Autoantibodies to Ezrin are an early sign of pancreatic cancer in humans and in genetically engineered mouse models
- Michela Capello1, 2,
- Paola Cappello1, 2,
- Federica Caterina Linty1, 2,
- Roberto Chiarle1,
- Isabella Sperduti3,
- Anna Novarino4,
- Paola Salacone5,
- Giorgia Mandili1, 2,
- Alessio Naccarati6,
- Carlotta Sacerdote6, 7,
- Stefania Beghelli8,
- Samantha Bersani9,
- Stefano Barbi9,
- Claudio Bassi10,
- Aldo Scarpa8, 9,
- Paola Nisticò11,
- Mirella Giovarelli1, 2,
- Paolo Vineis6, 12,
- Michele Milella13 and
- Francesco Novelli1, 2Email author
© Capello et al.; licensee BioMed Central Ltd. 2013
Received: 17 July 2013
Accepted: 20 August 2013
Published: 6 September 2013
Pancreatic Ductal Adenocarcinoma (PDAC) is a highly aggressive malignancy with only a 5% 5-year survival rate. Reliable biomarkers for early detection are still lacking. The goals of this study were (a) to identify early humoral responses in genetically engineered mice (GEM) spontaneously developing PDAC; and (b) to test their diagnostic/predictive value in newly diagnosed PDAC patients and in prediagnostic sera.
Methods and results
The serum reactivity of GEM from inception to invasive cancer, and in resectable or advanced human PDAC was tested by two-dimensional electrophoresis Western blot against proteins from murine and human PDAC cell lines, respectively. A common mouse-to-human autoantibody signature, directed against six antigens identified by MALDI-TOF mass spectrometry, was determined. Of the six antigens, Ezrin displayed the highest frequency of autoantibodies in GEM with early disease and in PDAC patients with resectable disease. The diagnostic value of Ezrin-autoantibodies to discriminate PDAC from controls was further shown by ELISA and ROC analyses (P < 0.0001). This observation was confirmed in prediagnostic sera from the EPIC prospective study in patients who eventually developed PDAC (with a mean time lag of 61.2 months between blood drawing and PDAC diagnosis). A combination of Ezrin-autoantibodies with CA19.9 serum levels and phosphorylated α-Enolase autoantibodies showed an overall diagnostic accuracy of 0.96 ± 0.02.
Autoantibodies against Ezrin are induced early in PDAC and their combination with other serological markers may provide a predictive and diagnostic signature.
KeywordsPancreatic ductal adenocarcinoma Tumor antigen Genetically engineered mouse model Early diagnosis Ezrin
Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer death in Western countries. Upon diagnosis, less than 20% of patients present localized, potentially curable tumors. The overall 5-year survival rate is <5% [1, 2]. This poor prognosis has been attributed to failure in early disease diagnosis, when the tumor may still be resectable, along with its propensity to disseminate and its resistance to systemic treatment . CA19.9 is the only biomarker that has demonstrated clinical value for therapeutic monitoring and early detection of recurrent disease after treatment in patients with known pancreatic cancer. However, its use as a screening tool has proved unsuccessful, thus other biomarkers alone or in combination with it are required for early diagnosis of PDAC .
Autoantibody levels can function as diagnostic and prognostic markers [4, 5]. By SERological Proteome Analysis (SERPA) we have previously identified a number of PDAC-associated antigens that are specifically recognized by circulating autoantibodies present in the serum of PDAC patients [6–9]. However as these autoantibodies were discovered in sera from patients at advanced stages of PDAC, earlier diagnostic markers would not have been identified.
Genetically engineered mice (GEM) that spontaneously develop PDAC may be used to facilitate the development of novel tests for the early detection and treatment of PDAC . LSL-Kras G12D/+ ; Pdx-1-Cre mice (KC) develop the entire histologic compendium of pancreatic intraepithelial neoplasia (PanIN) lesions observed in the human disease, and a subset of mice also develop invasive pancreatic carcinomas. LSL-Kras G12D/+ ; LSL-Trp53 R172H/+ ; Pdx-1-Cre double mutant mice (KPC), develop a more aggressive invasive and metastatic PDAC with an earlier time of onset, and display a reduced survival rate compared to KC mice [11, 12].
In the present study, we used SERPA to identify TAAs eliciting an early humoral response in KC and KPC. Results from two-dimensional electrophoresis (2DE), Western blotting (WB) and mass spectrometry (MS) were combined to compare the reactivity of KC and KPC sera to that of corresponding matched controls. Antigens recognized by autoantibodies in KC and KPC at PanIN stages were identified and validated in a set of resectable and advanced PDAC patients. Ezrin (EZR), the protein with the highest frequency of autoantibodies in both early stage GEM and resectable PDAC patients, was validated by ELISA test using PDAC sera either collected at the time of diagnosis or several months before cancer onset (prediagnostic PDAC). The sensitivity and specificity of EZR-autoantibodies for discriminating PDAC was evaluated together with other serological markers.
All animals were treated in accordance with European and institutional guidelines (Legislative Order No. 116/92). 129SvJae/B6 H-2Db mice carrying mutated KrasG12D and Trp53R172H under the endogenous promoter, and flanked by Lox-STOP-Lox cassettes (LSL-Kras G12D/+ and LSL-Trp53 R172H/+ ) were kindly provided from Dr. D.A. Tuveson (Cancer Research UK, Cambridge Research Institute, Cambridge, UK). C57BL/6 mice expressing Cre recombinase under a specific pancreatic transcriptional factor Pdx-1 (pancreatic duodenum homeobox 1) promoter (Pdx-1-Cre) were obtained from Dr. A.M. Lowy (University of California, San Diego, CA). Conditional LSL-Kras G12D/+ , LSL-Trp53 R172H/+ and Pdx-1-Cre strains were bred to obtain LSL-Kras G12D/+ ; Pdx-1-Cre single mutant (KC) and LSL-Kras G12D/+ ; LSL-Trp53 R172H/+ ; Pdx-1-Cre double mutant (KPC) mice [11, 12]. To collect serum, mice were euthanized and blood was collected by cardiac puncture using a 22-gauge needle and 1 ml syringe. Mice were surgically and pathologically examined to confirm the presence of pancreatic tumors and metastases.
Cross-sectional clinical study
Clinical features of PDAC patients analyzed by ELISA
Surgery with radical intent
Baseline CA19.9 (IU/ml)
2- > 12000
First-line chemotherapy c
Prospective pre-clinical study
Characteristics of the EPIC cohort subjects
Time span to diagnosis (mo)
Two-dimensional electrophoresis and western blot analysis
Cells (107) from the CF-PAC-1 (ECACC ref. No. 91112501) and K8484 isolated from a tumor arising in KPC mice, kindly provided by Dr. K.P. Olive (Columbia University, New York, NY), were solubilized, subjected to 2DE and electro-transferred onto a nitrocellulose membrane (GE Healthcare Bio-Sciences, Uppsala, Sweden) as previously described . Frozen PDAC tissues from eight surgically-treated patients (stage IIA and IIB of PDAC) were homogenized in 2DE lysis buffer, subjected to 2DE and electro-blotted onto a nitrocellulose membrane (GE Healthcare) as previously described . Sera from KC, KPC, PDAC patients and controls were tested to determine mouse and human IgG concentrations using commercial kits (IgG ELISA Quantitation Set from Bethyl Laboratories - Montgomery, TX, USA). Sera were individually tested on 2DE maps at a working dilution of 0.1 mg/ml IgG for 4 h, followed by incubation with horseradish peroxidase (HRP)-conjugated rabbit anti-human IgG (90 minutes, 1:1000; Santa Cruz Biotechnology, Santa Cruz, CA, USA) or sheep anti-mouse Ig (90 minutes, 1:5000; GE Healthcare) as a secondary antibody. Ezrin spots were revealed with anti-Ezrin antibody (1 hour incubation, 1:5000; Abcam, Cambridge, MA, USA) and HRP-conjugated donkey anti-rabbit IgG (1 hour incubation, 1:2000; GE Healthcare) as a secondary antibody. Immunodetection was accomplished by ECL PLUS (Enhanced Chemiluminescence, GE Healthcare). The chemifluorescent signals were scanned with “ProXPRESS 2D” (PerkinElmer, Waltham, MA, USA) with an excitation/emission filter setting of 460/80 and 530/30, respectively, for an exposure time of 12 s. Images were recorded in TIFF format. The volume of each spot recognized by autoantibodies was calculated after background subtraction using “ProFinder 2D” (PerkinElmer) software and reported as arbitrary units (AU). For proteins represented from more than one spot the volume was expressed as a mean value.
Protein identification by mass spectrometry
Coomassie G-stained spots were excised from 2DE preparative gels; destaining and in-gel enzymatic digestion were performed as previously described . Briefly each spot was destained with 100 μl of 50% vol/vol acetonitrile in 5 mmol/l ammonium bicarbonate and dried with 100 μl of acetonitrile. Each dried gel piece was rehydrated for 40 minutes at 4°C in 10 μl of a digestion buffer containing 5 mmol/l ammonium bicarbonate, and 10 ng/μl of trypsin. Digestion was allowed to proceed overnight at 37°C and peptide mixtures were stored at 4°C until assayed. All digests were analyzed by a MALDI micro MX - TOF Mass Spectrometer (Waters, MA, USA) equipped with a delayed extraction unit. Peptide solution was prepared with equal volumes of saturated α-cyano-4-hydroxycinnamic acid solution in 40% vol/vol acetonitrile-0.1% vol/vol trifluoroacetic acid. The MALDI-TOF was calibrated with a mix of PEG (PEG 1000, 2000 and 3000 with the ratio 1:1:2) and mass spectra were acquired in the positive-ion mode. Peak lists were generated with ProteinLynx Data Preparation (ProteinLynx Global Server 2.2.5) using the following parameters: external calibration with lock mass using mass 2465.1989 Da of ACTH, background subtract type adaptive combining all scans, performing deisotoping with a threshold of 1%. The 25 most intense masses were used for database searches against the SWISSPROT database (Release 2011_12 of 14-Dec-11) using the free search program MASCOT 2.3.02 (http://www.matrixscience.com/cgi/search_form.pl?FORMVER=2&SEARCH=PMF). The following parameters were used in the searches: taxa Homo sapiens or Mus musculus, trypsin digest, one missed cleavage by trypsin, carbamidomethylation of cysteine as fixed modification, methionine oxidation as variable modifications and maximum error allowed 100 ppm. Only proteins with a Mascot score >55 were taken into consideration.
Anti-Ezrin autoantibody capture by enzyme-linked immunosorbent assay
Purified recombinant protein of Homo sapiens Ezrin, transcript variant 1 (OriGene, Rockville, MD, USA) was used to capture autoantibodies to Ezrin. Briefly, the protein was coated (0.5 μg/ml in PBS) on 96-well micro-plates overnight at room temperature, followed by blocking with PBS containing 4% bovine serum albumin for 2 hours at room temperature. Sera (working dilution 0.01 mg/ml) were then added to the coated wells for 2 hours at room temperature. After washing with PBS-Tween-20, microplates were incubated with HRP-conjugated rabbit anti-human IgG (dilution 1:1000; Santa Cruz Biotechnology) for 1 hour at room temperature and TMB One Solution (Promega, Madison, WI, USA) was added to each well. The reaction was stopped by 2N HCl and the optical density (OD) value was measured at 450 nm. The corresponding background values of the sera on uncoated wells were subtracted. All samples were assayed in triplicate and the results represent mean values.
Statistical analysis was performed using GraphPad (Version 4, San Diego, CA), MedCalc (Version 220.127.116.11, Mariakerke, Belgium) and SPSS (Version 18.0, Chicago, IL, USA) software packages. Mouse survival was estimated by Kaplan-Meier analysis and compared with Log-rank tests. Receiver operating characteristic (ROC) curve analysis was performed in order to find the optimal cut-off levels capable of splitting patients into groups with different outcome probabilities. Specificity, sensitivity and area under curve (AUC) were estimated considering histology results as the gold standard. The classification and regression tree (CART) analysis, a type of decision tree methodology, is a nonparametric statistical procedure that identifies mutually exclusive and exhaustive subgroups of a population whose members share common characteristics that influence the dependent variable of interest. CART uses a binary recursive partitioning method that produces a decision tree that identifies subgroups of patients with a higher likelihood of being found positive in a test for a disease state. The exhaustive CHAID method was used for CART analysis. Correlations and associations between variables were tested by Pearson’s test, Student's t-test, χ2 test or Fisher’s exact test, as appropriate. For all tests, 2-sided P < 0.05 (*), P < 0.005 (**) and P < 0.0005 (***) values were considered significant.
Serological proteome analysis in mice that spontaneously develop PDAC
Serological proteome analysis in human PDAC
Frequencies of sera reactivity against protein spots in analyzed groups
(N = 120)
(N = 50)
(N = 46)
(N = 12)
(N = 40)
P < 0.0001
P = 0.0024
P = 0.0193
P = 0.0005
P < 0.0001
P = 0.0361
P = 0.1221
P = 0.0033
P < 0.0001
P < 0.0001
P = 0.0135
P < 0.0001
P < 0.0001
P = 0.0006
P = 0.0039
P < 0.0001
P = 0.0003
P = 0.0053
P = 0.2198
P = 0.0012
P < 0.0001
P = 0.0052
P = 0.0003
P < 0.0001
Cross-sectional clinical study: detection of anti-Ezrin autoantibodies
EZR was the antigen recognized at the highest frequencies by sera from both GEM at early stages of the disease and resectable PDAC patients, and its identification was later proved through 2DE WB in K8484, CF-PAC-1 cells and PDAC tissues (Additional file 1: Figure 1). This analysis confirmed the presence of different EZR isoforms both in murine and human PDAC, likely due to different post-translational modifications (e.g. phosphorylation).
Prospective pre-clinical study: validation of anti-Ezrin autoantibodies
To investigate the occurrence of autoantibodies to EZR several months before PDAC diagnosis, we took advantage of the serum specimens from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort where blood samples were collected from healthy volunteers monitored longitudinally for cancer or other diseases development over the years. Sixteen prediagnostic PDAC patient specimens, with a time span to diagnosis of 5–117.1 mo (mean, 61.2 mo), and thirty-two matched controls from the Turin EPIC cohort were used for this study. Controls were matched for age, sex, and date of enrollment (Table 2). Notably, the level of autoantibodies to EZR was significantly higher in prediagnostic PDAC serum samples compared to matched controls (P = 0.0002), showing a similar trend of reactivity in both newly diagnosed and prediagnostic PDAC sera (Figure 4B). Detailed time lag to diagnosis and ELISA values for each PDAC patient of the EPIC cohort are shown in Additional file 1: Table S3.
Analysis of diagnostic performance and clinical correlations
These ELISA results prompted us to use ROC analysis to assess the diagnostic performance of EZR-autoantibody detection. The analysis performed, using OD obtained in ELISA as a continuous variable, showed the greatest discriminating power between PDAC patients (n = 69) and benign controls (HS, CP and AD patients, n = 94) at a cut-off level of 0.1183 (sensitivity 93.2%, specificity 75.5%, AUC 0.90 ± 0.03; Figure 4C). With reference to the same cut-off, the ELISA test was also very efficient in discriminating between PDAC patients and patients with non-PDAC malignancies, with 94.9% sensitivity, 96.4% specificity, and an AUC of 0.99 ± 0.01 (data not shown). Thus we dichotomized the EZR-autoantibody variables into positive and negative according to the above-mentioned cut-off level (0.1183) for all subsequent analyses.
Dichotomized EZR-autoantibody levels did not show any correlation with clinical parameters (age, gender, stage at diagnosis, ECOG PS). However, mean and median OD values were significantly (P = 0.030) higher in PDAC patients who had undergone radical surgery (see also ROC analysis in Additional file 1: Figure S4, right panel).
We have previously demonstrated that autoantibodies to ENOA1,2, two phosphorylated isoforms of ENOA, usefully complement the diagnostic performance of CA19.9 serum levels [9, 16]. Thus, we tested by CART analysis the diagnostic performance of EZR-autoantibodies in concomitance with the above biomarkers: CA19.9 (using the most relevant clinical laboratory cut-off value of 37 IU/ml) and ENOA1,2-autoantibodies, in the cohort of samples where all three parameters were available (PDAC patients: n = 45; HS, AD, CP: n = 48) (Figure 4D). Using this approach, the first node that significantly discriminated PDAC patients from benign controls was CA19.9 (P < 0.001). EZR-autoantibodies significantly refined CA19.9 diagnostic performance, particularly in CA19.9-negative cases (P < 0.0001). Finally, in the few cases in which CA19.9 and EZR-autoantibodies yielded conflicting results (i.e. CA19.9 negative/EZR-autoantibodies positive), ENOA1,2-autoantibodies significantly improved diagnostic performance (P = 0.0022). Since only one control subject in our cohort displayed high CA19.9 serum levels, CART analysis could not further classify CA19.9 positive cases. However, among CA19.9 positive cases only one PDAC patient and the above mentioned control subject resulted negative for EZR-autoantibodies, and they were again properly classified by ENOA1,2-autoantibodies. Based on these findings, a diagnostic algorithm which assigned patients to the PDAC group when both EZR-autoantibodies and CA19.9 were positive, and separated discordant cases into PDAC or controls based on the presence or absence of ENOA1,2-autoantibodies, respectively, resulted in 100% sensitivity and 92.3% specificity, with an overall diagnostic accuracy (AUC) of 0.96 ± 0.02 (Figure 4E). The diagnostic performance of EZR-autoantibody, CA19.9 and ENOA1,2-autoantibody tested individually in the same cohort is shown in Additional file 1: Figure S4.
While EZR autoantibodies have diagnostic potential, they did not show the prognostic value we have previously reported for ENOA1,2 . Even though PDAC patients who had experienced disease control (either partial response or stable disease) upon first-line chemotherapy had significantly (P = 0.030) higher mean and median OD values in the EZR ELISA, EZR-autoantibodies analyzed as a continuous variable had no significant impact on survival (PFS or OS), either following surgery with radical intent or first-line chemotherapy. This demonstrates the power of the SERPA approach, combined with ELISA, to identify antigens that could serve distinct functions in an armament of tools for the diagnosis and prognosis of PDAC.
This study identifies autoantibodies to EZR as early markers in mouse and human PDAC. Of clinical relevance, we also show that EZR-autoantibodies efficiently complement the diagnostic performance of CA19.9.
To identify early immune response markers we applied SERological Proteome Analysis (SERPA) in KC and KPC mice spontaneously developing PDAC. As GEM can be sampled at defined stages of tumor development and under controlled breeding conditions, greater standardization is possible when using mouse models as opposed to human studies. GEM allowed us to identify EZR-autoantibodies as early biomarkers in PDAC, since precociously detected in their serum when the disease stage was limited to PanIN. Through this approach, we also identified additional antigens (VCL, PDC6I, FUBP2, hnRNPL, VIM, K2C8, ANXA1 e ANXA2) recognized at high frequencies by both KC and KPC sera.
Reactivity against some of these antigens was present in control mice, but the intensity of WB recognition was much greater in GEM. A clear example is represented by EZR, faintly recognized by a number of control mice but strongly evident in all KPC. Despite the fact that auto-reactive lymphocytes should have been removed from the repertoire before maturation into naïve B cells, a large number of circulating IgG+ memory B cells produce low affinity antibodies to self-antigens [17, 18]. The humoral response against these self-antigens is strongly increased in tumor conditions, as demonstrated in this work both in humans and in mice (Figure 1, Table 3 and Figure 4). Some differences in the pattern of recognition were present between mice of the same age, probably due to the molecular heterogeneity of tumor progression in this model that fully recapitulates the genetic and molecular features of human PDAC . Importantly, all the identified antigens, except for FUBP2 and ANXA1, induced a powerful humoral response not only in KPC but also in KC bearing PanIN lesions, indicating that the antibody response to these TAAs is already occurring when Kras is the only genetic alteration in the tumor, independently of p53 mutation, which is a later event in PDAC development. This reflects previous studies reporting how the immune response to TAAs in humans occurs at an early stage during tumorigenesis, as illustrated by the detection of high titers of autoantibodies, as early as 5 years before disease onset [19, 20].
By comparing the 2DE WB reactivity of GEM with that of a large cohort of PDAC patients and controls, six proteins, namely: EZR, ANXA2, VCL, hnRNPL, ANXA1 and PDC6I were common to both human and mouse signatures. EZR and ANXA2 were recognized by most PDAC patients who underwent surgery with curative intent. ELISA confirmed the diagnostic value of anti-EZR but not anti-ANXA2 autoantibodies, which were also present in control groups. Other studies have indeed reported the presence of autoantibodies against ANXA2 in systemic autoimmune diseases and lung cancer, as well as pancreatic cancer [21–23], suggesting that the humoral response to ANXA2 is not specific for PDAC transformation.
EZR is a member of the ezrin-radixin-moesin (ERM) family and a link between a number of growth factor receptors/adhesion molecules and the actin cytoskeleton. It is localized to the cytoplasm as an inactive form. Upon threonine and tyrosine phosphorylation, EZR is transported to the cell membrane whereupon it tethers F-actin . It works downstream of cell-surface receptors through the activation of Rho and PI3K/Akt signaling pathways [25, 26], and in physiological conditions, EZR is required for macropinocytosis, cell adhesion, and membrane ruffling in epithelial cells, whereas in tumor cells it is an important metastatic regulator . EZR is overexpressed in many cancers, including PDAC, even in PanIN lesions [28–30], and it interacts with cortactin to form podosomal rosettes in PDAC cells, which may play an important role in tumor invasion . These observations support the immunogenicity of EZR that we observed in the present study, even if it is not clear how TAAs overcome self-tolerance and thus become autoantibody targets in cancer patients, as many of those discovered so far are intracellular proteins [4, 32, 33]. Interestingly, EZR has been identified both in exosomes secreted by mesothelioma cells  and as a substrate of matrix metalloproteinases able to generate neo-epitopes from self-antigens .
The most important observation of our study is that autoantibodies against EZR were present also in prediagnostic PDAC samples from the prospective EPIC cohort that were collected several months or years before PDAC diagnosis. The EPIC study recruited over half a million healthy volunteers in ten European countries, including Italy, monitored longitudinally for cancer or other disease development . Since it has been estimated that the elapsed time between PDAC initiation to metastatic spread is at least 10 years , our results strongly support the hypothesis that EZR-autoantibody development is an early event in PDAC. Notably, prediagnostic patients with the highest levels of EZR-autoantibody in the ELISA test were the ones with an intermediate time lag to diagnosis (69.3 and 56.9 mo, Additional file 1: Table S3). This observation supports the hypothesis that autoantibody levels decrease closer to diagnosis due to immune complex formation .
Although EZR-autoantibody testing has displayed a high diagnostic performance, especially in resectable PDAC patients (Additional file 1: Figure S4), a single TAA may lack adequate sensitivity and specificity, and the combination of a panel of autoantibodies and serological markers can improve the overall accuracy of a diagnostic assay for cancer detection. We therefore assessed the diagnostic performance of combined dichotomized EZR-autoantibody levels, CA19.9, the only PDAC marker currently in clinical use, and ENOA1,2-autoantibodies. We have previously demonstrated that autoantibodies against Ser-419-phosphorylated ENOA isoforms (ENOA1,2) complement the performance of CA.19.9 . Interestingly, a diagnostic algorithm separating CA19.9 and EZR-autoantibodies discordant cases into PDAC or controls based on the presence or absence of ENOA1,2-autoantibodies respectively, resulted in an overall diagnostic accuracy of 0.96. Notably, the algorithm here applied is more stringent than the one previously described by our group , where tested cases were assigned to the PDAC group when either ENOA1,2-autoantibodies or CA19.9 were positive, as their values were inversely correlated. This finding is of real translational relevance, since CA19.9 is the only biomarker with demonstrated clinical value for therapeutic monitoring and detection of recurrent PDAC, but its use as a screening tool has proved unsuccessful until now .
Further validation studies, performed in a large and independent patient cohort, are warranted to establish the diagnostic performance of this multiplexed analysis and of the identified TAA panel tested alone or in combination.
Two dimensional electrophoresis
Area under the curve
Classification and regression tree
- ECOG PS:
Eastern cooperative oncology group performance status
Enzyme-linked immunosorbent assay
European Prospective Investigation into Cancer and Nutrition
Far upstream element binding protein 2
Genetically engineered mice
Heterogeneous nuclear ribonucleoprotein L
LSL-Kras G12D/+ , Pdx-1-Cre mice
LSL-Kras G12D/+ , LSL-Trp53 R172H/+ , Pdx-1-Cre mice
Matrix-assisted laser desorption ionization-time of flight
Pancreatic intraepithelial neoplasia
Pancreatic ductal adenocarcinoma
Programmed cell death-6 interacting protein
Pancreatic duodenum homeobox 1
Receiver operating curve
Serological analysis of tumor antigens by recombinant cDNA expression cloning
Serological proteome analysis
This work was supported in part by grants from: the European Community, Seventh Framework Program European Pancreatic Cancer-Tumor-Microenvironment Network (EPC-TM-Net, no. 256974); Associazione Italiana Ricerca sul Cancro (AIRC) 5 × 1000 (no. 12182) and IG (no. 5548 and 11643); Ministero della Salute: Progetto Integrato Oncologia; Regione Piemonte: Ricerca Industriale e Sviluppo Precompetitivo (BIOPRO and ONCOPROT), Ricerca Industriale “Converging Technologies” (BIOTHER), Progetti strategici su tematiche di interesse regionale o sovra regionale (IMMONC), Ricerca Sanitaria Finalizzata, Ricerca Sanitaria Applicata; Ministero dell’Istruzione e della Ricerca (MIUR), Progetti di Rilevante Interesse Nazionale (PRIN 2009); University of Turin-Progetti di Ateneo 2011: Mechanisms of REsistance to anti-angiogenesis regimens THErapy (grant Rethe-ORTO11RKTW). MC is recipient of a fellowship from the Fondazione Italiana Ricerca sul Cancro (FIRC).
We thank Drs. Marianne Murphy, John Iliffe and Radhika Srinivasan for critically reading the manuscript.
- Hidalgo M: Pancreatic cancer. N Engl J Med. 2010, 362: 1605-1617. 10.1056/NEJMra0901557.View ArticlePubMedGoogle Scholar
- Jemal A, Siegel R, Xu J, Ward E: Cancer statistics, 2010. CA Cancer J Clin. 2010, 60: 277-300. 10.3322/caac.20073.View ArticlePubMedGoogle Scholar
- Duffy MJ, Sturgeon C, Lamerz R, Haglund C, Holubec VL, Klapdor R, Nicolini A, Topolcan O, Heinemann V: Tumor markers in pancreatic cancer: a European Group on Tumor Markers (EGTM) status report. Ann Oncol. 2010, 21: 441-447. 10.1093/annonc/mdp332.View ArticlePubMedGoogle Scholar
- Tan HT, Low J, Lim SG, Chung MC: Serum autoantibodies as biomarkers for early cancer detection. FEBS J. 2009, 276: 6880-6904. 10.1111/j.1742-4658.2009.07396.x.View ArticlePubMedGoogle Scholar
- Hanash S: Harnessing immunity for cancer marker discovery. Nat Biotechnol. 2003, 21: 37-38. 10.1038/nbt0103-37.View ArticlePubMedGoogle Scholar
- Tomaino B, Cappello P, Capello M, Fredolini C, Ponzetto A, Novarino A, Ciuffreda L, Bertetto O, De Angelis C, Gaia E: Autoantibody signature in human ductal pancreatic adenocarcinoma. J Proteome Res. 2007, 6: 4025-4031. 10.1021/pr070281a.View ArticlePubMedGoogle Scholar
- Cappello P, Tomaino B, Chiarle R, Ceruti P, Novarino A, Castagnoli C, Migliorini P, Perconti G, Giallongo A, Milella M: An integrated humoral and cellular response is elicited in pancreatic cancer by alpha-enolase, a novel pancreatic ductal adenocarcinoma-associated antigen. Int J Cancer. 2009, 125: 639-648. 10.1002/ijc.24355.View ArticlePubMedGoogle Scholar
- Capello M, Ferri-Borgogno S, Cappello P, Novelli F: alpha-Enolase: a promising therapeutic and diagnostic tumor target. FEBS J. 2011, 278: 1064-1074. 10.1111/j.1742-4658.2011.08025.x.View ArticlePubMedGoogle Scholar
- Tomaino B, Cappello P, Capello M, Fredolini C, Sperduti I, Migliorini P, Salacone P, Novarino A, Giacobino A, Ciuffreda L: Circulating autoantibodies to phosphorylated alpha-enolase are a hallmark of pancreatic cancer. J Proteome Res. 2011, 10: 105-112. 10.1021/pr100213b.View ArticlePubMedGoogle Scholar
- Leach SD: Mouse models of pancreatic cancer: the fur is finally flying!. Cancer Cell. 2004, 5: 7-11. 10.1016/S1535-6108(03)00337-4.View ArticlePubMedGoogle Scholar
- Hingorani SR, Petricoin EF, Maitra A, Rajapakse V, King C, Jacobetz MA, Ross S, Conrads TP, Veenstra TD, Hitt BA: Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse. Cancer Cell. 2003, 4: 437-450. 10.1016/S1535-6108(03)00309-X.View ArticlePubMedGoogle Scholar
- Hingorani SR, Wang L, Multani AS, Combs C, Deramaudt TB, Hruban RH, Rustgi AK, Chang S, Tuveson DA: Trp53R172H and KrasG12D cooperate to promote chromosomal instability and widely metastatic pancreatic ductal adenocarcinoma in mice. Cancer Cell. 2005, 7: 469-483. 10.1016/j.ccr.2005.04.023.View ArticlePubMedGoogle Scholar
- Riboli E, Hunt KJ, Slimani N, Ferrari P, Norat T, Fahey M, Charrondiere UR, Hemon B, Casagrande C, Vignat J: European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection. Public Health Nutr. 2002, 5: 1113-1124. 10.1079/PHN2002394.View ArticlePubMedGoogle Scholar
- Chuang SC, Stolzenberg-Solomon R, Ueland PM, Vollset SE, Midttun O, Olsen A, Tjonneland A, Overvad K, Boutron-Ruault MC, Morois S: A U-shaped relationship between plasma folate and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition. Eur J Cancer. 2011, 47: 1808-1816. 10.1016/j.ejca.2011.02.007.PubMed CentralView ArticlePubMedGoogle Scholar
- Barbero G, Carta F, Giribaldi G, Mandili G, Crobu S, Ceruti C, Fontana D, Destefanis P, Turrini F: Protein/RNA coextraction and small two-dimensional polyacrylamide gel electrophoresis for proteomic/gene expression analysis of renal cancer biopsies. Anal Biochem. 2006, 349: 62-71. 10.1016/j.ab.2005.10.020.View ArticlePubMedGoogle Scholar
- Zhou W, Capello M, Fredolini C, Piemonti L, Liotta LA, Novelli F, Petricoin EF: Mass spectrometry analysis of the post-translational modifications of alpha-enolase from pancreatic ductal adenocarcinoma cells. J Proteome Res. 2010, 9: 2929-2936. 10.1021/pr901109w.View ArticlePubMedGoogle Scholar
- Wardemann H, Yurasov S, Schaefer A, Young JW, Meffre E, Nussenzweig MC: Predominant autoantibody production by early human B cell precursors. Science. 2003, 301: 1374-1377. 10.1126/science.1086907.View ArticlePubMedGoogle Scholar
- Tiller T, Tsuiji M, Yurasov S, Velinzon K, Nussenzweig MC, Wardemann H: Autoreactivity in human IgG + memory B cells. Immunity. 2007, 26: 205-213. 10.1016/j.immuni.2007.01.009.PubMed CentralView ArticlePubMedGoogle Scholar
- Disis ML, Pupa SM, Gralow JR, Dittadi R, Menard S, Cheever MA: High-titer HER-2/neu protein-specific antibody can be detected in patients with early-stage breast cancer. J Clin Oncol. 1997, 15: 3363-3367.PubMedGoogle Scholar
- Ladd JJ, Chao T, Johnson MM, Qiu J, Chin A, Israel R, Pitteri SJ, Mao J, Wu M, Amon LM: Autoantibody signatures involving glycolysis and splicesome proteins precede a diagnosis of breast cancer among postmenopausal women. Cancer Res. 2013, 73: 1502-1513. 10.1158/0008-5472.CAN-12-2560.PubMed CentralView ArticlePubMedGoogle Scholar
- Salle V, Maziere JC, Smail A, Cevallos R, Maziere C, Fuentes V, Tramier B, Makdassi R, Choukroun G, Vittecoq O: Anti-annexin II antibodies in systemic autoimmune diseases and antiphospholipid syndrome. J Clin Immunol. 2008, 28: 291-297. 10.1007/s10875-008-9188-1.View ArticlePubMedGoogle Scholar
- Brichory FM, Misek DE, Yim AM, Krause MC, Giordano TJ, Beer DG, Hanash SM: An immune response manifested by the common occurrence of annexins I and II autoantibodies and high circulating levels of IL-6 in lung cancer. Proc Natl Acad Sci USA. 2001, 98: 9824-9829. 10.1073/pnas.171320598.PubMed CentralView ArticlePubMedGoogle Scholar
- Zheng L, Foley K, Huang L, Leubner A, Mo G, Olino K, Edil BH, Mizuma M, Sharma R, Le DT: Tyrosine 23 phosphorylation-dependent cell-surface localization of annexin A2 is required for invasion and metastases of pancreatic cancer. PLoS One. 2011, 6: e19390-10.1371/journal.pone.0019390.PubMed CentralView ArticlePubMedGoogle Scholar
- Fehon RG, McClatchey AI, Bretscher A: Organizing the cell cortex: the role of ERM proteins. Nat Rev Mol Cell Biol. 2010, 11: 276-287. 10.1038/nrm2866.PubMed CentralView ArticlePubMedGoogle Scholar
- Hunter KW: Ezrin, a key component in tumor metastasis. Trends Mol Med. 2004, 10: 201-204. 10.1016/j.molmed.2004.03.001.View ArticlePubMedGoogle Scholar
- Chen Q, Zhang XH, Massague J: Macrophage binding to receptor VCAM-1 transmits survival signals in breast cancer cells that invade the lungs. Cancer Cell. 2011, 20: 538-549. 10.1016/j.ccr.2011.08.025.PubMed CentralView ArticlePubMedGoogle Scholar
- Niggli V, Rossy J: Ezrin/radixin/moesin: versatile controllers of signaling molecules and of the cortical cytoskeleton. Int J Biochem Cell Biol. 2008, 40: 344-349. 10.1016/j.biocel.2007.02.012.View ArticlePubMedGoogle Scholar
- Torer N, Kayaselcuk F, Nursal TZ, Yildirim S, Tarim A, Noyan T, Karakayali H: Adhesion molecules as prognostic markers in pancreatic adenocarcinoma. J Surg Oncol. 2007, 96: 419-423. 10.1002/jso.20654.View ArticlePubMedGoogle Scholar
- Abiatari I, Esposito I, Oliveira TD, Felix K, Xin H, Penzel R, Giese T, Friess H, Kleeff J: Moesin-dependent cytoskeleton remodelling is associated with an anaplastic phenotype of pancreatic cancer. J Cell Mol Med. 2010, 14: 1166-1179.PubMed CentralPubMedGoogle Scholar
- Meng Y, Lu Z, Yu S, Zhang Q, Ma Y, Chen J: Ezrin promotes invasion and metastasis of pancreatic cancer cells. J Transl Med. 2010, 8: 61-10.1186/1479-5876-8-61.PubMed CentralView ArticlePubMedGoogle Scholar
- Kocher HM, Sandle J, Mirza TA, Li NF, Hart IR: Ezrin interacts with cortactin to form podosomal rosettes in pancreatic cancer cells. Gut. 2009, 58: 271-284. 10.1136/gut.2008.159871.View ArticlePubMedGoogle Scholar
- Zinkernagel RM: What is missing in immunology to understand immunity?. Nat Immunol. 2000, 1: 181-185. 10.1038/79712.View ArticlePubMedGoogle Scholar
- Guo K, Li J, Tang JP, Tan CP, Hong CW, Al-Aidaroos AQ, Varghese L, Huang C, Zeng Q: Targeting intracellular oncoproteins with antibody therapy or vaccination. Sci Transl Med. 2011, 3: 99ra85-10.1126/scitranslmed.3002296.View ArticlePubMedGoogle Scholar
- Hegmans JP, Bard MP, Hemmes A, Luider TM, Kleijmeer MJ, Prins JB, Zitvogel L, Burgers SA, Hoogsteden HC, Lambrecht BN: Proteomic analysis of exosomes secreted by human mesothelioma cells. Am J Pathol. 2004, 164: 1807-1815. 10.1016/S0002-9440(10)63739-X.PubMed CentralView ArticlePubMedGoogle Scholar
- Cauwe B, Martens E, Proost P, Opdenakker G: Multidimensional degradomics identifies systemic autoantigens and intracellular matrix proteins as novel gelatinase B/MMP-9 substrates. Integr Biol (Camb). 2009, 1: 404-426. 10.1039/b904701h.View ArticleGoogle Scholar
- Bingham S, Riboli E: Diet and cancer–the European Prospective Investigation into Cancer and Nutrition. Nat Rev Cancer. 2004, 4: 206-215. 10.1038/nrc1298.View ArticlePubMedGoogle Scholar
- Costello E, Neoptolemos JP: Pancreatic cancer in 2010: new insights for early intervention and detection. Nat Rev Gastroenterol Hepatol. 2011, 8: 71-73. 10.1038/nrgastro.2010.214.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.