Ann Surg Oncol DOI 10.1245/s10434-014-3574-0

ORIGINAL ARTICLE – PANCREATIC TUMORS

Profiling of Autoantibodies in Sera of Pancreatic Cancer Patients Yosuke Nagayoshi, MD1, Masafumi Nakamura, MD, PhD2, Kazuhiro Matsuoka, PhD3, Takao Ohtsuka, MD, PhD1, Yasuhisa Mori, MD, PhD1, Hiroshi Kono, MD, PhD1, Teppei Aso, MD1, Noboru Ideno, MD1, Shunichi Takahata, MD, PhD1, Akihide Ryo, MD, PhD4, Hiroyuki Takeda, PhD3, Tetsuhide Ito, MD, PhD5, Yoshinao Oda, MD, PhD6, Yaeta Endo, PhD3, Tatsuya Sawasaki, PhD3, and Masao Tanaka, MD, PhD1 1

Departments of Surgery and Oncology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Department of Digestive Surgery, Kawasaki Medical School, Kurashiki, Japan; 3Cell-Free Science and Technology Research Center, Ehime University, Matsuyama, Japan; 4Department of Microbiology and Molecular Biodefense Research, Yokohama City University, Yokohama, Japan; 5Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; 6Department of Anatomic Pathology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

2

ABSTRACT Background. Although autoantibodies to cancer antigens are candidates for biomarkers, no comprehensive studies to detect cancer-specific antibodies have been performed. This study identified autoantibodies in the sera of pancreatic cancer (PC) patients using proteomics based on a wheat germ cell-free protein production system. Methods. We constructed a biotinylated protein library of 2,183 genes. Interactions between biotinylated proteins and serum antibodies were detected by AlphaScreenÒ assay. Relative luminescence signals of each protein in 37 PC patients and 20 healthy controls were measured, and their sensitivity and specificity for PC were calculated. Results. Luminescence signals of nine proteins were significantly higher than those of healthy controls, with calcium and integrin binding 1 (CIB1) protein showing the greatest significance (p = 0.002). Sensitivity, specificity, positive predictive value and negative predictive value of CIB1 autoantibody alone for PC were 76, 70, 82, and 61 %, respectively, and 97, 35, 74, and 88 %, respectively, when the four most significant proteins were combined. Presence of these autoantibodies did not vary significantly with other clinicopathological characteristics. Conclusion. Several autoantibodies, including CIB1, are potential biomarkers for PC.

Ó Society of Surgical Oncology 2014 First Received: 19 October 2013 M. Nakamura, MD, PhD e-mail: [email protected]

Despite progress in diagnostic modalities and operative procedures, prognosis for pancreatic cancer (PC) remains poor.1 Early-stage PC is asymptomatic and no sensitive diagnostic modality exists for its early detection. Although PC is usually diagnosed by ultrasonography (US), computed tomography, and magnetic resonance imaging/ cholangiopancreatography, these modalities rarely detect early-stage PC. Blood sampling is an ideal source of materials because of its limited invasiveness and relative abundance. Although several markers in blood such as carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA199) can sometimes be useful for diagnosis of PC, their sensitivity and specificity are not so high, and screening for PC using blood samples is not widely used. Therefore, establishment of a reliable biomarker for the detection of early-stage PC would be useful. Autoantibodies have attracted recent attention as possible biomarkers. Rheumatoid factor and immunoglobulin G4 (IgG4) are representative autoantibodies from which various collagen diseases and autoimmune pancreatitis can be diagnosed, respectively.2,3 Presence of autoantibody in patients with malignancies was described 30 years ago;4 advances in technology have allowed identification of autoantibodies against several malignancies, including PC.5–11 However, reported sensitivities of autoantibodies against antigens in PC such as PGK1, DEAD-box 48, and p53 seem to be quite low, i.e. 10–30 %.11–13 To date, comprehensive studies to detect cancer-specific autoantibodies have not been carried out. We previously reported a luminescence-based highthroughput method to detect antigen–antibody reactions

Y. Nagayoshi et al.

that successfully detected autoantibodies from mouse sera.14 In this method, an N-terminal biotinylated protein library (BPL) was prepared by wheat germ cell-free synthesis; binding between biotinylated protein and antibody was specifically detected by AlphaScreenÒ.15 We explored possible autoantibody biomarkers from sera of patients with PC, using the AlphaScreenÒ autoantigen screening system. MATERIALS AND METHODS Patients and Serum Samples This study was approved by the Institutional Review Board at Kyushu University Hospital. Serum samples came from randomly selected patients with PC before these patients underwent surgery or chemotherapy (n = 37). They consisted of 22 males and 15 females with a median age of 64 years (range 43–78 years). Twenty-one patients underwent pancreatectomy and were histologically confirmed to have PC. The other 16 patients were not surgically managed because of locally advanced PC or distant metastases; they were diagnosed by pancreatic juice cytology obtained during endoscopic retrograde pancreatography or by endoscopic US-guided aspiration biopsy. PC clinical stage was classified according to the 6th edition of the General Rules for the Study of Pancreatic Cancer by the Japan Pancreas Society (JPS) and the 7th edition of the International Union Against Cancer (UICC).16,17 Clinicopathological parameters included age, gender, JPS and UICC stage, CEA (normal limit \3.2 ng/mL at our institution), CA19-9 (normal limit \37 ng/mL), T stage in UICC classification, lymph node metastasis (positive/negative) and lymphatic and vessel invasion (positive/negative). Serum samples from healthy volunteers (n = 20) served as controls. Construction of DNA Template Mammalian Gene Collection (MGC) clones (Danaform, Tokyo, Japan) were used as human full-length complementary DNA (cDNA) resources, from which 2,183 human cDNA clones that included genes in autoimmune susceptibility loci18 and genes that coded membrane proteins and proteins in extracellular spaces were selected to construct the BPL. DNA transcription templates were constructed by the split-primer polymerase chain reaction (PCR) technique described in our previous reports.19,20 As this system works only when two primers are joined correctly, only complete messenger RNAs (mRNAs) were produced at transcription. For biotinylation, the biotin ligation site (bls) was fused onto the 5terminus of the open frame by PCR.

Construction of the Protein Library by Wheat-Based Cell-Free Protein Synthesis Wheat-germ extract was purchased from CellFree Science Co., Ltd (Yokohama, Japan). mRNA was transcribed by SP6 RNA polymerase from each DNA template. Cellfree protein was synthesized using the previously described bilayer diffusion system.21 Biotinylation was carried out by adding 1 lL (50 ng) of crude biotin ligase (BirA, Genbank Accession no. NP_312927) produced by wheat cell-free synthesis with 500 nM D-biotin (Nacalai Tesque, Kyoto, Japan), which specifically conjugates a single biotin on the bls on the synthesized protein.22 Transcription and cell-free protein synthesis were carried out using the robotic synthesizer GenDecoder 1000 (CellFree Sciences Co.), as previously described.20,23 The AlphaScreenÒ Assay The AlphaScreenÒ assay was performed according to the manufacturer’s protocol (PerkinElmer Life and Analytical Sciences, Boston, MA, USA). Repetitive dispensations were automated by a JANUS Automated Workstation (PerkinElmer Life and Analytical Science). The AlphaScreenÒ reactions were carried out in 25 lL of reaction volume per well in 384-well OptiPlate microtiter plates (PerkinElmer). First, 1 lL of translation mixture, including the biotinylated proteins, was mixed with 0.025 lL of serum in 15 lL of reaction buffer (100 mM Tris-HCl [pH 8.0], 0.01 % [v/v] Tween-20 and 0.1 % [w/v] bovine serum albumin) and incubated at 26 °C for 30 min. Subsequently, 10 lL of solution containing streptavidincoated Donor beads and protein G-conjugated Acceptor beads (PerkinElmer) in the reaction buffer was added, for a final concentration of 12 lg/mL per well, and incubated at 26 °C for 1 h in a dark box. The biotinylated protein was attached to streptavidin-coated Donor beads and serum antibodies were attached to protein G-conjugated Acceptor beads. When antibody and protein were in close proximity, the antibody–antigen reaction produced a luminescence signal at 640 nm, which was measured by the EnVision plate reader (PerkinElmer). A translation mixture without mRNA was used as negative control in each plate; each protein’s luminescence signal was calculated relative to the negative control. Screening Protocol In the first screening, we used AlphaScreenÒ to analyze antibody–antigen reactions between 2,183 biotinylated proteins and six serum mixtures, which varied by sex and JPS stage (III, Iva, or IVb). Each serum mixture consisted of four sera to be averaged. Maximum relative

Autoantibodies in Pancreatic Cancer Patients

luminescence signal of each protein was calculated. The top 44 proteins were selected and used for second screening. In the second screening, sera from 37 PC patients and 20 healthy controls were mixed with the above-mentioned 44 biotinylated proteins and analyzed with AlphaScreenÒ assay. Relative luminescence signals of each protein were compared between the PC patients and the healthy controls. Western Blotting Analysis Translation mixture (50 lL) expressing biotinylated protein was incubated with 20 lL of streptavidin agarose (Life Technologies, Carlsbad, CA, USA) for 30 min at room temperature. The agarose were washed with TBST (20 mM Tris–HCl, pH 7.6, containing 150 mM NaCl and 0.05 % Tween-20) and then boiled in SDS sample buffer (62.5 mM Tris–HCl pH 6.8, 2 % SDS, 25 % glycerol, 0.01 % bromophenol blue and 5 % 2-mercaptoethanol). After separation by SDS-PAGE, proteins were transferred to PVDF membranes (Millipore, Benford, MA, USA) and blocked with 5 % milk in Tris-buffered saline Tween-20 (TBST, 20 mM Tris–HCl, pH 7.6, containing 150 mM NaCl and 0.1 % Tween-20) for 1 h. The membrane was then washed in TBST and incubated with serum (1:200) overnight at 4 °C. After rinsing, the membrane was incubated with protein G HRP conjugate (1:10,000; Millipore) for 1 h. Immunoblots were detected by enhanced chemiluminescence with ChemiDoc XRS (Bio-Rad Laboratories, Hercules, CA, USA).

were IIa in four patients, IIb in 11 patients, III in nine patients, and IV in 13 patients. Screening of Auto Antigen Proteins Among the 2,183 autoantigen candidate proteins, 44 proteins exhibited relatively high luminescence signals (Table 1). In the second screening, sera from 37 PC patients and 20 healthy controls were individually mixed with the 44 biotinylated proteins described above. For the nine proteins shown in Table 2, relative luminescence signals of PC patients were significantly higher than those of healthy controls (p \ 0.05). Calcium and integrin binding 1 (CIB1) protein had the highest significance (p = 0.002); its area under the curve (AUC) was 0.753; and its sensitivity, specificity, positive predictive value, and negative predictive value for PC diagnosis were 75.7, 70.0, 82.4, and 60.9 %, respectively, when the optimal cutoff to detect PC was set at 1.22 by ROC curve (Table 2). When the four most significant proteins (CIB1, KIAA0409, RIT2 or TNP1) were positive, values for PC diagnosis were 97.3, 35.0, 73.5, and 87.5 %, respectively. Clinical parameters, including age, sex, clinical stage, and levels of CEA and CA19-9, did not differ between PC patients with high and low levels of CIB1 autoantibody (Table 3). High and low levels of CIB1 autoantibody did not significantly differ for 21 patients with pathologically confirmed PC (Table 4). Incidentally, luminescence signals did not differ for any proteins between patients who underwent pancreatectomy and those who did not (data not shown).

Statistical Analysis Statistical analyses were performed using JMP statistical software (version 8.0.1; SAS Institute, Cary, NC, USA). Optimal cutoff points for biomarkers to discriminate PC and healthy control groups came from receiver operating characteristic (ROC) curves, which were generated by calculating sensitivities and specificities at several predetermined cutoff points. Clinicopathological parameters were compared between patients with high relative luminescence signals of specific autoantibody and those with low signals. Comparison between the two groups was assessed by Mann–Whitney U test or Chi-squared test. A p value of \0.05 was considered significant.

Validation of Identified Autoantigen Protein by Immunoblotting Immunoblot analysis was used to confirm AlphaScreenÒ results. Purified biotinylated CIB1 was transferred to the PVDF membrane, which was incubated separately with the sera of four PC patients. Two columns of sera with relatively higher luminescence signals in the AlphaScreenÒ assay (3.51 and 2.17) showed bands corresponding to the CIB1 molecular weight seen for the positive control (Fig. 1), whereas the two sera columns with lower luminescence signals (1.29 and 1.18) showed no bands (Fig. 1). DISCUSSION

RESULTS Disease Staging Clinical JPS stages for PC were stage III in 15 patients, IVa in ten patients, and IVb in 12 patients; the UICC stages

Our study had the following findings: (1) autoantibodies significantly increased against nine proteins in PC patients; (2) in the BPL we used, CIB1 autoantigen varied most with PC, at 75.7 % sensitive and 70.0 % specific alone, and 97.3 % sensitive and 35.0 % specific when combined with

Y. Nagayoshi et al. TABLE 1 First screening: relative luminescence signals of 44 proteins from six serum mixtures Stage

III

IVa

IVb

Sex

M

F

M

F

M

1

ADAM20

1.05

1.12

1.40

1.15

1.03

1.12

23

NRAS

1.06

1.08

2

ATP6V1G1

1.24

1.29

1.31

1.03

1.16

1.54

24

PCNA

1.15

1.50

3

CALM3

1.10

1.11

1.12

1.14

1.03

2.24

25

PGAM2

1.18

1.11

1.11

4

CD2

1.10

1.11

1.05

0.99

1.41

1.17

26

PIGH

1.41

1.05

1.15

1.13

1.07

1.11

5

CIB1

1.27

1.24

1.28

1.47

1.18

1.13

27

PRM2

1.21

1.10

1.39

1.22

1.37

1.70

6

CLIC5

1.43

1.49

1.51

1.26

1.25

1.97

28

RIT2

1.25

1.23

1.33

1.22

1.24

1.78

7 8

COQ2 CXXC5

0.91 1.36

1.00 1.28

0.96 1.22

0.95 1.23

0.96 1.14

2.44 1.57

29 30

RNF10 RRM1

1.26 1.01

1.37 1.68

1.31 1.02

1.12 1.09

1.07 1.07

1.52 1.10

F

Stage

III

Sex

M

IVa F

M

IVb F

M

F

1.13

1.05

1.63

0.97

0.99

0.98

1.07

1.02

1.09

1.53

1.67

9

CYBRD1

0.89

1.07

0.99

0.95

0.97

2.25

31

SAMHD1

1.16

1.11

1.15

1.13

1.30

1.52

10

DTYMK

3.19

1.01

1.00

0.96

0.90

1.09

32

SERPINB5

1.15

1.07

1.03

1.00

3.13

1.07

11

EIF3S4

1.21

1.18

1.22

1.16

1.24

1.50

33

SLC7A11

1.22

1.52

1.08

1.06

1.06

1.00

12

GABARAPL2

1.74

1.56

1.99

1.76

1.53

3.50

34

SOX6

1.21

1.06

1.17

1.07

1.28

1.56

13

GMNN

1.12

1.19

1.11

1.63

1.17

1.21

35

SRP19

1.22

1.20

1.25

1.10

1.17

1.64

14

HIST1H1C

1.18

1.16

1.10

1.16

1.11

1.44

36

STK33

1.18

1.07

1.19

1.16

1.22

1.49

15

HM13

1.22

1.18

1.18

1.07

1.11

1.62

37

TAF11

1.19

1.24

1.28

1.17

1.23

1.48

16

HNRPA2B1

1.51

1.25

1.13

1.20

1.03

1.39

38

TNP1

1.27

1.17

1.20

1.07

1.21

1.55

17

IFNAR1

1.02

1.16

1.11

0.97

2.18

1.18

39

TOMM34

1.17

1.24

1.30

1.21

1.12

1.95

18

KCTD14

1.15

1.33

1.38

1.26

1.14

1.57

40

TPM3

1.03

1.59

1.09

1.09

1.06

1.08

19

KIAA0409

1.30

1.26

1.26

1.26

1.20

1.60

41

TPM4

0.96

1.00

0.94

0.89

3.88

1.07

20

LGALS3

1.29

1.26

1.39

1.23

1.30

1.41

42

TRPT1

1.17

1.24

1.32

1.35

1.11

1.59

21

LRRC6

1.24

1.44

1.33

1.19

1.22

1.32

43

UBXD1

1.03

1.96

0.99

1.01

0.94

1.02

22

METTL1

1.24

1.36

1.25

1.24

1.10

1.57

44

UBXD3

1.12

1.16

1.19

1.09

1.27

1.48

Maximum relative luminescence signal among six serum mixtures was indicated in bold TABLE 2 Mean relative luminescence signals of nine proteins and evaluation of nine specific protein markers Gene symbol

Mean relative luminescence signal PC (n = 37)

p value

Sensitivity

Specificity

PPV

NPV

AUC

Control (n = 20)

CIB1

1.62 ± 0.69

1.23 ± 0.17

0.002

75.7

70.0

82.4

60.9

0.753

TNP1

1.47 ± 0.54

1.15 ± 0.21

0.004

89.2

55.0

78.6

73.3

0.732

KIAA0409 RIT2

1.79 ± 1.06 1.54 ± 0.72

1.27 ± 0.37 1.12 ± 0.27

0.006 0.012

64.9 75.7

70.0 65.0

80.0 80.0

51.9 59.1

0.720 0.704

DTYMK

1.58 ± 0.81

1.19 ± 0.22

0.018

62.2

75.0

82.1

51.7

0.691

GABARAPL2

2.71 ± 2.33

1.67 ± 0.90

0.031

67.6

75.0

83.3

55.6

0.674

EIF3S4

1.24 ± 0.42

1.02 ± 0.15

0.035

48.7

85.0

85.7

47.2

0.670

PCNA

1.99 ± 2.29

1.24 ± 0.42

0.037

54.1

85.0

87.0

50.0

0.669

STK33

1.33 ± 0.37

1.13 ± 0.18

0.038

62.2

75.0

82.1

51.7

0.668

AUC area under the curve, NPV negative predictive value, PC pancreatic cancer, PPV positive predictive value

the next three most sensitive autoantigens; and (3) CIB1 autoantibody did not significantly vary with other clinicopathological characteristics. We used AlphaScreenÒ to identify several possible highly sensitive biomarkers for PC. The AlphaScreenÒ system with wheat-synthesized BPL seems useful for screening autoantibodies as this system has the unique

merit of recognizing biotinylated protein directly in the translation mixture without purification, unlike other conventional techniques such as serological proteome analysis and serological expression cloning. In addition, much of the procedure in this study is automated, including recombinant protein synthesis, antigen–antibody reaction, and AlphaScreenÒ detection. These enable high-throughput

Autoantibodies in Pancreatic Cancer Patients TABLE 3 Comparison of clinical features between high and low CIB1 signal in 37 patients with pancreatic cancer

Age (years)

High signal (n = 28)

Low signal (n = 9)

p value

64.7 ± 7.7

60.3 ± 11.5

0.29 Age (years)

Sex M F

16 12

6 3

0.61

clinical stage in jps III

12

3

IVa

8

2

IVb

8

4

0.68

p value

67.0 ± 7.7

60.3 ± 15.4

0.45 0.31

M

8

3

F

9

1

PD

6

1

DP

11

3

Operation

4

0

0.31

III

11

3

5

0

1

1

IIb

8

3

III

8

1

IVb

IV

8

5

8.9 ± 16.6

7.8 ± 18

CA19-9 (U/mL)

Low signal (n = 4)

Sex

IVa

CEA (ng/mL)

High signal (n = 17)

0.69

Clinical stage in JPS

TNM classification IIa

TABLE 4 Comparison of clinicopathological features between those with high and low CIB1 signals among 21 patients who underwent pancreatectomy for pancreatic cancer

1,160 ± 3,968

335 ± 539

0.29

Tumor status in TNM 0.10 0.97

CA19-9 carbohydrate antigen 19-9, CEA carcinoembryonic antigen, CIB1 calcium and integrin binding 1, JPS Japan Pancreas Society, TNM TNM clinical classification

T3

13

T4 4 Nodal status in TNM

4

0.28

0

N0

4

0

N1

13

4

0.28

Clinical stage in TNM 14

and universal array. Thus, this method is suitable for large-scale screening and could potentially be one of the simplest means of identifying autoantigen proteins in various diseases, including cancer. The serum that showed a signal intensity of 1.29 for CIB1 in the AlphaScreenÒ assay had no detectable CIB1 signal in the immunoblotting analysis. We previously reported that biotinylated protein in translation mixture was detectable by specific antibody in concentrations as low as 0.5 pg/ll in the AlphaScreenÒ system.14 Thus, this method may find autoantibodies in quantities that are too small to be detected by immunoblotting. Clinicopathological factors did not significantly correlate with autoantibody levels in this study, which accords with the previous reports about other gastrointestinal cancer biomarkers.24,25 On the other hand, in patients with small-cell lung cancer, the presence of small-cell lung cancer-associated autoantibodies seems to correlated with slower tumor growth, higher complete response rate to therapies, and better survival rate, compared with the absence of markers.26,27 Those reports also suggest that the presence of autoantibodies in cancer patients does not always reflect tumor stage or prognosis, and might only indicate the presence of malignancy. Although CIB1 antibody level and expression of CIB1 in immunostaining did not correlate in our study (data not shown), previous studies suggest that CIB1 expression correlates with tumor progression, and CIB1 may be a biomarker of other carcinomas, including hepatocellular carcinoma and breast

IIa

4

0

IIb

8

3

III

4

0

IV

1

1

Negative

5

2

Positive

12

2

Negative

8

1

Positive

9

3

0.31

Lymphatic invasion 0.44

Vessel invasion 0.42

CIB1 calcium and integrin binding 1, DP distal pancreatectomy, JPS Japan Pancreas Society, PD pancreatoduodenectomy, TNM TNM clinical classification

FIG. 1 Western blot analysis using purified biotinylated CIB1 protein. Purified biotinylated CIB1 was resolved on SDS-PAGE, and then probed with four sera, streptavidin–HRP conjugate and antiCIB1 antibody. CIB1 calcium and integrin binding 1

cancer.28,29 To the best of our knowledge, this is the first report associating CIB1 antibody in sera with PC based on proteomic analysis. Hence, a prospective study with a large

Y. Nagayoshi et al.

cohort sample, including different types of pancreatic malignancies or inflammatory and autoimmune diseases, is needed to validate future clinical use of serum CIB1 autoantibody levels. All patients in the current study had predominantly advanced disease; therefore, further analyses using sera of patients with early-stage PC are required to assess the clinical significance of autoantibodies. CIB1 is a Ca2?-binding protein of 22 kDa that was initially identified as a protein that interacts with integrin aIIbb3. Several CIB1-binding proteins, such as DNAdependent protein kinase, polo-like kinases (Plk) 2 and 3,30 Rac3,31 Pax3,32 and presenilin 233 have been identified; CIB1 may affect cancer progression by interaction with these kinases. CIB1 has been also shown to interact with Plk3, a member of the Plk family protein that mediated cell-cycle regulation and is negatively correlated with the development of some cancers.34 Naik et al.29 reported that CIB1 constitutively binds Plk3 and inhibits its kinase activity in a Ca2?dependent manner. Thus, upregulation of CIB1 in cancer cells could inhibit Plk3 activity, leading to abnormal cellcycle regulation in cancer cells. If this is the case, then CIB1 might become a new target of cancer therapy. CONCLUSIONS We found several autoantibodies increased in the sera of PC patients with a wheat cell-free protein production system; of these, autoantibodies against CIB1 protein were the most significant. Our results suggest that these autoantibodies could be used clinically to detect PC. DISCLOSURE Yosuke Nagayoshi, Masafumi Nakamura, Kazuhiro Matsuoka, Takao Ohtsuka, Yasuhisa Mori, Hiroshi Kono, Teppei Aso, Noboru Ideno, Shunichi Takahata, Akihide Ryo, Hiroyuki Takeda, Tetsuhide Ito, Yoshinao Oda, Yaeta Endo, Tatsuya Sawasaki, and Masao Tanaka have no conflicts of interest directly relevant to the content of this article.

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Profiling of autoantibodies in sera of pancreatic cancer patients.

Although autoantibodies to cancer antigens are candidates for biomarkers, no comprehensive studies to detect cancer-specific antibodies have been perf...
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