From Lipids to Leads: How Metabolomics Turns Fatty Acids into Therapeutic Targets

Lipids transcend their role as simple energy reservoirs; they dynamically construct cell membranes, precisely modulate signaling cascades, and potentially influence gene expression. Dysregulated lipid metabolism—including aberrant fatty acid synthesis or oxidation—acts as a pivotal mechanism driving pathogenesis in malignancies, metabolic syndromes, and neurodegenerative conditions. Nevertheless, translating lipid pathways into viable therapeutic targets has been historically impeded by intricate molecular architectures and biological dynamism. Metabolomics now catalyzes a paradigm shift: by comprehensively deciphering lipid networks, fatty acid biochemistry is being transformed into tangible targets for disease intervention.

The Metabolomic Revolution: Advancing from Lipid Chemistry to Systems Medicine

Conventional lipid profiling suffers from limited throughput and structural gaps. Modern metabolomics overcomes these constraints via three key technological advances, enabling comprehensive lipidome characterization:

1. Enhanced Analytical Resolution

• High-resolution mass spectrometry (HRMS) coupled with multidimensional separation achieves unprecedented specificity. Platforms like Orbitrap/Q-TOF deliver mass accuracy below 1 ppm, resolving challenging isomers (e.g., distinguishing PC 16:0/18:1 from PC 18:1/16:0).
• Ion mobility spectrometry (IM-MS) introduces conformational separation, accurately resolving spatial configurations like cis-trans isomerism and branched-chain fatty acids.
• Multidimensional chromatography (RP-LC × HILIC) significantly broadens polar lipid coverage, enabling precise quantitation of signaling lipids including sphingolipids and lysophospholipids.

2. Intelligent Data Processing Frameworks

• Automated Lipid Annotation: Leverages authoritative databases (e.g., LIPID MAPS, HMDB) for high-confidence identification of thousands of lipids based on fragment ion matching.
• Machine Learning-Driven Biomarker Discovery: Employs algorithms like Random Forest to prioritize disease-relevant lipid markers (e.g., VIP scores >1.5 identify C24:0-lysophosphatidylethanolamine in colon cancer).
• Network Medicine Integration: Constructs lipid-protein interaction networks to pinpoint regulatory hubs, such as sphingosine's central role in aging pathways.

3. Spatial Metabolomics Expansion

• Mass spectrometry imaging (MSI) integrated with cryosectioning visualizes lipid heterogeneity within tissue microenvironments. For instance, breast cancer studies reveal arachidonic acid (AA) enrichment in peritumoral fibroblasts and lipid-abundant stromal cells, suggesting their paracrine role in promoting malignancy.

Therapeutic Translation of Fatty Acid Targets: From Metabolic Dysregulation to Precision Intervention

(a) Fatty Acid Synthesis: The Oncogenic "Lipid Factory"

ACLY/ACC/FASN axis: Cancer cells exhibit a critical dependency on Fatty Acid Synthase (FAS) for rapid proliferation. Synthesized fatty acids serve dual purposes: as fundamental constituents of cellular membranes and as stored energy reserves within triglycerides. Furthermore, derivatives like prostaglandins fuel tumor-promoting signaling cascades and influence growth via post-translational modifications, notably RAS palmitoylation. To fuel FAS, malignancies co-opt metabolic flux through glycolysis → citric acid cycle → acetyl-CoA production, accompanied by consistent overexpression of key pathway enzymes (e.g., ACLY, ACC, FASN) across diverse cancers.

Key Targets and Therapeutic Strategies:

• ACLY (ATP Citrate Lyase): Overexpressed in lung and breast cancers; its suppression attenuates tumor growth.
• ACC (Acetyl-CoA Carboxylase): Exhibits context-dependent duality – inhibition impedes progression in malignancies like prostate cancer but may paradoxically enhance breast cancer metastasis.
• FASN (Fatty Acid Synthase): Inhibitors (e.g., TVB-2640) are undergoing clinical evaluation (e.g., in HER2+ breast cancer), necessitating careful assessment of potential pro-metastatic risks.

Consequently, the fatty acid synthesis cascade (from citrate via ACLY to FASN) plays an ambivalent role in oncology—acting both as a driver of tumorigenesis and a source of actionable therapeutic targets (Park JK et al., 2021).

Factors that can contribute to spatial and temporal heterogeneity in cancer cell lipid metabolism (Park JK et al., 2021).

Sterol regulatory element binding protein (SREBP) : As an SREBP inhibitor, Fatostatin significantly reduces tumor growth in melanoma (B16), colon (MC38), and lung cancer (LLC) murine models by disrupting SREBP-dependent cholesterol biosynthesis. This inhibition triggers two interconnected immunometabolic effects: reduced cholesterol accumulation with associated endoplasmic reticulum stress (via the XBP-1 pathway), and impaired immunosuppressive function of regulatory T (Treg) cells. Concurrently, Fatostatin alleviates CD8⁺ T cell exhaustion, enhancing their antitumor activity within the tumor microenvironment (TME).

Immune Dependence Validation

The attenuated efficacy of Fatostatin observed in immunodeficient nude mice confirms its anti-tumor effects require functional T-cell immunity.

Clinical Translation

Targeting the SREBP2-cholesterol axis represents a promising strategy to potentiate immunotherapy, particularly in combination with PD-1 blockade. Thus, Fatostatin demonstrates dual therapeutic mechanisms—direct tumor suppression coupled with immunomodulation (Zhu L et al., 2024).

(b) fatty acid oxidation (FAO) : energy hijacking and drug resistance fortress

OxFA: Diabetic patients exhibit markedly reduced HDL antioxidant capacity relative to nondiabetic controls, despite comparable circulating HDL-C levels and cholesterol efflux function. Significantly elevated oxidized fatty acid (OXFA) content was detected within diabetic HDL particles, demonstrating a strong positive correlation with endothelial oxidation indices.

Functional Validation

• Experimental introduction of OXFA compounds directly impairs HDL's antioxidant properties in healthy subjects.
• Treatment with the apolipoprotein A-I mimetic peptide D-4F effectively restores antioxidant functionality in diabetic HDL.

This evidence establishes that OXFA accumulation within HDL directly drives its impaired antioxidant activity in diabetes, identifying OXFA as a key mediator of HDL dysfunction.

Therapeutic Implication: Targeting OXFA clearance mechanisms within HDL—exemplified by D-4F peptide therapy—represents a novel therapeutic approach to enhance vascular endothelial protection in diabetic patients (Feng J et al., 2022).

The effects of oxidized fatty acids and D-4F on the antioxidant functions of HDLs (Feng J et al., 2022)

Et electron transport chain: The functional role of hepatocyte-derived immunoglobulin kappa light chain (Igκ) in hepatocellular carcinoma (HCC) pathogenesis remains poorly defined. Multi-omics analyses revealed that Igκ deletion dysregulates genes involved in cholesterol metabolism, cytochrome P450 pathways, and amino acid processing.

Proteomic & Metabolomic Impact

• Igκ ablation upregulated 359 proteins (e.g., mitochondrial electron transport chain subunit CYCS) and downregulated 117 proteins (e.g., sterol carrier protein SCP2).
• Significant perturbations occurred in glycerophospholipid metabolism, with 27 metabolites elevated (including lipid precursors) and 13 reduced.

Mechanistic Insights

• Mitochondrial Function: Igκ stabilizes ETFA—a core electron transport chain component—thereby enhancing fatty acid oxidation (FAO) and reducing intracellular lipid deposition.
• Lipid Homeostasis: Igκ deficiency triggers tumor cell accumulation of triglycerides (TG) and free fatty acids (FFA), suppressing HCC proliferation and migration. Consistent with this, Igκ-knockdown HCC mouse models exhibited elevated tumor lipid content and reduced mitochondrial complex III/IV expression (UQCRC2, COX I).

Conclusion & Translational Significance

Igκ fuels HCC progression by preserving ETFA stability → promoting FAO → attenuating lipotoxicity, establishing its role as a critical metabolic checkpoint. Therapeutic targeting of the Igκ-ETFA-FAO axis represents a novel strategy to disrupt HCC metabolic reprogramming (Guo J et al., 2024).

Hepatocyte-derived Igκ promotes HCC progression by stabilizing ETFA to facilitate fatty acid β-oxidation (Guo J et al., 2024).

(c) ω-6/Ω-3 Balance: an early switch in metabolic programming

Early life lipid exposure: Clinical studies indicate that an elevated dietary omega-6 (N6) to omega-3 (N3) fatty acid ratio during the perinatal period (pregnancy/lactation) correlates with increased childhood obesity risk. Using murine models, we demonstrate how perinatal N6-FA overexposure programs adipose-derived stem cells (ASCs) toward adipogenic differentiation, establishing obesity predisposition. Mechanistically, N6-FA suppresses the nuclear receptor NR2F2 in ASCs; NR2F2 deletion phenocopies N6-FA's pro-obesity effects (e.g., reduced FAO).

NR2F2's Restorative Role

Pharmacological activation of NR2F2 rescues PPARγ-PGC1α axis function, enhancing mitochondrial fatty acid oxidation (evidenced by elevated CPT1A, ATP5 synthase activity).

Experimental Validation

• In Vivo: Adipocytes differentiated from N6-FA-exposed ASCs exhibited significantly impaired oxidation of ¹³C-palmitate.
• In Vitro: Transient NR2F2 activation reverses N6-FA-induced metabolic suppression in ASCs and restores mitochondrial function.

Thus, early-life N6-FA excess promotes childhood obesity by inhibiting NR2F2, reprogramming metabolism toward energy storage over oxidative capacity.

Therapeutic Implications

Targeting NR2F2 signaling (via agonist compounds or N3-FA supplementation) represents a potential strategy to counteract this adverse metabolic programming (Das S et al., 2024).

Effects of N6-FA exposure on ASC and how it affects adipocyte metabolism (Das S et al., 2024)

Intervention strategy: Pups exposed to high omega-6 fatty acid (N6-FA) levels exhibited reduced whole-body oxidation of ¹³C-palmitate, diminished energy expenditure, and elevated triglyceride (TAG) deposition in inguinal adipose tissue. NR2F2's centrality was demonstrated through two complementary approaches:

• Genetic Ablation: NR2F2 knockout in adipose stem cells (ASCs) fully recapitulated the N6-FA exposure phenotype, characterized by impaired beige adipogenesis and lipid accumulation.
• Pharmacological Activation: Treatment with the ligand 1-deoxysphingosine (1-DSO) restored beige fat gene signatures, augmented mitochondrial oxidative function, and suppressed adipocyte formation.

Conclusion & Significance

NR2F2 acts as a molecular switch governing ASC fate: its expression level directs differentiation toward either energy-storing (obesity-susceptible) white adipocytes or thermogenic beige adipocytes.

Therapeutic Potential

Targeted NR2F2 activation (e.g., via 1-DSO) represents a novel preventive strategy against childhood obesity by counteracting the metabolic consequences of early-life N6-FA overexposure (Das S et al., 2025).

Mitochondrial oxidative pathways are absent and adipogenic pathways are increased in adipocytes from NR2F2-LOW ASCS (Das S et al., 2025)

Clinical Translation: Bridging Laboratory Discovery to Therapeutic Application

Case 1: Lipid Metabolism-Driven Classification Guides Precision Therapy in Breast Cancer

Lipogenic Subtype (HR+):

• Core Pathology: Cancer cells depend on Fatty Acid Synthase (FASN) to overproduce membrane lipids and signaling molecules, driving proliferation/metastasis.
• Clinical Correlates: Elevated FASN correlates with HER2 positivity, advanced stage, poor prognosis, and heightened metastasis (notably cerebral).
• Therapeutic Resistance: Promotes chemotherapy and endocrine therapy resistance.
• Intervention: FASN inhibitors (e.g., TVB-2640) suppress tumors and restore chemosensitivity. Synergy observed with immunotherapy/targeted agents.

Fatty Acid Oxidation (FAO)-Dependent Subtype (TNBC):

• Metabolic Adaptation: FAO catabolizes long-chain fatty acids to acetyl-CoA → ATP (via TCA/ETC) + NADPH (antioxidant defense), enabling survival under nutrient stress (e.g., nodal metastases).
• Resistance Mechanisms:
  • ER+: Tamoxifen resistance via c-Jun/CPT1A axis
  • TNBC: Chemoresistance via STAT3/CPT1B pathway
• Targeting Strategy: CPT1 inhibitors (e.g., etomoxir) show efficacy in MYC-amplified TNBC. Combining FAO blockade with chemo/endocrine therapy reverses resistance.

Microenvironment-Driven Immunosuppression:

• TAM Reprogramming: Tumor-associated macrophages (TAMs) utilize FAO/lipid uptake to adopt immunosuppressive states.
• Pro-Tumor Mechanisms:
  • Lipid Storage: FABP4-mediated lipid accumulation inhibits T-cell activity (e.g., CXCL12-CXCR4 axis suppression)
  • Cholesterol Dysregulation: SREBP2-driven synthesis fuels tumor proliferation
  • Inflammatory Signaling: Prostaglandins (e.g., PGE2) activate MDSCs and impair CD8⁺ T/NK cells
• Metabolic Checkpoint Inhibition:
  • Target TAMs via CPT1 inhibitors or SREBP2 antagonists
  • Neutralize PGE2 to restore antitumor immunity
  • Combine FABP4 inhibitors with PD-1/CTLA-4 blockade (Wan M et al., 2025)

Lipid-targeted therapy in BC (Wan M et al., 2025)

Case 2: Lipid Metabolic Profiling and Therapeutic Opportunities in Clear Cell Renal Cell Carcinoma (CCRCC)

Aberrant Lipid Metabolism as a Core Pathological Driver

Accumulation of lipid droplets represents a defining pathological hallmark of CCRCC, strongly linked to tumor initiation, progression, and adverse clinical outcomes. Key metabolic alterations include:

• Fatty Acid Sourcing: Dual reliance on exogenous acquisition (mediated by CD36) and de novo synthesis (via FASN, ACLY, ACC)
• Metabolic Imbalance: Upregulation of enzymes like SCD1 (monounsaturated fatty acid production) and CPT1A (suppressed fatty acid oxidation) promotes lipid storage over catabolism
• Cholesterol Paradox: CCRCC exhibits suppressed endogenous cholesterol synthesis while depending on exogenous uptake to meet cellular demands

Clinical Translation: Biomarkers and Targeted Interventions

• Prognostic Indicators:
  • Elevated FASN and SCD1 expression correlates with reduced survival
  • Adipokine Signatures:
    • Adiponectin: Lower circulating levels associate with increased CCRCC risk and poor prognosis (potentially indicating metabolic dysregulation rather than direct carcinogenesis)
    • Chemerin: Promotes lipid droplet formation and HIF signaling, demonstrating positive correlation with tumor advancement and potential as a circulating biomarker
    • Serum Lipidomics: Specific species like very-long-chain fatty acids (VLCFAs) show promise as immunotherapy response predictors, requiring further validation

Therapeutic Avenues:

• Metabolic Enzyme Inhibition: Targeting FASN, SCD1, or CPT1A suppresses tumor growth (e.g., Belzutifan indirectly modulates HIF2α-downstream metabolism)
• Immunometabolic Modulation: ChemR23 antagonists may counteract immunosuppressive microenvironments and potentiate checkpoint inhibitor efficacy (Tan SK et al., 2023).

Fatty acid metabolism pathways in clear-cell renal cell carcinoma and potential therapeutic targets (Tan SK et al., 2023)

Case 3: Lipid Metabolic Networks Driving Gastric Cancer (GC) Progression

Lipid Synthesis Pathways:

• ACLY (citrate → acetyl-CoA) and ACC (acetyl-CoA → malonyl-CoA) provide substrates for FASN, facilitating fatty acid synthesis including palmitate (PA)
• SCD1 converts saturated to monounsaturated FAs (MUFAs), maintaining cancer stemness via Hippo/YAP signaling and conferring chemotherapy resistance

Fatty Acid Catabolism:

• CPT1-mediated fatty acid oxidation (FAO) generates NADPH/ATP to meet GC bioenergetic demands

Master Regulatory Hub:

• SREBP1 transcriptionally controls ACLY, ACC, FASN, and SCD1 – modulated by HIF-1α and natural agents (e.g., oregano essential oil)

Clinical Correlates & Therapeutic Opportunities

• Prognostic Biomarkers:
  Tumor Progression Markers:
  • Elevated ACLY, ACSL4/5, SCD1, FABP1/6, CPT1A
  • Poor Survival Predictors:
    • High ACSS3, CD36, FABP3/4/8, CPT1C expression

Intervention Strategies:

• Targeted Inhibition: FASN/SCD1 inhibitors (e.g., A939572) or CPT1 antagonists (e.g., etomoxir) suppress tumor growth and chemosensitize GC
• Combination Therapy: Norbergenin downregulates ACC/FASN or synergizes with immunotherapy (Li C et al., 2022).

Fatty acid metabolism in GC (Li C et al., 2022)

Challenges and Future Directions: Advancing Lipidomics

Persisting Technological Limitations:

• Absolute quantification of lipid isomers remains dependent on reference standards
• Single-cell lipidomics faces sensitivity constraints (current minimum: ~100-cell samples)

Clinical Translation Complexities:

• Tumor lipid metabolism's dynamic spatiotemporal nature necessitates developing in vivo real-time monitoring technologies
• Microenvironmental lipid exchange networks (e.g., cancer-fibroblast-immune cell crosstalk) require comprehensive mapping

Next-Generation Solutions:

• AI-Driven Innovation: AlphaFold3 enables prediction of lipid-protein interaction interfaces to accelerate targeted inhibitor development
• Synthetic Biology Approaches: Reprogramming plant lipid biosynthesis pathways (e.g., high-value lipid production from kiwifruit (Actinidia arguta) seeds)
• Multi-Omics Integration: Closed-loop analysis combining genomic data (e.g., PPARγ mutations), lipidomic profiles, and clinical phenotypes to enable precision targeting

Conclusion: Dawn of the Lipid Metabolomics Era

Deciphering therapeutic targets within lipid chemical diversity fundamentally translates cellular metabolic language into precision medicine's codebook. Beyond revealing fatty acids' paradoxical functions in pathology—acting as both disease culprits and therapeutic saviors—metabolomics has validated the clinical translatability of lipid-centric targets (e.g., Igκ/ETFA, CPT1A, NR2F2) through successful therapeutic development. The convergence of spatial multi-omics and artificial intelligence now elevates lipid metabolic reprogramming from mere biomarker status to a prolific wellspring for next-generation therapeutics.

For more on the role of Fatty Acidomics in drug discovery see "How Fatty Acid Metabolomics Can Accelerate Your Drug Discovery Pipeline".

The application of fatty acids in microbial research can be consulted "Applications of Fatty Acids Profiling in Microbiome Research".

People Also Ask

Which of the following metabolomics databases is used for biomarker discovery?

The Human Metabolome Database (HMDB) is a freely available database containing detailed information about small molecule metabolites found in the human body.

What is metabolomics for drug discovery?

Discovery metabolomics primarily provides relative or semiquantitative measurements of metabolites.

What are the 7 types of biomarkers?

BEST defines seven biomarker categories: susceptibility/risk, diagnostic, monitoring, prognostic, predictive, pharmacodynamic/response, and safety.

References

1. Park JK, Coffey NJ, Limoges A, Le A. "The Heterogeneity of Lipid Metabolism in Cancer." Adv Exp Med Biol. 2021;1311:39-56. doi: 10.1007/978-3-030-65768-0_3
2. Zhu L, Shi Y, Feng Z, Yuan D, Guo S, Wang Y, Shen H, Li Y, Yan F, Wang Y. "Fatostatin promotes anti-tumor immunity by reducing SREBP2 mediated cholesterol metabolism in tumor-infiltrating T lymphocytes." Eur J Pharmacol. 2024 May 15;971:176519. doi: 10.1016/j.ejphar.2024.176519
3. Feng J, Wang Y, Li W, Zhao Y, Liu Y, Yao X, Liu S, Yu P, Li R. "High levels of oxidized fatty acids in HDL impair the antioxidant function of HDL in patients with diabetes." Front Endocrinol (Lausanne). 2022 Oct 20;13:993193. doi: 10.3389/fendo.2022.993193
4. Guo J, Gu H, Yin S, Yang J, Wang Q, Xu W, Wang Y, Zhang S, Liu X, Xian X, Qiu X, Huang J. "Hepatocyte-derived Igκ promotes HCC progression by stabilizing electron transfer flavoprotein subunit α to facilitate fatty acid β-oxidation." J Exp Clin Cancer Res. 2024 Oct 9;43(1):280. doi: 10.1186/s13046-024-03203-8
5. Das S, Varshney R, Farriester JW, Kyere-Davies G, Martinez AE, Hill K, Kinter M, Mullen GP, Nagareddy PR, Rudolph MC. "NR2F2 Reactivation in Early-life Adipocyte Stem-like Cells Rescues Adipocyte Mitochondrial Oxidation." bioRxiv [Preprint]. 2024 Sep 9:2024.09.09.611047. doi: 10.1101/2024.09.09.611047
6. Das S, Varshney RR, Farriester JW, Kyere-Davies G, Martinez AE, Hill KB, Kinter M, Mullen GP, Nagareddy PR, Rudolph MC. "Activating nuclear receptor subfamily 2 group F member 2 in adipocyte stem cells rescues beige adipocyte metabolism impaired by excess early-life omega-6 fatty acids." Clin Nutr. 2025 Jun 10;51:63-80. doi: 10.1016/j.clnu.2025.06.003
7. Wan M, Pan S, Shan B, Diao H, Jin H, Wang Z, Wang W, Han S, Liu W, He J, Zheng Z, Pan Y, Han X, Zhang J. "Lipid metabolic reprograming: the unsung hero in breast cancer progression and tumor microenvironment." Mol Cancer. 2025 Mar 3;24(1):61. doi: 10.1186/s12943-025-02258-1
8. Tan SK, Hougen HY, Merchan JR, Gonzalgo ML, Welford SM. "Fatty acid metabolism reprogramming in ccRCC: mechanisms and potential targets." Nat Rev Urol. 2023 Jan;20(1):48-60. doi: 10.1038/s41585-022-00654-6
9. Li C, Zhang L, Qiu Z, Deng W, Wang W. "Key Molecules of Fatty Acid Metabolism in Gastric Cancer." Biomolecules. 2022 May 15;12(5):706. doi: 10.3390/biom12050706