC was 0.913). Pathway analyses revealed there existed alterd lipid and purine metabolism between cancers and HCs, together with disordered amino acid and purine metablism between BC and RCC with hematuria. Conclusions: The UPLC-MS urine metabolomic analyses could not only differentiate the cancers from HCs but also discriminate the BC from RCC. Besides, pathway analyses could demonstrate the deeper metabolic mechanism of BC and RCC.

show abstract

“…Another remarkable finding was the profound up-regulation of α-tocopherol concentration in RCC and despite previous allusions to such an elevated vitamin E concentration [ 29 , 30 ] this finding has as yet not received particular attention. Among all metabolites investigated in our study, α-tocopherol emerged as the most important classifier of normal versus tumorous tissue and therefore underlines the putative importance of vitamin E in RCC biology.…”

Section: Discussionmentioning

confidence: 99%

Metabolic profiling reveals key metabolic features of renal cell carcinoma

Catchpole

Platzer

Weikert

et al. 2011

J Cellular Molecular Medi

105

View full text Add to dashboard Cite

Recent evidence suggests that metabolic changes play a pivotal role in the biology of cancer and in particular renal cell carcinoma (RCC). Here, a global metabolite profiling approach was applied to characterize the metabolite pool of RCC and normal renal tissue. Advanced decision tree models were applied to characterize the metabolic signature of RCC and to explore features of metastasized tumours. The findings were validated in a second independent dataset. Vitamin E derivates and metabolites of glucose, fatty acid, and inositol phosphate metabolism determined the metabolic profile of RCC. α-tocopherol, hippuric acid, myoinositol, fructose-1-phosphate and glucose-1-phosphate contributed most to the tumour/normal discrimination and all showed pronounced concentration changes in RCC. The identified metabolic profile was characterized by a low recognition error of only 5% for tumour versus normal samples. Data on metastasized tumours suggested a key role for metabolic pathways involving arachidonic acid, free fatty acids, proline, uracil and the tricarboxylic acid cycle. These results illustrate the potential of mass spectroscopy based metabolomics in conjunction with sophisticated data analysis methods to uncover the metabolic phenotype of cancer. Differentially regulated metabolites, such as vitamin E compounds, hippuric acid and myoinositol, provide leads for the characterization of novel pathways in RCC.

show abstract

Liposoluble Vitamins E and A in Human Renal Cortex and Renal Cell Carcinomas

Cited by 9 publications

References 4 publications

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

UPLC-MS based urine untargeted metabolomic analyses to differentiate bladder cancer from renal cell carcinoma

Metabolic profiling reveals key metabolic features of renal cell carcinoma

Contact Info

Product

Resources

About