Dataset Information

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia.

ABSTRACT: Acute Leukaemia (AL) is a neoplasm of WBCs (white blood cells). Being an important class of metabolites, alteration in free fatty acids (FFAs) levels play a key role in cancer development and progression. As they involve in cell signaling, maintain membrane integrity, regulate homeostasis and effect cell and tissue functions. Considering this fact, a comprehensive analysis of FFAs was conducted to monitor their alteration in AL, pre-leukaemic diseases and healthy control. Fifteen FFAs were analyzed in 179 serum samples of myelodysplastic syndrome (MDS), aplastic anemia (APA), acute lymphoblastic leukaemia (ALL), acute myeloid leukaemia (AML) and healthy control using gas chromatography-multiple reaction monitoring-mass spectrometry (GC-MRM-MS). A multivariate statistical method of random forest (RF) was employed for chemometric analysis. Serum level of two FFAs including C18:0 and C14:0 were found discriminative among all five groups, and between ALL and AML, respectively. Moreover, C14:0 was identified as differentiated FFAs for systematic progression of pre-leukaemic conditions towards AML. C16:0 came as discriminated FFAs between APA and MDS/AML. Over all it was identified that FFAs profile not only become altered in leukaemia but also in pre-leukaemic diseases.

SUBMITTER: Khalid A

PROVIDER: S-EPMC6173776 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia.

Khalid Ayesha A Siddiqui Amna Jabbar AJ Huang Jian-Hua JH Shamsi Tahir T Musharraf Syed Ghulam SG

Scientific reports 20181005 1

Acute Leukaemia (AL) is a neoplasm of WBCs (white blood cells). Being an important class of metabolites, alteration in free fatty acids (FFAs) levels play a key role in cancer development and progression. As they involve in cell signaling, maintain membrane integrity, regulate homeostasis and effect cell and tissue functions. Considering this fact, a comprehensive analysis of FFAs was conducted to monitor their alteration in AL, pre-leukaemic diseases and healthy control. Fifteen FFAs were analy ...[more]

PMID: 30291286

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Project description:BackgroundLung cancer (LC) is the deadliest cancer, with earlier stage patients having a better opportunity of long-term survival. The goal of this study is to screen less-invasive and efficient biomarkers for early detection of non-small cell LC (NSCLC).Material and methodsWe performed the simultaneous quantitative detection of six serum unsaturated free fatty acids (FFAs, C16:1, C18:3, C18:2, C18:1, C20:4, and C22:6) from 317 healthy controls, 78 patients with benign lung diseases (BLD), and 202 patients with NSCLC using chip-based direct-infusion nanoelectrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (CBDInanoESI-FTICR MS) in the negative ion mode. Multiple point internal standard calibration curves between the concentration ratios of individual fatty acids to internal standards (ISs, C17:1 as IS of C16:1, C18:3, C18:2, and C18:1 and C21:0 as IS of C20:4 and C22:6) and their corresponding intensity ratios were constructed, with correlation coefficient of > 0.99. Mann-Whitney U test was employed to compare the differences in the levels of the FFAs between the patients and healthy controls.ResultsSignificantly decreased levels of the FFAs in NSCLC patients were observed compared with healthy controls and BLD patients. Receiver operating characteristic curve analysis indicated that a combination of C16:1, C18:1, C18:3, C18:2, C20:4, and C22:6 could excellently differentiate patients with early-stage NSCLC from healthy controls plus BLD patients, with an AUC value of 0.933, a sensitivity of 84.2%, and a specificity of 89.1%. In addition, a biomarker panel (C16:1 and C18:1) was also confirmed preliminarily to monitor disease progression in NSCLC patients treated with icotinib, with a lead time between 8 and 48 weeks relative to clinical medical imaging.ConclusionA combination of C16:1, C18:1, C18:3, C18:2, C20:4, and C22:6 may be a powerful biomarker panel for the early detection of NSCLC and a combination of C16:1 and C18:1for disease progression monitoring of NSCLC.

Project description:Autoimmune diseases (ADs) are rapidly increasing worldwide and accumulating data support a key role of disrupted metabolism in ADs. This study aimed to identify an improved combination of Total Fatty Acids (TFAs) biomarkers as a predictive factor for the presence of autoimmune diseases. A retrospective nested case-control study was conducted in 403 individuals. In the case group, 240 patients diagnosed with rheumatoid arthritis, thyroid disease, multiple sclerosis, vitiligo, psoriasis, inflammatory bowel disease, and other AD were included and compared to 163 healthy individuals. Targeted metabolomic analysis of serum TFAs was performed using GC-MS, and 28 variables were used as input for the predictive models. The primary analysis identified 12 variables that were statistically significantly different between the two groups, and metabolite-metabolite correlation analysis revealed 653 significant correlation coefficients with 90% level of significance (p < 0.05). Three predictive models were developed, namely (a) a logistic regression based on Principal Component Analysis (PCA), (b) a straightforward logistic regression model and (c) an Artificial Neural Network (ANN) model. PCA and straightforward logistic regression analysis, indicated reasonably well adequacy (74.7 and 78.9%, respectively). For the ANN, a model using two hidden layers and 11 variables was developed, resulting in 76.2% total predictive accuracy. The models identified important biomarkers: lauric acid (C12:0), myristic acid (C14:0), stearic acid (C18:0), lignoceric acid (C24:0), palmitic acid (C16:0) and heptadecanoic acid (C17:0) among saturated fatty acids, Cis-10-pentadecanoic acid (C15:1), Cis-11-eicosenoic acid (C20:1n9), and erucic acid (C22:1n9) among monounsaturated fatty acids and the Gamma-linolenic acid (C18:3n6) polyunsaturated fatty acid. The metabolic pathways of the candidate biomarkers are discussed in relation to ADs. The findings indicate that the metabolic profile of serum TFAs is associated with the presence of ADs and can be an adjunct tool for the early diagnosis of ADs.

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Dataset Information

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia.

Publications

Alteration of Serum Free Fatty Acids are Indicators for Progression of Pre-leukaemia Diseases to Leukaemia.

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