Differences in lipidomics may be potential biomarkers for early diagnosis of pancreatic cancer

Zhou, Dehua; Mu, Di; Cheng, Ming; Dou, Yuting; Zhang, Xianwei; Feng, Zhensheng; Qiu, Guangyu; Yu, Hua; Chen, Yang; Xu, Hong; Sun, Jian; Zhou, Ling

doi:10.1590/s0102-865020200050000008

Cited by 10 publications

(13 citation statements)

References 29 publications

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“…The pancreas was an important organ of lipid metabolism in human body and the study of lipid omics could help to understand the changes of pancreas function. It is reported that the concentration of arachidonic acid, lysophosphatidylcholine, phosphatidylcholine (PC) and phosphatidyl ethanolamine (PE) in the plasma of patients with early pancreatic cancer was found to be increased by the method of lipid group analysis [8,9]. However, lipid metabolites with differences in pancreatic cancer and adjacent tissues were screened out through tissue samples, and the results showed that PC, PE were signi cantly increased in cancer tissues, which was basically consistent with previous plasma studies.…”

Section: Discussionsupporting

confidence: 84%

“…The correlation analysis between the proportion of immune cells and the expression of lipid metabolism genes in tumor microenvironment showed that there were differences in the expression of immune-related lipid metabolism genes, suggesting a potential interaction between lipid metabolism and immune response [20]. Our previous study suggested abnormal lipid metabolism in the serum of pancreatic cancer, and this study further veri ed this study through tissue samples, which laid a foundation for the later study on the molecular mechanism of lipid metabolism and pancreatic cancer [9].…”

Section: Discussionsupporting

confidence: 58%

“…Although our previous studies have suggested that differences in serum lipid metabolites might serve as potential biomarkers for early diagnosis of pancreatic cancer [9], tissue samples represented changes in the local environment of the tumor and were less affected by systemic factors. We aimed to investigate the predictive value of the local tissue lipid metabolites pro le in patients undergoing radical resection of pancreatic cancer.…”

Section: Introductionmentioning

confidence: 99%

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The Lipid Metabolites Profile in Patients with Pancreatic Cancer: A Controlled Study of Cancer Tissue Versus Matched Para-Cancer Tissue

Hong¹,

Sun²,

Zhou³

et al. 2020

Preprint

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Background and objectives: Most patients with pancreatic cancer were diagnosed at a late stage because identifying pancreatic cancer early was difficult. Therefore, it was of great significance to screen specific biomarkers in early stage of pancreatic cancer. The aim of this study was to demonstrate the profile and characteristics of lipid metabolites in patients with pancreatic cancer and to correlate the expression level of these metabolites with the tumor.Methods: A total of 9 tissue samples from patients with pancreatic cancer were collected and divided into cancer group and para-cancer group according to different sites. All patients’ samples were performed a metabolomics analysis based on Liquid Tandem Chromatography Quadrupole Time of Flight Mass Spectrometry.Results: PCA based on lipidomics analysis could clearly distribute in different regions. OPLS-DA analysis could filter out the irrelevant variables in metabolites and obtain more reliable information about the intergroup differences of metabolites. The volcano plot was used to visualize all variables with VIP>1 and presented the important variables with P<0.05 and |FC|>2. Euclidean distance matrix was calculated for the quantitative values of the differential metabolites, and the differential metabolites were clustered by using the full linkage method and heat map was used to demonstrate. The different metabolites of each group were compared and analyzed by radar map, the corresponding ratio of the quantitative value of differential metabolites were calculated. Heatmap of correlation analysis showed the correlation coefficient between different metabolites. Bar plot visualized the variation degree and classification information of metabolites. Bubble plot showed the variation degree, difference significance degree and classification information of metabolites.Conclusion: The tissue samples of pancreatic cancer had the characteristics of lipidomics, and the difference of lipid metabolites could be used as potential tumor markers of pancreatic cancer.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionsupporting

confidence: 58%

Section: Introductionmentioning

confidence: 99%

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The Lipid Metabolites Profile in Patients with Pancreatic Cancer: A Controlled Study of Cancer Tissue Versus Matched Para-Cancer Tissue

Hong¹,

Sun²,

Zhou³

et al. 2020

Preprint

Self Cite

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“…Given the high risk of pancreatic surgery, it was difficult to obtain healthy controls for pancreatic tissue. However, our previous studies showed differences in lipid metabolites between pancreatic cancer patients and healthy controls in blood samples[ 36 ]. In addition, the association between the risk score and immune activity was not further validated in the corresponding experiments.…”

Section: Discussionmentioning

confidence: 99%

Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer

Xu¹,

Sun²,

Zhou³

et al. 2021

WJCC

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BACKGROUND Pancreatic cancer is a highly heterogeneous disease, making prognosis prediction challenging. Altered energy metabolism to satisfy uncontrolled proliferation and metastasis has become one of the most important markers of tumors. However, the specific regulatory mechanism and its effect on prognosis have not been fully elucidated. AIM To construct a prognostic polygene signature of differentially expressed genes (DEGs) related to lipid metabolism. METHODS First, 9 tissue samples from patients with pancreatic cancer were collected and divided into a cancer group and a para-cancer group. All patient samples were subjected to metabolomics analysis based on liquid tandem chromatography quadrupole time of flight mass spectrometry. Then, mRNA expression profiles and corresponding clinical data of pancreatic cancer were downloaded from a public database. Least absolute shrinkage and selection operator Cox regression analysis was used to construct a multigene model for The Cancer Genome Atlas. RESULTS Principal component analysis and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) based on lipid metabolomics analysis showed a clear distribution in different regions. A Euclidean distance matrix was used to calculate the quantitative value of differential metabolites. The permutation test of the OPLS-DA model for tumor tissue and paracancerous tissue indicated that the established model was consistent with the actual condition based on sample data. A bar plot showed significantly higher levels of the lipid metabolites phosphatidylcholine (PC), phosphatidyl ethanolamine (PE), phosphatidylethanol(PEtOH), phosphatidylmethanol (PMeOH), phosphatidylserine (PS) and diacylglyceryl trimethylhomoserine (DGTS) in tumor tissues than in paracancerous tissues. According to bubble plots, PC, PE, PEtOH, PMeOH, PS and DGTS were significantly higher in tumor tissues than in paracancerous tissues. In total, 12.3% (25/197) of genes related to lipid metabolism were differentially expressed between tumor tissues and adjacent paracancerous tissues. Six DEGs correlated with overall survival in univariate Cox regression analysis ( P < 0.05), and a 4-gene signature model was developed to divide patients into two risk groups, with patients in the high-risk group having significantly lower overall survival than those in the low-risk group ( P < 0.05). ROC curve analysis confirmed the predictive power of the model. CONCLUSION This novel model comprising 4 lipid metabolism-related genes might assist clinicians in the prognostic evaluation of patients with pancreatic cancer.

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“…Patients with high CD36 expression have lower overall survival, and the use of anti-CD36 strategies could represent a promising therapeutic approach. Recently, a clinical investigation using liquid chromatography tandem mass spectrometry (LC-MS/MS) revealed that differences in lipidomics may be potential biomarkers for early diagnosis of pancreatic cancer [ 13 ]. It was found that free fatty acids (FFAs) were significantly decreased in patients with pancreatic cancer.…”

Section: Altered Fatty Acid Metabolismmentioning

confidence: 99%

Pancreatic cancer and adaptive metabolism in a nutrient-deficient environment

Słotwiński¹,

Słotwińska²

2021

cejoi

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Despite tremendous progress in the treatment of many cancer types, leading to a significant increase in survival, pancreatic ductal adenocarcinoma (PDAC) is still burdened with high mortality rates (5-year survival rate < 9%) due to late diagnosis, aggressiveness, and a lack of more effective treatment methods. Early diagnosis and new therapeutic approaches based on the adaptive metabolism of the tumor in a nutrient-deficient environment are expected to improve the future treatment of PDAC patients. It was found that blocking selected metabolic pathways related to the local adaptive metabolic activity of pancreatic cancer cells, improving nutrient acquisition and metabolic crosstalk within the microenvironment to sustain proliferation, may inhibit cancer development, increase cancer cell death, and increase sensitivity to other forms of treatment (e.g., chemotherapy). The present review highlights selected metabolic signaling pathways and their regulators aimed at inhibiting the neoplastic process. Particular attention is paid to the adaptive metabolism of pancreatic cancer, including fatty acids, autophagy, macropinocytosis, and deregulated cell-surface glycoproteins, which promotes cancer cell development in an oxygen-deficient and nutrient-poor environment.

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Differences in lipidomics may be potential biomarkers for early diagnosis of pancreatic cancer

Abstract: Intellectual, scientific, conception and design of the study; acquisition, analysis and interpretation of data; technical procedures; statistical analysis; manuscript preparation, final approval.

Cited by 10 publications

References 29 publications

The Lipid Metabolites Profile in Patients with Pancreatic Cancer: A Controlled Study of Cancer Tissue Versus Matched Para-Cancer Tissue

The Lipid Metabolites Profile in Patients with Pancreatic Cancer: A Controlled Study of Cancer Tissue Versus Matched Para-Cancer Tissue

Development of a lipid metabolism-related gene model to predict prognosis in patients with pancreatic cancer

Pancreatic cancer and adaptive metabolism in a nutrient-deficient environment

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