Guixue Hou (Presenter)
BIG, Chinese Academy of Science
Authorship: Guixue Hou(1, 2);Hui Ye(2); Liang Lin(2); Jin Zi(2);Lin Wu(1); Siqi Liu(1,2)
(1)Beijing Institute of Genomics, CAS, Beijing, China; (2)BGI-Shenzhen, Shenzhen, China;
| Short Abstract It is gradually recognized that integration of the data from genomics, transcriptomics, proteomics and metabolomics may expand our knowledge to understand of disease. Recently, genomics sequencing and proteomics analysis to esophageal squamous cell carcinoma (ESCC) revealed several significant evidence related with tumor gene mutations as well as expression, such as APO clearly dis-regulated in ESCC. Herein, we proposed an approach that integrates genomics, proteomics and lipidomics to find how these lipid associated genes and proteins impact the lipids" abundance in serum during the development of ESCC. We selected the sera of health, mild/moderate/severe dysplasia and ESCC for lipidomics analysis by MSE, then combined proteomics and genomics data in publications for further analysis of lipid candidates during the ESCC development. |
Long Abstract
Introduction
It is gradually recognized that integration of the data from genomics, transcriptomics, proteomics and metabolomics may expand our knowledge to understand of disease. Recently, genomics sequencing and proteomics analysis to esophageal squamous cell carcinoma (ESCC) revealed several significant evidence related with tumor gene mutations as well as expression, such as APO clearly dis-regulated in ESCC. Herein, we proposed an approach that integrates genomics, proteomics and lipidomics to find how these lipid associated genes and proteins impact the lipids" abundance in serum during the development of ESCC. We selected the sera of health, mild/moderate/severe dysplasia and ESCC for lipidomics analysis by MSE, then combined proteomics and genomics data in publications for further analysis of lipid candidates during the ESCC development.
Methods
The sera from different groups, health, mild/moderate dysplasia, severe dysplasia and ESCC, were collected followed by lipid extraction with pre-cold isopropanol. Equal volume of each sample was pooled as QC. The samples were injected onto a reverse-phase CSH C18 1.7 0…8M 2.1x100 mm column using an Acquity UPLC system (Waters Corporation, USA) equipped with a Waters XS QTOF at MSE mode. The QC was conducted per 10 injections. Raw data was imported into Progenesis QI (Waters Corporation, USA) for alignment and peak picking, and all measured features with CV<30% were further analyzed by MetaboAnalyst.
Preliminary Data
Lipidomics analysis in the serum samples: To determine the changed lipids during the development of ESCC, the features extracted from raw data in the four serum groups were treated by the Principal Component Analysis (PCA) for unsupervised clustering and classification. In PCA graph, the ESCC group could be completely separated from other groups, while the health and dysplasia groups were clearly clustered, even though a few of the samples in the two groups were slightly overlapped. The PCA analysis, however, could not recognize the differences among the dysplasia samples. The lipid compounds corresponding to the MS signals was further identified by searching LIPID MAPs and HMDB v3.6. The search result showed the pathways relevant with metabolism of arachidonic acid, retinol and linoleic acid changed significantly in response to ESCC development.
Integration of the trans-omics data: Genomics data revealed that the apo mutant genes might affect the expression of apoliprotein family. Proteomics data based on SWATH MS, 2157 unique proteins with 10198 peptides and 1955 unique proteins with 9708 peptides were identified in ESCC and the adjacent tissues, respectively. According to the statistical analysis by SRMstats, total of 523 unique proteins were found with their abundance in the pooled ESCC tissue lysate significantly different from that in the pooled lysate of the adjacent tissue, including 294 up-regulated and 228 down-regulated. By searching the LIPID MAPS Proteome Database (LMPD), 43 ESCC-related proteins like Apo B were found functional at lipids metabolism, such as fatty acid degradation and metabolism of lipids or lipoproteins. These differential lipid-associated proteins could offer an explanation why the abnormality of lipid metabolism such as arachidonic acid, retinol or linoleic acid metabolism was found in the ESCC serum.
Conclusion
The strategy that combines genomics, proteomics and lipidomics appears the advantages to find how these lipid associated genes and proteins impact the lipids" abundance in serum during the development of ESCC.
References & Acknowledgements:
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