Background/Objectives: Endometrial cancer (EC) is the most prevalent gynecological malignancy in developed countries, yet no clinically validated noninvasive screening biomarker exists. Fatty acid metabolic reprogramming is a hallmark of cancer that produces measurable changes in systemic free fatty acid (FFA) profiles. We aimed to identify serum FFAs altered in EC and evaluate their potential as early diagnostic biomarkers. Methods: Gene expression of fatty acid metabolic enzymes in EC tissues was assessed using public databases. Serum levels of 19 FFAs were quantified by gas chromatography–mass spectrometry in 72 patients with EC and 84 healthy donors. A two-variable diagnostic model was constructed using logistic regression and validated in an independent dataset. Results: Multiple fatty acid metabolic enzymes involved in de novo synthesis were upregulated in EC tissues as early as stage I, while enzymes mediating fatty acid uptake and release were downregulated. Serum levels of palmitoleic acid, oleic acid and dihomo-γ-linolenic acid were significantly elevated, whereas arachidic acid and arachidonic acid were significantly decreased in patients with EC from stage I onward. A diagnostic model combining palmitoleic acid and arachidonic acid achieved an area under the receiver operating characteristic curve of 0.9674, with a sensitivity of 91.3% and specificity of 96.4% in the validation dataset, including for stage I disease, and was independent of body mass index, age, metastasis status, and family history. Conclusions: Serum FFA profiling represents a promising noninvasive strategy for early EC detection, with the potential to complement existing diagnostic methods.

Background/Objectives: Cervical cancer (CC) is usually caused by high-risk human papillomavirus (hrHPV); however, some hrHPV-negative cases are undetectable by current screening programs. We evaluated a previously established diagnostic model based on serum free fatty acids (FFAs) in an independent cohort including hrHPV-negative CC. Methods: We analyzed serum FFAs from 101 patients with CC (16 hrHPV-negative), 60 healthy donors, and 16 patients with benign gynecological diseases, none of whom were included in the previous study, and gene expression levels of fatty acid metabolism-related enzymes in 64 surgical CC and five normal cervix samples. Results: Levels of nine FFAs differed between CC and the non-cancer groups but not between hrHPV-negative and hrHPV-positive CC. Gene expression levels of acetyl-CoA carboxylase 1, fatty acid synthase, stearoyl-CoA desaturase 1, and monoacylglycerol lipase were increased in CC compared with normal tissues, with no significant differences between hrHPV-negative and hrHPV-positive CC. The previous model (diagnostic index = −5.631 + 0.030 × (stearic acid) + 9.188 × (dihomo-γ-linolenic acid)) distinguished CC from the non-cancer groups (area under the curve, 0.969). At the pre-specified cut-off value, sensitivity was 97.0% (hrHPV-negative CC, 93.8%) and specificity in healthy donors was 58.3%; at the cut-off value derived in this cohort, these were 82.2% (93.8%) and 98.3%, respectively. In hrHPV-negative CC, the positivity rate exceeded those of squamous cell carcinoma antigen, carcinoembryonic antigen, and CA125. Conclusions: The serum-FFA-based diagnostic model detected CC, including hrHPV-negative cases, in an independent cohort. With calibration of the cut-off value, this approach may complement existing HPV-based testing.