Shared Plasma Fatty Acid Profiles in Four Cancer Types Enable Diagnosis and Discrimination of Gastrointestinal and Lung Cancers

<b>Background:</b> Cancer is a leading cause of mortality worldwide, characterized by metabolic reprogramming, including alterations in fatty acid (FA) metabolism. Plasma FA profiles hold promise as non-invasive biomarkers for the diagnosis and classification of cancer. <b>Objectives:</b> This study aimed to investigate the diagnostic potential of plasma FA profiles across four major cancers and to identify shared and cancer-type-specific metabolic alterations. <b>Methods:</b> We examine comprehensive FA profiling of plasma samples from 368 individuals, including patients with colorectal (CRC, n = 94), gastric (GC, n = 55), esophageal (EC, n = 53), and lung cancer (LC, n = 73), alongside 93 healthy controls (HCs) by gas chromatography-mass spectrometry. Data were analyzed using univariate statistics and multivariate modeling analysis. <b>Results:</b> Univariate analysis showed a shared set of altered FAs across the cancer types, demonstrating a shared pan-cancer metabolic shift. A comprehensive comparison revealed a remarkable shared pattern within the gastrointestinal (GI) cancers (GC, CRC, EC), while LC showed opposite trends for most FAs. Partial Least Squares Discriminant Analysis (PLS-DA) models on a 70% training set excellently discriminated each cancer type from HCs. The cross-validation of the model demonstrated robust internal performance with Q<sup>2</sup> = 0.675 (LC), 0.559 (GC), 0.774 (CRC), and 0.628 (EC). This is followed by assessing the diagnostic accuracy on a 30% hold-out test set, with area under the curve (AUC) values of 0.686 (LC), 0.926 (GC), 0.905 (CRC), and 0.843 (EC). <b>Conclusions:</b> Plasma FA profiles may provide a potential source of biomarkers, capturing both shared cancer markers and distinct tissue-specific metabolic alterations. These findings highlight the high diagnostic and classificatory potential of FAs alterations in oncology.

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Journal
Metabolites
Published
2026-02-12
DOI
https://doi.org/10.3390/metabo16020128
Primary Topic
Cancer, Lipids, and Metabolism
Type
article
Field-Weighted Citation Impact
0.00
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article

Shared Plasma Fatty Acid Profiles in Four Cancer Types Enable Diagnosis and Discrimination of Gastrointestinal and Lung Cancers

Li Xie, Ahad Hussain, Yan Yan, Xuejun Kang et al.
Metabolites
Cancer, Lipids, and Metabolism
article

Shared Plasma Fatty Acid Profiles in Four Cancer Types Enable Diagnosis and Discrimination of Gastrointestinal and Lung Cancers

Li Xie, Ahad Hussain, Yan Yan, Xuejun Kang, Kangwe Shen
article en

Abstract

<b>Background:</b> Cancer is a leading cause of mortality worldwide, characterized by metabolic reprogramming, including alterations in fatty acid (FA) metabolism. Plasma FA profiles hold promise as non-invasive biomarkers for the diagnosis and classification of cancer. <b>Objectives:</b> This study aimed to investigate the diagnostic potential of plasma FA profiles across four major cancers and to identify shared and cancer-type-specific metabolic alterations. <b>Methods:</b> We examine comprehensive FA profiling of plasma samples from 368 individuals, including patients with colorectal (CRC, n = 94), gastric (GC, n = 55), esophageal (EC, n = 53), and lung cancer (LC, n = 73), alongside 93 healthy controls (HCs) by gas chromatography-mass spectrometry. Data were analyzed using univariate statistics and multivariate modeling analysis. <b>Results:</b> Univariate analysis showed a shared set of altered FAs across the cancer types, demonstrating a shared pan-cancer metabolic shift. A comprehensive comparison revealed a remarkable shared pattern within the gastrointestinal (GI) cancers (GC, CRC, EC), while LC showed opposite trends for most FAs. Partial Least Squares Discriminant Analysis (PLS-DA) models on a 70% training set excellently discriminated each cancer type from HCs. The cross-validation of the model demonstrated robust internal performance with Q<sup>2</sup> = 0.675 (LC), 0.559 (GC), 0.774 (CRC), and 0.628 (EC). This is followed by assessing the diagnostic accuracy on a 30% hold-out test set, with area under the curve (AUC) values of 0.686 (LC), 0.926 (GC), 0.905 (CRC), and 0.843 (EC). <b>Conclusions:</b> Plasma FA profiles may provide a potential source of biomarkers, capturing both shared cancer markers and distinct tissue-specific metabolic alterations. These findings highlight the high diagnostic and classificatory potential of FAs alterations in oncology.

MetabolitesVol. 16(2)
Ministry of Education (CL), Jinling Institute of Technology (CN), Southeast University (CN)
Reduced inequalities
Openalex Percentile: Top 59%
Cancer, Lipids, and Metabolism
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