The International Journal of Biochemistry & Cell Biology 70 (2016) 68–75

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Glycosylated Alpha-1-acid glycoprotein 1 as a potential lung cancer serum biomarker Asima Ayyub a , Mahjabeen Saleem a,∗ , Iram Fatima b , Asma Tariq b , Naghma Hashmi c , Syed Ghulam Musharraf c a

Institute of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan School of Biological Sciences, University of the Punjab, Lahore 54590, Pakistan c Hussain Ebrahim Jamal Research Institute, University of Karachi, 75270 Karachi, Pakistan b

a r t i c l e

i n f o

Article history: Received 12 June 2015 Received in revised form 16 October 2015 Accepted 4 November 2015 Available online 10 November 2015 Keywords: Candidate biomarker Cancer 2DE MALDI-TOF/TOF

a b s t r a c t Presently existing screening approaches for lung cancer are not being proving sufficient and sensitive, so a study was conducted to identify disease related biomarker proteins for diagnostic applications. A total of 100 lung cancer patients (88 non-small cell lung cancer and 12 small cell lung cancer) and 50 healthy controls were included in this study. Serum samples of patients and healthy controls were subjected to a series of proteomic approaches and as a result of two dimensional gel electrophoresis, a ∼43 kDa protein was found to be differentially expressed compared to healthy controls. Quantitative profiling of two dimensional gels by Dymension software analysis displayed 3.58 fold increased expression of ∼43 kDa protein in squamous cell carcinoma and 2.92 fold in case of adenocarcinoma. Mass spectrometric analysis resulted in identification of 8 differentially expressed proteins, out of which human Alpha-1-acid glycoprotein 1 was targeted for further validations. This candidate protein exhibited N-linked glycosylation at five amino acid residues; 33, 56, 72, 93, and 103 with significant score of 0.66, 0.78, 0.78, 0.53 and 0.66, respectively. Sandwich ELISA quantified high serum levels of Alpha-1-acid glycoprotein 1 in squamous cell carcinoma (2.93 g/l ± 1.22) and adenocarcinoma (2.39 g/l ± 1.13) when compared with healthy controls (0.83 g/l ± 0.21). One-way ANOVA analysis predicted highly significant variation of Alpha-1-acid glycoprotein 1, among all the study types (F-value 65.37, p-value 0.000). This study may prove as a noninvasive, cost effective and sensitive scheme for diagnosis of lung cancer, by passing the expensive and painful screening procedures. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction Lung cancer, a leading cause of cancer mortalities all over the world; in both males and females (Lihong et al., 2014). Amongst 28% of total cancer mortalities 1.3 million deaths are attributed to lung cancer annually (Mascaux et al., 2010). In Asian population, especially in Pakistan male mortality due to lung cancer is elevated since last few years (GLOBOCAN, 2008). Lack of health education about smoking, radiation exposure and air pollution along with specific occupational toxicity may act as causative agent for this elevation. Biomarker is defined as a molecule present in blood, tissues or other body fluids which acts as an indicator of a normal orabnormal

∗ Corresponding author. E-mail address: [email protected] (M. Saleem). http://dx.doi.org/10.1016/j.biocel.2015.11.006 1357-2725/© 2015 Elsevier Ltd. All rights reserved.

process or disease (NCI, n.d.). Serum is a rich source of biochemical products which may serve as predictor of physiological or clinical status of patients (Steel et al., 2003). Acute phase proteins like Alpha-1-acid glycoprotein 1 have been related to less prognostic outcomes in varied pathological states like cancer (Suarez Nieto et al., 1986). Over expression of Alpha1-acid glycoprotein 1 has been reported in non-small cell lung cancer (NSCLC) patients (Kremer et al., 1988) and found exceptionally sensitive and specific predictor of lung cancer (Ganz et al., 1984). Considerable rise in Alpha-1 acid glycoprotein was observed in patients with active lung and gastrointestinal carcinomas compared to inactive disease (Ganz et al., 1983). In this study, using different proteomic methodologies, differential lung cancer serum protein biomarkers have been identified and validated as compare to healthy control samples. This strategy will be helpful to study effective utility of identified proteins for timely diagnosis of disease and evaluation of therapeutic feedback.

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2. Materials and methods 2.1. Sampling, serum preparation and protein quantification Whole blood from healthy volunteers was collected from University of the Punjab, Lahore, while of patients from Allah Wali Oncology ward (Gulab Devi Chest Hospital, Lahore) according to approved Institutional Review committee protocol. Samples from patients were categorized in two groups: NSCLC (n = 88) and SCLC (n = 12). Amongst them NSCLC was further sub-divided into adenocarcinoma (n = 34), squamous cell carcinoma (n = 48) and large cell carcinoma (n = 6). Serum was separated and stored at −80 ◦ C prior to assay. Total protein contents were estimated by Bradford method (Bradford, 1976). 2.2. One dimensional SDS-PAGE analysis of serum SDS-PAGE (10%) was run according to method described by Laemmli (1970) and kept in fixative solution (30% ethanol, 10% acetic acid and 60% deionized water) for four hours. Staining was carried out overnight using Colloidal Coomassie stain G-250 (Sigma Chemicals Co., USA). After destaining, images were scanned by gel documentation system (SynGene, Gene snap). 2.3. 2DE (two dimensional gel electrophoresis) analysis of serum On the basis of decreased incidence of small cell lung cancer as well as large cell type, only squamous cell carcinoma and adenocarcinoma were selected for further proteomic investigations (Siddiqui et al., 2010). 350 ␮l of rehydration buffer was used for IPG strips (18 cm,non-linear, pH 3–10, Serva) and 1–2 ml silicon oil (Fluka) was overlaid for preventing the dehydration of gel. Complete assembly was incubated at 20 ◦ C overnight. 2.3.1. Isoelectric focusing (first dimension) After rehydration, 500 ␮g of total serum proteins from both patients and healthy controls were resolved on IPG strips on flat bed equipment (Amersham, Scie plus, UK) to achieve 32 kV h. 2.3.2. SDS-PAGE (second dimension) IPG strips were kept at room temperature until normalized and equilibration steps were carried out as recommended. Focused strips were run on 12% gel at recommended voltage followed by staining and destaining steps. 2.3.3. Image analysis The gel images were scanned using image scanner (HP ScanJet 8200). 2D gel images of patient serum samples were compared with healthy controls by Dymension v 3.2.1 (SynGene, UK). The protein spots with expression intensity more than 1.5 fold (increase or decrease) were considered statistically significant for further proteomic analysis. 2.4. Tryptic digestion (In-gel) and mass spectrometric analysis (MALDI-TOF/TOF) Labeled protein spots were picked, washed and incubated several times for removing stain and other contaminants in multiple steps. Finally, 400 ng (per spot) of trypsin (Promaga) was added and incubated on ice for 45 min followed by addition of 50 mM Ambic and then incubated at 37 ◦ C overnight. Digested peptide extracts were obtained with trifluoro acetic acid for their mass spectrometric analysis. Peptide mass fingerprinting was carried out on (Ultraflex III; BrukerDaltonics GmbH, Breman, Germany) MALDI-TOF/TOF mass spectrometer, by mixing 1:1 of tryptic digest and matrix (␣-Cyano

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4-hydroxy Cinnamic acid) followed by spotting on MALDI plate. Procedure was carried out according to the recommended instrumental protocol and resulting peak data was subjected to MASCOT search program for protein identification. The protein identity showing MASCOT score greater than 60 and sequence coverage 20% or more was accepted. MASCOT search parameters were set as follows: carbamidomethyl modification of Cysteine and possible oxidation of Methionine up to one missed cleavage, the enzyme was trypsin (Promaga, Cat# V5111). Protein identification databases were SwissProt and NCBInr, the specie selected for analysis was homo sapiens. Peptide mass tolerance used for search was less than 1.0 Dalton. 2.5. Detection of glycosylation Glycosylation was predicted and confirmed in protein sequences of targeted protein using software; NetNGlyc 1.0 Server-CBS for prediction of N-linked glycosylation. 2.6. Immunological validation Primary antibody of Alpha-1-acid glycoprotein 1 was raised in male albino mice in triplicate. The guidelines provided by the animal ethical committee were followed during whole immunization procedure. For each mouse, 50 ␮g of antigenic protein was mixed with PBS (phosphate buffer saline, pH 7.4) and inoculated subcutaneously using Freund’s complete adjuvant. Three booster doses were prepared in incomplete Freund’s adjuvant. After immunization, blood was drawn by cardiac puncture scheme and anti-serum was purified by using Pearl, IgG purification kit (G-Biosciences, Cat# 786-798) according to the manufacturer’s instructions. Western blotting was performed following the protocol of Towbin et al. (1979). 10 ␮g of serum proteins from all serum samples were resolved on 15% SDS-gels and gels were transferred to blotting membrane (8.5 × 7.5) (Nitrocellulose, 0.22 ␮m pore size (G-Biosciences, Cat# 786-018NC) allowing transfer of proteins for 1.5 h, at constant voltage of 18volts in a Semi Dry Transfer Cell assembly (Bio-Rad Trans-Blot Sd). The optimized dilution ratio (1:200) of primary antibody was applied to the blotting membrane and incubated at 4 ◦ C overnight. Goat anti-mouse IgG, AP-conjugated secondary antibody (Cat# 786-R43, G-Biosciences) was added and incubated for 2 h at room temperature, followed by three washings with same washing buffer. Finally, the blot was developed by AP-substrate buffer and obtained desired signal intensity of the bands. 2.7. Densitometric analysis The protein abundance in patient and healthy control samples was analyzed by Image J software (1.48v) for signal intensity measurements according to the recommended protocol of software. 2.8. Sandwich ELISA Serum levels of targeted protein were quantified by sandwich ELISA using commercial ELISA kit (Antibodies-online.com, Cat # ABIN819742), following recommended protocol. 2.9. Data analysis One-way ANOVA (SPSS version 19.0) was applied on 2D quantification data and ELISA data to compare and evaluate the statistical significance of targeted protein among study groups. p-value < 0.01 was considered to be significant in both cases. False discovery rate was also calculated. The histological types of patients

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were taken as independent variables while targeted biomarker protein as dependent variable. ELISA serum levels were presented as mean ± standard deviation, box plot and scatter plot were used to show data point distribution of serum levels of targeted protein. 3. Results and discussion 3.1. Proteomic profiling of serum samples Proteins expressed differentially when patient and control serum samples were subjected to electrophoretic resolution (Figs. 1 and 2). Detection of spots and image analysis was carried out by Dymension (v 3.2.1) analysis. 46 differentially expressed protein spots from all 2D gels of patients and healthy controls were analyzed by MALDI-TOF/TOF, resulting in identification of 8 differentially expressed proteins (molecular mass range 27–70 kDa) and pI (4.0–9.5), with high confidence (Table 1). The detailed layout of these identified proteins is summarized in Fig. 3A. Spot 1(Alpha-1-acid glycoprotein 1), with observed (by Dymension software) molecular mass of ∼43 kDa was found to be over-expressed (red circle) in squamous cell carcinoma samples (Fig. 2B) while under-expressed (blue circle) in adenocarcinoma (Fig. 2C) as compared to healthy controls (Fig. 2A) shown as green circle. The spot 2(Apolipoprotein-A1) (observed mass ∼27 kDa) and spot 3 (Haptoglobin) (observed mass ∼42–46 kDa) were

Fig. 1. One dimensional SDS-PAGE (12%) resolution of proteins expressed in lung cancer serum samples along with healthy control. Lane M: unstained protein ladder (Invitrogen); Lane C: healthy control serum; Lane 1–5: patient samples. 10 ␮g of serum proteins from patients and control individuals was loaded.

found to be significantly up-regulated (red circles and ovals in Fig. 2B and C). Spot 5 (Haptoglobin isoform) (observed mass ∼38 kDa); Spot 6 (SDHL Human) (observed mass ∼35 kDa) and spot 7 (ST134 Human) (observed mass ∼27 kDa) were also observed to be differentially expressed with respect to healthy controls (red circles in Fig. 2B). Interestingly, spot 4 (Novel protein) appeared to be

Fig. 2. (A) Two dimensional serum protein profiling of healthy control serum sample. On left side: Fermantas protein marker, Page Rular Cat#SM0661. The differentially expressed protein spots (1, 2, 3, 5, 6 and 7) are marked as green circles and oval. High abundant proteins like albumin have been marked as purple colored rectangle (alb). (B) Two dimensional serum protein profiling of lung squamous cell carcinoma, serum sample. On left side: Fermantas protein marker, Page Rular Cat#SM0661, 10–200 kDa). The differentially expressed protein spots (1, 2, 3, 5, 6 and 7) are marked as red circles and oval along with abundantly occurring proteins like albumin as purple colored rectangle (alb) while a unique spot (4) is marked as yellow circle. (C) Two dimensional serum protein profiling of lung adenocarcinoma serum sample. On left side: Fermantas protein marker, Page RularCat#SM0661, 10–200 kDa. The over-expressed protein spots (2–3) are marked as red and one under-expressed protein spot (1) is marked as blue circle. The abundantly occurring proteins like albumin have been marked as purple rectangle (alb). (D) A closer view of differentially expressed protein spots from 2D gels: (A): healthy control; (B): squamous cell carcinoma; and (C): adenocarcinoma. The encircled spot ‘1’ corresponds to observed mass of ∼43 kDa (alpha-1-acid glycoprotein 1). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Table 1 A detailed representation of peptide mass fingerprinting and protein database search analysis of in-gel digested peptide of targeted protein from 2D gels. Spot ID

alb 1 2 3 4 5 6 7

Protein ID

Human Serum Albumin Human Apolipoprotein-A1 Alpha-1-acid glycoprotein 1 Human Haptoglobin Q5JSG1 Human, Novel protein Haptoglobin SDHL Human ST134 Human

Accession no.

Observed

Experimental

MASCOT Score

Sequence coverage

Database

Mass values searched

Mass values matched

5.92 5.56

174 110

33% 46%

SwissProt SwissProt

95 22

24 12

23.725

4.93

73

36%

SwissProt

15

6

5.5–6.2 9.5

45.861 33.528

6.13 9.62

87 68

23 34%

SwissProt SwissProt

14 63

10 15

6.0 7.3 6.3

38.94 34.945 27.561

6.27 8.15 5.01

68 60 66

26% 22% 20%

NCBInr SwissProt SwissProt

36 15 21

9 5 6

Mw (kDa)

pI

Mw (kDa)

pI

Q9P157 P02647

65–70 27

6–7 6.0

71.317 30.759

P02763

43

4.0

P00738 Q5JSG1

42–46 33

gi|1212947 P20132 Q8IZP2

38 35 27

Accession No. is based on MASCOT search program using database SwissProt and NCBInr. pI is isoelectric point of protein and Mw is meant for molecular mass of identified protein.

a unique protein with observed mass of ∼33 kDa (yellow circle) in Fig. 2B. Dymension v 3.2.1(SynGene, UK) software analysis results (Tables 2 and 3) suggested that the expression of this protein is strongly related to the particular histology of disease, so selected for further immune validations. The statistical assessment of 2D quantification data was carried out on the spots with fold change ≤1.5, by one-way ANOVA and evaluated at 0.01 significance levels showing p-value 0.000. The analysis exhibited substantial up-regulation of ∼43 kDa protein in both histological types compared to healthy controls concluding that both patient types demonstrate significant relevance between targeted protein and histological type of lung cancer patients. On the basis of fold change variation, significant score (73), peptide sequence coverage (36%), Alpha-1-acid glycoprotein 1 (spot 1, ∼43 kDa) was selected for further proteomic analysis and validations. The comparative 2D cropped views of ∼43 kDa protein are shown in Fig. 2D, displaying significant variation in protein intensity. The experimental molecular mass was found to be 23.725 kDa with pI of 4.93 (Table 1). Mass spectrum, score histogram and matched peptide profile are presented in Fig. 3B–D, respectively. 3.2. Proteomic characterization of Alpha-1-acid glycoprotein 1and its validation studies Post translational modifications are the chemical changes which take place after protein synthesis for example; glycosylation, proteolytic cleavage, acetylation, phosphorylation, methylation, sialylation and oxidation (Krueger and Srivastava, 2006). In present study, Alpha-1-acid glycoprotein-1 appeared on 2DE gels with isoelectric point ∼4.0 (observed value) in comparison to experimental pI value of 4.93. Similar discrepancy in isoelectric point of Alpha-1acid glycoprotein 1 has also been reported previously (Chirwa et al., 2012). Interestingly, this protein showed major drift in its molecular mass i.e. observed at ∼43 kDa on 2D gels while 23.725 kDa obtained after proteomic profiling by MALDI-TOF/TOF followed by MASCOT search analysis. This apparent shift in molecular mass can be explained on the basis of glycosylation of Alpha-1-acid glycoprotein 1. Chirwa et al. (2012) have also reported an observed molecular mass of 50 kDa for Alpha-1-acid glycoprotein 1 which was almost double to that of the predicted (23 kDa) molecular mass and explained this change on the basis of N-linked glycosylation of protein. 3.2.1. Detection of N-linked glycosylation in Alpha-1-acid glycoprotein 1 Glycosylation is the most biologically relevant type of post translational modifications playing a central role in progression of

lung cancer and other carcinomas (Okano et al., 2006). Glycosylation phenomenon in Alpha-1-acid glycoprotein 1 was observed by subjecting its peptide sequence to glycosylation prediction software NetNGlyc 1.0 Server-CBS. As a result, five glycosylation sites at amino acid residue No. 33, 56, 72, 93, and 103 with significant score of 0.66, 0.78, 0.78, 0.53 and 0.66 were predicted. All these scores were lying within the recommended threshold values (≥0.5) as shown in Fig. 4 and Table 4. Ferens-Sieczkowska et al. (2013) and Tsai et al. (2011) have also predicted N-linked glycosylation in Haptoglobin protein. 3.2.2. Western blotting and band densitometry of Alpha-1-acid glycoprotein 1 The immuno-detection experiments showed an over expression of Alpha-1-acid glycoprotein 1(∼43 kDa) in squamous cell carcinoma (Fig. 5A) and adenocarcinoma (Fig. 5B) compared to healthy controls; however, expression intensity signal was more intense in case of squamous cell carcinoma than adenocarcinoma. Band density was analyzed by Image J software and relative density values of individual bands ranged from 204 to 365 in adenocarcinoma patient samples while 270–483 in squamous cell carcinoma samples, respectively. The reference value of relative density of control was taken as 100 and results are summarized in Tables 5 and 6. Relative density values obtained by this analysis were plotted on scatter plot versus study group type, demonstrating the expression pattern in both histological patient types compared to healthy controls (Fig. 6). This graphical representation exhibited significant up-regulated expression in both histological types than controls, but squamous cell cancer type showed relatively higher expression compared to adenocarcinoma. Based on this finding, this glycosylated isoform of Alpha-1-acid glycoprotein 1 may be regarded as a potential biomarker of squamous cell carcinoma and adenocarcinoma and further studies may lead to develop a fruitful diagnostic as well prognostic strategy resulting in better treatment of the disease. 3.3. Elevated levels of Alpha-1-acid glycoprotein 1 in lung cancer sera To evaluate expression of Alpha-1-acid glycoprotein 1 on quantitative basis, serum protein levels were estimated in both healthy controls as well as patients, by putting the absorbance values of samples in standard curve of protein and represented as mean ± standard deviation (Table 7). Mean serum concentration of Alpha-1-acid glycoprotein 1 was 2.39 g/l ± 1.13 and 2.93 g/l ± 1.22 in adenocarcinoma and squamous cell carcinoma patients, respectively, as compared to 0.83 g/l ± 0.21 in healthy control individuals. Our results are in agreement with previous study where Fraeyman

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Fig. 3. (A) Layout of identified proteins by MALDI-TOF/TOF. (B) Mass spectrometric chromatogram of Alpha-1-acid glycoprotein 1. (C) Score histogram of Alpha-1-acid glycoprotein 1. (D) A symbolic representation of identified peptides of Alpha-1-acid glycoprotein 1 among theoretical and experimental data. Matched peptides are shown as red and unmatched as blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Table 2 Quantitative and statistical analysis of targeted protein spot of squamous cell lung carcinoma compared to healthy controls. Protein spot

Rate of presencea

Study group type (n = 10)

Mean % volumeb

Standard deviation

Fold change

FDRc

p-valued

∼43 kDa protein, pI 4.0

20

Healthy controls Squamous cell carcinoma Squamous cell carcinoma

1.15 4.12 17.70

0.12 0.33 2.58

+3.58

0.00

0.000

a Rate of presence of protein is the number of times that spot appeared in 2D gels of patients and healthy controls. Here, each protein spot observed in 10 2DE gels of squamous cell lung cancer and healthy controls. b (mean % volume) is the relative volume of each spot as % age of total spots volume. c FDR is false discovery rate. d p-value less than 0.01 was considered to be significant after carrying out FDR by SPSS version (19.0).

Table 3 Quantitative and statistical analysis of targeted protein spot of lung adenocarcinoma compared to healthy controls. Protein spot

Rate of presencea

Study group type (n = 10)

Mean % volumeb

Standard deviation

Fold change

FDRc

p-valued

∼43 kDa protein, pI 4.0

20

Healthy controls Adenocarcinoma Adenocarcinoma

1.15 3.36 11.32

0.12 0.48 2.16

+2.92

0.00

0.000

a Rate of presence of protein is the number of times that spot appeared in 2D gels of patients and healthy controls. Here, each protein spot observed in 10 2DE gels of lung adenocarcinoma patients and healthy controls. b (mean % volume) is the relative volume of each spot as %age of total spots volume. c FDR is false discovery rate. d p-value less than 0.01 was considered to be significant after carrying out FDR by SPSS version (19.0).

Fig. 4. Score representation of N-linked glycosylation profile of Alpha-1-acid glycoprotein 1.

Table 4 Detection of N-glycosylation in Alpha-1-acid glycoprotein 1. Seq name

Position

Potential

Jury agreement

N-Glyc result

Sequence Sequence Sequence Sequence Sequence

33 NATL 56 NKSV 72 NKTE 93 NTTY 103 NGTI

0.6608 0.7816 0.7852 0.5327 0.6609

(8/9) (9/9) (9/9) (5/9) (8/9)

+ +++ +++ + +

et al. (1988) have reported elevated serum levels of this candidate protein i.e. 1.65 g/l ± 0.16 in lung cancer patients versus 0.91 g/l ± 0.04 in case of healthy control subjects. 3.4. Data analysis and graphical representation The datasets were analyzed by one way ANOVA (version 19.0) for assessment of statistical comparison among study groups. This analysis predicted highly significant variation of Alpha-1-acid glycoprotein 1, among all the study types. The level of significance

Fig. 5. Western blot validation of lung cancer serum sample against Alpha-1-acid glycoprotein 1. (a): Lane C: healthy control serum sample; Lane 1–8: squamous cell carcinoma samples. (b): Lane C: healthy control serum sample; Lanes 1–3: adenocarcinoma samples.

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Table 5 Densitometric analysis of Alpha-1-acid glycoprotein 1 expression in squamous cell lung carcinoma by Image J software. Sample

Area

Percentage

Relative density

C 8 7 6 5 4 3 2 1

1388.376 5452.418 6706.51 5079.024 4969.894 3895.882 5492.853 5733.326 3743.548

3.27 12.84 15.79 11.96 11.70 9.17 12.93 13.50 8.81

100 393 483 366 358 281 396 413 270

Table 6 Densitometric analysis of Alpha-1-acid glycoprotein 1 expression in lung adenocarcinoma by Image J software. Sample

Area

Percentage

Relative density

C 1 2 3

5081.175 10,348.024 14,758.267 18,566.279

10.42 21.22 30.27 38.08

100 204 290 365

Fig. 6. Densitometric scatter plot representation of expression bands of Alpha-1acid glycoprotein 1. Table 7 Quantification of Alpha-1-acid glycoprotein 1 in healthy controls and lung cancer serum samples by sandwich ELISA. Study cases

Mean

SD

Healthy controls (n = 50) Adenocarcinoma (n = 34) Squamous cell carcinoma (n = 48)

0.83 2.39 2.93

0.21 1.13 1.22

These levels are the mean of total samples values. SD, standard deviation.

was found to be 0.000, which was found to be significant as less than 0.01 (Table 8). F value for Alpha-1-acid glycoprotein 1 was found to be 65.37. This statistical comparison helps to document the expression of this biomarker protein in relation to disease status. Box plot representation of data exhibits the statistical summary of data points showing higher Alpha-1-acid glycoprotein 1 levels in both histological types of patients compared to healthy controls with comparatively high levels in squamous cell carcinoma Table 8 Statistical data analysis of Alpha-1-acid glycoprotein 1 by one-way ANOVA. Biomarker protein

F-value

Significance (p-value)

Alpha-1-acid glycoprotein-1

65.37

0.000

F-value represents the ratio of two sample variance.

Fig. 7. Graphical representation of expression levels of Alpha-1-acid glycoprotein 1 (A) box plot, (B) scatter plot.

(Fig. 7A). This graphical view indicates median value of protein levels as 0.85, 2.97 and 3.24 g/l for healthy controls, for adenocarcinoma patients and for squamous cell carcinoma, respectively. The scatter plot representation is exhibiting an overall distribution of data points (Fig. 7B), and similar expression tendency as in box plots. These graphical views further authenticate the significance of Alpha-1-acid glycoprotein 1, as lung cancer biomarker protein. 3.5. Drug binding property of Alpha-1-acid glycoprotein 1 As proteins act as therapeutic targets, proteomic analysis offers a more direct way of identification of malignant carcinomas. Discovery of specific and sensitive biomarkers lead to cancer therapeutics (Tesseromatis et al., 2011). Alpha-1-acid glycoprotein 1 can bind to acidic, neutral and basic drugs (Kremer et al., 1988). Docetaxel, a lung cancer drug, is well bound to Alpha-1-acid glycoprotein 1 and other plasma proteins. Due to this binding affinity of the drug, free form of Docetaxel in blood decreases while protein bound form level increases (Urien et al., 1996). Alpha-1-acid glycoprotein also exhibits high binding affinity for ␤-adrenoceptoroxprenolol (anti-lung cancer drug) in lung cancer and increased levels of Alpha1-acid glycoprotein in serum decreases the free form of the drug, therefore, leading to reduced pharmacological response (Fraeyman

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et al., 1988). This observation strengthens the clinical application of this protein, further proving its therapeutic utility. 4. Conclusion In conclusion, this study highlights that Alpha-1-acid glycoprotein 1 may serve as an important diagnostic as well as differentiating biomarker protein for both lung adenocarcinoma as well as squamous cell carcinoma. Identification and targeting of such disease related biomolecules produce a screening pathway from discovery to validation phase leading to clinical applications. Proteomic characterization of Alpha-1-acid glycoprotein 1 may also facilitate to study the metabolic pathways and to establish a diagnostic platform leading to prognostic and therapeutic discoveries. Further work on molecular, physiological and kinetic aspects of Alpha-1-acid glycoprotein 1 and its correlation with lung cancer may facilitate the clinical application of this protein. Moreover, monitoring the protein serum levels before and after chemotherapy may also assist to analyze the sensitivity of this candidate protein biomarker with reference to a particular histological type and clinical stage. Acknowledgements This work was supported by technical assistance of School of Biological Sciences, University of the Punjab, H.E.J Research Institute of Chemistry, University of Karachi and financial aid of Higher Education Commission of Pakistan. References Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254. Chirwa, N., Govender, D., Ndimba, B., Lotz, Z., Tyler, M., Panieri, E., et al., 2012. A 40–50 kDa glycoprotein associated with mucus is identified as ␣-1-acid glycoprotein in carcinoma of the stomach. J. Cancer 3, 83–92. ´ Ferens-Sieczkowska, M., Kratz, E.M., Kossowska, B., Passowicz-Muszynska, E., Jankowska, R., 2013. Comparison of haptoglobin and alpha1-acid glycoprotein glycosylation in the sera of small cell and non-small cell lung cancer patients. Postepy Hig. Med. Dosw. 67, 828–836.

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Glycosylated Alpha-1-acid glycoprotein 1 as a potential lung cancer serum biomarker.

Presently existing screening approaches for lung cancer are not being proving sufficient and sensitive, so a study was conducted to identify disease r...
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