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INTRODUCTION: Breast cancer (BC) is the most common cancer in women, with a high disease burden, especially in the advanced disease stages. Our study investigated the metabolomic profile of breast cancer patients' serum with the aim of identifying novel diagnostic biomarkers that could be used, especially for early disease detection. MATERIALS AND METHODS: Using targeted metabolomic serum profiling based on high-performance liquid chromatography mass spectrometry, women with BC (n = 39) and a control group (n = 21) were examined for 232 endogenous metabolites. RESULTS: The top performing biomarkers included acylcarnitines (ACs) and 9,12-linoleic acid. A combined panel of the top 4 biomarkers achieved 83% sensitivity and 81% specificity, with an area under the curve (AUC) of 0.839 (95% confidence interval, 0.811-0.867). Individual markers also provided significant predictive values: AC 12:0, sensitivity of 72%, specificity of 67%, and AUC of 0.71; AC 14:2, sensitivity of 74%, specificity of 71%, and AUC of 0.73; AC 14:0: sensitivity of 67%, specificity of 81%, and AUC of 0.73; and 9,12-linoleic acid, sensitivity of 69%, specificity of 67%, and AUC of 0.71. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination. CONCLUSION: Using mass spectrometry-targeted metabolomic profiling, ACs and 9,12-linoleic acid were identified as potential diagnostic biomarkers for breast cancer. Additionally, these identified metabolites could provide additional insight into cancer cell metabolism.

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PURPOSE: Endometrial cancer (EC) is the most common gynecological malignancy with high disease burden especially in advanced stages of the disease. Our study investigated the metabolomic profile of EC patient's serum with the aim of identifying novel diagnostic biomarkers that could be used especially in early disease detection. MATERIAL AND METHODS: Using targeted metabolomic serum profiling based on HPLC-TQ/MS, women with EC (n â€‹= â€‹15) and controls (n â€‹= â€‹21) were examined for 232 endogenous metabolites. RESULTS: Top performing biomarkers included ceramides, acylcarnitines and 1-methyl adenosine. Top 4 biomarkers combined achieved 94% sensitivity with 75% specificity with AUC 92.5% (CI 90.5-94.5%). Individual markers also provided significant predictive values: C16-ceramide achieved sensitivity 73%, specificity 81%, AUC 0.83, C22-ceramide sensitivity 67%, specificity 81%, AUC 0.77, hydroxyhexadecenoylcarnitine sensitivity 60%, specificity 96%, AUC 0.76 and 1-methyladenosine sensitivity 67%, specificity 81%, AUC 0.75. The individual markers, however, did not reach the high sensitivity and specificity of the 4-biomarker combination. CONCLUSIONS: Using mass spectrometry targeted metabolomic profiling, ceramides, acylcarnitines and 1-methyladenosine were identified as potential diagnostic biomarkers for EC. Additionally, these identified metabolites may provide additional insight into cancer cell metabolism.

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The data presented here are related to the research paper entitled "Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer." (Kozar et al., 2018) [1]. Metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign gynecological conditions. HPLC-TQ/MS was performed on all samples. PLS-DA was used for the first line classification of epithelial ovarian cancer and healthy control group based on metabolomic profiles. Random forest algorithm was used for building a prediction model based over most significant markers. Univariate analysis was performed on individual markers to determine their distinctive roles. Furthermore, markers were also evaluated for their biological significance in cancer progression.

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INTRODUCTION: Epithelial ovarian cancer (EOC) is a disease with a poor survival rate mostly due to its discovery in late stages. The aim of this study was to investigate the metabolomic profile of ovarian cancer with the intention of identifying and describing novel biomarkers with diagnostic potential. MATERIAL AND METHODS: Targeted serum metabolomic profiling was performed on 15 patients with ovarian cancer, 21 healthy controls and 21 patients with benign ovarian conditions, using HPLC-TQ/MS. RESULTS: Panel of 49 top performing biomarkers shows separation between EOC and controls with 87% specificity and 87% sensitivity with AUC of 93% (CI 90%-95%). Using only 5 top biomarkers, specificity of 80% and sensitivity of 83% was achieved on extended sample set. Most significant biomarkers belong to sphingolipid classes, especially long chain ceramides and sphingomyelins. Different concentrations of various fatty acid chain lengths ceramides and sphingomyelins are also implying their respective roles in cell proliferation and growth inhibition. CONCLUSION: Long chain ceramides and sphingomyelins may serve as a novel biomarker for epithelial ovarian cancer detection and may also offer insight into the role of sphingolipid metabolism in cell proliferation.

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To explain the higher tolerance of Thellungiella to abiotic stress in comparison to Arabidopsis, several studies have focused on differences in ion absorption and gene expression. However, little is known about hormone regulation and metabolic responses. In this work, plants of both species were subjected to desiccation and salt stress to compare common and divergent responses. In control conditions, the number of significantly upregulated mass features as well as proline levels was higher in Tellungiella than in Arabidopsis. When subjected to desiccation, both species exhibited similar rates of water loss but proline over accumulation only occurred in Thellungiella; both species accumulated ABA and JA with a similar trend although Arabidopsis showed higher concentrations of both hormones which indicated a stronger impact of desiccation on Arabidopsis. However, Arabidopsis showed a higher number of significantly altered mass features than Thellungiella. Under salt stress, Thellungiella plants accumulated lower amounts of Cl(-) ions than Arabidopsis but exhibited a similar proline response. Under these conditions, ABA and JA levels increased in Arabidopsis whereas minimal changes in both hormone concentrations were recorded in Thellungiella. Contrastingly, the impact of salt stress on metabolite profiles was higher in Thellungiella than in Arabidopsis. Overall, data indicated that physiological responses in Arabidopsis are induced after stress imposition through hormonal regulation whereas Thellungiella has a basal metabolic configuration, better prepared to endure environmental cues.

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Citrumelo CPB 4475 and Carrizo citrange are two citrus genotypes that differ in their tolerance to abiotic stress. Little information is found on flavonoid content in citrus leaves and even less on the role of flavonoids on citrus tolerance to environmental stress. This work developed a multiplexed approach utilizing HPLC-DAD-ESI-MS and NMR for the identification and profiling of flavonoids in citrus leaves. A total of 47 phenolic compounds were detected and 45 tentatively identified. Eleven of them were acylated with hydroxycinnamic acid derivatives. Some of the compounds identified were not reported in citrus and two of them not even in the plant kingdom. In response to soil flooding, the relative reduction in leaf flavonoids was more important in citrumelo, which can give additional insights to the low tolerance of this genotype to flooding. The method reported could serve as an effective tool for profiling flavonoids in leaves of different genotypes under distinct environmental situations.

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