Research ArticleExperimental Studies
Open Access

Exploration of Lipid Mediators for Therapeutic Monitoring of Pancreatic Cancer Patients

NOBUHIKO NAKAGAWA, MASAMICHI HAYASHI, DAIGO KOBAYASHI, TOMOHISA OTSU, FUMINORI SONOHARA, KEISUKE KURIMOTO, HARUYOSHI TANAKA, YOSHIKUNI INOKAWA, HIDEKI TAKAMI, NORIFUMI HATTORI, MITSURO KANDA, CHIE TANAKA, GORO NAKAYAMA and YASUHIRO KODERA
Anticancer Research April 2025, 45 (4) 1343-1353; DOI: https://doi.org/10.21873/anticanres.17520

Abstract

Background/Aim: Multimodal treatment is now the primary strategy for managing pancreatic cancer. Blood-based protein markers are sometimes useless for evaluating the real-time disease condition to determine treatment strategies. This study focused on detecting novel exosomal lipid biomarkers, as exosomes contain several biological mediators.

Materials and Methods: Lipidomic analysis was conducted by liquid chromatography-mass spectrometry (LC-MS) using serum exosome-derived lipid samples from four pancreatic ductal adenocarcinoma (PDAC) patients and four healthy controls. Some candidates were ascertained using multiple time-point blood samples from four additional PDAC patients. Furthermore, we validated them using an additional twelve multimodal-treated PDAC patient cohort.

Results: Nontarget LC-MS analysis revealed that lysophosphatidylcholine (LPC) expression levels were significantly decreased in PDAC patients compared to healthy controls. Multiple time-point blood samples demonstrated that LPC (16:0) and LPC (18:1) consistently showed lower levels in relapsed cases than in non-relapsed cases over time. In the validation cohort, a low LPC level before initial treatment was associated with histological lymphatic invasion (p=0.04) and was linked to progressive-free survival (PFS) (p=0.04).

Conclusion: PDAC patients with initially low LPC levels in the blood exosomes demonstrated an unfavorable PFS. Exosomal lipid markers may serve as potential indicators for disease monitoring in pancreatic cancer patients undergoing multimodal treatment.

Keywords:

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease that accounts for almost 95% of pancreatic malignancies (1). Over the last decade, intense efforts to improve survival rates have still been insufficient. Effective treatment for PDAC is limited mainly by a low early diagnosis rate, a high relapse probability, and the therapy-refractory nature of PDAC. Furthermore, socioeconomic factors are also known to influence the prognosis of pancreatic cancer treatment (2). As a result, it has the lowest 5-year survival rate among digestive organ cancers (3, 4). PDAC is predicted to become the second leading cause of cancer-related death by 2030 (5). Furthermore, it is impossible to improve the treatment results of pancreatic cancer by surgery alone as a local treatment.

Recently, multimodal sequential treatment with systemic chemotherapy or chemoradiation therapy and surgery has become common for pancreatic cancer regardless of the resectability status at initial diagnosis (6). Tumor markers such as CA19-9 and DUPAN-2 and imaging modalities are usually applied to judge the real-time therapy effect. However, they do not always reflect ongoing oncological activity status, mainly due to the loss of Lewis antigen, cholangitis or tumor degeneration. Therefore, identifying essential oncological blood markers is necessary. We recently conducted an analysis of microRNA expression as a molecular marker for predicting local invasiveness in pancreatic cancer (7).

Metabolomics is a research field that comprehensively assesses metabolites produced by metabolic activities, such as enzymatic processes in the living body. It is attracting attention for its role in elucidating biological phenomena and pathological conditions (8-10). Lipids and their metabolites (lipidomes), proteins, sugars, and nucleic acids are the main constituents and energy sources needed for biological activities in living organisms. Furthermore, lipid mediators such as prostaglandin and leukotrienes play a vital role in signaling pathways (11). Since lipid mediators are involved in various physiological functions, including the endocrine and exocrine systems of the pancreas (12, 13), and serve as indicators of inflammatory conditions, they could be utilized as sensitive blood markers reflecting the PDAC-related dysfunction or inflammation. Some previous lipidome studies have shown the relationship between certain diseases and blood lipids (14-16). However, no study has focused on lipid mediators in pancreatic cancer-treated patients.

This study focused on lipid mediators and assessed their utility as noninvasive biomarkers for PDAC. Since multimodal treatment requires an extended treatment period, candidate lipid mediators were evaluated using multiple time-point blood samples.

Materials and Methods

Patients and samples. As a derivation cohort, we first performed a comprehensive analysis of lipids from the exosomes of four healthy controls and four PDAC patients (PDAC1-4). Next, we collected the exosomes from PDAC patients (PDAC5-8) who received the same multimodal treatment, including preoperative FOLFIRINOX chemotherapy, surgery, and postoperative adjuvant chemotherapy, at Nagoya University Hospital (Nagoya, Japan) from June 2017 to November 2020.

For the validation cohort, we collected the exosomes from another 12 PDAC patients who underwent curative surgery at Nagoya University Hospital during the same period. Histological findings were assessed based on the 7th edition of the Classification of Pancreatic Carcinoma for Japan Pancreas Society. This study was approved by the Institutional Review Board of Nagoya University (No. 2014-0042), and all patients provided written informed consent.

Exosome extraction and comprehensive analysis of lipid mediators. According to the manufacturer’s instructions, the exosomes were isolated from the serum of healthy controls and PDAC patients by the MagCapture™ Exosome Isolation Kit PS (Wako, Osaka, Japan). The number of nanoparticles in whole-serum-derived exosomes was measured using the NanoSight NS300 nanoparticle characterization system (NanoSight Ltd., Amesbury, UK). Samples were diluted to 1/50 and injected into the 405 nm laser chamber with a constant output controlled by a syringe pump. Nanoparticle Tracking Analysis software (NanoSight Ltd.) was used to measure nanoparticle size and concentration. To identify lipid mediators that behaved differently in the four healthy controls and four PDAC patients, we performed a comprehensive lipid mediator analysis of serum exosome specimens with Kazusa Genome Technologies (Kisarazu, Japan).

Quantification of lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) in exosomes. LPC and LPE were quantified by liquid chromatography-tandem mass spectrometry (LC-MS) using exosomes extracted from blood samples. The analysis was performed by the Chemicals Evaluation and Research Institute, Japan (Saitama, Japan).

Quantification of LPC in exosomes with ELISA. We used commercially available enzyme-linked immunosorbent assay (ELISA) kits (Abbexa Ltd., Cambridge, UK) to quantify LPC levels in the validation cohort due to cost considerations. This is a competitive binding ELISA technology where antibodies specific to LPC are precoated onto 96-well plates. Briefly, we added 50 μl of standard solution and serum sample to a 96-well plate. Next, 50 μl of detection reagent A was added to each well, and the plates were gently shaken. The plates were then sealed and incubated at 37°C for 1 h. Then, the liquid part was discarded, and the plates were washed properly using wash buffer. Afterward, 100 μl of detection reagent B was dispensed into each well with gentle mixing, and the plates were sealed for a 30 min incubation at 37°C. After the repeated washing process, 90 μl of tetramethylbenzidine (TMB) substrate was added to each well. The plates were incubated again for 15 min at 37°C. Finally, we stopped the reaction by adding 50 μl of stop solution and measured the absorbances immediately at 450 nm. We calculated the serum LPC levels from these absorbance values. The assay sensitivity for serum LPC was <92.4 ng/ml.

Statistical analysis. Continuous variables were compared with the Wilcoxon signed-rank test or Student’s t-test, as appropriate. Categorical variables were compared using the χ2 or Fisher’s exact tests, as appropriate. Recurrence-free survival (RFS) was defined as the time between curative resection of PDAC and confirmation of recurrence. Overall survival (OS) was the time between surgery and all-cause death. The OS and RFS rates at each follow-up time point were estimated using the Kaplan–Meier method and compared using a log-rank test. The Cox proportional hazard regression model was used to perform univariate and multivariate OS and RFS analyses. All statistical analyses were performed using JMP version 16 software (SAS Institute, Cary, NC, USA). The threshold for significance was p<0.05.

Results

Derivation cohort. Comprehensive lipidomic analysis. We first performed a comprehensive lipidomic analysis of samples from four healthy control and four PDAC patients (PDAC1-4) using LC-MS to investigate differentially expressed lipid mediators. A comprehensive quantitative lipidomic analysis was performed, and trends were analyzed at the lipid class level. As a result, 631 lipid molecules and 36 lipid classes were recognized (Table I). Several lipid classes with significant differences in expression between healthy controls and PDAC patients were identified. The fold changes in LPC and LPE expression in PDAC cases were more prominent than others, with significant differences highlighted in the volcano plots (Figure 1).

View this table:
Table I.

Comprehensive quantitative lipidomic analysis of four healthy controls and four pancreatic ductal adenocarcinoma (PDAC) patients.

Figure 1.
Figure 1.

Volcano plot of comprehensive quantitative lipidomic analysis of four healthy controls and four pancreatic ductal adenocarcinoma patients.

Multiple time-point assessment of LPC and LPE. We measured LPC and LPE levels in exosomes extracted from serum samples of an additional four PDAC patients (PDAC5-8). Sex, chemotherapy regimen, tumor location, operative procedure, and resectability status were unified. The nanoparticle tracking analysis measured the sizes of the collected extracellular vesicles, and particles with diameters from 30 to 200 nm were regarded as exosomes. Multiple time points included before IT, before surgery, and 3-6 months after surgery. Figure 2 shows the LPC expression in PDAC patients with and without recurrence. LPC (16:0) and LPC (18:1) values tended to be higher at each time point in patients without recurrence. Similarly, Figure 3 shows that LPE (16:0) and LPE (18:0) values tended to be higher at each timepoint in non-recurrence cases than in recurrence cases.

Figure 2.
Figure 2.

Lysophosphatidylcholine (LPC) (16:0) values of healthy controls and pancreatic ductal adenocarcinoma (PDAC) patients with recurrence and without recurrence at multiple time points (A). LPC (18:1) values of healthy controls and PDAC patients with and without recurrence at multiple time points (B).

Figure 3.
Figure 3.

Lysophosphatidylethanolamine (LPE) (16:0) values of healthy controls and pancreatic ductal adenocarcinoma (PDAC) patients with recurrence and without recurrence at multiple time points (A). LPE (18:0) values of healthy controls and PDAC patients with and without recurrence at multiple time points (B).

Validation cohort. Patient characteristics. To validate the findings from the derivation cohort, we retrospectively analyzed serum LPC expression in twelve PDAC patients who underwent curative surgery at Nagoya University Hospital from June 2017 to November 2020. Due to insufficient sample volume, we focused our analysis on LPC. The baseline demographic characteristics of the twelve patients are summarized in Table II. This retrospective study included three women and nine men; the median age was 68 years (range=40-79 years). The median body mass index was 19.2 kg/m2 (range=15.5-21.7 kg/m2). The tumor location was the pancreatic head in ten patients and the pancreatic body or tail in two patients. The median CA19-9 value before NAT was 193. We performed ten pancreaticoduodenectomies and two distal pancreatectomies. The pathological stage was 0 in one patient, IA in three patients, IB in two patients, IIA in one patient, and IIB in five patients. The resectability status of the twelve patients was resectable in seven patients, borderline resectable in four patients, and unresectable in one patient. The median LPC value was 1.95 μg/ml (range=1.87-2.01 μg/ml) before initial therapy (IT), 1.94 μg/ml (range=1.61-2.02 μg/ml) before surgery, and 1.89 μg/ml (range=1.72-2.01 μg/ml) after surgery.

View this table:
Table II.

Characteristics of patients with pancreatic ductal adenocarcinoma (PDAC) (n=12).

Association of the LPC value and clinicopathological characteristics. Twelve patients were classified into the high LPC value group and the low LPC value group based on the median LPC value before initial therapy. The associations between LPC values and clinicopathological characteristics are shown in Table III. No significant differences were detected between the high and low LPC groups in tumor markers, tumor size, TNM stage, or resectability status. In contrast, a low LPC value was associated with lymphatic invasion (50.0% vs. 0%, p=0.04).

View this table:
Table III.

Association of the lysophosphatidylcholine (LPC) value before initial therapy and clinicopathological characteristics in 12 pancreatic ductal adenocarcinoma (PDAC) patients.

LPC expression at multiple time points. We evaluated changes in the LPC value at multiple time points and investigated whether these changes might help monitor the status of PDAC progression. No significant difference was observed between the pre-IT, preoperative, and postoperative time points. Then, we divided the patients into recurrence and no-recurrence groups based on recurrence within two years. We compared the changes in the LPC value at multiple time points (Figure 4). In the no-recurrence group, the value of LPC before IT tended to be higher than that before surgery and after surgery (p=0.13, p=0.06), while there was no significant difference in the LPC value in the recurrence group (p=0.73, p=0.85).

Figure 4.
Figure 4.

Lysophosphatidylcholine (LPC) values at multiple time points in patients with recurrence (A) and without recurrence (B).

Prognostic significance of LPC. In this context, low LPC expression before IT correlated significantly with a shorter PFS than high LPC expression (MST=14.8 months vs. not reached, p=0.04, Figure 5A). On the other hand, there was no significant difference in OS between the low and high LPC expression groups (MST=33.4 months vs. not reached, p=0.12, Figure 5B). Univariate and multivariate analyses by the Cox proportional hazard model were performed to identify the risk factors associated with PFS. In the univariate analysis, low LPC expression (HR=6.73, 95%CI=0.73-61.9, p=0.09) tended to be a risk for PFS, but not significantly (Table IV). As for overall survival (OS), no factors showed significant differences (Table V). In addition, operative results were compared between the groups. No significant difference was observed.

Figure 5.
Figure 5.

Kaplan–Meier analysis of recurrence-free survival (A) and overall survival (B) for twelve patients with pancreatic ductal adenocarcinoma stratified by lysophosphatidylcholine (LPC) expression before initial therapy.

View this table:
Table IV.

Univariate Cox proportional hazard regression analyses of progressive-free survival.

View this table:
Table V.

Univariate Cox proportional hazard regression analyses of overall survival.

Discussion

In this study, we performed a comprehensive lipidomic analysis of exosomes extracted from blood samples in PDAC patients. We analyzed LPC expression multiple times during the multimodal PDAC treatment and analyzed changes in lipid mediators over time. As a result, we found that LPC expression before IT tended to be higher in the no-recurrence group than in the recurrence group.

LPC, also called lysolecithins, is a vital lipid molecule in human tissues belonging to bioactive lysophospholipids (17). LPC is produced from cell membrane-derived phosphatidylcholine via phospholipase A2 activation (18). LPC molecular species are identified by the lengths and saturation of their acyl chains. It has been reported that LPC inhibits vasodilation, which is involved in atherosclerotic disease (15), and induces apoptosis in various types of cells (19, 20). LPE is a deacylated product of phosphatidylethanolamine hydrolysis induced by phospholipase A2. LPE is a minor component of the cell membrane and plays a role in cell-mediated cell signaling and the activation of other enzymes (21).

Our quantitative lipidome analysis showed that several lipid classes in PDAC patients differed significantly from those in healthy controls. Among these classes, PDAC patients exhibited larger ratios of LPC and LPE than healthy controls. Breeur et al. reported a pan-cancer analysis of prediagnostic blood metabolite concentrations (22). LPC was one of the metabolites associated with the risk of most cancer types. However, this analysis included breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma but not PDAC. Naudin et al. reported associations between lipidomics and pancreatic cancer risk (23). They found that the prediagnostic serum lipidome, including 43 lipid species from 8 lipid classes and five fatty acids, was associated with PDAC. Similar to our results, this study also included LPC.

LPC and LPE in the four PDAC patients tended to be lower in the recurrence group than in the no-recurrence group over time. Mainly, low LPC values before the initial therapy seemed to be associated with the malignancy of PDAC, such as lymphatic invasion (p=0.04), venous invasion (p=0.08), and lymph node metastasis (p=0.08). On the other hand, the LPC value had no association with tumor markers, tumor size, or resectability status. This may be because host conditions influence this lipid marker. For prognosis, low LPC before the initial therapy was associated with significantly poorer PFS compared to high LPC levels. Low LPC levels might reflect the malignancy of the tumor or the weakness of the host’s tumor immunity. Furthermore, LPC levels decreased even in the non-recurrence group after chemotherapy or surgery. It may indicate that exosomal LPC expression is also affected by radical treatment. In contrast, the LPC value had no association with OS, possibly due to the variation in therapy regimens after the first recurrence. Several studies have reported the significance of LPC as a marker in colorectal and ovarian cancer (24, 25), as well as changes in LPC levels during the short postoperative period and their association with complications (26). However, to our knowledge, this is the first report to examine the change in LPC expression using blood samples from the same patients at multiple time points.

Study limitations. First, this was a retrospective study with limited patients from a single institution. Tumor stage and resectability status included a variety of factors, and patient backgrounds were not uniform. Second, perioperative treatment regimens were not unified. To prove the importance of LPC blood concentration during preoperative treatment and surgery, it is necessary to conduct large-scale studies with patients at the same stage and resectability status of PDAC, as well as consistent perioperative treatment protocols.

Conclusion

LPC is a lipid that reflects the progression of PDAC and the host’s condition. It can be used as a blood marker for monitoring patients during the multimodal treatment period of PDAC.

Footnotes

  • Authors’ Contributions

    Conception and design: NN, MH, FS; Financial support: FS, YK; Administrative support: MH, YK; Provision of study materials and patients: NN, MH, FS, KK, YI, HT, NH, MK, CT, GN; Collection and assembly of data: NN, DK, TO, MH; Article writing: NN, DK, MH; Final approval of article: all Authors.

  • Conflicts of Interest

    The Authors have no conflicts of interest to declare in relation to this study.

  • Funding

    This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Scientific Research (C) number 20K17643 and 23K14604 to Nobuhiko Nakagawa.

  • Received February 9, 2025.
  • Revision received February 25, 2025.
  • Accepted February 26, 2025.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Stathis A,
    2. Moore MJ
    : Advanced pancreatic carcinoma: current treatment and future challenges. Nat Rev Clin Oncol 7(3): 163-172, 2010. DOI: 10.1038/nrclinonc.2009.236
    OpenUrlCrossRefPubMed
  2. ↵
    1. Jimenez PB,
    2. Popp R,
    3. Sharan S,
    4. Manaise HK,
    5. Ahmed SH,
    6. Bansal S,
    7. Kowkabany G,
    8. Raikot S,
    9. Do KBS,
    10. George A,
    11. Gabriel E
    : Sociodemographic barriers to the timely treatment of pancreatic cancer. Anticancer Res 43(11): 4969-4974, 2023. DOI: 10.21873/anticanres.16695
    OpenUrlAbstract/FREE Full Text
  3. ↵
    1. Mizrahi JD,
    2. Surana R,
    3. Valle JW,
    4. Shroff RT
    : Pancreatic cancer. Lancet 395(10242): 2008-2020, 2020. DOI: 10.1016/S0140-6736(20)30974-0
    OpenUrlCrossRefPubMed
  4. ↵
    1. Grossberg AJ,
    2. Chu LC,
    3. Deig CR,
    4. Fishman EK,
    5. Hwang WL,
    6. Maitra A,
    7. Marks DL,
    8. Mehta A,
    9. Nabavizadeh N,
    10. Simeone DM,
    11. Weekes CD,
    12. Thomas CR Jr.
    : Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma. CA Cancer J Clin 70(5): 375-403, 2020. DOI: 10.3322/caac.21626
    OpenUrlCrossRefPubMed
  5. ↵
    1. Rahib L,
    2. Smith BD,
    3. Aizenberg R,
    4. Rosenzweig AB,
    5. Fleshman JM,
    6. Matrisian LM
    : Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res 74(11): 2913-2921, 2014. DOI: 10.1158/0008-5472.CAN-14-0155
    OpenUrlAbstract/FREE Full Text
  6. ↵
    1. Versteijne E,
    2. Vogel JA,
    3. Besselink MG,
    4. Busch ORC,
    5. Wilmink JW,
    6. Daams JG,
    7. van Eijck CHJ,
    8. Groot Koerkamp B,
    9. Rasch CRN,
    10. van Tienhoven G, Dutch Pancreatic Cancer Group
    : Meta-analysis comparing upfront surgery with neoadjuvant treatment in patients with resectable or borderline resectable pancreatic cancer. Br J Surg 105(8): 946-958, 2018. DOI: 10.1002/bjs.10870
    OpenUrlCrossRefPubMed
  7. ↵
    1. Otsu T,
    2. Hayashi M,
    3. Fujita K,
    4. Kobayashi D,
    5. Nakagawa N,
    6. Kurimoto K,
    7. Takami H,
    8. Nakanishi K,
    9. Umeda S,
    10. Shimizu D,
    11. Hattori N,
    12. Kanda M,
    13. Tanaka C,
    14. Nakayama G,
    15. Kodera Y
    : Genome-wide microRNA analysis identified miR-210-3p over-expression in pancreatic cancer tissues as a predictor of their local invasiveness. Anticancer Res 44(11): 4709-4721, 2024. DOI: 10.21873/anticanres.17297
    OpenUrlAbstract/FREE Full Text
  8. ↵
    1. Nicholson JK,
    2. Holmes E,
    3. Kinross JM,
    4. Darzi AW,
    5. Takats Z,
    6. Lindon JC
    : Metabolic phenotyping in clinical and surgical environments. Nature 491(7424): 384-392, 2012. DOI: 10.1038/nature11708
    OpenUrlCrossRefPubMed
    1. Shin SY,
    2. Fauman EB,
    3. Petersen AK,
    4. Krumsiek J,
    5. Santos R,
    6. Huang J,
    7. Arnold M,
    8. Erte I,
    9. Forgetta V,
    10. Yang TP,
    11. Walter K,
    12. Menni C,
    13. Chen L,
    14. Vasquez L,
    15. Valdes AM,
    16. Hyde CL,
    17. Wang V,
    18. Ziemek D,
    19. Roberts P,
    20. Xi L,
    21. Grundberg E, Multiple Tissue Human Expression Resource (MuTHER) Consortium,
    22. Waldenberger M,
    23. Richards JB,
    24. Mohney RP,
    25. Milburn MV,
    26. John SL,
    27. Trimmer J,
    28. Theis FJ,
    29. Overington JP,
    30. Suhre K,
    31. Brosnan MJ,
    32. Gieger C,
    33. Kastenmüller G,
    34. Spector TD,
    35. Soranzo N
    : An atlas of genetic influences on human blood metabolites. Nat Genet 46(6): 543-550, 2014. DOI: 10.1038/ng.2982
    OpenUrlCrossRefPubMed
  10. ↵
    1. Kettunen J,
    2. Tukiainen T,
    3. Sarin AP,
    4. Ortega-Alonso A,
    5. Tikkanen E,
    6. Lyytikäinen LP,
    7. Kangas AJ,
    8. Soininen P,
    9. Würtz P,
    10. Silander K,
    11. Dick DM,
    12. Rose RJ,
    13. Savolainen MJ,
    14. Viikari J,
    15. Kähönen M,
    16. Lehtimäki T,
    17. Pietiläinen KH,
    18. Inouye M,
    19. McCarthy MI,
    20. Jula A,
    21. Eriksson J,
    22. Raitakari OT,
    23. Salomaa V,
    24. Kaprio J,
    25. Järvelin MR,
    26. Peltonen L,
    27. Perola M,
    28. Freimer NB,
    29. Ala-Korpela M,
    30. Palotie A,
    31. Ripatti S
    : Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet 44(3): 269-276, 2012. DOI: 10.1038/ng.1073
    OpenUrlCrossRefPubMed
  11. ↵
    1. Robinson DR
    : Lipid mediators of inflammation. Rheum Dis Clin North Am 13(2): 385-405, 1987.
    OpenUrlPubMed
  12. ↵
    1. Ketavarapu V,
    2. Addipilli R,
    3. Ragi N,
    4. Pallerla P,
    5. Simhadri V,
    6. Manne S,
    7. Sannapaneni K,
    8. Aslam M,
    9. Talukadar R,
    10. Ch VD,
    11. Gv R,
    12. Amanchy R,
    13. Reddy DN,
    14. Sripadi P,
    15. Sasikala M
    : Plasma metabolite profiling identifies nondiabetic chronic pancreatitis patients with metabolic alterations progressing to prediabetes before HbA1c. Clin Transl Gastroenterol 15(6): e1, 2024. DOI: 10.14309/ctg.0000000000000704
    OpenUrlCrossRef
  13. ↵
    1. Gumpper-Fedus K,
    2. Crowe O,
    3. Hart PA,
    4. Pita-Grisanti V,
    5. Velez-Bonet E,
    6. Belury MA,
    7. L Ramsey M,
    8. Cole RM,
    9. Badi N,
    10. Culp S,
    11. Hinton A,
    12. F Lara L,
    13. Krishna SG,
    14. Conwell DL,
    15. Cruz-Monserrate Z
    : Differences in plasma fatty acid composition related to chronic pancreatitis: a pilot study. Pancreas 53(5): e416-e423, 2024. DOI: 10.1097/MPA.0000000000002318
    OpenUrlCrossRefPubMed
  14. ↵
    1. Loew A,
    2. Köhnke T,
    3. Rehbeil E,
    4. Pietzner A,
    5. Weylandt KH
    : A role for lipid mediators in acute myeloid leukemia. Int J Mol Sci 20(10): 2425, 2019. DOI: 10.3390/ijms20102425
    OpenUrlCrossRefPubMed
  15. ↵
    1. Schauberger E,
    2. Peinhaupt M,
    3. Cazares T,
    4. Lindsley AW
    : Lipid mediators of allergic disease: pathways, treatments, and emerging therapeutic targets. Curr Allergy Asthma Rep 16(7): 48, 2016. DOI: 10.1007/s11882-016-0628-3
    OpenUrlCrossRefPubMed
  16. ↵
    1. Artru F,
    2. McPhail MJW,
    3. Triantafyllou E,
    4. Trovato FM
    : Lipids in liver failure syndromes: a focus on eicosanoids, specialized pro-resolving lipid mediators and lysophospholipids. Front Immunol 13: 867261, 2022. DOI: 10.3389/fimmu.2022.867261
    OpenUrlCrossRefPubMed
  17. ↵
    1. Ren J,
    2. Lin J,
    3. Yu L,
    4. Yan M
    : Lysophosphatidylcholine: potential target for the treatment of chronic pain. Int J Mol Sci 23(15): 8274, 2022. DOI: 10.3390/ijms23158274
    OpenUrlCrossRefPubMed
  18. ↵
    1. Law SH,
    2. Chan ML,
    3. Marathe GK,
    4. Parveen F,
    5. Chen CH,
    6. Ke LY
    : An updated review of lysophosphatidylcholine metabolism in human diseases. Int J Mol Sci 20(5): 1149, 2019. DOI: 10.3390/ijms20051149
    OpenUrlCrossRefPubMed
  19. ↵
    1. Takahashi M,
    2. Okazaki H,
    3. Ogata Y,
    4. Takeuchi K,
    5. Ikeda U,
    6. Shimada K
    : Lysophosphatidylcholine induces apoptosis in human endothelial cells through a p38-mitogen-activated protein kinase-dependent mechanism. Atherosclerosis 161(2): 387-394, 2002. DOI: 10.1016/s0021-9150(01)00674-8
    OpenUrlCrossRefPubMed
  20. ↵
    1. Han MS,
    2. Park SY,
    3. Shinzawa K,
    4. Kim S,
    5. Chung KW,
    6. Lee JH,
    7. Kwon CH,
    8. Lee KW,
    9. Park CK,
    10. Chung WJ,
    11. Hwang JS,
    12. Yan JJ,
    13. Song DK,
    14. Tsujimoto Y,
    15. Lee MS
    : Lysophosphatidylcholine as a death effector in the lipoapoptosis of hepatocytes. J Lipid Res 49(1): 84-97, 2008. DOI: 10.1194/jlr.M700184-JLR200
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Makide K,
    2. Kitamura H,
    3. Sato Y,
    4. Okutani M,
    5. Aoki J
    : Emerging lysophospholipid mediators, lysophosphatidylserine, lysophosphatidylthreonine, lysophosphatidylethanolamine and lysophosphatidylglycerol. Prostaglandins Other Lipid Mediat 89(3-4): 135-139, 2009. DOI: 10.1016/j.prostaglandins.2009.04.009
    OpenUrlCrossRefPubMed
  22. ↵
    1. Breeur M,
    2. Ferrari P,
    3. Dossus L,
    4. Jenab M,
    5. Johansson M,
    6. Rinaldi S,
    7. Travis RC,
    8. His M,
    9. Key TJ,
    10. Schmidt JA,
    11. Overvad K,
    12. Tjønneland A,
    13. Kyrø C,
    14. Rothwell JA,
    15. Laouali N,
    16. Severi G,
    17. Kaaks R,
    18. Katzke V,
    19. Schulze MB,
    20. Eichelmann F,
    21. Palli D,
    22. Grioni S,
    23. Panico S,
    24. Tumino R,
    25. Sacerdote C,
    26. Bueno-de-Mesquita B,
    27. Olsen KS,
    28. Sandanger TM,
    29. Nøst TH,
    30. Quirós JR,
    31. Bonet C,
    32. Barranco MR,
    33. Chirlaque MD,
    34. Ardanaz E,
    35. Sandsveden M,
    36. Manjer J,
    37. Vidman L,
    38. Rentoft M,
    39. Muller D,
    40. Tsilidis K,
    41. Heath AK,
    42. Keun H,
    43. Adamski J,
    44. Keski-Rahkonen P,
    45. Scalbert A,
    46. Gunter MJ,
    47. Viallon V
    : Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition. BMC Med 20(1): 351, 2022. DOI: 10.1186/s12916-022-02553-4
    OpenUrlCrossRefPubMed
  23. ↵
    1. Naudin S,
    2. Sampson JN,
    3. Moore SC,
    4. Albanes D,
    5. Freedman ND,
    6. Weinstein SJ,
    7. Stolzenberg-Solomon R
    : Lipidomics and pancreatic cancer risk in two prospective studies. Eur J Epidemiol 38(7): 783-793, 2023. DOI: 10.1007/s10654-023-01014-3
    OpenUrlCrossRefPubMed
  24. ↵
    1. Zhao Z,
    2. Xiao Y,
    3. Elson P,
    4. Tan H,
    5. Plummer SJ,
    6. Berk M,
    7. Aung PP,
    8. Lavery IC,
    9. Achkar JP,
    10. Li L,
    11. Casey G,
    12. Xu Y
    : Plasma lysophosphatidylcholine levels: potential biomarkers for colorectal cancer. J Clin Oncol 25(19): 2696-2701, 2007. DOI: 10.1200/JCO.2006.08.5571
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Sutphen R,
    2. Xu Y,
    3. Wilbanks GD,
    4. Fiorica J,
    5. Grendys EC, Jr.,
    6. LaPolla JP,
    7. Arango H,
    8. Hoffman MS,
    9. Martino M,
    10. Wakeley K,
    11. Griffin D,
    12. Blanco RW,
    13. Cantor AB,
    14. Xiao YJ,
    15. Krischer JP
    : Lysophospholipids are potential biomarkers of ovarian cancer. Cancer Epidemiol Biomarkers Prev 13(7): 1185-1191, 2004.
    OpenUrlAbstract/FREE Full Text
  26. ↵
    1. Matsuda A,
    2. Yamada M,
    3. Matsumoto S,
    4. Sakurazawa N,
    5. Yamada T,
    6. Matsutani T,
    7. Miyashita M,
    8. Uchida E
    : Lysophosphatidylcholine as a predictor of postoperative complications after colorectal cancer surgery. Surg Today 48(10): 936-943, 2018. DOI: 10.1007/s00595-018-1675-2
    OpenUrlCrossRefPubMed
Back to top

In this issue

Print
Download PDF
Article Alerts
Email Article
Citation Tools
Reprints and Permissions
Exploration of Lipid Mediators for Therapeutic Monitoring of Pancreatic Cancer Patients
NOBUHIKO NAKAGAWA, MASAMICHI HAYASHI, DAIGO KOBAYASHI, TOMOHISA OTSU, FUMINORI SONOHARA, KEISUKE KURIMOTO, HARUYOSHI TANAKA, YOSHIKUNI INOKAWA, HIDEKI TAKAMI, NORIFUMI HATTORI, MITSURO KANDA, CHIE TANAKA, GORO NAKAYAMA, YASUHIRO KODERA
Anticancer Research Apr 2025, 45 (4) 1343-1353; DOI: 10.21873/anticanres.17520
Twitter logo Facebook logo Mendeley logo

Jump to section

Keywords