Comparative Proteomics of Pulmonary Tumors with Neuroendocrine Differentiation Nam Hoon Cho,*,†,§ Eun Suk Koh,‡ Dong Wha Lee,‡ Haeryoung Kim,† Youn Pyo Choi,†,§ Sang Ho Cho,† and Dong Su Kim| Department of Pathology, Yonsei University College of Medicine and Soonchunhyang University Hospital, Brain Korea 21 Project for Medical Science, Yonsei University, and Genomine Research Division, Genomine, Inc. Received December 14, 2005
We aimed to evaluate neuroendocrine pulmonary tumors (NEPT) by a novel method involving map tree construction by comparing all of the protein spots. We performed a proteomics analysis to assess the similarities in protein expression between neuroendocrine pulmonary tumors (NEPT), including typical carcinoids (TC), atypical carcinoids (AC), large cell neuroendocrine carcinomas (LCNEC) and small cell carcinomas (SCLC). Total protein lysates were obtained from seven histologically confirmed frozen NEPT tissues, including 1TC, 2 SCLC, and 4 cases ranging from AC to LCNEC. 2-DE demonstrated that TC was similar to normal lung. AC, LCNEC, and SCLC were similar to each other, forming a group separate from TC, however, SCLC at an early stage showed a similarity to TC. MALDI analysis detected 9 surrogate endpoint biomarkers, including eIF5A1, GST M3, cytokeratin 18 (CK 18), FK506-binding protein p59, p63, MAGE-D2, mitochondrial short-chain enoyl-coenzyme A hydratase 1, tranferrin and poly (rC) binding protein 1. Immunohistochemical staining revealed a gradual decrease in expression rate of p63 and CK 18 with poor differentiation of NEPT. Our results demonstrate that (1) the comparative proteomics of NEPT match the WHO classification except for AC and LCNEC; (2) SCLC show differences in their proteomics according to tumor stage; and (3) CK 18 and p63 may be useful as diagnostically and prognostically available markers. Keywords: neuroendocrine pulmonary tumor • proteomics map tree • large cell neuroendocrine carcinoma • small cell carcinoma
1. Introduction Although neuroendocrine pulmonary tumors (NEPT) occupy a relatively high proportion of lung cancers (20-25%), they are among the least understood of all lung cancers, and their prognoses remain unclear. Presently, NEPT are defined as tumors exhibiting morphological features of neuroendocrine differentiation by light microscopy, immunohistochemistry, or electron microscopy, and include low-grade typical carcinoids (TC), intermediate-grade atypical carcinoids (AC), high-grade small cell lung carcinomas (SCLC), and large cell neuroendocrine carcinomas (LCNEC). Oat cell carcinomas and intermediate cell carcinomas, previously distinguished based on their morphological findings,1 are now considered to be SCLC according to the 1999 World Health Organization (WHO) classification.2 LCNEC are large cell tumors showing evidence of neuroendocrine differentiation, with organoid nesting patterns or rosettes by light microscopy, and although these * To whom correspondence should be addressed. Tel: 82-2-2228-1767. Fax: 82-2-362-0860. E-mail:
[email protected]. † Yonsei University College of Medicine. ‡ Soonchunhyang University Hospital. § Brain Korea (BK) 21 Project for Medical Science, Yonsei University College of Medicine. | Genomine Research Division, Genomine, Inc. 10.1021/pr050460x CCC: $33.50
2006 American Chemical Society
tumors are poorly differentiated morphologically, their biological prognosis is said to be between that of AC and SCLC.3 SCLC and LCNEC are differentiated histologically by their nuclear and cytoplasmic features, however, due to their diverse morphology, the distinction may be difficult to make and thus these two neoplasms are sometimes collectively referred to as high grade neuroendocrine tumors. Recently, with the development of high-throughput techniques that analyze many genes simultaneously, cDNA arrays and proteomics are being actively researched, and cDNA array studies on adenocarcinomas of the lung have been reported.4-6 Tumors showing neuroendocrine differentiation have been reported to demonstrate an overexpression of type II pneumocyte genes in comparison to normal lung tissues,7 and in nonsmall cell lung cancers (NSCLC), overexpression of genes encoding cytoskeletons, collagens, and metalloproteinases has been reported.8,9 Proteomics studies of NSCLC have demonstrated the overexpression of various proteins including macrophage migration inhibitory factor (MIF), cyclophilin A (CyPA), SUMO-2, and thymosin-β4.10,11 In contrast to the vast number of in vitro molecular studies on SCLC up to date, similar studies focused on LCNEC have seldom been published,5,12 and clinicians have treated cases Journal of Proteome Research 2006, 5, 643-650
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research articles of LCNEC according to the guidelines for SCLC. The paucity of such studies using human tissues is not surprising, as SCLC and LCNEC are conventionally treated by chemotherapy immediately after biopsy and in vivo samples are difficult to obtain. Thus, cell lines have been used for most molecular biological studies.6,8,13,14 In this study, we aimed to evaluate NEPT based on their proteomics, by examining seven histologically and immunohistochemically confirmed cases of NEPT collected in our lung cancer frozen tissue bank. The similarities and differences between the groups of NEPT were evaluated by a novel method involving map tree construction by comparing the entire protein spots.
2. Materials and Methods Tissue Preparation and Protein Extraction. All tumors and corresponding normal tissues with informed consent from donors were stored in sterile bottles in a deep freezer. The present study was approved by the ethical committee of the university. Prior to protein extraction, all cases were examined on cryosections, and again matched with the paraffin-embedded tissues. Each frozen tissue was selected for protein extraction when it was estimated to contain >98% of the desired cells. They were then washed with PBS/phosphate inhibitor, incubated in lysis buffer [40 mM Tris-HCl, 7 M urea, 2 M thiourea, 4% 3-[(3-cholamidopropy)dimethyammonio]-1-propanesulfonate (CHAPS; Sigma-Aldrich, St. Louis, MO), 100 mM 1, 4-dithioerythtitol (DTT; Sigma-Aldrich, St. Louis, MO) with protease inhibitor cocktail (Sigma-Aldrich, St. Louis, MO)], and the samples were shaken for 15 min. Subsequently, lysates were incubated at 4 °C for 40 min, with vigorous shaking every 10 min, and then centrifuged at 4 °C for 30 min at 14 000 rpm. The protein-containing supernatant was transferred to a new tube. The protein concentration was determined using a BioRad Protein Assay (Bio-Rad, Hercules, California, USA). IPG-2DE. Nonlinear gradient strips of pH 3-10 (Amersham Biosciences, Uppsala, Sweden) were equilibrated for 12 to 16 h by applying 7 M urea containing 2% CHAPS, 1% DTT, 1% Pharmalyte, and 2 M thiourea, and 200 µg of sample was loaded onto each strip. Isoelectric focusing (IEF) was performed using a Multiphor II electrophoresis unit and an EPS 3500 XL power supply (Amersham Biosciences, Uppsala, Sweden) at 20 °C. During IEF, the voltage was increased slowly over 3 h from 150 V to 3500 V. Prior to the second dimension, the strips were incubated in equilibration buffer [6 M urea, 2% SDS, 50 mM Tris-HCl, pH 6.8, and 30% glycerol] for 10 min, using 1% DTT and 2.5% iodoacetamide (Sigma-Aldrich, St. Louis, MO) in order. The equilibrated strips were inserted into SDS-PAGE gels (20-24 cm, 10-16%), and SDS-PAGE was performed using a Hoefer DALT 2D system (Amersham Biosciences, Uppsala, Sweden). 2D gels were downloaded at 1700 Vh at 20 °C and treated with silver staining. To secure the reliability of data and exclude the experimental variation, expression data was obtained from three gel replicates per sample tissue from same individual. Image Analysis. An image analysis was performed using a PDQuest software (version 7.0; Bio-Rad, Hercules, California, USA), and the amount of protein in each spot was normalized to the total valid spot intensity. Only the spots that clearly showed a greater than a 2-fold change in expression compared to controls were selected. Protein Profile Distance Comparison and Clustering Analysis. We applied filtering method to the protein expression data 644
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to avoid including in the data analysis those proteins that did not vary or that were not highly expressed.We selected only proteins whose expressions showed over 2-fold spot quantity change in tumor samples compared with normal samples. The selected protein spots were filtered by the student’s t-test (0.05 < P) and for these spots, we performed protein profile distance comparison and clustering analysis. The overall distances between protein expression profiles were calculated using the formula below by summing up the absolute ratio of the proteins (n ) number of proteins calculated in the tissue). xjja
n
∑ |log i)1
2
xjib
|
The normalized intensity of protein spots in each a and b sample tissue was used. The pairwise distance metric of protein expression profile was used to build distance trees. The values were entered into a MEGA software program (http://www. megasoftware.net), and the neighbor joining tree was constructed. The average of the pairwise distances measured between the triplicates for each tissue sample were used to estimate a tree depicting the overall differences in gene expression measured between individuals. Clustering analysis was performed for selected filtered spots. To calculate the protein expression ratios, mean average spot volume of normal reference pools was used for individual normal and tumor samples. The Cluster and Tree View software were used (http://rana.Stanford.EDU/software/) to group proteins with similar expression patterns and to display the tree. We used average linkage clustering with a modified Pearson correlation as similarity metric and protein and array was median centered. A pair of neighbors is a pair of operational taxonomic units (OTU) connected through a single interior node in an unrooted, bifurcating tree. Our method of constructing a tree starts with a starlike tree, which is produced under the assumption that there is no clustering of OUTs. In addition, we constructed model tree with two neighboring pairs to examine the effect of topological differences under the assumption of varying t rate of unit substitution. MALDI-TOF MS. For each gel spot, a biopsy punch was prepared and transferred to a 1.5 mL siliconized Eppendorf tube (Ambion, Austin, TX). Subsequently, the transferred gelspots were destained in destaining solution [100 mM Na2S2O3 (Sigma-Aldrich, St. Louis, MO) and 30 mM K3Fe(CN)6 (SigmaAldrich, St. Louis, MO)(V/V, 1:1)]. The destained gel slices underwent prereduction using 100% acetonitrile (HPLC grade). Gel slices were dried in a Speed-Vac (GMI, Ramsey, MN). The dried gel slices were incubated at 37 °C for 12-16 h in ABC buffer [50mM ammonium bicarbonate (Sigma-Aldrich, St. Louis, MO), pH 8.0] containing 0.1 mg/mL sequencing grade modified trypsin (Promega Biosciences, San Luis Obispo, CA). The peptide mixture, treated with trypsin, was concentrated using ZipTips (Millipore Corp., Billerica, MA). Peptide samples were mixed at a ratio of 0.5 µL matrix (R-cyano-4-hydroxytranscinnamic acid; Sigma-Aldrich, St. Louis, MO) and 0.5 µL sample, loaded into a 96 × 2 samples plate (P/N V700813), and crystallized. The crystallized samples were analyzed using an Applied Biosystems Voyager System 4307 MALDI-TOF Mass Spectrometer (Applied Biosystems, Foster City, CA). Parameters were set as follows: positive ion-reflector mode, accelerating voltage 20 kV, grid voltage 64.5%, mirror voltage ratio 1.12, N2 laser wavelength 337 nm, pulse width 3 ns, number of laser
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completely removed with xylene, and to inactivate the endogenous hydrogen peroxide activity, tissue sections were soaked in 0.3% hydrogen peroxide for 15 to 30 min and washed with phosphate buffer solution 2 to 3 times. To undergo antigen retrieval, the tissues were soaked in 10 mM citrate buffer (pH 7.0), treated in a microwave for 10 min, cooled at room temperature, and washed with phosphate buffer solution for 10 min. To prevent nonspecific reactions, the tissues were pretreated with normal goat serum blocker (DAKO, Carpinteria) for 15 to 30 min. They were incubated with diluted primary antibody to cytokeratin 18, p63 in a refrigerator for 16 h. Biotinylated secondary antibody and streptavidin were conjugated using a LSAB kit (DAKO). The samples were stained with diaminobenzene (DAB), counterstained with hematoxylin, and mounted with a crystal mount. As a negative control, normal goat serum was used instead of the primary antibody.
Table 1. Clinical Features of the Neuroendocrine Pulmonary Tumor Casesa,b label
age
sex
size (cm)
location
stage (TNM)
F/U (months/status)
TC AC LC-1 LC-2 LC-3 SC-1 SC-2
46 62 63 69 72 66 62
M M M M M M M
2.4 1.5 4 3 4 4 1
RLL LLL LLL + LML RUL RLL RUL RRL
1-0-0 1-0-0 2-1-0 2-0-0 2-1-0 2-0-0 1-0-0
16.3/alive 50.0/alive 4.4/dead 15.3/alive 1.0/dead 31.7/alive 6/alive
a TC: typical carcinoid; AC: atypical carcinoid; LC: large cell neuroendocrine carcinoma; SC: small cell lung carcinoma. b RUL: right upper lobe, RLL: right lower lobe, LML: left middle lobe, LLL: left lower lobe.
shots 300, acquisition mass range 800-3500 Da, delay 100 ns, and vacuum degree 4 × 10-7 Torr. In addition, des-Arg1Bradykinin, Glu1-Fibrinopeptide B, and ACTH (clip 18-39) were used as external standards for mass calibration. Database Analysis. The ProFound (http://129.85.19.192/ profound_bin/WebProFound.exe) was used to search protein database for protein identification using peptide mass fingerprinting (PMF). The internal standard spectra were adjusted to a trypsin auto-digestion ion peak m/z (842.510, 2211.1046). Search parameters were assigned as follows: the databases used were Swiss-Prot (01.06.2005) and NCBI (nr) (01.06.2005), the mass tolerance was (50 ppm, the missed cleavage site value was permitted up to 1, the species was Homo sapiens (human), monoisotope mass was used, and the test range was experimental pI ( 2 pH units, and Mr (20%. The analysis standard, Est′Z was applied, which is a method used to measure the identification confidence level by evaluating the z-score of various candidate groups (estimation of z). The z-score is a measurement of the standard deviation distance from the mean value and is obtained by the formula z ) (x - x-)/σ, where x is Gaussian random variable, x- is the mean value of x, and σ is the standard deviation of x. In this study, z-scores of 1.65, 2.326, and 3.090 represent confidence levels of 95%, 99%, and 99.9%, respectively. Tissue Microarray. Twenty-eight lung tumors diagnosed as NEPT from 1998 to 2005 were retrieved from the surgical pathology files at Yonsei University. They consisted of 9 cases of TC, 10 cases of LCNEC containing areas of AC, and 9 cases of SCLC. The most representative tissue slides were reviewed under the light microscope and three areas with the least necrosis and hemorrhage were selected from each case, from which tissue core samples were obtained. Tissue microarrays of 2 mm diameter were prepared from these samples using an automated machine (Petagen Co, Seoul, Korea). Immunohistochemical Staining. The blocks prepared by tissue microarray were serially sectioned at 4 µm thickness onto sialine coated slides (DAKO, Carpinteria), and immunohistochemical staining was performed as follows. Paraffin was
3. Results Analysis of Research Materials. Fresh frozen tissue was available for 7 cases of NEPT. The clinical features of the cases are summarized in Table 1. All cases were early pulmonary tumors with a T stage of 1 or 2, and nodal metastases were detected in only 2 cases, both being LCNEC. Distant metastasis was not detected in any case. The two patients with LCNEC at stage T2N1 died within four months; one of respiratory failure and the other postoperative complications. Histopathological examination of the frozen sections and paraffin-embedded sections confirmed the samples as being NEPT, based on morphological evidence of neuroendocrine differentiation and positivity for CD56, chromogranin and synaptophysin on immunohistochemistry (Table 2). The TC sample showed uniform nests with rare mitosis and no necrosis. The AC was characterized by uniform nests with occasional mitosis around 10/10 HPF and spotty necrosis. The two cases of LCNEC (cases 2-2 and 2-3) were pure, but one case contained areas of SCLC (case 2-4). However, the common findings included evidence of neuroendocrine differentiation with organoid patterns, spotty or extensive necrosis, and high mitotic indices (at least 8 per 10 high power magnification fields). In addition, dinstinctive cytologic features including a large nucleus, coarse granular chromatins, a detectable nucleolous and abundant cytoplasm were recognized in LCNEC. Mixed LCNEC/SCLC showed a combination of diffusely infiltrative and vaguely organized trabecular patterns, with extensive necrosis. However, as the nuclear findings were closer to those of LCNEC than to SCLC, this case was classified into the LCNEC. In contrast, SCLC was characterized mainly by their infiltrative growth pattern and cytological features including scant cytoplasm and loss of nucleoli (Figure 1). NSCLC components were not detected in any of the cases. One SCLC was detected at an early stage, measuring smaller than 1 cm,
Table 2. Pathological Features of the Neuroendocrine Pulmonary Tumor Cases label
histological pattern
mitosis/10 HPFa
necrosis
pleomorphism
diagnosis
TC AC LC-1 LC-2 LC-3 SC-1 SC-2
100% nest 70% nest/30% trabecular 70% nests/30% trabecular 50% nest/50% trabecular 80% diffusely infiltrative/20% trabecular 100% infiltrative 90% infiltrative/10% Trabecular
2 10 14 8 20 25 20
+ +++ + +++
+ ++ + ++ +++ +++
TC AC LCNEC LCNEC mixed LCNEC/SCLC SCLC SCLC
a
High-power field; TC: typical carcinoid; AC: atypical carcinoid; LCNEC: large cell neuroendocrine carcinoma; SCLC: small cell lung carcinoma
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Figure 1. Pathological findings of neuroendocrine pulmonary tumors. (A) A typical carcinoid tumor shows a distinct organoid arrangement of uniform cells. (B) An atypical carcinoid tumor displays variable sized organoid nests with focal comedo necrosis, some pleomorphism and a low mitotic index. (C) A large cell neuroendocrine carcinoma demonstrates both organized nests and infiltrative growth, a moderate degree of nuclear pleomorphism, prominent nucleoli, and frequent mitoses. (D) A small cell carcinoma displays diffusely infiltrative growth with marked anaplasia and frequent mitoses.
and could be subjected to a proteomics study as the normal tissue component occupied less than 20% of the entire area. Proteomics Analysis. 2-D Electrophoresis. With TC and SCLC designated as two reference groups for comparison, a proteomics analysis was performed to assess the molecular similarities or differences between LCNEC, AC and SCLC (Figure 2). In the analyzed samples, approximately 1400 protein spots were detected. In comparison with the control group, only spots that clearly showed a 2-fold change were selected. These were subsequently confirmed and analyzed by MALDI. The quantity analysis performed on 196 such spots is demonstrated in Figure 3. Distance Map Tree Construction. A distance map tree was constructed to assess the similarities in protein expression between each group by adding the calculated distance of 196 spots as pairwise comparisons and generating a distance matrix (Figure 4). While TC showed protein expression profiles similar to those of normal tissues, other samples showed map tree results distinctly different from TC: AC and LCNEC samples, whether pure or combined with SCLC, demonstrated similarities in their protein expression profiles. SCLC formed a separate group from the other NEPT. However, although the conventional SCLC was found in a cluster distant from TC and close to LCNEC, the early stage SCLC was closer to TC. MALDI-TOF Analysis. A total of 27 spots that showed 2-fold changes in expression (spot position or protein concentration) in comparison to controls were selected and subjected to a MALDI-TOF MS analysis (Table 3). Significantly increased proteins in comparison with controls were as follows: eIF5A1, GST M3, cytokeratin 18 (CK 18), FK506-binding protein p59, p63, MAGE-D2, mitochondrial short-chain enoyl-coenzyme A hydratase 1, and poly (rC) binding protein 1, while transferrin 646
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Figure 2. 2-DE gel images of neuroendocrine pulmonary tumors and their corresponding normal tissues. To compare the protein expression differences of the tumor and the normal samples, each histologically and biologically different tumor was categorized. (A) Normal lung, (B) typical carcinoid (TC) and atypical carcinoid (AC), (C) large cell neuroendocrine carcinoma (LCNEC), (D) small cell lung carcinoma (SCLC).
being decreased (Table 4). To individually confirm each spot, a MALDI-TOF analysis was performed. PMF maps obtained by
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Figure 3. Nomination of spots using 2-dimensional electrophoresis. The x-axis represents the pI of the protein; the y-axis represents the molecular weight of the protein. A total of 196 differential protein spots were selected. Spots from each image were identified and sequentially numbered using an automatic program. A Gaussian synthetic image was used to designate the selected 196 spots.
MALDI-TOF MS were used for protein identification (Figure 5). Immunohistochemical Studies. To assess surrogate endpoint biomarkers, immunohistochemical staining was performed on tissue microarrays of 28 cases of lung tumors showing neuroendocrine differentiation. The antibodies used were as follows: p63, and cytokeratin 18. TC was positive for p63 and cytokeratin 18 in 55.6% (5/9) and 89% (8/9), respectively. The positivity for p63 and cytokeratin 18 were 20% (2/10) and 50% (5/10), respectively in AC/LCNEC and 11.1% (1/9) and 56% (5/9), respectively in SCLC.
4. Discussion Pulmonary tumors showing neuroendocrine differentiation are presently classified according to the 1999 WHO classification into four groups: small cell carcinoma (SCLC), large cell neuroendocrine carcinoma (LCNEC), typical carcinoid (TC) and atypical carcinoid (AC).2 They are differentiated from other nonneuroendocrine tumors by their distinct histopathological, ultrastructural, and immunohistochemical characteristics. However, as the classification of NEPT is primarily based on the cytomorphological features, such as mitotic indices and nuclear size, interobserver variations in the diagnosis of NEPT can be inevitable, further adding to the confusion in their clinical management. Therefore, an accurate diagnosis is needed and correlations between the morphological classification and the proteomics profiles would aid in reaching an accurate diagnosis.
The recent advent of high-throughput techniques has allowed the analysis of expression of all transcription factors and proteins in tumor samples, and the simultaneous comparison of expression between different tumors by the means of distance map tree construction.15 The latter technique involves calculation of the overall distance between all genes from the differences in apparent protein expression levels,16 and was a technique initially used in the comparison of human and primate organs. In this study, we applied this technique to analyze the similarities and differences in protein between TC, AC, LCNEC, and SCLC. The results show that the molecular profiles of TC and normal lung tissue were similar, and although AC, pure LCNEC, and LCNEC with areas of SCLC were similar, SCLC tended to form a separate group. Although pathological differentiation between LCNEC and AC according to the number of mitoses and cytologic features was possible, there was no clear-cut difference between the two groups in the protein expression profiles. As SCLC tissues are rarely obtained surgically, there have not been any proteomics studies using human tissues. In this study, we were able to obtain surgically removable two cases of SCLC; one (3 cm) at stage 2, and the other (1 cm) at stage 1. Interestingly, the two SCLC showed different expression patterns, with the stage 1 SCLC showing a pattern similar to that of TC rather than to the other SCLC or LCNEC cases. From this finding, it can be postulated that the protein expression patterns of SCLC may be similar to TC at an early stage and then resemble that of LCNEC at a later stage. Journal of Proteome Research • Vol. 5, No. 3, 2006 647
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Cho et al. Table 3. List of Up- or Down-Regulated Proteins Showing ∼2 Fold Changes in Neuroendocrine Pulmonary Tumors after 2-DE Followed by MALDI-TOF MS Analysis
34 5.3 47.32 44 5,3 26.92 40 11.4 8.76
3.69 6.14 7.74
47
5.4 33.54
5.67
26 32 26 29
5.3 5.4 5.8 5.6
52.07 21.54 64.14 25.72
10.75 13.86 2.6 2.86
18 20
8.8 35.71 9.5 49.59
2.48 2
23 40 38
5.4 43.93 9.4 15.58 8.9 31.81
3.39 1.95 3.39
29
6
2.13
45 57
9.1 16 -4.21 6.6 15.49 1.25
23 11 24 36 41 32
6.3 7.5 7 6.7 6.7 5.5
eIF5AI glyoxalase I - human HRAS-like suppressor 3 GST M3 Chain B, Human Branched-Chain Alpha-Keto Acid Dehydrogenase Cytokeratin 18 hypothetical protein SB156 amyloid beta precursor protein (ABPP) Chromosome 17 open reading frame 25 FK506-binding protein 4 SIPL protein P63 platelet-activating factor acetylhydrolase, isoform Ib, beta subunit 30kDa 3-hydroxyisobutyrate dehydrogenase GTP-binding protein era homologue (hERA) beta-succinyl CoA synthetase MAGE-D2 mitochondrial short-chain enoylcoenzyme A hydratase 1 precursor ARP1 actin-related protein 1 homologue B, centractin beta Transferring fatty acid binding protein 5 (psoriasisassociated) annexin VII isoform 1 (synexin) myotubularin related protein 6 ras-related nuclear protein poly(rC) binding protein 1 Phosphoglycerate mutase A HSPC267
40 38 21 36 19
3212 3507 4404 4510 5103 5424 5732 6011
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11.71 3.59 19.67 5.94 7.48
8 102 514 1106 1315
2501 3002 3016 3104
648
17.04 20.99 18.05 27.01 38.53
%
2206
Our study revealed 9 types of surrogate endpoint biomarkers that are potential candidates for biomarkers in the assessment of biological progression of NEPT. Except for eIF5A1, GST M3, FK506-binding protein p59, MAGE-D2, mitochondrial shortchain enoyl-coenzyme A hydratase 1, tranferrin and poly (rC) binding protein 1swhose function in humans is not yet characterizedsthe remaining two biomarkers which showed confidence levels of over 95% included cytokeratin 18 and p63. In addition, hsp70, cdc25B, Ki-1, and cyclin B3 demonstrated differences in expression between groups with low probability. FK506-binding 59kD protein is a factor involved in the excretion of copper from tissues and plays an important role in protecting the nervous system from copper toxicity. It is thought to form a heterocomplex with glucocorticoid/Hsp90/ immunophilin.17 MAGE-D2, novel member of MAGE superfamily, was recently identified in the fetal airway epithelium.18 Its function remains unknown, but is suspected to be associated with cell differentiation and/or tumorigenesis.18 Poly (rC) binding protein 1 is known to be associated with c-myc translation regarding the activation of the c-myc internal ribosome entry segment, which is alternative to translation initiation of c-myc associated with eIF complex.19 Mitochondrial short chain enoyl coenzyme A hydratase 1 precursor was associated with the stimulating effect of linoleic acid on cell proliferation due to interference with the metabolic pathway of fatty acid metabolism.20 The biomarkers assessed in this study were cytokeratin 18 and p63; p63, which is known as a marker of squamous
foldb
protein name
1413 2108 2201
Figure 4. Map tree and clustergram of neuroendocrine pulmonary tumors expression profiles. (A) Distance map tree representing the relative extents of expression changes between lung tumors and corresponding normal tissues. (B) Clustering of distance map tree. Each tumor is categorized according to protein expression extents.
MW (kDa)a
spot
6401 7204 8115 8312 8708 8810
pIa
5.1 5.1 7.9 5.4 5.3
42.36
50.58 2.16 54.22 5.3 24.58 3.23 38.02 4.72 28.9 -5.1 22.66 8.75
a The mass and pI values specified are theoretically matched by database search. b Plus (+): the rate of increase of intensity (sample/normal). Minus (-): the rate of decrease of intensity (normal/sample).
Table 4. Classification of Surrogate Endpoint Biomarkers spot
protein name
%
pI
MW (kDa)
8 1106 1413 2501 3016 4510 5103
eIF5A1 GST M3 Cytokeratin 18 FK506-binding protein (59kD) P63 MAGE-D2 Mitochondrial short-chain enoylcoenzyme A hydratase 1 precursor Transferrin Poly (rC) binding protein 1
40 36 34 26 26 40 38
5.1 5.4 5.3 5.3 5.8 9.4 8.9
17.04 27.01 47.32 52.07 64.14 15.58 31.81
45 36
9.1 6.7
16.00 38.02
5732 8312
a The mass and pI values specified are theoretically matched by database search. b Abbreviations: eIF5A1: eukaryotic translation initiation factor 5A; GST: glutathione-S-transferase; MAGE: melanoma-associated antigene gene.
differentiation, has been frequently used in differentiating between squamous cell carcinomas and SCLC, and an increased expression of p63 in squamous cell carcinomas is related to a better prognosis.21,22 In our study, it was expressed in approximately half (55.6%) of the TC, but the expression rate decreased in the other NPET with poorer differentiation, thus showing that p63 expression may also be related to the differentiation of NEPT. Cytokeratin 8 and cytokeratin 19 have been reported to be useful serological markers of lung cancer;23,24 however, the role of cytokeratin 18 has not been previously studied. We found
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Figure 5. Identification of differentially expressed proteins between lung tumors and the normal sample. (A) PMF of each spot selected in 2-DE image analysis. Peptide mass fingerprinting of 9 spots showing significant differences between pulmonary neuroendocrine tumors and corresponding normal tissues in 2-DE map (B) Nomination of 9 spots which were finally identified by MALDI-TOF MS between normal and each tumor group. The circles show the finally selected spots, which were identified by MALDI-TOF MS. (C) According to the criteria of 2-fold changes, differentially expressed protein spots from the 2-DE gels were selected. (D) Histogram depicting the intensity of spots. TC: typical carcinoid, AC: atypical carcinoid, LC: large cell neuroendocrine carcinoma, LC-3: mixed large and small neuroendocrine carcinoma. SC: small cell carcinoma, NL: normal lung. Journal of Proteome Research • Vol. 5, No. 3, 2006 649
research articles that cytokeratin 18 was significantly overexpressed in NEPT compared to normal tissues. In conclusion, our results demonstrate that (1) the comparative proteomics of NEPT match the WHO classification based on histopathological features except for AC and LCNEC; (2) SCLC show differences in their proteomics according to tumor stage; and (3) cytokeratin 18 and p63 may be valid diagnostic and prognostic markers.
Acknowledgment. This study was supported by CMBYUHAN (6-2004-91; N.H.C. & S.H.C.) and Brain Korea 21 Project for Medical Science (N.H.C. & Y.P.C.). Note Added after ASAP Publication. This manuscript was originally published on the Web 02/15/2006 missing an author name. The version published on the Web 02/23/2006 and in print is correct.
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