Altered Plasma Fatty Acid Abundance Is Associated with Cachexia in Treatment-Naïve Pancreatic Cancer
by
, ,
Kristyn Gumpper-Fedus
1,2
,
Phil A. Hart
1,2,
Martha A. Belury
3,
Olivia Crowe
4,
Rachel M. Cole
3,
Valentina Pita Grisanti
1,2,
Niharika Badi
1,2,
Sophia Liva
2,5,
Alice Hinton
6,
Christopher Coss
2,5,
Mitchell L. Ramsey
1,2,
Anne Noonan
2,7,
Darwin L. Conwell
1,2 and
Zobeida Cruz-Monserrate
1,2,* 1
Division of Gastroenterology, Hepatology, and Nutrition, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
2
The James Comprehensive Cancer Center, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
3
Program of Human Nutrition, College of Education and Human Ecology, The Ohio State University, Columbus, OH 43210, USA
4
College of Medicine, The Ohio State University, Columbus, OH 43210, USA
5
Division of Pharmaceutics and Pharmacology, College of Pharmacy, The Ohio State University, Columbus, OH 43210, USA
6
Division of Biostatistics, College of Public Heath, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
7
Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA
*
Author to whom correspondence should be addressed.
Cells 2022, 11(5), 910; https://doi.org/10.3390/cells11050910
Submission received: 11 February 2022
/
Revised: 1 March 2022
/
Accepted: 4 March 2022
/
Published: 7 March 2022
(This article belongs to the Special Issue Cancer-Induced Cachexia)
Abstract
:Cachexia occurs in up to 80% of pancreatic ductal adenocarcinoma (PDAC) patients and is characterized by unintentional weight loss and tissue wasting. To understand the metabolic changes that occur in PDAC-associated cachexia, we compared the abundance of plasma fatty acids (FAs), measured by gas chromatography, of subjects with treatment-naïve metastatic PDAC with or without cachexia, defined as a loss of > 2% weight and evidence of sarcopenia (n = 43). The abundance of saturated, monounsaturated, and polyunsaturated FAs was not different between subjects with cachexia and those without. Oleic acid was significantly higher in subjects with cachexia (p = 0.0007) and diabetes (p = 0.015). Lauric (r = 0.592, p = 0.0096) and eicosapentaenoic (r = 0.564, p = 0.015) acids were positively correlated with age in cachexia patients. Subjects with diabetes (p = 0.021) or both diabetes and cachexia (p = 0.092) had low palmitic:oleic acid ratios. Linoleic acid was lower in subjects with diabetes (p = 0.018) and correlated with hemoglobin (r = 0.519, p = 0.033) and albumin (r = 0.577, p = 0.015) in subjects with cachexia. Oleic or linoleic acid may be useful treatment targets or biomarkers of cachexia in patients with metastatic PDAC, particularly those with diabetes.
Keywords:
pancreatic cancer; fatty acids; sarcopenia; diabetes; hemoglobin; albumin; oleic acid; linoleic acid1. Introduction
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with a dismal 5-year survival rate of less than 10% [1]. Cachexia, a multi-systemic, cancer-related metabolic disorder that includes weight loss (either ≥ 5% weight loss, a BMI < 20, or ≥ 2% weight loss with sarcopenia), tissue wasting, and loss of appetite, occurs in up to 80% of PDAC patients, being more common as cancer stage progresses [2,3,4,5]. Cachexia is associated with shorter survival, reduced efficacy of cancer therapy, dysregulated metabolism, impaired physical function, and reduced quality of life in PDAC patients.
The metabolic changes that occur in patients with cachexia stem from accelerated breakdown of adipose and muscle tissue, which leads to weight loss, elevated plasma lipoproteins, and release of circulating fatty acids (FAs) [6]. The release of FAs during tissue wasting can alter the normal plasma concentration of saturated (SFAs), monounsaturated (MUFAs), and polyunsaturated FAs (PUFAs), as described for other pancreatic inflammatory diseases [7]. Changes in FA abundance are associated with several metabolic disorders, including diabetes and metabolic syndrome [8,9]. FA release has also been correlated with changes in the inflammation status of patients with cachexia, which was defined by greater than 5% or 10% weight loss [10,11]. To counteract cachexia-induced weight loss, patients are often prescribed appetite stimulants, anti-inflammatory medications, nutritional supplements, and exercise [12,13]. Fish oils high in omega-3 PUFAs are often recommended as nutritional supplements and are reported to mitigate cachexia symptoms by reducing inflammation signaling, which improves cellular metabolism and increases muscle and fat mass. However, any improvements are mild, and compliance in clinical trials is low [14,15,16,17,18,19]. The limited effectiveness of current FA supplementation therapies may also be partially due to targeting FAs that are not dysregulated in all cachexia patient populations. Therefore, defining the changes in FA abundance that occur in cachexia patients is critical to the development of effective nutritional interventions.
The goal of this study was to identify changes in plasma FA abundance in metastatic PDAC associated with sarcopenic cachexia to better understand the metabolic changes that occur in cachexia and to discover new targets for cachexia treatments. We also evaluated the relationship between FA abundance and other clinical factors that may contribute to sarcopenia, including age, body mass index (BMI), diabetes status, and levels of hemoglobin and albumin.
2. Materials and Methods
2.1. Study Population
We performed an auxiliary study using baseline plasma samples from a cohort of treatment-naïve metastatic PDAC subjects enrolled in a phase 2, multicenter, randomized, and controlled study (NCT01280058) that occurred between February 2011 and February 2014 [20]. Subjects were selected for the study presented here based on the availability of clinical data, computed tomography (CT) scans, and plasma from the baseline blood draw of the clinical trial, resulting in a final cohort of 43 subjects (Figure 1). The original trial and current study were approved by The Ohio State University Wexner Medical Center Institutional Review Board (2010C0055) and followed the protocols and standards of the Declaration of Helsinki. Clinical data from study subjects were abstracted using a standardized form, including age at enrollment, sex, height, weight, CT images of the third lumbar vertebra, diabetes status, hemoglobin, and albumin.
2.2. Cachexia Classification
In this study, cachexia was determined using the definition published by Fearon et al. in 2011 [21]. We stratified subjects using a >2% weight loss cutoff and CT evidence of sarcopenia. CT scans were evaluated for skeletal muscle area at the third lumbar vertebra (L3) [22]. Images were analyzed for cross-sectional area (cm2) using the Slice-O-Matic software V4.3 (Tomovision, Montreal, Quebec, QC, Canada), as previously described [23,24]. For normalization, the skeletal muscle index (SMI) (cm2/m2) was calculated by dividing the cross-sectional area of the skeletal muscle by the height of the patient squared (m2). Sarcopenia was defined using the SMI stratified by sex and BMI. Subjects were classified with sarcopenia if they met the following criteria: SMI < 41 cm2/m2 for females with any BMI, < 43 cm2/m2 for males with a BMI < 24.9 kg/m2, and <53 cm2/m2 for males with a BMI > 25 kg/m2 [25]. Subjects with weight loss <2% or no CT evidence of sarcopenia were classified as subjects without cachexia (no cachexia), and subjects with both >2% weight loss and sarcopenia were classified as subjects with cachexia (cachexia).
2.3. Blood Collection and Processing
Random (i.e., non-fasting) blood collections were performed in all subjects at the baseline study visit in a tube containing sodium heparin as an anti-coagulant. Aliquots of plasma were separated and frozen in a −80 °C freezer until samples were batch analyzed for FA abundance.
2.4. Fatty Acid Analysis
Total lipids were extracted from plasma samples using the 2:1 chloroform:methanol method and then washed with 0.88% potassium chloride, as previously described [26]. FA methyl esters were then prepared using the 5% hydrochloric acid in methanol method [27], heated overnight at 76 °C, and extracted with hexane. FA methyl esters were analyzed by gas chromatography using a 30-m Omegawax 320 fused silica capillary column (Supelco Bellefonte, PA, USA). The oven temperature was set to 175 °C, heated at a rate of 3 °C/min until reaching 220 °C, and cooled at a rate of 5 °C/min until reaching 210 °C. The flow rate of carrier gas helium was set to 30 mL/min. FA measurements were recorded as a percentage of the total FAs identified (% area) [28] and compared to FA methyl ester standards (Matreya LLC, Pleasant Gap, PA, USA; Supelco, Bellefonte, PA, USA; and Nu-Check Prep Inc, Elysian, MN, USA). We assessed individual FAs as well as FAs grouped by saturation type abundance: SFA, MUFA, or PUFA.
2.5. Statistical Analysis
FA abundance was compared using an uncorrected Fishers Least Significant Difference (LSD) test. Saturation type, BMI, and the presence or absence of diabetes as indicated in the clinical chart was assessed using two-way ANOVA with Sidak’s multiple comparisons for pairwise differences. Differences in categorical variables were analyzed with chi-square tests. Pearson correlations of each FA with continuous variables, such as age, hemoglobin, albumin, or BMI, were performed. Positive R-values indicate positive correlations. Pearson correlations were used to determine the probability that the correlation observed occurred due to random sampling when p was equal to or less than 0.05. Data analyses were performed in Prism (GraphPad, version 9.0, San Diego, CA, USA).
3. Results
3.1. Characteristics of the Study Population
Of the 43 subjects in this study (Figure 1), 41.9% (n = 18) had cachexia and 58.1% (n = 25) did not. Age, sex, BMI, diabetes, hemoglobin, and albumin were not significantly different between the subjects with and without cachexia (Table 1). As expected, the percent weight loss and SMI were significantly different, as these were used for cachexia classification.
3.2. Oleic Acid Abundance Is Elevated in Subjects with Cachexia
We then investigated differences in plasma FA abundance between subjects with and without cachexia. There was no difference in overall FA abundance based on saturation type (Figure 2A). Oleic acid was the only MUFA that demonstrated higher abundance in subjects with cachexia (p = 0.0007) (Figure 2B). No individual SFAs or PUFAs exhibited changes in abundance between subjects with and without cachexia (Figure 2C,D).
3.3. Lauric and Eicosapentaenoic Acid Abundance Correlate with Age in Subjects with Cachexia
Aging impacts energy metabolism and modulates FA abundance in adipose tissue [29,30]. As PDAC is more common in older populations [31], we assessed whether plasma FA abundance was related to age and cachexia. We found that lauric (r = 0.592, p = 0.0096) and eicosapentaenoic (r = 0.564, p = 0.015) acids were positively correlated with age in cachexia patients, suggesting that the abundance of these FAs increases with age (Table 2).
3.4. BMI and Diabetes Alter Oleic and Linoleic Acid Levels in Subjects with Cachexia
Obesity is a strong risk factor for PDAC and is associated with changes in free FAs related to insulin resistance [32,33,34,35]. Additionally, sarcopenic obesity, where obesity occurs simultaneous with muscle wasting, occurs in up to 15% of patients with respiratory or gastrointestinal cancers [36]. Therefore, we assessed whether any FAs correlated with BMI. As BMI increased in subjects without cachexia, docosapentaenoic omega-6 (n6) acid abundance decreased (r = –0.550, p = 0.004) (Table 3). In subjects with cachexia, docosapentaenoic n6 acid abundance was no longer correlated with BMI. In contrast, vaccenic acid abundance increased as BMI increased in subjects with cachexia (r = 0.483, p = 0.042).
We also explored whether FA abundance was associated with diabetes status. Oleic acid was significantly higher in subjects with diabetes (p = 0.015) (Figure 3A). Additionally, linoleic acid was reduced overall in subjects with diabetes (p = 0.018) (Figure 3B). Gondoic acid was higher overall in subjects with diabetes compared to those without diabetes (p = 0.047) (Figure 3C). Similarly, α-linolenic acid was elevated overall in subjects with diabetes (p = 0.046) (Figure 3D). A low ratio of palmitic to oleic acid can indicate the presence of diabetes [37], which we confirmed in subjects with diabetes (p = 0.021) in our study. Interestingly, we observed a trend toward lower palmitic to oleic acid ratios in subjects with cachexia compared to those without cachexia (p = 0.092) (Figure 3E).
3.5. Some FAs Correlate with Other Indicators of Cachexia
Levels of hemoglobin and albumin are typically lower in patients with cachexia, and these clinical factors are used in some definitions of cachexia [38,39]. Additionally, albumin is an FA transporter in blood [38,39,40]. Although hemoglobin and albumin were not significantly lower in patients with cachexia (Table 1), we still assessed whether any FAs correlated with either clinical value. In subjects without cachexia, lauric acid negatively correlated (r = –0.423, p = 0.035) and gondoic acid positively correlated (r = 0.406, p = 0.044) with hemoglobin levels. In subjects with cachexia, palmitic (r = −0.489, p = 0.046) and linoleic (r = 0.519, p = 0.033) acids positively correlated with hemoglobin levels (Table 4). When comparing FA abundance with albumin (Table 5), lauric and vaccenic acids were strongly negatively correlated with albumin in subjects without cachexia (r = –0.533, p = 0.006 and r = –0.560, p = 0.004; respectively). Additionally, γ-linolenic acid was positively correlated with albumin in subjects without cachexia. In subjects with cachexia, vaccenic remained strongly negatively correlated with albumin (r= −0.646, p = 0.005), whereas linoleic was positively correlated with albumin (r = 0.577, p = 0.015).
4. Discussion
Although cachexia is prevalent among metastatic PDAC patients and worsens patient outcomes, the nutritional therapies used for cachexia are not highly effective at mitigating symptoms. Therefore, we conducted a small retrospective study to identify changes in plasma FA abundance in metastatic PDAC associated with sarcopenic cachexia to better understand the metabolic changes in cachexia and to discover new targets for cachexia treatments.
The omega-9 MUFA oleic acid was significantly elevated in subjects with cachexia compared to those without (Figure 2). This correlation is consistent with previous studies using alternative definitions of cachexia, such as ≥ 5% weight loss [10]. Additionally, we found that oleic acid was higher in patients with diabetes (Figure 3). Oleic acid contributes to insulin sensitivity, and its accumulation in muscle is lower in subjects with type 2 diabetes compared to those without [41,42]. Similar to metformin, which is commonly used to treat type 2 diabetes, oleic acid blocks the palmitic acid-mediated inhibition of adenosine monophosphate-activated protein kinase activity. If oleic acid uptake into metabolically active tissues, such as muscle, is inhibited in the context of a pancreatic disorder, such as diabetes, a similar phenomenon may occur in PDAC-associated cachexia, leading to elevated oleic acid levels in the plasma. Consistent with this hypothesis, we observed significantly lower palmitic:oleic acid ratios in subjects with cachexia and a trend for lower ratios in subjects with both cachexia and diabetes (Figure 3). The higher plasma levels of oleic acid in diabetic subjects and cachexia diabetic subjects in this cohort may result from the body compensating for malnutrition caused by PDAC or loss of oleic acid uptake into tissue, causing an accumulation in the plasma. A follow-up study on oleic acid metabolism or supplementation in malnutrition would elucidate this mechanism.
Omega-3 PUFA supplementation has been suggested for the treatment of cancer-related cachexia symptoms [14,16,43]. The absorption and metabolism of omega-3 PUFAs found in fish oils, such as eicosapentaenoic acid or docosahexaenoic acid, are theorized to improve cachexia by inhibiting proteolysis, lipolysis, and nuclear factor kappa B-induced inflammation [14,16,44]. However, some clinical trials indicate these FAs may not be as effective as once thought [45,46]. Indeed, we did not observe any differences in the abundance of PUFAs between subjects with cachexia compared to those without cachexia. However, we did find a strong positive correlation between age and eicosapentaenoic acid in subjects with cachexia only (Table 2). Previous studies have reported age-related increases in eicosapentaenoic and docosahexaenoic acids in the plasma fractions and red blood cells of “healthy” individuals [47,48]. Our results suggest that cachexia may intensify or accelerate age-related elevation of eicosapentaenoic acid, which warrants further investigation. The similarity of omega-3 PUFA abundance in our cohort provides some explanation for the ineffectiveness of omega-3 PUFA supplementation in metastatic PDAC subjects with cachexia.
Linoleic acid, an omega-6 PUFA, was significantly lower in subjects with diabetes and positively correlated with both albumin and hemoglobin in subjects with cachexia only (Figure 3, Table 4 and Table 5). High linoleic acid levels are associated with reduced risk in type 2 diabetes mellitus, improved insulin sensitivity, and reduced inflammation [49]. In addition to improving glycemic control, linoleic acid supplementation in women with type 2 diabetes mellitus increases lean mass and reduces trunk fat mass compared to conjugated linoleic acid supplementation [50], suggesting a potential benefit in diabetic PDAC patients similar to the present cohort. Mitochondrial dysfunction also contributes to insulin resistance and type 2 diabetes mellitus [41,51]. Linoleic acid improves the fatty acid composition of mitochondrial cardiolipins by increasing the levels of tetralinoleoyl (L4) cardiolipins, which are beneficial to mitochondrial function [52]. Although hemoglobin and albumin are reportedly lower in subjects with cachexia, we did not observe any differences in our cohort between subjects with cachexia and those without. However, we did observe a positive correlation between linoleic acid and these factors. Therefore, increasing dietary linoleic acid may provide nutritional support for patients experiencing cachexia.
This study utilized a unique treatment-naïve metastatic PDAC patient population to identify changes in FA abundance, albeit with a few limitations. Due to the retrospective study design, we were unable to completely characterize all aspects of cachexia, such as muscle function and appetite [38]. Similarly, FA analyses were performed using available non-fasted plasma samples instead of red blood cells, which are resistant to day-to-day changes in FA abundance caused by diet [53]. Additionally, we could not assess the impact of exocrine pancreatic function, physical activity, or diet on FA composition due to lack of survey data. Future studies of cachexia in larger PDAC patient populations with and without metastasis should be designed to collect this information to better inform the overall metabolic status of each individual and better track these metabolic changes across the stages of disease.
Despite the limitations of this retrospective study, we found differences in FA abundance that were associated with sarcopenic cachexia in treatment-naïve metastatic PDAC. A more extensive prospective study that addresses diet and exocrine function is necessary to confirm the FA abundance patterns identified here and to determine whether FAs are viable as novel therapies for cancer-associated sarcopenic cachexia.
Author Contributions
Conceptualization, K.G.-F., P.A.H., M.A.B. and Z.C.-M.; methodology, K.G.-F., P.A.H., M.A.B. and Z.C.-M.; formal analysis, K.G.-F., P.A.H., M.A.B., O.C., R.M.C., V.P.G., N.B., S.L., A.H. and Z.C.-M.; investigation, K.G.-F., P.A.H., M.A.B., O.C., R.M.C., V.P.G., N.B., S.L., A.H. and Z.C.-M.; resources, C.C., M.L.R., A.N., D.L.C. and Z.C.-M.; data curation, K.G.-F., P.A.H., O.C., N.B., S.L., M.L.R. and Z.C.-M.; writing—original draft preparation, K.G.-F., P.A.H., M.A.B. and Z.C.-M.; writing—review and editing, K.G.-F., P.A.H., M.A.B., O.C., R.M.C., V.P.G., N.B., S.L., A.H., C.C., M.L.R., A.N., D.L.C. and Z.C.-M. All authors have read and agreed to the published version of the manuscript.
Funding
Research in this publication was supported by grants from the National Center for Advancing Translational Sciences (TL1TR002735 to K.G.-F.), the National Cancer Institute (R21CA256409 to Z.C.-M., P.A.H., M.A.B., and C.C. and R21209566 to M.A.B.), the USDA National Institute of Food and Agriculture Hatch Project (M.A.B.), and by the National Cancer Institute and National Institute of Diabetes and Digestive and Kidney Diseases (U01DK108327 to D.L.C., Z.C.-M., P.A.H.). The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the Ohio State University (2010C0055 February 22, 2010).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data presented in this study are contained within the article.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Siegel, R.L.; Miller, K.D.; Fuchs, H.E.; Jemal, A. Cancer Statistics, 2021. CA Cancer J. Clin. 2021, 71, 7–33. [Google Scholar] [CrossRef] [PubMed]
- Fearon, K.C.; Voss, A.C.; Hustead, D.S. Definition of cancer cachexia: Effect of weight loss, reduced food intake, and systemic inflammation on functional status and prognosis. Am. J. Clin. Nutr. 2006, 83, 1345–1350. [Google Scholar] [CrossRef]
- Sun, L.; Quan, X.-Q.; Yu, S. An Epidemiological Survey of Cachexia in Advanced Cancer Patients and Analysis on Its Diagnostic and Treatment Status. Nutr. Cancer 2015, 67, 1056–1062. [Google Scholar] [CrossRef]
- Kays, J.K.; Shahda, S.; Stanley, M.; Bell, T.; O′Neill, B.H.; Kohli, M.D.; Couch, M.E.; Koniaris, L.G.; Zimmers, T.A. Three cachexia phenotypes and the impact of fat-only loss on survival in FOLFIRINOX therapy for pancreatic cancer. J. Cachexia Sarcopenia Muscle 2018, 9, 673–684. [Google Scholar] [CrossRef] [PubMed]
- von Haehling, S.; Anker, S.D. Cachexia as a major underestimated and unmet medical need: Facts and numbers. J. Cachexia Sarcopenia Muscle 2010, 1, 1–5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Felix, K.; Fakelman, F.; Hartmann, D.; Giese, N.A.; Gaida, M.M.; Schnölzer, M.; Flad, T.; Büchler, M.W.; Werner, J. Identification of serum proteins involved in pancreatic cancer cachexia. Life Sci. 2010, 88, 218–225. [Google Scholar] [CrossRef] [PubMed]
- Zeman, M.; Macášek, J.; Burda, M.; Tvrzická, E.; Vecka, M.; Krechler, T.; Staňková, B.; Hrabák, P.; Žák, A. Chronic pancreatitis and the composition of plasma phosphatidylcholine fatty acids. Prostaglandins Leukot. Essent. Fat. Acids 2016, 108, 38–44. [Google Scholar] [CrossRef] [PubMed]
- Fernández-Real, J.-M.; Broch, M.; Vendrell, J.; Ricart, W. Insulin Resistance, Inflammation, and Serum Fatty Acid Composition. Diabetes Care 2003, 26, 1362–1368. [Google Scholar] [CrossRef] [Green Version]
- Klein-Platat, C.; Drai, J.; Oujaa, M.; Schlienger, J.-L.; Simon, C. Plasma fatty acid composition is associated with the metabolic syndrome and low-grade inflammation in overweight adolescents. Am. J. Clin. Nutr. 2005, 82, 1178–1184. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Riccardi, D.M.D.R.; Das Neves, R.X.; De Matos-Neto, E.M.; Camargo, R.G.; Lima, J.D.C.C.; Radloff, K.; Alves, M.J.; Costa, R.G.F.; Tokeshi, F.; Otoch, J.P.; et al. Plasma Lipid Profile and Systemic Inflammation in Patients with Cancer Cachexia. Front. Nutr. 2020, 7, 4. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Han, J.; Lu, C.; Meng, Q.; Halim, A.; Yean, T.J.; Wu, G. Plasma concentration of interleukin-6 was upregulated in cancer cachexia patients and was positively correlated with plasma free fatty acid in female patients. Nutr. Metab. 2019, 16, 80–88. [Google Scholar] [CrossRef] [PubMed]
- Naito, T. Emerging Treatment Options for Cancer-Associated Cachexia: A Literature Review. Ther. Clin. Risk Manag. 2019, 15, 1253–1266. [Google Scholar] [CrossRef] [Green Version]
- Yakovenko, A.; Cameron, M.; Trevino, J.G. Molecular therapeutic strategies targeting pancreatic cancer induced cachexia. World J. Gastrointest. Surg. 2018, 10, 95–106. [Google Scholar] [CrossRef] [PubMed]
- Gorjão, R.; dos Santos, C.M.M.; Serdan, T.D.A.; Diniz, V.L.S.; Alba-Loureiro, T.C.; Cury-Boaventura, M.F.; Hatanaka, E.; Levada-Pires, A.C.; Sato, F.T.; Pithon-Curi, T.C.; et al. New insights on the regulation of cancer cachexia by N-3 polyunsaturated fatty acids. Pharmacol. Ther. 2018, 196, 117–134. [Google Scholar] [CrossRef]
- Garcia, J.M.; Shamliyan, T.A. Omega-3 Fatty Acids in Patients with Anorexia-Cachexia Syndrome Associated with Malignancy and Its Treatments. Am. J. Med. 2017, 130, 1151–1155. [Google Scholar] [CrossRef] [PubMed]
- Wijler, L.A.; Raats, D.A.; Elias, S.G.; Dijk, F.J.; Quirindongo, H.; May, A.M.; Furber, M.J.; Dorresteijn, B.; van Dijk, M.; Kranenburg, O. Specialized nutrition improves muscle function and physical activity without affecting chemotherapy efficacy in C26 tumour-bearing mice. J. Cachexia Sarcopenia Muscle 2021, 12, 796–810. [Google Scholar] [CrossRef] [PubMed]
- Dewey, A.; Baughan, C.; Dean, T.; Higgins, B.; Johnson, I. Eicosapentaenoic acid (EPA, an omega-3 fatty acid from fish oils) for the treatment of cancer cachexia. Cochrane Database Syst. Rev. 2007, 2007, CD004597. [Google Scholar] [CrossRef] [PubMed]
- Patursson, P.; Møller, G.; Muhic, A.; Andersen, J.R. N-3 fatty acid EPA supplementation in cancer patients receiving abdominal radiotherapy—A randomised controlled trial. Clin. Nutr. ESPEN 2021, 43, 130–136. [Google Scholar] [CrossRef]
- McGlory, C.; Calder, P.C.; Nunes, E.A. The Influence of Omega-3 Fatty Acids on Skeletal Muscle Protein Turnover in Health, Disuse, and Disease. Front. Nutr. 2019, 6, 144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Noonan, A.M.; Farren, M.R.; Geyer, S.M.; Huang, Y.; Tahiri, S.; Ahn, D.; Mikhail, S.; Ciombor, K.K.; Pant, S.; Aparo, S.; et al. Randomized Phase 2 Trial of the Oncolytic Virus Pelareorep (Reolysin) in Upfront Treatment of Metastatic Pancreatic Adenocarcinoma. Mol. Ther. 2016, 24, 1150–1158. [Google Scholar] [CrossRef] [Green Version]
- Fearon, K.; Strasser, F.; Anker, S.D.; Bosaeus, I.; Bruera, E.; Fainsinger, R.L.; Jatoi, A.; Loprinzi, C.; MacDonald, N.; Mantovani, G.; et al. Definition and classification of cancer cachexia: An international consensus. Lancet Oncol. 2011, 12, 489–495. [Google Scholar] [CrossRef]
- Mourtzakis, M.; Prado, C.M.; Lieffers, J.R.; Reiman, T.; McCargar, L.J.; Baracos, V.E. A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl. Physiol. Nutr. Metab. 2008, 33, 997–1006. [Google Scholar] [CrossRef] [PubMed]
- Heymsfield, S.B.; Smith, R.; Aulet, M.; Bensen, B.; Lichtman, S.; Wang, J.; Pierson, R.N. Appendicular skeletal muscle mass: Measurement by dual-photon absorptiometry. Am. J. Clin. Nutr. 1990, 52, 214–218. [Google Scholar] [CrossRef]
- Dennis, R.A.; Long, D.E.; Landes, R.D.; Padala, K.P.; Padala, P.; Garner, K.K.; Wise, J.N.; Peterson, C.A.; Sullivan, D.H. Tutorial for using SliceOmatic to calculate thigh area and composition from computed tomography images from older adults. PLoS ONE 2018, 13, e0204529. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Martin, L.; Birdsell, L.; MacDonald, N.; Reiman, T.; Clandinin, M.T.; McCargar, L.J.; Murphy, R.; Ghosh, S.; Sawyer, M.B.; Baracos, V.E. Cancer Cachexia in the Age of Obesity: Skeletal Muscle Depletion Is a Powerful Prognostic Factor, Independent of Body Mass Index. J. Clin. Oncol. 2013, 31, 1539–1547. [Google Scholar] [CrossRef] [PubMed]
- Folch, J.; Lees, M.; Sloane Stanley, G.H. A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem. 1957, 226, 497–509. [Google Scholar] [CrossRef]
- Stoffel, W.; Chu, F.; Ahrens, E.H. Analysis of Long-Chain Fatty Acids by Gas-Liquid Chromatography–Micromethod for Preparation of Methyl Esters. Anal. Chem. 1959, 31, 307–308. [Google Scholar] [CrossRef]
- Yee, L.D.; Lester, J.L.; Cole, R.M.; Richardson, J.R.; Hsu, J.C.; Li, Y.; Lehman, A.; A Belury, M.; Clinton, S.K. ω-3 Fatty acid supplements in women at high risk of breast cancer have dose-dependent effects on breast adipose tissue fatty acid composition. Am. J. Clin. Nutr. 2010, 91, 1185–1194. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bolton-Smith, C.; Woodward, M.; Tavendale, R. Evidence for age-related differences in the fatty acid composition of human adipose tissue, independent of diet. Eur. J. Clin. Nutr. 1997, 51, 619–624. [Google Scholar] [CrossRef] [Green Version]
- de Groot, R.H.M.; van Boxtel, M.P.J.; Schiepers, O.J.G.; Hornstra, G.; Jolles, J. Age dependence of plasma phospholipid fatty acid levels: Potential role of linoleic acid in the age-associated increase in docosahexaenoic acid and eicosapentaenoic acid concentrations. Br. J. Nutr. 2009, 102, 1058–1064. [Google Scholar] [CrossRef] [Green Version]
- Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Eibl, G.; Cruz-Monserrate, Z.; Korc, M.; Petrov, M.S.; Goodarzi, M.O.; Fisher, W.E.; Habtezion, A.; Lugea, A.; Pandol, S.J.; Hart, P.A.; et al. Diabetes Mellitus and Obesity as Risk Factors for Pancreatic Cancer. J. Acad. Nutr. Diet. 2018, 118, 555–567. [Google Scholar] [CrossRef] [PubMed]
- Abbruzzese, J.L.; Andersen, D.K.; Borrebaeck, C.A.; Chari, S.T.; Costello, E.; Cruz-Monserrate, Z.; Eibl, G.; Engleman, E.G.; Fisher, W.E.; Habtezion, A.; et al. The Interface of Pancreatic Cancer with Diabetes, Obesity, and Inflammation: Research Gaps and Opportunities. Pancreas 2018, 47, 516–525. [Google Scholar] [CrossRef]
- Boden, G. Obesity, insulin resistance and free fatty acids. Curr. Opin. Endocrinol. Diabetes Obes. 2011, 18, 139–143. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fryk, E.; Olausson, J.; Mossberg, K.; Strindberg, L.; Schmelz, M.; Brogren, H.; Gan, L.-M.; Piazza, S.; Provenzani, A.; Becattini, B.; et al. Hyperinsulinemia and insulin resistance in the obese may develop as part of a homeostatic response to elevated free fatty acids: A mechanistic case-control and a population-based cohort study. eBioMedicine 2021, 65, 103264. [Google Scholar] [CrossRef]
- Prado, C.M.; Lieffers, J.R.; McCargar, L.J.; Reiman, T.; Sawyer, M.B.; Martin, L.; Baracos, V.E. Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: A population-based study. Lancet Oncol. 2008, 9, 629–635. [Google Scholar] [CrossRef]
- Kien, C.L.; Bunn, J.Y.; Poynter, M.E.; Stevens, R.; Bain, J.; Ikayeva, O.; Fukagawa, N.K.; Champagne, C.M.; Crain, K.I.; Koves, T.R.; et al. A Lipidomics Analysis of the Relationship Between Dietary Fatty Acid Composition and Insulin Sensitivity in Young Adults. Diabetes 2013, 62, 1054–1063. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Evans, W.J.; Morley, J.E.; Argilés, J.; Bales, C.; Baracos, V.; Guttridge, D.; Jatoi, A.; Kalantar-Zadeh, K.; Lochs, H.; Mantovani, G.; et al. Cachexia: A new definition. Clin. Nutr. 2008, 27, 793–799. [Google Scholar] [CrossRef]
- Schwarz, S.; Prokopchuk, O.; Esefeld, K.; Gröschel, S.; Bachmann, J.; Lorenzen, S.; Friess, H.; Halle, M.; Martignoni, M.E. The clinical picture of cachexia: A mosaic of different parameters (experience of 503 patients). BMC Cancer 2017, 17, 130. [Google Scholar] [CrossRef] [Green Version]
- van der Vusse, G.J. Albumin as Fatty Acid Transporter. Drug Metab. Pharmacokinet. 2009, 24, 300–307. [Google Scholar] [CrossRef]
- Palomer, X.; Pizarro-Delgado, J.; Barroso, E.; Vázquez-Carrera, M. Palmitic and Oleic Acid: The Yin and Yang of Fatty Acids in Type 2 Diabetes Mellitus. Trends Endocrinol. Metab. 2018, 29, 178–190. [Google Scholar] [CrossRef] [PubMed]
- Bakke, S.S.; Feng, Y.Z.; Nikolić, N.; Kase, E.T.; Moro, C.; Stensrud, C.; Damlien, L.; Ludahl, M.O.; Sandbu, R.; Solheim, B.M.; et al. Myotubes from Severely Obese Type 2 Diabetic Subjects Accumulate Less Lipids and Show Higher Lipolytic Rate than Myotubes from Severely Obese Non-Diabetic Subjects. PLoS ONE 2015, 10, e0119556. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Freitas, R.D.S.; Muradás, T.C.; Dagnino, A.P.A.; Rost, F.L.; Costa, K.M.; Venturin, G.T.; Greggio, S.; Da Costa, J.C.; Campos, M.M. Targeting FFA1 and FFA4 receptors in cancer-induced cachexia. Am. J. Physiol. Metab. 2020, 319, E877–E892. [Google Scholar] [CrossRef]
- Werner, K.; De Gaudry, D.K.; Taylor, L.A.; Keck, T.; Unger, C.; Hopt, U.T.; Massing, U. Dietary supplementation with n-3-fatty acids in patients with pancreatic cancer and cachexia: Marine phospholipids versus fish oil-a randomized controlled double-blind trial. Lipids Health Dis. 2017, 16, 104. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fearon, K.C.; Barber, M.D.; Moses, A.G.; Ahmedzai, S.; Taylor, G.S.; Tisdale, M.J.; Murray, G. Double-Blind, Placebo-Controlled, Randomized Study of Eicosapentaenoic Acid Diester in Patients with Cancer Cachexia. J. Clin. Oncol. 2006, 24, 3401–3407. [Google Scholar] [CrossRef] [PubMed]
- Jatoi, A.; Rowland, K.; Loprinzi, C.L.; Sloan, J.A.; Dakhil, S.R.; Macdonald, N.; Gagnon, B.; Novotny, P.J.; Mailliard, J.A.; Bushey, T.I.; et al. An Eicosapentaenoic Acid Supplement Versus Megestrol Acetate Versus Both for Patients with Cancer-Associated Wasting: A North Central Cancer Treatment Group and National Cancer Institute of Canada Collaborative Effort. J. Clin. Oncol. 2004, 22, 2469–2476. [Google Scholar] [CrossRef]
- Sands, S.A.; Reid, K.J.; Windsor, S.L.; Harris, W.S. The impact of age, body mass index, and fish intake on the EPA and DHA content of human erythrocytes. Lipids 2005, 40, 343–347. [Google Scholar] [CrossRef]
- Walker, C.G.; Browning, L.M.; Mander, A.P.; Madden, J.; West, A.L.; Calder, P.C.; Jebb, S.A. Age and sex differences in the incorporation of EPA and DHA into plasma fractions, cells and adipose tissue in humans. Br. J. Nutr. 2013, 111, 679–689. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Belury, M.A.; Cole, R.M.; Snoke, D.B.; Banh, T.; Angelotti, A. Linoleic acid, glycemic control and Type 2 diabetes. Prostaglandins Leukot. Essent. Fat. Acids 2018, 132, 30–33. [Google Scholar] [CrossRef] [PubMed]
- E Norris, L.; Collene, A.L.; Asp, M.L.; Hsu, J.C.; Liu, L.-F.; Richardson, J.R.; Li, D.; Bell, D.; Osei, K.; Jackson, R.D.; et al. Comparison of dietary conjugated linoleic acid with safflower oil on body composition in obese postmenopausal women with type 2 diabetes mellitus. Am. J. Clin. Nutr. 2009, 90, 468–476. [Google Scholar] [CrossRef]
- Yaribeygi, H.; Farrokhi, F.R.; Butler, A.E.; Sahebkar, A. Insulin resistance: Review of the underlying molecular mechanisms. J. Cell. Physiol. 2018, 234, 8152–8161. [Google Scholar] [CrossRef] [PubMed]
- Cole, R.; Angelotti, A.; Belury, M. The Impact of Consuming Healthy Cookies Enriched with Linoleic Acid for Two Weeks on Blood Fatty Acid Profiles (P08-099-19). Curr. Dev. Nutr. 2019, 3. [Google Scholar] [CrossRef]
- Sailaja, Y.; Baskar, R.; Rao, C.S.; Saralakumari, D. Membrane lipids and protein-bound carbohydrates status during the maturation of reticulocytes to erythrocytes in type 2 diabetics. Clin. Chim. Acta 2004, 341, 185–192. [Google Scholar] [CrossRef] [PubMed]
Figure 1.
Subject selection flow chart. Created using Biorender.com.
Figure 2.
Fatty acid (FA) abundance in pancreatic ductal adenocarcinoma subjects based on cachexia. (A) FA abundance presented as % area and grouped by FA saturation type. Two-way ANOVA used to assess significance. (B) Individual SFA, (C) MUFAs, or (D) PUFAs assessed by two-way ANOVAs with multiple comparisons and no corrections. Data are presented as mean ± SD. *** p ≤ 0.001.
Figure 2.
Fatty acid (FA) abundance in pancreatic ductal adenocarcinoma subjects based on cachexia. (A) FA abundance presented as % area and grouped by FA saturation type. Two-way ANOVA used to assess significance. (B) Individual SFA, (C) MUFAs, or (D) PUFAs assessed by two-way ANOVAs with multiple comparisons and no corrections. Data are presented as mean ± SD. *** p ≤ 0.001.
Figure 3.
Fatty acid (FA) abundance relative to diabetes status in subjects with pancreatic ductal adenocarcinoma and cachexia. Percent area of (A) oleic, (B) linoleic, (C) gondoic, (D) α-linolenic acids were compared by cachexia and diabetes using a two-way ANOVA with Sidak’s correction for multiple comparison. (E) Ratio of the % area of palmitic acid to oleic acid using a t-test. Data are presented as mean ± SD. FAs were selected based on significant differences. * p ≤ 0.05.
Figure 3.
Fatty acid (FA) abundance relative to diabetes status in subjects with pancreatic ductal adenocarcinoma and cachexia. Percent area of (A) oleic, (B) linoleic, (C) gondoic, (D) α-linolenic acids were compared by cachexia and diabetes using a two-way ANOVA with Sidak’s correction for multiple comparison. (E) Ratio of the % area of palmitic acid to oleic acid using a t-test. Data are presented as mean ± SD. FAs were selected based on significant differences. * p ≤ 0.05.
Table 1.
Baseline characteristics of the study subjects.
| No Cachexia (n = 25) | Cachexia (n = 18) | p-Value | |
|---|---|---|---|
| Mean age (years) | 62.9 ± 11.1 | 60.5 ± 10.5 | 0.480 |
| Male sex, n (%) | 18 (72.0) | 10 (55.6) | 0.338 |
| % Weight loss | 4.3 ± 7.5 | 11.1 ± 8.5 | 0.002 * |
| Skeletal muscle index (SMI) | 49.6 ± 9.3 | 40.9 ± 5.9 | 0.0002 * |
| Body mass index (BMI) (kg/m2) 18.5–24.9 (% Normal) 25–29.9 (% Overweight) ≥ 30 (% Obese) | 7 (28.0) 11 (44.0) 7 (28.0) | 5 (27.8) 8 (44.4) 5 (27.8) | 0.999 |
| Diabetes present, n (%) | 5 (20) | 6 (33.3) | 0.481 |
| Hemoglobin (g/dL) | 13.5 ± 1.8 | 13.5 ± 1.1 | 0.953 |
| Albumin (g/dL) | 3.9 ± 0.6 | 3.9 ± 0.4 | 0.652 |
Starred p-values indicate statistical significance < 0.05 by Student’s t-test.
Table 2.
Correlation between FA abundance and age stratified by cachexia status.
| Fatty Acid | No Cachexia R | Cachexia R |
|---|---|---|
| Lauric | 0.364 | 0.592 ** |
| Myristic | 0.032 | 0.307 |
| Palmitic | 0.281 | −0.030 |
| Palmitoleic | −0.300 | −0.115 |
| Stearic | −0.071 | 0.381 |
| Oleic | −0.187 | −0.083 |
| Vaccenic | −0.037 | −0.204 |
| Linoleic | −0.048 | −0.306 |
| γ-Linolenic | −0.055 | 0.271 |
| α-Linolenic | −0.002 | 0.137 |
| Arachidic | 0.116 | 0.107 |
| Gondoic | 0.029 | −0.169 |
| Eicosadienoic | −0.170 | −0.058 |
| Dihomo-γ-Linolenic | −0.109 | 0.213 |
| Arachidonic | 0.087 | 0.349 |
| Eicosapentaenoic | 0.364 | 0.564 * |
| Behenic | −0.086 | 0.094 |
| Adrenic | −0.053 | 0.151 |
| Docosapentaenoic n6 | 0.059 | 0.130 |
| Docosapentaneoic n3 | 0.323 | 0.378 |
| Lignoceric | 0.114 | 0.083 |
| Docosahexaneoic | 0.355 | 0.318 |
Starred numbers indicate statistical significance. * p < 0.05, ** p < 0.01.
Table 3.
Correlation between FA abundance and BMI stratified by cachexia status.
| Fatty Acid | No Cachexia R | Cachexia R |
|---|---|---|
| Lauric | −0.250 | −0.287 |
| Myristic | 0.199 | −0.281 |
| Palmitic | −0.045 | 0.162 |
| Palmitoleic | −0.99 | 0.291 |
| Stearic | −0.099 | −0.101 |
| Oleic | 0.070 | 0.426 |
| Vaccenic | −0.014 | 0.483 * |
| Linoleic | 0.116 | −0.258 |
| γ-Linolenic | −0.166 | −0.293 |
| α-Linolenic | 0.386 | −0.052 |
| Arachidic | −0.187 | 0.094 |
| Gondoic | −0.026 | 0.304 |
| Eicosadienoic | 0.013 | −0.207 |
| Dihomo-γ-Linolenic | −0.255 | −0.204 |
| Arachidonic | −0.152 | −0.169 |
| Eicosapentaenoic | 0.009 | −0.420 |
| Behenic | −0.301 | −0.201 |
| Adrenic | −0.37 | −0.067 |
| Docosapentaenoic n6 | −0.550 * | −0.135 |
| Docosapentaneoic n3 | −0.342 | −0.334 |
| Lignoceric | −0.258 | −0.433 |
| Docosahexaneoic | 0.074 | −0.111 |
Bolded numbers indicate statistical significance. * p < 0.05.
Table 4.
Correlation between FA abundance and hemoglobin stratified by cachexia status.
| Fatty Acid | No Cachexia R | Cachexia R |
|---|---|---|
| Lauric | −0.423 * | 0.143 |
| Myristic | −0.274 | −0.123 |
| Palmitic | −0.187 | −0.489 * |
| Palmitoleic | −0.270 | −0.102 |
| Stearic | −0.089 | 0.003 |
| Oleic | −0.004 | −0.419 |
| Vaccenic | −0.130 | 0.048 |
| Linoleic | 0.232 | 0.519 * |
| γ-Linolenic | 0.023 | −0.121 |
| α-Linolenic | −0.212 | 0.346 |
| Arachidic | −0.024 | −0.379 |
| Gondoic | 0.406 * | −0.070 |
| Eicosadienoic | 0.248 | 0.229 |
| Dihomo-γ-Linolenic | −0.127 | 0.186 |
| Arachidonic | −0.109 | 0.014 |
| Eicosapentaenoic | 0.074 | −0.145 |
| Behenic | 0.304 | −0.052 |
| Adrenic | −0.182 | −0.364 |
| Docosapentaenoic n6 | −0.392 | −0.182 |
| Docosapentaneoic n3 | −0.209 | 0.050 |
| Lignoceric | 0.178 | 0.139 |
| Docosahexaneoic | 0.021 | −0.007 |
Starred numbers indicate statistical significance. * p < 0.05.
Table 5.
Correlation between FA abundance and albumin stratified by cachexia status.
| Fatty Acid | No Cachexia R | Cachexia R |
|---|---|---|
| Lauric | −0.533 ** | 0.006 |
| Myristic | −0.010 | 0.010 |
| Palmitic | −0.181 | −0.225 |
| Palmitoleic | 0.049 | −0.276 |
| Stearic | −0.171 | −0.058 |
| Oleic | −0.099 | −0.361 |
| Vaccenic | −0.560 ** | −0.646 ** |
| Linoleic | 0.116 | 0.577 * |
| γ-Linolenic | 0.464 * | −0.432 |
| α-Linolenic | 0.367 | 0.014 |
| Arachidic | −0.184 | −0.293 |
| Gondoic | −0.026 | −0.025 |
| Eicosadienoic | −0.056 | −0.278 |
| Dihomo-γ-Linolenic | 0.098 | −0.217 |
| Arachidonic | 0.167 | −0.018 |
| Eicosapentaenoic | 0.102 | −0.388 |
| Behenic | 0.021 | 0.175 |
| Adrenic | 0.221 | −0.346 |
| Docosapentaenoic n6 | −0.008 | −0.132 |
| Docosapentaneoic n3 | 0.132 | −0.134 |
| Lignoceric | 0.048 | 0.481 |
| Docosahexaneoic | −0.090 | −0.049 |
Starred numbers indicate statistical significance. * p < 0.05, ** p < 0.01.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Gumpper-Fedus, K.; Hart, P.A.; Belury, M.A.; Crowe, O.; Cole, R.M.; Pita Grisanti, V.; Badi, N.; Liva, S.; Hinton, A.; Coss, C.; et al. Altered Plasma Fatty Acid Abundance Is Associated with Cachexia in Treatment-Naïve Pancreatic Cancer. Cells 2022, 11, 910. https://doi.org/10.3390/cells11050910
AMA Style
Gumpper-Fedus K, Hart PA, Belury MA, Crowe O, Cole RM, Pita Grisanti V, Badi N, Liva S, Hinton A, Coss C, et al. Altered Plasma Fatty Acid Abundance Is Associated with Cachexia in Treatment-Naïve Pancreatic Cancer. Cells. 2022; 11(5):910. https://doi.org/10.3390/cells11050910
Chicago/Turabian StyleGumpper-Fedus, Kristyn, Phil A. Hart, Martha A. Belury, Olivia Crowe, Rachel M. Cole, Valentina Pita Grisanti, Niharika Badi, Sophia Liva, Alice Hinton, Christopher Coss, and et al. 2022. "Altered Plasma Fatty Acid Abundance Is Associated with Cachexia in Treatment-Naïve Pancreatic Cancer" Cells 11, no. 5: 910. https://doi.org/10.3390/cells11050910
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
