
==== Front
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Sci Rep
Scientific Reports
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10.1038/s41598-024-71606-w
Article
Serum levels of stearic and dihomo-γ-linolenic acids can be used to diagnose cervical cancer and cervical intraepithelial neoplasia
http://orcid.org/0000-0002-7467-3377
Katoh Yuki kato.yuki@nihon-u.ac.jp
yukikatoh@keio.jp

12
Kubo Akiko 3
Hayashi Nobuki 4
Sugi Toshihiro 4
Katoh Kanoko 4
Udagawa Seiichi 5
Ogawa Tadashi 6
Iwata Takashi 2
Nishio Hiroshi 2
Sugawara Masaki 2
Hirai Shuichi 1
Kawana Kei 4
1 https://ror.org/05jk51a88 grid.260969.2 0000 0001 2149 8846 Division of Anatomical Science, Department of Functional Morphology, Nihon University School of Medicine, 30-1 Ohyaguchi-Kami-Cho, Itabashi-Ku, Tokyo, 173-8610 Japan
2 https://ror.org/02kn6nx58 grid.26091.3c 0000 0004 1936 9959 Department of Obstetrics and Gynecology, Keio University School of Medicine, 35 Shinano-Machi, Shinjuku-Ku, Tokyo, 160-8582 Japan
3 https://ror.org/03tgsfw79 grid.31432.37 0000 0001 1092 3077 Division of Dermatology, Department of Internal Related, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-Cho, Chuo-Ku, Kobe, Hyogo 650-0017 Japan
4 https://ror.org/05jk51a88 grid.260969.2 0000 0001 2149 8846 Department of Obstetrics and Gynecology, Nihon University School of Medicine, 30-1 Ohyaguchi-Kami-Cho, Itabashi-Ku, Tokyo, 173-8610 Japan
5 https://ror.org/05jk51a88 grid.260969.2 0000 0001 2149 8846 Mathematics Section, Division of Natural Sciences, Nihon University School of Medicine, 30-1 Ohyaguchi-Kami-Cho, Itabashi-Ku, Tokyo, 173-8610 Japan
6 https://ror.org/02h6cs343 grid.411234.1 0000 0001 0727 1557 Department of Legal Medicine, Aichi Medical University School of Medicine, 1-1 Yazakokarimata, Nagakute, Aichi 480-1195 Japan
6 9 2024
6 9 2024
2024
14 2083320 6 2024
29 8 2024
© The Author(s) 2024
2024
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Despite widespread cervical cancer (CC) screening programs, low participation has led to high morbidity and mortality rates, especially in developing countries. Because early-stage CC often has no symptoms, a non-invasive and convenient diagnostic method is needed to improve disease detection. In this study, we developed a new approach for differentiating both CC and cervical intraepithelial neoplasia (CIN)2/3, a precancerous lesion, from healthy individuals by exploring CC fatty acid metabolic reprogramming. Analysis of public datasets suggested that various fatty acid metabolizing enzymes were expressed at higher levels in CC tissues than in normal tissues. Correspondingly, 11 free fatty acids (FFAs) showed significantly different serum levels in CC patient samples compared with healthy donor samples. Nine of these 11 FFAs also displayed significant alterations in CIN2/3 patients. We then generated diagnostic models using combinations of these FFAs, with the optimal model including stearic and dihomo-γ-linolenic acids. Receiver operating characteristic curve analyses suggested that this diagnostic model could detect CC and CIN2/3 more accurately than using serum squamous cell carcinoma antigen level. In addition, the diagnostic model using FFAs was able to detect patients regardless of clinical stage or histological type. Overall, the serum FFA diagnostic model developed in this study could be a powerful new tool for the non-invasive early detection of CC and CIN2/3.

Keywords

Cervical cancer
Cervical intraepithelial neoplasia
Free fatty acids
Diagnostic biomarker
Liquid biopsy
Diagnostic model
Subject terms

Tumour biomarkers
Diagnostic markers
Cervical cancer
http://dx.doi.org/10.13039/501100001700 Ministry of Education, Culture, Sports, Science and Technology 21K15602 Katoh Yuki Takeda Science Foundation 2021Research Grant for Public Health Science (2024)The Japan Society of Gynecologic Oncology 2022Nihon University Research Grant for 2024issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Cervical cancer (CC) develops primarily through precancerous lesions, called cervical intraepithelial neoplasia (CIN), and is caused by persistent infection with high-risk human papillomavirus1. Despite the widespread implementation of screening programs, CC still has high incidence and mortality rates, especially in developing countries2–6. Low participation in these screening programs has led to their limited effectiveness, mainly because early-stage CC often has no clinical symptoms6. CC has a good prognosis when detected and treated at stage I, with a five-year survival rate of 81% to 96%7,8. Furthermore, CIN progression to CC can be prevented if it is detected and managed appropriately9. Conversely, the CC five-year survival rates for stages II, III, and IV are approximately 65% to 87%, 35% to 50%, and 15% to 20%, respectively, with a poor prognosis7,8,10. Therefore, a non-invasive and convenient diagnostic method, such as liquid biopsy, is needed to help identify CC in individuals not participating in the current screening programs.

Squamous cell carcinoma antigen (SCC-Ag) is widely accepted in current clinical practice as a tumor marker for cervical squamous cell carcinoma. However, SCC-Ag is not a sufficient indicator of early-stage CC or CIN8. Additionally, there is no specific tumor marker for cervical adenocarcinoma. Molecular markers, such as Keratin 4/1711,12, Annexin A213, and PTEN14, as well as certain microRNAs (miRNAs)15,16 and urinary DNA methylation17, have been reported as candidate diagnostic markers for CC. However, these markers have not yet been used in clinical practice, nor has any validation study been conducted to demonstrate their ability to decrease CC patient morbidity and mortality rates. Therefore, there is an urgent need to develop new non-invasive, convenient, and highly sensitive early diagnostic technologies to improve the prognosis of CC patients.

Cancer cells can reprogram their metabolic pathways to favor their own survival. Many studies have examined cancer cell-specific glucose and amino acid metabolism, which have been applied to therapeutics and diagnostics18–21. We have previously demonstrated that lung and ovarian cancers can also reprogram their fatty acid metabolic systems22,23. Furthermore, we reported that the composition of serum free fatty acids (FFAs) in ovarian cancer is significantly altered from early-stage because of this reprogramming23. Interestingly, the early diagnosis of ovarian cancer was found to be possible by examining specific serum FFAs23. Fatty acid metabolic reprogramming occurs in a wide range of cancer types and may expand the indications for cancer diagnosis using serum FFAs. However, no studies have examined the utility of serum FFAs for diagnosing CC and CIN.

In this study, we identified several serum FFAs that display dramatically altered levels in patients with CC or CIN. Furthermore, we combined these FFAs to develop a highly sensitive and specific diagnostic model.

Results

The serum FFA composition is altered in patients with CC and CIN2/3

We have previously reported that the FFA composition is altered in lung and ovarian cancer patient serum samples from the aberrant expression of fatty acid metabolic enzymes, particularly stearoyl-CoA desaturase 1 (SCD1), in tumor tissues22,23. Analysis using public databases revealed that the expression patterns of fatty acid synthases (ACACA, FASN), fatty acid desaturase (SCD1), and fatty acid elongase (ELOVL) 1, 3, and 6 are also upregulated in CC tissues compared with the patterns of those in normal cervical tissues (Figure S1). Therefore, we first comprehensively measured 19 FFAs in serum samples from healthy donors, CIN2/3 patients, and stage I–IV CC patients using gas chromatography-mass spectrometry (GC–MS) (Tables 1 and 2). The results showed that the serum FFA composition was dramatically altered in CC patients compared with that in healthy donors. Furthermore, the serum FFA composition changes occurred from stage I (Fig. 1A and Figure S2A). The serum FFA composition of CIN2/3 patients also differed from that of healthy donors, although not to the same extent as CC patients (Fig. 1A and Figure S2B). Specifically, the levels of 10 FFAs (sapienic, palmitoleic, linoleic, α-linolenic, dihomo-γ-linolenic, oleic, arachidonic, stearic, arachidic, and palmitic acids) were significantly higher, while those of docosapentaenoic acid were significantly lower, in CC samples compared with the findings in healthy donor samples (Fig. 1B). Furthermore, FFA levels of 8 of the 11 species significantly altered in CC were significantly elevated from CIN2/3 (Fig. 1B). On the other hand, there were eight FFAs that remained unchanged (Figure S3). These results strongly suggest that the serum FFA compositions in CC and CIN2/3 patients significantly differ from that of healthy donors.Table 1 Characteristics of participants whose serum free fatty acid concentrations were measured in this study.

Characteristics	healthy donors (n = 40)	CIN patients (n = 30)	CC patients (n = 50)	
Age	
 Median (range)	43 (21–62)	37 (28–71)	46 (29–73)	
BMI	
 Median (range)		21.2 (17.2–26.8)	21.0 (14.8–32.8)	
Tumor size, mm	
 Median (range)			45 (4–160)	
Histopathological subtypes, n (%)	
 Squamous cell carcinoma			36 (72.0%)	
 Adenocarcinoma			14 (28.0%)	
Pathological stage, n (%)	
 CIN2		3 (10%)		
 CIN3		27 (90%)		
 I			27 (54.0%)	
 II			2 (4.0%)	
 III			20 (40.0%)	
 IV			1 (2.0%)	
CIN Cervical intraepithelial neoplasia, CC Cervical cancer.

Table 2 The gas chromatography-mass spectrometry (GC/MS) analyses of serum free fatty acids.

Compound	Target ion m/z	Rta (min)	LODb (ng/20μL)	LOQc (ng/20μL)	
Sapienic acid	311.2	5.720	0.13	0.32	
Palmitoleic acid	311.2	5.750	0.13	0.32	
Palmitic acid	313.2	5.833	0.09	0.22	
γ-linolenic acid	335.2	6.569	1.89	4.96	
Stearidonic acid	333.2	6.611	0.75	1.75	
Linoleic acid	337.2	6.652	0.04	0.08	
Oleic acid	339.2	6.669	0.09	0.24	
α-linolenic acid	335.2	6.698	0.19	0.48	
Vaccenic acid	339.2	6.703	0.09	0.24	
Stearic acid	341.2	6.790	0.08	0.21	
Arachidonic acid	361.2	7.540	2.58	6.58	
Eicosapentaenoic acid	359.2	7.595	9.65	21.31	
Dihimo-γ-linolenic acid	363.2	7.657	0.15	0.30	
Arachidic acid	369.2	7.917	0.12	0.31	
Docosahexaenoic acid	385.25	8.798	0.91	2.25	
Adrenic acid	389.25	8.842	4.35	8.93	
Docosapentaenoic acid	387.25	8.915	0.43	1.02	
Nervonic acid	423.3	10.745	0.03	0.07	
Lignoceric acid	425.3	10.938	0.01	0.02	
Margaric acid	327.2	6.293	I.S	I.S	
aRetention time.

bLimit of detection.

cLimit of quantification.

Fig. 1 The serum free fatty acid (FFA) compositions of cervical cancer (CC) and cervical intraepithelial neoplasia (CIN)2/3 patients differ from that of healthy donors (HD). The levels of 19 FFAs (shown in Table 2) were measured by gas chromatography-mass spectrometry (GC–MS) in serum samples from HD (n = 40), CIN2/3 patients (n = 30), stage I CC patients (n = 27), and stage II/III/IV CC patients (n = 23). (A) Heatmap of the average serum levels of the FFAs. (B) Comparison of the serum FFA levels between sample types. The FFAs that were significantly altered in CC and CIN2/3 patients compared with those in healthy donors are shown. Statistical analysis was performed by one-way ANOVA with Bonferroni's multiple comparison test. P-values were determined by comparing the healthy donors with each subject group. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. CC Pt, cervical cancer patient.

Serum FFAs are useful in the diagnosis of patients with CC and CIN2/3.

After identifying 11 FFAs that were altered in CC patient serum samples, we next investigated if these FFAs are useful for diagnosing this disease. Receiver operating characteristic (ROC) curve analysis of healthy donors and CC patients showed that all fatty acids had high diagnostic accuracy (area under the curve (AUC) values > 0.7) (Fig. 2A and B), especially nine FFAs that had very high diagnostic abilities (AUC > 0.8) (Fig. 2A). These results suggest that 11 serum FFAs may be useful as diagnostic markers for CC. Interestingly, similar results were obtained in the ROC analysis for healthy donors and only stage I CC patients (Figure S4A and B), suggesting that these serum FFAs vary in a clinical stage-independent manner. Thus, the early diagnosis of CC may also be possible using serum FFAs.Fig. 2 Serum free fatty acid (FFA) levels are useful as diagnostic markers for stage I–IV cervical cancer (CC). Receiver operating characteristic (ROC) curves for detecting stage I–IV CC patients using serum FFAs in Fig. 1B. (A) Area under the ROC curve (AUC) values of “AUC > 0.8” for the FFAs. (B) AUC values of “0.8 > AUC > 0.7” for the FFAs.

Because it is important to detect CIN, a precancerous lesion, to improve CC patient prognosis, we next examined if CIN2/3 could be diagnosed by examining serum FFA levels. SCC-Ag levels, a squamous cell carcinoma tumor marker, are known to not vary in patients with CIN24. Data from our cohort confirmed that SCC-Ag levels are not useful for diagnosing CIN2/3 (AUC = 0.5725) (Figure S5). However, nine serum FFAs displayed high diagnostic ability for CIN2/3 (AUC > 0.7), especially palmitic, palmitoleic, and dihomo-γ-linolenic acids (AUC > 0.8) (Fig. 3A–C). These results suggest that these serum FFAs can be used to diagnose not only CC, but also CIN2/3.Fig. 3 Serum free fatty acid (FFA) levels are useful as diagnostic markers for cervical intraepithelial neoplasia (CIN)2/3. Receiver operating characteristic (ROC) curves for detecting CIN2/3 patients using serum FFAs in Fig. 1B. (A) Area under the ROC curve (AUC) values of “AUC > 0.8” for the FFAs. (B) AUC values of “0.8 > AUC > 0.7” for the FFAs. (C) AUC values of “AUC < 0.7” for the FFAs.

A diagnostic model combining serum stearic acid and dihomo-γ-linolenic acid has high sensitivity for detecting CC and CIN2/3

Because we identified serum FFAs that are useful for diagnosing both CC and CIN2/3, we investigated if examining certain fatty acids in combination could improve the diagnostic accuracy. We aimed to establish a diagnostic model that could distinguish healthy donors from CIN2/3 and stage I–IV CC patients for the use of serum FFAs as a broad screening tool. First, using the discovery dataset (healthy donor: n = 24, CC and CIN2/3: n = 56), a multivariable logistic regression model was performed using the eleven FFA markers. With a combination of forward-selection and backward-elimination procedures, the combination of stearic acid and dihomo-γ-linolenic acid was identified to be statistically effective for distinguishing CIN2/3 and stage I–IV CC patients. ROC analysis was performed using these two markers, with the results showing that the AUC value was 0.9427 (diagnostic index (DI) = –5.631 + 0.030 × (Stearic acid) + 9.188 × (Dihomo-γ-linolenic acid)) (Fig. 4A and B). The diagnostic performance of this model was assessed using the validation dataset (healthy donor: n = 16, CC and CIN2/3: n = 24), which revealed that the model was very accurate, with an AUC value of 0.9531 (Fig. 4C). These results suggest the importance of combining serum FFA markers to improve the diagnostic accuracy of this approach. Furthermore, the DI using SCC-Ag values showed an AUC of 0.6165, indicating that the DI (Stearic acid, Dihomo-γ-linolenic acid) demonstrated high diagnostic ability (Fig. 4D and E).Fig. 4 Development of a cervical cancer (CC) and cervical intraepithelial neoplasia (CIN)2/3 detection model using serum free fatty acid (FFA) levels. (A–C) Diagnostic performance of the diagnostic index (DI) using stearic acid and dihomo-γ-linolenic acid (DI (Stearic acid, Dihomo-γ-linolenic acid)). (A) The DI (Stearic acid, Dihomo-γ-linolenic acid) established by multivariate logistic regression. (B, C) Receiver operating characteristic (ROC) curve analysis of healthy donors and CC + CIN2/3 patients in the (B) discovery (healthy donor: n = 24, CC and CIN2/3: n = 56) and (C) validation data sets (healthy donor: n = 16, CC and CIN2/3: n = 24). (D, E) Diagnostic performance of the DI using squamous cell carcinoma antigen (DI (SCC-Ag)). (D) The DI (SCC-Ag) established by multivariate logistic regression. (E) ROC curve analysis of healthy donors and CC + CIN2/3 patients. (F, G) The cut-off values in the (F) DI (Stearic acid, Dihomo-γ-linolenic acid) and (G) DI (SCC-Ag) were set, then the true negative/positive rates were calculated. The cut-off value was set by calculating Youden’s index by ROC analysis. SCC, squamous cell carcinoma; adeno, adenocarcinoma; CC Pt, cervical cancer patient.

We subsequently assessed the properties of the DI (Stearic acid, Dihomo-γ-linolenic acid) system. The results showed that the true positive rates of the DI (Stearic acid, Dihomo-γ-linolenic acid) in stage I CC and CIN2/3 patients were 96.3% and 70.0%, respectively (Fig. 4F). The true positive rates for the DI (SCC-Ag) in stage I CC and CIN2/3 patients were 52.2% and 16.7%, respectively (Fig. 4G), indicating that the DI (Stearic acid, Dihomo-γ-linolenic acid) has superior early diagnostic ability. Furthermore, for histological type, the DI (Stearic acid, Dihomo-γ-linolenic acid) was highly sensitive (true positive rate: 100.0%) in detecting adenocarcinoma, which is not detectable using the DI (SCC-Ag) (true positive rate: 0.0%) (Fig. 4F and G). These results strongly suggest that the DI (Stearic acid, Dihomo-γ-linolenic acid) can be used to diagnose CC and CIN2/3 independently of clinical stage and histological type.

Discussion

The prevention and treatment of CC is a global public health issue25,26. The five-year survival rate of CC detected at stage I is 81% to 96%, but the survival rate drops dramatically after the cancer cells invade surrounding the tissues or metastasize8. Therefore, it is critical to identify new diagnostic markers for the early diagnosis of CC. In this study, we demonstrated that the sapienic, palmitoleic, linoleic, α-linolenic, dihomo-γ-linolenic, oleic, arachidonic, stearic, arachidic, palmitic, and docosapentaenoic acid levels were dramatically altered in CC patient serum samples compared with the levels in samples from healthy donors. Furthermore, some of these FFAs also displayed differential levels in CIN2/3 patient serum samples, suggesting that both CC and CIN2/3 can be diagnosed using specific serum FFAs. Finally, we developed an optimal diagnostic model for the combination of FFAs using statistical methods, finding that the DI using stearic acid and dihomo-γ-linolenic acid levels had higher sensitivity and specificity (discovery set: sensitivity 0.89, specificity 0.96; validation set: sensitivity 0.88, specificity 0.89). Furthermore, the DI (Stearic acid, Dihomo-γ-linolenic acid) was highly sensitive (true positive rate: 100.0%) in detecting adenocarcinoma. Thus, the DI (Stearic acid, Dihomo-γ-linolenic acid) can be used to detect CC in a clinical stage- and histological type-independent manner.

We previously reported that palmitoleic, oleic, linoleic, α-linolenic, vaccenic, arachidic, docosahexaenoic, and lignoceric acid levels were altered in ovarian cancer patients23. In this study, palmitoleic, oleic, linoleic, α-linolenic, and arachidic acids were found to also be altered in CC patient serum samples, suggesting that these FFAs may display differential patterns in a relatively wide range of cancer types. In addition, these five FFAs would be suitable for very early disease screening to distinguish between cancer and non-cancer without determining the cancer type because their concentrations in serum are high and easily detected by GC–MS. Because the other six FFAs (sapienic, dihomo-γ-linolenic, docosapentaenoic, arachidonic, stearic, and palmitic acids) were altered in CC but not in ovarian cancer23, they may be CC-specific diagnostic markers. In this study, a DI using stearic acid and dihomo-γ-linolenic acid was constructed and determined to be the optimal diagnostic model for CC. In ovarian cancer, a DI using oleic and arachidic acid has been constructed23. The identification of different FFAs in cervical and ovarian cancers is very interesting because it suggests the possibility of a cancer type-specific diagnostic marker.

The sensitive detection of CIN2/3 is most important in repeat non-responders to CC screening, a subgroup known to be at high-risk of developing CC27. In this study, we identified several FFAs that could be used to detect CIN2/3 in patients. In addition, true positive rates for DI (SCC-Ag) in CIN2/3 were 16.7%, while the DI (Stearic acid, Dihomo-γ-linolenic acid) constructed in this study detected not only CC but also CIN2/3 with high sensitivity (true positive rate: 70.0%). These findings suggest that serum FFA screening is a promising alternative for detecting CIN2/3 and could significantly improve the current CC prevention strategies. However, the mechanism by which these specific serum FFAs levels are altered in CIN2/3 is unknown. We previously reported that serum FFA levels are altered from changes in fatty acid metabolizing enzyme expression patterns, particularly of SCD1, in cancer tissues23. High SCD1 expression levels in tumor tissues and elevated serum concentrations of palmitoleic acid and oleic acid, SCD1-generated fatty acids, were observed in CC, consistent with the previous report22,23. However, in CIN2/3, changes in fatty acid metabolic properties in a very limited range of lesions are unlikely to be reflected in systemic changes in fatty acid metabolism, suggesting that other mechanisms are involved. Liquid factors, such as cancer cell-derived miRNAs and long non-coding RNAs (lncRNAs), can reportedly regulate the activity of fatty acid metabolizing enzymes, such as SCD128,29. Cancer cells potentially release miRNAs and lncRNAs associated with fatty acid metabolic reprogramming to control systemic fatty acid metabolism.

First, diagnostic accuracy should be further examined in a larger cohort because the cohort used in this study has a very small sample size. In addition, comparisons with benign gynecological diseases　(e.g. endometriosis and uterine fibroids) and other HPV-related cancers (e.g. HPV + oropharyngeal, anal, penile, vulvar and vaginal cancers) must be performed to verify the specificity of this diagnostic tool. Second, all the healthy donors and patients enrolled in this study were Japanese, and the study has not been validated in a cohort of low-and middle-income countries (LMIC), which have high CC morbidity and mortality rates. Clinical studies with LMIC cohorts should be conducted because of the different dietary cultures that may affect serum FFA levels in LMIC. Nevertheless, the significance of this study is noteworthy because serum FFAs screening is highly sensitive in detecting stage I CC, cervical adenocarcinoma, and CIN2/3, which are difficult to detect by SCC-Ag screening.

Although CC screening programs are widely implemented, they have not been satisfactorily effective in LMIC because of a lack of pathologists and medical equipment to perform cytology for cancer screening. Therefore, 90% of CC-related deaths worldwide are in LMIC26,30,31. Blood sampling is commonly performed in clinical practice and is considered to be a convenient and non-invasive method. Furthermore, the serum FFAs test can be performed using any commercially available GC–MS with basic specifications. In addition, the patients can simply send the dried blood spots via regular mail to the laboratory for analysis32. Therefore, our serum FFA diagnostic model may be a new cancer screening tool that can be implemented in LMIC, potentially contributing to significantly increasing the number of cervical screening program recipients and improving CC patient prognosis.

Methods

Clinical samples

Serum samples were obtained from 50 patients with CC, 30 patients with CIN2/3, and 40 healthy donors (Table 1). Serum samples from CC and CIN2/3 patients were obtained at the Department of Gynecology and Obstetrics, Nihon University Hospital (Tokyo, Japan) between 2017 and 2024. Serum samples from healthy donors were collected at Nihon University and Keio University (Tokyo, Japan). All samples were stored at − 150 °C until use. Clinicopathological information of the patients was collected from clinical records and pathology reports. CC patients were classified from stage I to stage IV according to the clinical staging system of the International Federation of Gynecology and Obstetrics (FIGO) 201833. Serum samples were collected randomly from consenting patients before removal of the tumor at the time of initial surgery. To avoid any potential bias, each serum sample was collected prior to any treatment. Additionally, cases treated with neoadjuvant chemotherapy were excluded from sample collection. We obtained written informed consent from patients for the use of clinical materials for research purposes.

Measurement of SCC-Ag levels

SCC-Ag levels in samples from healthy donors and CIN2/3 patients were measured using a commercial service (SRL, Tokyo, Japan). SCC-Ag levels in samples from CC patients were collected from clinical records and pathology reports.

GC–MS sample preparation

Prior to GC–MS analysis, 0.3 mL of PBS containing internal standards (100 ng of margaric acid) was added to 20 µL of serum and mixed by vortexing. FFAs were extracted from samples using an ISOLUTE SLE + column (Biotage, Vimpelgatan, Uppsala, Sweden) and dichloromethane. The lower organic region of the sample was collected and dried under a nitrogen stream. The residue was dissolved in 5 µL of pyridine and 30 µL of the reagent BSTFA + TMCS (99:1) (TS-38831, Thermo Fisher Scientific, Waltham, MA, USA) for trimethylsilylation. The derivatization reaction was performed for 30 min at 40 °C.

GC–MS analyses

GC–MS analysis was performed on a Shimadzu GC–MS QP2010 Ultra equipped with an AOC20i autoinjector and Rtx-5MS column (30 m, 0.25 mm, 0.25 µm df) in the 70 eV electron ionization mode. The oven temperature program was as follows: 150 °C for 1 min, 20 °C/minute to 250 °C, 5 °C/minute to 280 °C, hold for 5 min, then 20 °C/minute to 330 °C, hold for 3 min, after which the temperature was maintained for 10 min. Helium was the carrier gas with a constant flow speed of 42.0 cm/sec. One microliter was injected at a 5:1 split ratio with an injector temperature of 250 °C. The MS interface temperature was held at 280 °C. The target ion (m/z), retention time, limit of detection, and limit of quantification for the 19 FFAs evaluated are summarized in Table 2.

Gene expression analysis with public databases

The expression levels of the fatty acid metabolizing enzymes ACACA, FASN, SCD1, ELOVL1, ELOVL3, and ELOVL6 in cancer and non-cancer patients were analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA) database (http://gepia.cancer-pku.cn). Tumor tissues were obtained from patients with cervical squamous cell carcinoma and endocervical adenocarcinoma. GEPIA is a web-based tool that uses data from The Cancer Genome Atlas and Genotype-Tissue Expression projects.

Statistical analysis

Unsupervised clustering and heatmap generation with sorted datasets were performed using MetaboAnalyst 5.0. Comparisons between two groups were assessed using unpaired or paired (for matched comparisons) two-tailed Student’s t-tests or non-parametric Mann–Whitney U-tests. Multiple comparisons were assessed by one-way analysis of variance (ANOVA), including Tukey’s or Bonferroni’s multiple comparisons tests. The diagnostic sensitivity, specificity, and AUC values were calculated for each FFA.

To construct an optimal diagnostic model for CC and CIN2/3, samples were randomly divided into discovery and validation sets at a 2:1 ratio stratified by malignancy status (control/CC + CIN2/3). The discovery set was used to select lipid markers and construct a model, then the validation set was used to validate the model. Using the discovery set, multivariable analyses were conducted using the logistic regression model. Variables were first selected from univariate screening by comparing those of healthy controls and CC + CIN2/3, which yielded 11 FFAs with significant differences, followed by a combination of forward-selection and backward-elimination procedures. Correlations between serum concentrations of these lipid markers were calculated using Spearman’s rank correlation method to assess for multicollinearity. The variable selection procedure was set to a threshold of 0.05 for inclusion and 0.05 for exclusion. The Akaike Information Criterion was applied to determine the best model. The DI score was calculated using the intercept and coefficients rounded to one decimal place. Finally, the performance of the DI was assessed with the validation dataset. For comparison, a DI with SCC-Ag values was also calculated using the discovery dataset. For each DI, the diagnostic sensitivity, specificity, and AUC values were calculated.

The Jump Pro 13.2.1 statistical software package (SAS Institute Inc, Cary, NC, USA), Prism software (version 9.0; GraphPad Software, La Jolla, CA, USA), and MetaboAnalyst 5.0 were used for data management and statistical analyses. Significance levels were set at P < 0.05 for all tests. Data are presented as the mean ± standard deviation.

Data availability

The authors declare that all other data supporting the findings of this study are available within the article and its supplementary information files, and from the corresponding author upon reasonable request.

Supplementary Information

Supplementary Information.

Abbreviations

AUC Area under the curve

CC Cervical cancer

CESC Cervical squamous cell carcinoma and endocervical adenocarcinoma

CIN Cervical intraepithelial neoplasia

DI Diagnostic index

FASN Fatty acid synthase

FFA Free fatty acid

FIGO The International federation of gynecology and obstetrics

GC–MS Gas chromatography-mass spectrometry

GEPIA Gene expression profiling interactive analysis

HD Healthy donor

LMIC Low- and middle-income countries

ROC Receiver operating characteristic

SCC-Ag Squamous cell carcinoma antigen

SCC Squamous cell carcinoma

SCD1 Stearoyl-CoA desaturase 1

miRNA MicroRNA

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71606-w.

Acknowledgements

This study was supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan (21K15602 to Dr. Yuki Katoh); a grant from Takeda Science Foundation 2021 to Dr. Yuki Katoh; a Research Grant for Public Health Science (2024) to Dr. Yuki Katoh; The Japan Society of Gynecologic Oncology 2022 to Dr. Yuki Katoh; and a Nihon University Research Grant for 2024 to Dr. Yuki Katoh. We would like to thank Dr. Yuji Ikeda and Ms. Naoko Tomita for collecting the clinical specimens and Mr. Taro Kanagawa, Dr. Hiroyuki Hara, and Dr. Toshikatsu Ikeda for technical assistance.

Author contributions

Research study design: Y.K., A.K.; Conducting experiments: Y.K., A.K., N.H., T.O., M.S., S.H.; Acquiring data: Y.K., A.K.; Analyzing data: Y.K., A.K.; Collecting clinical specimens: N.H., T.S., K.Kat., T.I., H.N., K.Kaw.; Statistical analysis: S.U.; Writing the manuscript: Y.K.; Supervision: Y.K.; Funding acquisition: Y.K.

Funding

Ministry of Education,Culture,Sports,Science and Technology,21K15602,Takeda Science Foundation 2021,Research Grant for Public Health Science (2024),The Japan Society of Gynecologic Oncology 2022,Nihon University Research Grant for 2024.

Competing interests

The authors declare no competing interests.

Ethical approval

This study was conducted according to the guidelines of the Declaration of Helsinki and was approved by the Nihon University Institutional Review Board (RK-170711–6, approved on 25 August 2017; RK-200609–1, approved on 9 September 2020) and Keio University Institutional Review Board (20110159, approved on 26 September 2011; 20130122 approved on 7 August 2013). Written informed consent was obtained from patients for the use of clinical materials for research purposes.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Yuki Katoh, Akiko Kubo, Nobuki Hayashi.
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