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Erythrocyte and Platelet Phospholipid Fatty Acids asMarkers of Advanced Non-Small Cell Lung Cancer:Comparison with Serum Levels of Sialic Acid, TPS andCyfra 21-1Javier de Castro a; Marina C. Rodríguez b; Vicenta S. Martínez-Zorzano c; ÁngelHernández-Hernández d; Marcial Llanillo d; Jesús Sánchez-Yagüe da Radiology Service, Santísima Trinidad Foundation Hospital, Salamanca, Spainb Neumosalud, Santísima Trinidad Foundation Hospital, Salamanca, Spainc Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo,Spaind Department of Biochemistry and Molecular Biology, University of Salamanca,Salamanca, Spain

Online Publication Date: 01 May 2008To cite this Article: de Castro, Javier, Rodríguez, Marina C., Martínez-Zorzano, Vicenta S., Hernández-Hernández,Ángel, Llanillo, Marcial and Sánchez-Yagüe, Jesús (2008) 'Erythrocyte and Platelet Phospholipid Fatty Acids as Markersof Advanced Non-Small Cell Lung Cancer: Comparison with Serum Levels of Sialic Acid, TPS and Cyfra 21-1', CancerInvestigation, 26:4, 407 - 418To link to this article: DOI: 10.1080/07357900701788114URL: http://dx.doi.org/10.1080/07357900701788114

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ISSN: 0735-7907 print / 1532-4192 onlineCopyright c© Informa Healthcare USA, Inc.DOI: 10.1080/07357900701788114

ORIGINAL ARTICLEImaging, Diagnosis, Prognosis

Erythrocyte and Platelet Phospholipid Fatty Acids asMarkers of Advanced Non-Small Cell Lung Cancer:Comparison with Serum Levels of Sialic Acid, TPS

and Cyfra 21-1Javier de Castro,1 Marina C. Rodrıguez,2 Vicenta S. Martınez-Zorzano,3 Angel Hernandez-Hernandez,4

Marcial Llanillo,4 and Jesus Sanchez-Yague4

Radiology Service,1 Neumosalud,2 Santısima Trinidad Foundation Hospital, Salamanca, Spain.Department of Biochemistry, Genetics and Immunology, University of Vigo, Vigo, Spain.3

Department of Biochemistry and Molecular Biology, University of Salamanca, Salamanca, Spain.4

ABSTRACT

The phospholipid fatty acid profiles of erythrocytes and platelets from fifty patients withadvanced non-small cell lung cancer were investigated using gas chromatography/mass spec-trometry, followed by “ROC” curves analysis to gain novel biomarker information. Sialic acidand cytokeratins were also examined. Potentially useful fatty acid markers: Erythrocytes: phos-phatidylcholine, 18:2n6 and 20:4n6; phosphatidylethanolamine, 22:4n6 and 22:6n3 + 24:1n9.Platelets: phosphatidylcholine, 22.0; phosphatidylethanolamine, 22:5n3 + 24:0. At the cut-off value to obtain maximum accuracy, the best biomarkers were found in platelets: phos-phatidylserine + phosphatidylinositol (PS + PI), 21:0; sphyngomyelin: 20:1n9 and 22:1n9. Allthese fatty acids showed similar/higher diagnostic yields than the commonly used markerssialic acid or cytokeratins.

INTRODUCTION

There is growing interest in finding new substances or pa-rameters that could be used as tumor markers for neoplasticdiseases in order to gain more knowledge about these diseasesand improve therapeutic approaches.

Keywords: Tumor markers, Non-small cell lung cancer, Fatty acids,Sialic acids, Cytokeratins, Erythrocyte, Platelet.This work has been supported in part by FIS PI020081 and theJunta de Castilla y Leon (SA 126A07 and Biomedicina,SAN191/SA29/06).Correspondence to:Jesus Sanchez Yague PhDDepartment of Biochemistry and Molecular Biology, University ofSalamancaEdificio Departamental. Lab. 106Plaza Doctores de la Reina s/n37007 SalamancaSpainemail: sanyaj@usal.es

Different laboratory studies have shown increased sialic acidlevels at the surface of malignant or transformed cells (1, 2).Since a rapid turnover of sialic acid from cell components ap-pears in the circulation, elevations in sialic acid levels in serumhave been used as a tumor marker for the diagnosis and man-agement of cancer patients (3) specifically lung cancer patients(4–6).

Cytokeratins are intermediate filaments expressed by epithe-lial cells and their malignant counterparts (7). Some cytokeratinfragments are released to the serum owing to cell lysis or tu-mor necrosis, and hence serum cytokeratins, mainly TPS (tissuepolypeptide-specific antigen) and Cyfra 21-1 (cytokeratin frag-ment recognized by the KS 19-1 and BM 19-21 antibodies) havebeen used as markers of cancer, including lung cancer (8).

Furthermore, metabolic profiling has increasingly been usedas a probe in disease diagnosis and pharmacological analysis (9).Essential fatty acids play an important role in complex metabolicreactions, and essential polyunsaturated fatty acids (PUFA) ap-pear to be one of the critical targets in the complex metabolicstages that lead to, or are associated with, cancer. Although ev-idence of the alterations in lipid and fatty acid metabolism in

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of fatty acid profiles, especially from erythrocytes or platelets,as markers in clinical oncology has not been addressed, andonly recently has plasma fatty acid metabolic profiling assessedby gas chromatography/mass spectrometry (GC/MS) been usedto detect biomarkers of type 2 diabetes mellitus (14). In thisregard, we have recently described that the fatty acid compo-sition of total lipids from erythrocytes and platelets is alteredin patients with advanced non-small cell lung cancer (NSCLC),probably as a result of the formation of free radicals and lipidperoxidation processes (15). The latter two phenomena are bothlinked both to carcinogenesis and tumor behavior (16, 17).Accordingly, in this study we analyzed the fatty acid profilesof phospholipid species in erythrocytes and platelets from pa-tients with advanced NSCLC to check which of those fattyacids might eventually provide an additional test for the diag-nosis and/or management of NSCLC patients. For comparison,we also examined previously described markers for lung car-cinoma such as sialic acid (FSA, free sialic acid; TSA, totalsialic acid; BSA, glicoconjugated-bound sialic acid; TSA/TP,total sialic acid/total protein; BSA/TP, glycoconjugated-boundsialic acid/total protein) and the cytokeratins TPS andCyfra 21–1.

MATERIALS AND METHODS

Patients

We studied 50 patients with a clear histological diagno-sis of primary NSCLC (39 squamous cell carcinoma, and 11adenocarcinoma) according to the World Health Organization(WHO) classification. Eligibility criteria included: no previouschemotherapy or radiotherapy; ECOG performance status ≤ 2;adequate bone marrow, liver, renal and cardiac function; noknown brain metastasis; no previous malignancy; no seriousconcurrent medical illness, and no extreme dietary habits. Thestaging of the tumors, performed according to the TNM stag-ing system of the International Union Against Cancer (UICC),was IIIA, IIIB and IV for 9, 28 and 13 patients, respectively.For TNM staging, all patients underwent a computed tomogra-phy (CT) scan of the chest and upper part of the abdomen, abone scintigram, and a brain CT or magnetic resonance imag-ing. These subjects were well informed as to the purpose of, andfully agreed to participate in the study, which was performedafter approval by our local institutional review boards at theUniversity of Salamanca and the Santısima Trinidad Founda-tion Hospital in Salamanca. We also studied 50 healthy male andfemale volunteers as controls, whose age, body weight, bloodlipids, blood pressure, smoking habits and BMI (body mass in-dex) were equivalent to those of the patient group (Table 1).Blood samples were taken the day after the patients were in-formed of their illness. None of the individuals had receiveddrugs interfering with platelet or erythrocyte functions, clotting,or fibrinolytic activity within the three months preceding bloodsampling.

Table 1. Clinical and biochemical characteristics of control subjectsand NSCLC patients

Lung cancerVariable Controls patients

Age (years) 61 ± 5 68 ± 5Weight (kg) 67 ± 10 69 ± 12Mean arterial pressure (mm Hg) 91 ± 10 95 ± 5Platelets (x 103 mL) 191 ± 54 261 ± 69Erythrocytes (x 106 mL) 5.2 ± 0.9 4.7 ± 0.9Total cholesterol (mg/dL) 180 ± 47 177 ± 25HDL-cholesterol (mg/dL) 52 ± 10 53 ± 10Triacylglycerols (mg/dL) 83 ± 30 89 ± 27Smoking history (pack-years) >19 ≥ 20BMI (kg/m2) 25.4 ± 4.2 25.0 ± 2.8

Values given as means ± S.D. BMI, body mass index.

Blood sampling and isolation of serum,plasma, erythrocyte and platelets

Two blood samples were drawn from all the individuals.One sample was allowed to coagulate at room temperature andserum was then obtained after centrifugation. The other one cor-responded to heparinized blood samples. The latter were cen-trifuged at 1,000 ×g for 5 minutes to obtain a lower phase (ery-throcytes) and an upper phase (platelet-rich plasma). Two thirdsof the platelet-rich plasma was then centrifuged at 2,600 ×g for10 minutes. The platelet pellet was washed three times with 3volumes of a solution of 150 mM NaCl, 5 mM sodium phosphatebuffer, pH 8.0 (PBS). After washing, platelets were resuspendedin 10 mM HEPES, pH 6.5, 0.2 mM EGTA, 5 mM KCl, 5.5 mMglucose in order to obtain platelet homogenates (18,19). Isolatederythrocytes were washed as indicated above for platelets. Theserum or plasma was stored at −80◦C until tested.

Biochemical measurements in serumand plasma

β-Thromboglobulin (β-TG) and Platelet Factor 4 (PF4)were measured in plasma by the ELISA technique (BoehringerMannheim Italy, Milan, Italy) following the manufacturer’sinstructions.

Sialic acids and cytokeratins were measured in serum. FSAwas determined by means of the thiobarbituric acid method (20)according to the procedure described by Aminoff (21). TSAwas quantified by the same procedure after hydrolysis of thesamples in five volumes of 0.1N H2SO4 at 80◦C for one hour.BSA was calculated as the difference between TSA and FSA.The levels of Cyfra 21-1 were determined using a double de-terminant immunoradiometric assay (ELSA Cyfra 21-1; CISBiointernational; Gif-sur-Yvette; Cedex, France). Two differentmonoclonal antobodies (KS 19.1 catcher and BM 19.21 tracerantibodies) were used in this two-step sandwich assay. TPS wasmeasured using a two-site immunoradiometric assay, employingtwo monoclonal antibodies to the M3 epitope of TPA, the formerobtained from mice and the latter from horses (TPS IRMA; BekiDiagnostics AB; Bromma, Sweden). Serum protein contents

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serum albumin as standard.

Lipid Extraction, Determination ofPhospholipid Classes and Fatty Acid Analyses

Total lipids were extracted from erythrocytes or plateletswith mixtures of isopropanol/chloroform (23). Separation ofthe phospholipid classes was accomplished by two-dimensionalthin layer chromatography (24). Fatty acid analyses were car-ried out by gas chromatography-mass spectrometry (GC-MS)(15, 24, 25). Before analysis, wet silica gel areas containingthe individual phospholipids were transmethylated with BF3

reagent, and fatty acid methyl esters (FAME) were partitionedin a water/petroleum hydrocarbon system, brought to drynessunder nitrogen, and dissolved in 10 µL of isooctane (24). GC-MS (triplicate determinations per sample) was performed on aShimadzu 17A apparatus with a TR-Wax (30 m × 0.25 mm ×0.25 µm) capillary column connected to a Shimadzu MS QP5000. GC was programmed under the following temperaturegradient: initial time at 130◦C for 3 minutes, 15◦C/minute from130◦C to 190◦C, 2◦C/minute from 190◦C to 230◦C and holdingat 230◦C for 23 minutes, with helium as carrier gas. Injector anddetector temperatures were 210◦C and 240◦C, respectively.

Statistical analyses

Data were analyzed using the non-parametric Mann-WhitneyU test. Statistical significance was considered at P < 0.05.“ROC” (receiver operating characteristics) curves, which cor-relate the percentages between true and false positives, werecalculated in order to select the cut-off level. The cut-off pointfor each tumor marker was selected on the basis of the best ac-curacy. If several cut-off points had the same accuracy, the valuewith the best specificity was chosen. Correlation indices wereassessed using Spearman’s correlation coefficient test. Analyseswere implemented using the SPSS program for MS Windows(version 13.0.1).

RESULTS

Levels of TP and biomarkers in serum

The serum levels of all sialic acid and cytokeratin biomarkerswere significantly increased in the NSCLC patients (Table 2). Nosignificant differences in TP values were found between patientsand controls (83.4 ± 8.1 vs. 83.3 ± 8.4 mg/mL in controls andNSCLC patients, respectively).

Profiles of phospholipid fatty acids inerythrocytes and platelets

The β-TG/PF4 ratio was not <2.5 in any of the samples,and hence incorrect sampling and manipulation of the bloodwithdrawn was ruled out (26).

The fatty acid profile of individual phospholipids from ery-throcytes changed significantly in the lung cancer patients(Tables 3–7). In phosphatidylcholine (PC), the most significantchanges observed were the decreases in 18:2n6, 20:4n6, 20:5n3

Table 2. Serum levels of the biomarkers sialic acid and the cytokeratinsTPS and Cyfra 21-1 in control subjects and NSCLC patients

NSCLC StatisticalControls patients significance

FSA (µmol/mL) 0.027 ± 0.008 0.031 ± 0.007 P < 0.033TSA (µmol/mL) 2.25 ± 1.04 2.89 ± 0.67 P < 0.001BSA (µmol/mL) 2.22 ± 1.04 2.86 ± 0.67 P < 0.001TSA/TP (µmol/mg) 0.027 ± 0.011 0.035 ± 0.008 P < 0.001BSA/TP (µmol/mg) 0.026 ± 0.011 0.034 ± 0.008 P < 0.001TPS (U/L) 45.14 ± 79.3 96.7 ± 58.2 P < 0.005Cyfra 21.1 (ng/mL) 0.98 ± 0.49 5.99 ± 9.15 P < 0.044TPS/TP 0.54 ± 0.48 1.15 ± 0.69 P < 0.005Cyfra 21.1/TP 0.014 ± 0.009 0.07 ± 0.103 P < 0.045

Values given as means ± S.D.FSA, free sialic acid; TSA, total sialicacid; BSA, glycoconjugate-bound sialic acid; TP, total protein; TPS,tissue polypeptide specific antigen; Cyfra 21-1, cytokeratin fragmentrecognized by KS 19-1 and BM 19-21 antibodies.

and 22:6n3 + 24:1n9 (23, 50, 68 and 39%, P < 0.001, respec-tively). By contrast, 18:1n9 increased significantly (10%, P <

0.015). These changes mainly contributed to the significant de-crease in polyunsaturated fatty acids (PUFA) (15%, P < 0.006),and they elicited a significant reduction in the unsaturation in-dex (UI) (10%, P < 0.025). In phosphatidylethanolamine (PE),20:4n6, 20:5n3 and 22:6n3 + 24:1n9 decreased significantly(39%, P < 0.001; 41%, P < 0.003; 47%, P < 0.001, respec-tively), whereas 16:0, 18:0 and 18:1n9 increased significantly(10%, P < 0.009; 17%, P < 0.031; 10%, P < 0.011, re-spectively). These changes mainly contributed to the significantdecrease in PUFA and total unsaturated fatty acids (UFA) (24%,P < 0.004; 6%, P < 0.030, respectively). The UI was also sig-nificantly reduced (18%, P < 0.004). In phosphatidylserine +phosphatidylinositol (PS + PI), 16:0 and 18:1n9 decreased sig-nificantly (33%, P < 0.001; 26%, P < 0.003, respectively),whereas 18:0 increased significantly (13%, P < 0.037). In thiscase, monounsaturated fatty acids (MUFA) decreased signifi-cantly (25%, P < 0.041), although the fatty acid changes didnot elicit any variations in the UI. The fatty acid changes insphyngomyelin (SM) were less numerous, with significant de-creases in 18:1n9 and 22:0 (37%, P < 0.024; 18%, P < 0.035,respectively). Finally, in phosphatidic acid (PA), among the mainfatty acids, 18:2n6 decreased significantly (35%, P < 0.013),whereas 18:1n9 increased significantly (14%, P < 0.002).These changes mainly contributed to the significant decreasein PUFA (33%, P < 0.006) and in the UI (17%, P < 0.021).

The fatty acid profile of individual phospholipids fromplatelets also changed significantly in the lung cancer patients(Tables 3–7). In PC, decreases occurred in 20:0, 20:1n9, 20:5n3and 22:0 (41%, P < 0.041; 42%, P < 0.037; 56%, P <

0.013; and 71%, P < 0.05, respectively). By contrast, 16:0and 18:1n9 increased significantly (20%, P < 0.034 and P <

0.008, respectively). These changes contributed to the significantincrease in saturated fatty acids (SFA) (15%, P < 0.040). In PE,20:0, 22:1n9 and 22:5n3 + 24:0 decreased significantly (40%,P < 0.006; 58%, P < 0.009; 58%, P < 0.018, respectively),

Fatty Acids as Markers of Lung Cancer 409

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08 Table 3. Changes in the fatty acid composition of phosphatidylcholine from erythrocytes and platelets in control subjects and NSCLC patients

Erythrocytes PlateletsFatty acid Controls NSCLC patients Statistical significance Controls NSCLC patients Statistical significance

14:0 0.74 ± 0.43 0.75 ± 0.30 NS 0.95 ± 0.34 1.82 ± 1.38 N.S.15:0 0.26 ± 0.17 0.39 ± 0.10 P < 0.001 0.50 ± 0.21 0.67 ± 0.62 N.S.16:0 37.84 ± 6.52 37.66 ± 6.82 N.S. 24.26 ± 6.14 29.18 ± 6.28 P < 0.03416:1n7 0.97 ± 0.57 1.24 ± 0.61 N.S. 2.06 ± 0.89 1.78 ± 0.52 N.S.17:0 0.55 ± 0.21 0.74 ± 0.18 P < 0.001 0.63 ± 0.30 0.76 ± 0.38 N.S.17:1 0.21 ± 0.15 0.28 ± 0.21 N.S. 0.43 ± 0.21 0.36 ± 0.20 N.S.18:0 14.50 ± 2.19 15.28 ± 3.04 N.S. 14.74 ± 3.23 16.39 ± 2.85 N.S.18:1n9 20.99 ± 3.48 22.98 ± 3.37 P < 0.015 20.97 ± 4.18 25.28 ± 3.51 P < 0.00818:2n6 20.46 ± 3.18 15.57 ± 5.83 P < 0.001 17.99 ± 9.21 11.80 ± 3.37 N.S.20:0 0.28 ± 0.26 0.36 ± 0.39 N.S. 1.00 ± 0.58 0.59 ± 0.32 P < 0.04120:1n9 0.68 ± 0.93 0.74 ± 0.61 N.S. 1.68 ± 0.73 0.98 ± 0.36 P < 0.03720:2n6 0.19 ± 0.31 0.36 ± 0.49 N.S. N.D. N.D.20:4n6 2.88 ± 1.02 1.40 ± 1.03 P < 0.001 5.07 ± 1.34 4.73 ± 2.03 N.S.20:5n3 0.29 ± 0.24 0.09 ± 0.11 P < 0.001 0.57 ± 0.24 0.25 ± 0.09 P < 0.01321:0 1.12 ± 0.66 0.76 ± 0.40 P < 0.026 1.26 ± 0.63 0.98 ± 0.45 N.S.22:0 0.18 ± 0.23 0.23 ± 0.30 N.S. 1.38 ± 0.67 0.40 ± 0.23 P < 0.0522:1n9 0.45 ± 0.39 0.33 ± 0.47 N.S. 1.11 ± 0.77 0.56 ± 0.45 N.S.22:2 0.07 ± 0.27 0.23 ± 0.31 P < 0.001 N.D. N.D.22:4n6 0.15 ± 0.20 0.07 ± 0.20 P < 0.003 N.D. N.D.22:5n3 + 24:0 0.52 ± 0.36 0.41 ± 0.60 P < 0.038 1.23 ± 0.46 0.94 ± 0.39 N.S.22:6n3 + 24:1n9 1.15 ± 0.61 0.70 ± 0.58 P < 0.001 N.D. N.D.SFA 55.60 ± 7.45 56.26 ± 6.24 N.S. 43.47 ± 7.44 49.82 ± 5.22 P < 0.040MUFA 22.29 ± 5.80 25.03 ± 5.83 P < 0.015 26.64 ± 3.98 30.47 ± 5.54 N.S.PUFA 21.97 ± 9.34 18.59 ± 6.36 P < 0.006 24.52 ± 10.96 17.88 ± 4.25 N.S.TOTAL UFA 44.26 ± 7.61 43.62 ± 6.24 N.S. 51.12 ± 10.84 47.29 ± 4.93 N.S.SFA/UFA 1.34 ± 0.49 1.34 ± 0.35 N.S. 0.96 ± 0.36 1.02 ± 0.18 N.S.UI 76.84 ± 17.98 68.72 ± 12.98 P < 0.025 89.72 ± 24.44 77.25 ± 13.23 N.S.

Data are given in percentages of total fatty acid contents and are means ± S.D. with GLC determinations performed in triplicate. N.D., not detected;N.S., not significant; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids; UFA, unsaturated fattyacids; UI, unsaturation index, calculated as the sum of the percentage by weight of each fatty acid times the number of olefinic bonds.

whereas mainly 18:0 and 20:4n6 increased significantly (64%,P < 0.017; 26%, P < 0.033; 154%, P < 0.025, respectively),although the changes did not elicit variations in the saturation orunsaturation indices. In PS + PI, decreases in 21:0 and 22:1n9(63%, P < 0.001; 37%, P < 0.041, respectively) were alsoinsufficient to elicit variations in the saturation or unsaturationindices. Finally, in SM, the most significant changes were thedecreases in 18:2n6, 20:1n9, and 22:1n9 (40%, P < 0.015;70%, P < 0.001; and 62%, P < 0.008, respectively), whereas16:0 increased significantly (70%, P < 0.001). These changesmainly contributed to the significant increase in SFA (30%, P <

0.002) and the decrease in the UI (43%, P < 0.009).A detailed analysis of the changes in the fatty acids also re-

vealed that some of those were cell specific while others werecommon to both erythrocyte and platelets. The most signifi-cant specific changes were: PC, decreases in 18:2n6, 20:4n6,22:5n3 + 24:0 and 22:6n3 + 24:1n9 in erythrocytes, and an in-crease in 16:0 in platelets. PE, decreases in 20:4n6, 20:5n3 and22:6n3 + 24:1n9 in erythrocytes, and a decrease in 22:5n3 +24:0 in platelets. PS + PI, decreases in 16:0, 18:1n9 and22:5n3 + 24:0 and an increase in 18:0 in erythrocytes. SM,a decrease in 22:0 in erythrocytes, and an increase in 16:0 inplatelets. The most significant common changes were: PC, a de-crease in 20:5n3 and an increase in 18:1n9; PE, an increase in

18:0. We did not detect common changes in PS + PI or SM fattyacids.

ROC curves for biomarkers in serumand phospholipid fatty acids in erythrocytes

and platelets

We then calculated ROC curves for most of the erythrocyteor platelet phospholipid fatty acids that changed in the NSCLCpatients, as well as for the tumor markers (Table 8) in orderto compare the different markers by analyzing their diagnosticaccuracy (area below the ROC curve). We observed that the di-agnostic accuracy of several phospholipid fatty acids was similarto or greater than that of sialic acid (0.81 for TSA/TP and 0,79for TSA and BSA) or cytokeratins (0.76 and 0.68 for TPS andCyfra 21-1, respectively). The most significant were: Erythro-cytes: PC, 18:2n6 (0.81) and 20:4n6 (0.85); PE, 22:4n6 (0.84),22:6n3 + 24:1n9 (0.82); PA, 20:5n3 (0.93). Platelets: PC, 18:1n9(0.81), 20:5n3 (0.93), 22:0 (0.96); PE, 20:0 (0.88), 20:4n6 (0.80),22:1n9 (0.92), 22:5n3 + 24:0 (0.93); PS + PI, 21:0 (0.97), SM,16:0 (0.91), 20:1n9 (0.96), 22:1n9 (0.97).

The operating characteristics for the individual fatty acids andtumor markers with their cut-off points for achieving the best in-dividual accuracy are shown in Table 9. The highest specificity,

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08 Table 4. Changes in the fatty acid composition of phosphatidylethanolamine from erythrocytes and platelets in control subjects and NSCLC patients

Erythrocytes PlateletsFatty acid Controls NSCLC patients Statistical significance Controls NSCLC patients Statistical significance

14:0 1.09 ± 0.73 0.95 ± 0.59 N.S. 2.14 ± 0.87 2.23 ± 0.68 N.S.15:0 0.33 ± 0.24 0.34 ± 0.36 N.S. 0.74 ± 0.35 0.56 ± 0.25 N.S.16:0 24.46 ± 3.09 26.77 ± 3.21 P < 0.009 15.85 ± 5.34 15.18 ± 4.23 N.S.16:1n7 0.95 ± 0.50 1.02 ± 0.62 N.S. 2.74 ± 0.91 2.46 ± 0.87 N.S.17:0 0.58 ± 0.21 1.03 ± 0.76 P < 0.002 1.25 ± 0.56 1.02 ± 0.53 N.S.17:1 1.09 ± 0.71 1.31 ± 1.12 N.S. 0.70 ± 0.46 1.65 ± 1.14 P < 0.01718:0 13.91 ± 2.43 16.34 ± 4.79 P < 0.031 18.21 ± 6.17 23.00 ± 3.68 P < 0.03318:1n9 28.01 ± 2.95 30.74 ± 4.43 P < 0.011 17.89 ± 7.84 17.81 ± 6.69 N.S.18:2n6 9.36 ± 3.72 7.96 ± 3.38 N.S. 7.54 ± 3.99 8.68 ± 4.27 N.S.20:0 0.23 ± 0.46 0.43 ± 0.56 P < 0.007 1.65 ± 0.42 0.99 ± 0.42 P < 0.00620:1n9 0.50 ± 0.33 0.77 ± 0.59 N.S. 1.90 ± 0.73 1.17 ± 0.85 N.S.20:4n6 10.92 ± 3.56 6.67 ± 4.40 P < 0.001 5.94 ± 3.67 15.12 ± 9.16 P < 0.02520:5n3 0.68 ± 0.52 0.40 ± 0.56 P < 0.003 0.67 ± 0.37 0.49 ± 0.16 N.S.21:0 0.77 ± 0.33 0.77 ± 0.49 N.S. 0.86 ± 0.67 0.44 ± 0.15 N.S.22:0 0.46 ± 0.56 0.29 ± 0.40 N.S. 1.07 ± 0.98 0.57 ± 0.28 N.S.22:1n9 0.41 ± 0.29 0.34 ± 0.42 N.S. 1.10 ± 0.47 0.46 ± 0.26 P < 0.00922:4n6 3.52 ± 1.04 1.67 ± 1.57 P < 0.001 2.65 ± 1.34 2.51 ± 1.04 N.S.22:5n3 + 24:0 0.55 ± 1.14 1.11 ± 1.49 P < 0.033 2.27 ± 0.84 0.94 ± 0.63 P < 0.01822:6n3 + 24:1n9 2.97 ± 1.21 1.57 ± 1.29 P < 0.001 N.D. N.D.SFA 41.94 ± 5.75 44.14 ± 9.91 N.S. 43.12 ± 10.82 45.16 ± 8.03 N.S.MUFA 31.75 ± 2.86 34.59 ± 4.55 P < 0.012 24.52 ± 9.10 22.76 ± 6.88 N.S.PUFA 24.85 ± 9.42 18.75 ± 6.94 P < 0.004 26.09 ± 14.07 32.88 ± 11.91 N.S.TOTAL UFA 56.60 ± 8.08 53.34 ± 7.08 P < 0.030 52.11 ± 14.72 53.60 ± 10.24 N.S.SFA/UFA 0.77 ± 0.23 0.84 ± 0.27 N.S. 0.98 ± 0.64 0.91 ± 0.41 N.S.UI 118.05 ± 28.52 96.25 ± 25.04 P < 0.004 98.09 ± 36.39 120.12 ± 46.96 N.S.

Data are given in percentages of total fatty acid contents and are means ± S.D. with GLC determinations performed in triplicate. N.D., not detected;N.S., not significant; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids; UFA, unsaturated fattyacids; UI, unsaturation index, calculated as the sum of the percentage by weight of each fatty acid times the number of olefinic bonds.

sensitivity, positive predictive value (PPV) and accuracy werefound with: (a) Erythrocytes: PC fatty acids, 20:5n3 and 18:2n6(90 and 68%, 56 and 81%, 83 and 78%, and 74 and 75%, re-spectively); PE fatty acids, 20:4n6 and 22:4n6 (77 and 65%,71 and 75%, 85 and 77%, and 73 and 71%, respectively); PS+ PI fatty acids, 16:0 and 22:5n3 + 24:0 (74 and 100%, 89and 24%, 85 and 100%, and 84 and 63%, respectively); SMfatty acids, 22:0 (94, 64, 96 and 61 %, respectively); PA fattyacids, 18:1n9, 22:5n3 and 22:1n9 (67, 80 and 80%; 81, 57 and50%; 78, 57 and 57%, and 75, 73 and 69%, respectively); (b)Platelets: PC fatty acids, 20:5n3 and 22:0 (80 and 88%, 100and 83%, 86 and 83%, and 92 and 86%, respectively); PE fattyacids, 22:1n9 and 22:5n3 + 24:0 (86 and 80%, 86 and 100%,86%, and 86 and 91%, respectively); PS + PI fatty acids, 21:0(80, 91, 83 and 86%, respectively); SM fatty acids, 16:0 and18:2n6 (77 and 75%, 82 and 89%, 75 and 73%, and 79 and81%, respectively). As regards serum markers, with respect tothe sialic acids BSA showed the best accuracy, specificity andPPV (84, 83 and 92%), while FSA showed the best sensitiv-ity (95%). Additionally, when sialic acids were normalized byTP, the accuracy, specificity and PPV values decreased, whilethe sensitivity values remained similar (74%, 44%, 79% and88 and 86% for TSA/TP and BSA/TP, respectively). We alsofound positive correlations among TSA, FSA, BSA, FSA/TPand BSA/TP (data not shown); e.g., between TSA and BSA orFSA and BSA, we found Spearman’s correlation coefficients

of 1 (P < 0.0001) and 0.886 (P < 0.0001) or 0.303 (P <

0.017) and 0.272 (P < 0.034) when BSA values were notnormalized or normalized by TP, respectively. Both cytoker-atins showed similar values, although TPS proved to be slightlysuperior at the cut-off point for achieving the best individualaccuracy (37 U/L and 1 ng/mL, for TPS and Cyfra 21-1, re-spectively). Nevertheless, at commonly reported cut-off val-ues (140 U/L and 3.6 ng/mL for TPS and Cyfra 21-1, respec-tively, both with 100% specificity), Cyfra 21-1 showed otherbetter values than TPS (39, 100, 56% and 24, 100, 45% sen-sitivity, PPV and accuracy, respectively. Data not shown). Ithas been reported that the correlation index between the cy-tokeratins TPA and Cyfra 21-1 is very high [27]. Here, wefound a positive correlation between the two cytokeratin mark-ers TPS and Cyfra 21-1 [Spearman’s correlation coefficientsof 0.651 and 0.637 (P < 0.001) when the markers were nor-malized or not normalized by TP, respectively]. No correlationwas found between either of the cytokeratins and sialic acidvalues.

According to the data shown in Table 9, when the diagnos-tic yields (sensitivity and specificity) were analyzed at the cutoff point to achieve the best accuracy, some fatty acids showedsimilar or even higher values than cytokeratins. Especially sig-nificant were: erythrocytes: PC, 18:2n6 and 20:4n6 (81 and 68%,and 79 and 65%, respectively); PE, 20:4n6, 22:4n6 and 22:6n3+ 24:1n9 (71 and 77%, 75 and 65%, and 71%, respectively);

Fatty Acids as Markers of Lung Cancer 411

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08 Table 5. Changes in the fatty acid composition of phosphatidylserine + phosphatidylinositol from erythrocytes and platelets in control subjects and

NSCLC patients

Erythcocytes PlateletsFatty acid Controls NSCLC patients Statistical significance Controls NSCLC patients Statistical significance

14:0 2.18 ± 1.49 1.27 ± 0.79 P < 0.001 2.77 ± 1.37 2.36 ± 1.34 N.S.15:0 0.42 ± 0.39 0.38 ± 0.36 N.S. 0.86 ± 0.46 0.64 ± 0.35 N.S.16:0 21.46 ± 9.82 14.33 ± 5.25 P < 0.001 16.41 ± 5.39 15.07 ± 7.46 N.S.16:1 1.44 ± 0.92 1.19 ± 0.69 N.S. 2.42 ± 0.85 2.53 ± 1.25 N.S.17:0 0.68 ± 0.58 0.77 ± 0.72 N.S. 0.89 ± 0.29 0.72 ± 0.36 N.S.17:1 0.25 ± 0.26 0.33 ± 0.45 N.S. 0.57 ± 0.23 0.63 ± 0.29 N.S.18:0 42.11 ± 11.53 47.65 ± 11.23 P < 0.037 25.58 ± 9.50 24.56 ± 8.46 N.S.18:1n9 24.32 ± 10.01 17.80 ± 5.48 P < 0.003 20.37 ± 6.23 22.03 ± 6.24 N.S.18:2n6 6.65 ± 3.71 6.42 ± 4.03 N.S. 15.66 ± 10.57 17.55 ± 8.93 N.S.20:0 0.18 ± 0.23 0.48 ± 0.57 P < 0.050 1.26 ± 0.74 0.99 ± 0.54 N.S.20:1n9 0.71 ± 0.72 0.60 ± 0.71 N.S. 1.82 ± 0.98 1.62 ± 1.12 N.S.20:2n6 0.06 ± 0.23 0.30 ± 0.61 N.S. N.D. N.D. N.S.20:4n6 7.07 ± 11.41 4.72 ± 2.82 N.S. 5.07 ± 4.95 5.22 ± 4.40 N.S.20:5n3 0.14 ± 0.34 0.30 ± 0.48 N.S. 0.61 ± 0.46 0.51 ± 0.33 N.S.21:0 0.54 ± 0.94 1.08 ± 0.75 P < 0.001 1.80 ± 0.77 0.66 ± 0.27 P < 0.00122:0 0.17 ± 0.37 0.62 ± 0.79 P < 0.003 1.12 ± 0.95 0.97 ± 0.54 N.S.22:1n9 0.16 ± 0.43 0.39 ± 0.53 P < 0.012 1.59 ± 0.58 1.00 ± 0.46 P < 0.04122:4n6 0.70 ± 1.12 0.60 ± 0.77 N.S. N.D. N.D. N.S.22:5n3 + 24:0 1.51 ± 1.96 0.58 ± 0.85 P < 0.050 N.D. N.D. N.S.22:6n3 + 24:1n9 1.18 ± 1.56 1.09 ± 1.07 N.S. N.D. N.D. N.S.SFA 55.34 ± 19.83 63.56 ± 13.03 N.S. 51.06 ± 7.35 45.04 ± 8.74 N.S.MUFA 25.48 ± 11.12 18.74 ± 7.41 P < 0.005 26.65 ± 6.75 25.19 ± 7.02 N.S.PUFA 16.17 ± 12.87 13.63 ± 5.65 N.S. 22.13 ± 10.05 26.36 ± 10.17 N.S.TOTAL UFA 41.65 ± 19.63 32.38 ± 7.64 P < 0.041 47.75 ± 8.39 51.56 ± 5.32 N.S.SFA/UFA 1.73 ± 1.06 2.12 ± 1.05 N.S. 1.07 ± 0.29 0.89 ± 0.24 N.S.UI 79.93 ± 52.12 61.47 ± 17.57 N.S. 83.64 ± 19.63 95.19 ± 18.73 N.S.

Data are given in percentages of total fatty acid contents and are means ± S.D. with GLC determinations performed in triplicate. N.D., not detected;N.S., not significant; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids; UFA, unsaturated fattyacids; UI, unsaturation index, calculated as the sum of the percentage by weight of each fatty acid times the number of olefinic bonds.

PS + PI, 16:0 (89 and 74%, respectively). Platelets: PC, 20:5n3(100 and 80%, respectively); PE, 20:4n6 and 22:5n3 + 24:0 (77and 100%, and 100 and 80%, respectively); PS + PI, 21:0 (91and 80%); SM, 20:1n5 and 22:1n9 (100 and 77%, and 100 and80%, respectively).

DISCUSSIONIt is acknowledged that different biochemical parame-

ters and serum tumor markers have several potential appli-cations in clinical oncology, such as screening, diagnosis,prognosis, monitoring responses to therapy, or assessment ofthe spontaneous course of the disease. For many years, lungserum tumor markers, including a heterogeneous group of sub-stances, have been used for a wide range of clinical applica-tions (27,28), although high concentrations of these markers aremainly found at advanced stages of the disease (29). Amongthese serum markers, soluble degradation products of cytoker-atins, such as TPS and Cyfra 21-1, are measurable in the periph-eral blood of patients and are able to mark the existence of cancer(27). Furthermore, the high sensitivity of sialic acid as a tumormarker has been reported in a variety of cancerous conditions(3). The relevance of sialic acid to the tumor cell is apparent fromthe increased sialylation and sialyltransferase activity observed

in many cancer cells (3). Also, metabolomics, and specificallyplasma fatty acid profiling, has increasingly been used in manyfields, including disease diagnosis (10).

Since we have previously described that advanced NSCLCis associated with changes in the fatty acids of total lipids fromperipheral erythrocytes and platelets (15), here we analyzed thefatty acid profiles of phospholipid species in erythrocytes andplatelets from this type of patient in order to detect potentialfatty acids that could eventually be used as biomarkers. Forcomparison, we also examined the previously described markersfor lung carcinoma: sialic acid, TPS and Cyfra 21-1.

Cyfra 21-1, TPA and TPS are closely related markers. TPAand Cyfra 21-1 are known to provide fairly similar informa-tion owing to the presence of a common antigenic determi-nant (cytokeratin-19) (27). TPS was proposed as a step for-ward in comparison with TPA because it is highly correlatedwith the proliferation rate of cancer cells (27). Several stud-ies of patients with lung lesions (revised in 27) have foundthat both TPS and Cyfra 21-1 are elevated in all cell types oflung cancer, are more sensitive in advanced stages of disease,are useful in monitoring the course of disease, and are prog-nostically meaningful. It has been reported that TPS sensitivityrates range between 13 and 54%, with elevated values of TPS

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08 Table 6. Changes in the fatty acid composition of sphingomyelin from erythrocytes and platelets in control subjects and NSCLC patients.

Erythrocytes PlateletsFatty acid Controls NSCLC patients Statistical significance Controls NSCLC patients Statistical significance

14:0 1.41 ± 0.55 1.10 ± 0.67 P < 0.016 2.12 ± 0.59 2.24 ± 0.92 N.S.15:0 0.35 ± 0.19 0.35 ± 0.30 N.S. 0.77 ± 0.26 0.55 ± 0.30 N.S.16:0 30.98 ± 3.98 32.54 ± 6.43 N.S. 17.37 ± 3.29 29.71 ± 12.40 P < 0.00116:1n7 0.82 ± 0.70 0.60 ± 0.55 N.S. 3.04 ± 1.19 2.35 ± 1.03 N.S.17:0 0.71 ± 0.38 0.83 ± 0.65 N.S. 1.02 ± 0.59 1.02 ± 0.33 N.S.17:1 ND ND 0.67 ± 0.28 0.39 ± 0.02 P < 0.02418:0 14.81 ± 6.54 15.64 ± 7.65 N.S. 14.31 ± 3.97 15.50 ± 3.97 N.S.18:1n9 8.53 ± 6.28 5.35 ± 5.33 P < 0.024 17.11 ± 4.33 16.97 ± 11.07 N.S.18:2n6 3.71 ± 2.54 4.36 ± 4.85 N.S. 19.67 ± 7.81 11.71 ± 3.66 P < 0.01520:0 1.49 ± 0.38 1.30 ± 0.51 N.S. 1.95 ± 0.77 2.37 ± 2.47 N.S.20:1n9 0.22 ± 0.32 0.32 ± 0.47 N.S. 3.35 ± 1.19 1.01 ± 0.62 P < 0.00120:2n6 0.06 ± 0.21 0.01 ± 0.08 N.S. N.D. N.D. N.S.21:0 0.17 ± 0.34 0.24 ± 0.46 N.S. 2.05 ± 0.68 1.70 ± 1.62 N.S.22:0 7.13 ± 2.27 5.85 ± 2.21 P < 0.035 3.54 ± 1.36 4.95 ± 3.35 N.S.22:1n9 0.28 ± 0.49 0.17 ± 0.46 N.S. 2.40 ± 0.95 0.92 ± 0.38 P < 0.00822:2n6 0.43 ± 0.76 0.53 ± 0.75 N.S. N.D. N.D. N.S.23:0 1.35 ± 0.37 1.49 ± 1.01 N.S. N.D. N.D. N.S.24:0 17.95 ± 4.37 16.81 ± 6.03 N.S. 3.42 ± 2.07 3.93 ± 4.19 N.S.24:1n9 15.99 ± 6.07 15.34 ± 6.51 N.S. 5.46 ± 4.48 5.31 ± 3.17 N.S.SFA 71.14 ± 8.03 71.80 ± 13.60 N.S. 45.57 ± 4.17 59.25 ± 14.26 P < 0.002MUFA 23.88 ± 6.85 22.27 ± 8.55 N.S. 29.91 ± 5.66 26.20 ± 10.27 N.S.PUFA 4.85 ± 2.75 5.02 ± 4.87 N.S. 22.63 ± 9.11 12.56 ± 3.35 P < 0.009TOTAL UFA 28.72 ± 7.95 25.29 ± 9.84 N.S. 51.12 ± 7.80 36.45 ± 14.94 P < 0.009SFA/UFA 2.75 ± 1.09 3.56 ± 2.53 N.S. 0.91 ± 0.24 1.19 ± 0.47 N.S.UI 34.20 ± 10.28 30.73 ± 13.25 N.S. 76.07 ± 20.06 50.47 ± 17.70 P < 0.009

Data are given in percentages of total fatty acid contents and are means ± S.D. with GLC determinations performed in triplicate. N.D., not detected;N.S., not significant; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; SFA, saturated fatty acids; UFA, unsaturated fattyacids; UI, unsaturation index, calculated as the sum of the percentage by weight of each fatty acid times the number of olefinic bonds.

occurring more often in the most advanced stages (27). More-over, Cyfra 21-1 seems to show higher accuracy in compari-son with TPS in both small cell lung cancer and NSCLC (30).In the present work, higher levels of sensitivity were observedfor TPS and at the best cutt-off point the sensitivity of bothTPS and Cyfra 21-1 were quite similar (70 and 68%, respec-tively). Also, TPS showed higher areas under the ROC curvesthan Cyfra 21-1 (0.76 and 0.68, respectively). Nevertheless, aspreviously described [30] at commonly reported cut-off values(140 U/L and 3.6 ng/mL for TPS and Cyfra 21-1, respectively),Cyfra 21-1 showed higher sensitivity, PPV and accuracy thanTPS.

It is known that both TSA and BSA are increased in a varietyof tumors, including lung cancer, not only in plasma, but also inBAL fluid and pleural effusions (31). Importantly, TSA levelsare not altered by the smoking habit (6), one of the main causesof lung cancer. Although most work has concluded that TSA andBSA are highly sensitive markers of lung cancer, their specificityseems to be low (3). Nevertheless, the usefulness of sialic acidseems clear in the monitoring of responses to treatment in pa-tients and in the detection of recurrence in a variety of tumors,including lung carcinoma (3). At the designated cut-off levelsused in this work (chosen on the basis of the highest accuracy),the sensitivity of TSA or BSA (86 and 84%, respectively) wassimilar to that reported previously (6, 32). Also, at these cut-off

levels TSA/TP and BSA/TP showed lower specificity than TSA,FSA or BSA. Nevertheless, it has previously been reported thatTSA/TP is a more tumor-specific marker than TSA (33, 34).This difference can be explained because in the present workTP in serum remained unchanged, and TSA/TP seemed to bea better tumor marker than TSA in patients with decreases inserum TP levels, perhaps as a result of the particular tumor type,metastatic phenomena, or metabolic alterations.

It has been described that in a series of human pathologiessharing redox alterations as a hallmark, significant modifica-tions of erythrocyte integrity and function occurs (35–37). Pre-viously, we also described that in advanced NSCLC not onlytotal fatty acids, but also some membrane proteins, includingband 3 and glycophorins, change significantly (38). In plateletsfrom patients with advanced NSCLC, increased protein oxida-tion has also been reported (15). Additionally, several studieshave described different changes in the fatty acid compositionof erythrocyte total lipids in patients with different types of can-cer (13), including lung cancer (39), although we are not awareof any studies describing erythrocyte fatty acids from individualphospholipids. With respect to platelets, we are only aware ofone report addressing fatty acid profiles in isolated PC, PE andPS + PI phospholipids (40). Although in that report, patientssuffered exclusively from squamous cell lung carcinoma andstaging was different from the one used here, we have coincident

Fatty Acids as Markers of Lung Cancer 413

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08 Table 7. Changes in the fatty acid composition of phosphatidic acid

from erythrocytes in control subjects and NSCLC patients

Lung cancer StatisticalFatty acid Controls patients significance

14:0 2.59 ± 1.06 2.35 ± 1.27 N.S.15:0 0.63 ± 0.38 0.47 ± 0.43 N.S.16:0 24.19 ± 5.39 27.08 ± 8.30 N.S.16:1n7 3.03 ± 1.15 2.70 ± 0.94 N.S.17:0 0.78 ± 0.37 0.72 ± 0.50 N.S.18:0 20.12 ± 6.72 21.45 ± 6.08 P < 0.04918:1n9 24.14 ± 4.20 27.72 ± 6.02 P < 0.00218:2n6 20.52 ± 8.46 13.33 ± 8.41 P< 0.013420:0 1.01 ± 0.94 0.22 ± 0.29 P < 0.00320:1n9 1.00 ± 1.15 0.83 ± 0.92 N.S.20:2n6 0.04 ± 0.17 0.11 ± 0.37 N.S.20:4n6 1.60 ± 1.09 2.36 ± 2.47 N.S.20:5n3 0.97 ± 0.91 0.15 ± 0.26 P < 0.00121:0 1.35 ± 0.67 1.12 ± 0.95 N.S.22:0 1.34 ± 1.24 0.36 ± 0.58 P < 0.00122:1n9 1.10 ± 0.74 0.36 ± 0.58 P < 0.00122:4n6 0.17 ± 0.40 0.19 ± 0.55 N.S.22:5n3 + 24:0 0.82 ± 1.28 0.39 ± 0.62 N.S.22:6n3 + 24:1n9 0.39 ± 0.76 0.32 ± 0.62 N.S.SFA 46.91 ± 9.81 50.84 ± 11.17 N.S.MUFA 27.14 ± 7.51 31.61 ± 6.58 N.S.PUFA 25.85 ± 8.09 17.22 ± 10.31 P < 0.006TOTAL UFA 52.99 ± 9.71 48.83 ± 10.77 N.S.SFA/UFA 0.95 ± 0.38 1.15 ± 0.54 N.S.UI 89.84 ± 16.61 73.70 ± 23.84 P < 0.021

Data are given in percentages of total fatty acid contents and aremeans ± S.D. with GLC determinations performed in triplicate. N.S.,not significant; MUFA, monounsaturated fatty acids; PUFA,polyunsaturated fatty acids; SFA, saturated fatty acids; UFA,unsaturated fatty acids; UI, unsaturation index, calculated as the sumof the percentage by weight of each fatty acid times the number ofolefinic bonds.

data regarding decreases in the main phosphoglyceride fractionsof n3 fatty acids. The main differences are that our decreases in20:5n3 and 22:5n3 seem to be phospholipid-specific (PC and PE,respectively), although those authors did find such decreases inboth phospholipids. In our case, no changes in 22:6n3 fatty acidswere detected. These data could be physiologically relevant be-cause it is known that platelets with low levels of n3 PUFAproduce more thromboxane B2 when stimulated with thrombin(41), and we (15) and others (40) have reported platelet activa-tion in lung cancer, as shown by increased β-thromboglobulinconcentration in plasma (15, 40) and by increased thromboxaneB2 formation by platelets (40). The PUFA depletion describedhere could be due to different phenomena. First, the contributionof phospholipase A2 does not seem to be important because wehave already observed that the erythrocyte or platelet phospho-lipid profile remains unchanged in advanced NSCLC, with nosignificant increases in lysophospholipid percentages (15). Thesecond phenomenon involves fatty acid metabolic alterations intissues from NSCLC patients. In cancer, changes in Delta 9 andDelta 6 desaturases have been suggested (13), and in our case, adecrease in such enzymes could at least partially explain the de-

creased levels of PUFA (42). A final possibility would involvelipid peroxidation, a phenomenon well known to be linked toboth carcinogenesis and tumor behavior (43) that finally pro-duces fluorescent chromolipids. In this regard, we have previ-ously described that in advanced NSCLC, at least in platelets, thedecrease in PUFA from total lipids is correlated with an increasein lipid fluorescence (15). Thus, a comparison of the changes inthe fatty acids of total lipids from erythrocytes and platelets(15), together with the data reported here, lead us to propose,for advanced NSCLC, the phospholipid(s) that the changes insome of the main fatty acids from total lipids are due to. Thus,in erythrocytes the increase in 18:0 from total lipids is due to PEand PS + PI (mainly to PE, considering that it represents a 31%of total phospholipids, while PS + PI represents a 9%, [15]).The decrease in 18:2n6 is due to PC. The decrease in 20:4n6 isdue to PC and PE (mainly to PE considering the percentage of20:4n6 in this phospholipid). The decrease in 22:6n3 + 24:1n9is due to PC and PE. The decrease in PUFA and IU, and theincrease in MUFA is also due to PC and PE. In platelets, theincrease in 16:0 and SFA from total lipids is due both to PCand SM.

In spite of all previous evidence concerning changes in thelipid composition of erythrocytes and platelets in cancer, noefforts have been made to analyze whether the fatty acids fromthose blood cells could be used as potential biomarkers in cancerin general, and lung cancer in particular. Accordingly, analysisof the operating characteristics for the well established serummarkers sialic acid and cytokeratins led us to compare themwith those obtained for some of the erythrocyte- and platelet-specific phospholipid fatty acids than change in NSCLC pa-tients. We considered it more appropriate to look mainly forfatty acids that decrease rather than increase because, as indi-cated above, changes in desaturases and lipid peroxidation pro-cesses occurring in cancer will always elicit PUFA depletion. Inthis regard, we detected some potential useful fatty acid mark-ers. Some could be used because their changes are cell-specific,and their diagnostic accuracy is high: Erythrocytes: PC, 18:2n6and 20:4n6; PE, 22:4n6 and 22:6n3 + 24:1n9. Platelets: PC,22:0; PE, 22:5n3 + 24:0. Another one is 20:5n3 of PC, a phys-iologically relevant species, although not cell-specific. At thecut-off value to obtain maximum accuracy, the best cell-specificbiomarkers are located in platelets: PS + PI, 21:0; SM:20:1n9and 22:1n9. In erythrocytes, the best candidate is 16:0 in PS + PI.

Now that potential individual fatty acid biomarkers have beendetected we can target our research more precisely. In this re-gard, it will be necessary to increase the size of the sample and toinclude patients with benign lung pathologies, mainly of inflam-matory nature, to ascertain the best applications of erythrocyteor platelet fatty acid analysis in relation to screening, diagnosis(either of tumors, cell type, or stage of disease), prognosis, mon-itoring responses to anti-cancer therapies and follow-up of thedisease. Efforts are now under way to elucidate some of thesefeatures and draw the pertinent conclusions.

It will also be interesting to compare the potential fattyacid biomarkers found in this work using ROC operatingcharacteristics with those found using other, more complex

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Table 8. Areas under the ROC curves for erythrocyte- and platelet-specific phospholipid fatty acids, and serum sialicacids and cytokeratins

CI 95%Area Lower limit Upper limit

Blood cell type Erythrocyte Platelet Erythrocyte Platelet Erythrocyte Platelet

PC16:0 0.75 0.54 0.9618:1n9 0.68 0.81 0.54 0.62 0.81 1.0018:2n6 0.81 0.69 0.9120:0 0.76 0.55 0.9720:1 0.78 0.58 0.9820:4n6 0.85 0.76 0.9420:5n3 0.78 0.93 0.65 0.77 0.91 1.08422:0 0.96 0.86 1.05922:2 0.68 0.55 0.8222:4n6 0.68 0.54 0.8122:6n3 + 24:1n9 0.73 0.61 0.85

PE16:0 0.70 0.56 0.8318:0 0.67 0.75 0.53 0.56 0.80 0.9518:1n9 0.69 0.56 0.8320:0 0.88 0.72 1.03420:4n6 0.79 0.80 0.67 0.59 0.91 1.00722:1n9 0.92 0.77 1.06522:4n6 0.84 0.74 0.9422:5n3 + 24:0 0.93 0.78 1.08822:6n3 + 24:1n9 0.82 0.72 0.93

PS + PI16:0 0.78 0.64 0.9218:0 0.66 0.51 0.8118:1n9 0.72 0.58 0.8621:0 0.97 0.91 1.03222:1n9 0.77 0.56 0.9822:5n3 + 24:0 0.63 0.50 0.77

SM14:0 0.68 0.55 0.8116:0 0.91 0.80 1.02518:1n9 0.67 0.53 0.8018:2n6 0.82 0.63 1.00120:1n9 0.96 0.88 1.04822:0 0.66 0.53 0.7922:1n9 0.97 0.88 1.061

PA18:1n9 0.77 0.62 0.9218:2n6 0.72 0.57 0.8720:0 0.75 0.59 0.9120:5n3 0.93 0.85 1.0122:1n9 0.80 0.66 0.94

Serum markersSialic Acids

TSA 0.79 0.65 0.94FSA 0.67 0.52 0.83BSA 0.79 0.65 0.94TSA/TP 0.81 0.68 0.94BSA/TP 0.76 0.61 0.92

CytokeratinsTPS 0.76 0.63 0.89Cyfra 21-1 0.68 0.54 0.83

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Table 9. Diagnostic characteristics of erythrocyte- and platelet-specific phospholipid fatty acids, and serumsialic acids and cytokeratins

Cut-off point Sensitivity Specificity PPV NPV AccuracyBlood cell type Ery Pla Ery Pla Ery Pla Ery Pla Ery Pla Ery Pla

Phospholipid fatty acidPC

16:0 25 77 75 77 75 7618:1n9 21 24 69 77 57 77 68 77 59 77 63 7718:2n6 19 11 81 50 68 67 78 64 71 53 75 5720:0 0.7 70 58 58 70 6320:1 1.15 75 67 60 80 7020:4n6 2.4 79 65 75 71 7320:5n3 0.18 0.4 56 100 90 80 83 86 69 100 74 9222:0 0.7 83 88 83 88 8622:222:4n622:6n3 + 24:1n9 0.81 65 71 71 65 68

PE16:0 25 70 63 76 56 6718:0 14 19 64 79 54 55 69 69 48 67 60 6818:1n9 28 65 63 76 50 6420:0 1.3 80 78 80 78 7920:4n6 8 11 71 77 77 100 85 100 59 73 73 8622:1 0.7 86 86 86 86 8622:4n6 3 75 65 77 62 7122:5n3 + 24:0 1.75 100 80 86 100 9122:6n3 + 24:1n9 2.1 71 71 80 60 71

PS+PI16.0 20 89 74 85 81 8418:0 38 79 55 75 60 7018:1n9 21 78 69 78 69 7421:0 0.7 1 82 91 67 80 85 83 63 89 77 8622:1n9 0.7 1.3 42 70 60 70 80 70 21 70 46 7022:5n3 + 24:0 0.6 24 100 100 58 63

SM14:0 1.2 63 52 65 50 5816:0 21 82 77 75 83 7918:1n9 7 58 64 70 50 6018:2n6 14 89 75 73 90 8120:1n9 2 100 77 67 100 8422:0 6.5 64 94 96 52 6122:1n9 1.5 100 80 80 100 91

PA18:1n9 24 81 67 78 71 7518:2n6 16.5 71 63 68 67 6720:5n3 0.6 57 80 57 80 7322:1n9 0.75 50 80 57 75 69

Serum markersSialic acids

TSA 2.25 86 78 90 70 84FSA 0.027 95 61 85 85 70BSA 2.25 84 83 92 68 84TSA/TP 0.025 88 44 79 62 74BSA/TP 0.025 86 44 79 57 74

CytokeratinsTPS 37 70 71 87 48 70Cyfra 21-1 1 68 57 81 40 65

The best cut-off points (given as percentages of total fatty acid content) were chosen on the basis of the highestaccuracy. Ery, erythrocytes; Pla, platelets; PPV, positive predictive value; NPV, Negative predictive value.

416 J. de Castro et al.

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08 statistical or mathematical approaches, such as supervised par-

tial least squares-linear discrimination analysis (PLS-LDA)method. This multivariate approach has recently been success-fully employed to detect plasma fatty acid biomarkers in type-2diabetes mellitus patients after analysis of the plasma fatty acidprofiles using GC/MS (14).

ACKNOWLEDGMENT

The authors wish to thank N. Skinner for his assistance in thepreparation of the manuscript.

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