Dataset Information

Use of UHPLC-HRMS to profile the metabolites from the serum of breast cancer patients

ABSTRACT:

Breast cancer (BC) is the most common malignancy and the leading cause of cancer-related mortality in women worldwide. As such exploring the metabolic changes during human breast carcinogenesis is important for developing disease prevention methods and treatments. In the present study, non-targeted metabolomics with chemometrics based on ultrahigh performance liquid chromatography-high resolution mass spectrometry was conducted to analyze the differences in serum metabolite patterns between female patients with BC and healthy individuals. A total of 3246 metabolites at various concentrations in the sera of healthy controls and patients with BC were found. Kyoto Encyclopedia of Genes and Genomes pathway analysis demonstrated that arginine, proline, nicotinate, nicotinamide, caffeine and arachidonic acid metabolism as well as fatty acid biosynthesis were significantly altered in BC patients in comparison to controls. These results suggest that serum metabolic profiling has great potential in discovering molecular biomarkers for the detection of BC breast cancer. They may also help to further our understanding of the underlying mechanisms associated with this debilitating disease.

INSTRUMENT(S): Liquid Chromatography MS - positive - hilic, Liquid Chromatography MS - negative - hilic

SUBMITTER: haoyu leng

PROVIDER: MTBLS8920 | MetaboLights | 2024-02-13

REPOSITORIES: MetaboLights

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Dataset's files

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			Action	DRS
	MTBLS8920	Other
	FILES	Other
	a_MTBLS8920_LC-MS_negative_hilic_metabolite_profiling.txt	Txt
	a_MTBLS8920_LC-MS_positive_hilic_metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt

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Project description:Purpose: There is a quest for novel non-invasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA signatures using a cohort of Asian Chinese breast cancer patients, and to compare microRNA profiles between tumour and serum samples. Experimental design: MicroRNAs from paired breast cancer tumours, normal tissue and serum samples derived from 32 patients were comprehensively profiled using microarrays (1300 microRNAs against tumour and normal tissues) or LNA RT-PCR panels (742 microRNAs against serum samples). Serum samples from healthy individuals (n=22) were also employed as normal controls. Significant serum microRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n=82) and healthy controls (n=53). Results: The 20 most significant microRNAs differentially expressed in breast cancer tumours included miR-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Interestingly, 16 of the 20 most significant microRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these microRNAs exhibited areas under the curves of 0.944-0.946. Only seven microRNAs were overexpressed in both tumours and serum, suggesting that microRNAs may be released into the serum selectively. Conclusion: The clinical employment of microRNA signatures as a non-invasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers. Blood samples were collected in Becton Dickinson (Franklin Lakes, NJ) Vacutainer SST tubes. Serum was harvested by centrifugation at 2200g after allowing blood to clot for 30mins. 32 patient samples and 22 samples from healthy controls were obtained for profiling. Sera samples were stored at -80oC.

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Use of UHPLC-HRMS to profile the metabolites from the serum of breast cancer patients

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