Lipidomic Signatures for Colorectal Cancer Diagnosis and Progression Using UPLC-QTOF-ESI+MS.

Claudiu Răchieriu,Dan Tudor Eniu,Mihai Adrian Socaciu,Florin Graur,Carmen Socaciu,Nadim Al Hajjar,Emil Moiş

doi:10.3390/biom11030417

Abstract

Metabolomics coupled with bioinformatics may identify relevant biomolecules such as putative biomarkers of specific metabolic pathways related to colorectal diagnosis, classification and prognosis. This study performed an integrated metabolomic profiling of blood serum from 25 colorectal cancer (CRC) cases previously classified (Stage I to IV) compared with 16 controls (disease-free, non-CRC patients), using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI+ MS). More than 400 metabolites were separated and identified, then all data were processed by the advanced Metaboanalyst 5.0 online software, using multi- and univariate analysis, including specificity/sensitivity relationships (area under the curve (AUC) values), enrichment and pathway analysis, identifying the specific pathways affected by cancer progression in the different stages. Several sub-classes of lipids including phosphatidylglycerols (phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and PAs), fatty acids and sterol esters as well as ceramides confirmed the “lipogenic phenotype” specific to CRC development, namely the upregulated lipogenesis associated with tumor progression. Both multivariate and univariate bioinformatics confirmed the relevance of some putative lipid biomarkers to be responsible for the altered metabolic pathways in colorectal cancer.

Highlights

Colorectal cancer (CRC) is an important public health issue, among the three leading causes of cancer-related mortality in both men and women, according to recent cancer statistics [1,2,3,4], in Western countries and in developing countries, and is strongly related to lifestyle, stress, food diet and habits.The early detection and endoscopic resection of adenomatous polyps and screening colonoscopy significantly improve the survival rate, being considered a gold standard for the detection of colorectal neoplasms, beside sigmoidoscopy, colon capsule endoscopy and magnetic resonance colonography
According to the principal component analysis (PCA) and partial least squares discriminant analysis (PLSDA) plots, the C group was less homogeneous than the colorectal cancer (CRC) group, two or three subgroups being visible in this group
To summarize the findings presented above, in relation to our results we can assume that in CRC, several classes of lipids including phosphatidylglycerols (PCs, phosphatidylethanolamines (PEs) and phosphatidic acids (PAs)), fatty acids and sterol esters, as well as ceramides, confirm the “lipogenic phenotype” for CRC development, dependent on lipogenesis and lipolysis, upregulated and associated with tumor progression

Summary

Introduction

Colorectal cancer (CRC) is an important public health issue, among the three leading causes of cancer-related mortality in both men and women, according to recent cancer statistics [1,2,3,4], in Western countries and in developing countries, and is strongly related to lifestyle, stress, food diet and habits.The early detection and endoscopic resection of adenomatous polyps (premalignant conditions) and screening colonoscopy significantly improve the survival rate, being considered a gold standard for the detection of colorectal neoplasms, beside sigmoidoscopy, colon capsule endoscopy and magnetic resonance colonography. The biopsy specimens of colorectal mucosa and colonic lesions are useful diagnosis procedures; all these techniques are invasive. This is the reason why scientists are more and more keen on using non-invasive techniques with good predictive value and high sensitivity such as metabolomics. Biomolecules 2021, 11, 417 radically, using omics technologies for finding diagnosis, stratification and prognosis biomarkers, as well as for treatment monitoring [5]. Metabolomics-based procedures using biofluids (especially blood serum or plasma) assure a systematic screening or fingerprinting of small metabolites (with less than 2000 Da) related to the metabolic signature and pathway alterations in different stages of CRC

Methods

Results

Discussion

Conclusion