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Clinical Cancer Research Vol. 11, 1776-1785, March 2005
© 2005 American Association for Cancer Research

Imaging, Diagnosis, Prognosis

Overexpression of the Aldo-Keto Reductase Family Protein AKR1B10 Is Highly Correlated with Smokers' Non–Small Cell Lung Carcinomas

Shin-ichi Fukumoto1,8, Naoko Yamauchi3, Hisashi Moriguchi2, Yoshitaka Hippo1, Akira Watanabe1, Junji Shibahara3, Hirokazu Taniguchi3, Shumpei Ishikawa1, Hirotaka Ito1, Shogo Yamamoto1, Hiroko Iwanari5, Mitsugu Hironaka6, Yuichi Ishikawa4, Toshiro Niki3, Yasunori Sohara7, Tatsuhiko Kodama2, Masaharu Nishimura8, Masashi Fukayama3, Hirotoshi Dosaka-Akita9 and Hiroyuki Aburatani1

1 Genome Science Division and 2 Laboratory for Systems Biology and Medicine, Research Center for Advanced Science and Technology, and 3 Department of Pathology, Graduate School of Medicine, University of Tokyo; 4 Department of Pathology, Cancer Institute, Japanese Foundation for Cancer Research; and 5 Perseus Proteomics, Inc., Tokyo, Japan; Departments of 6 Pathology and 7 Thoracic Surgery, Jichi Medical School, Tochigi, Japan; and 8 First Department of Medicine and 9 Department of Medical Oncology, Hokkaido University Graduate School of Medicine, Sapporo, Japan

Requests for reprints: Hiroyuki Aburatani, Genome Science Division, Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan. Phone: 81-3-5452-5235; Fax: 81-3-5452-5355; E-mail: haburata-tky{at}umin.ac.jp.


   ABSTRACT
Top
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Purpose: Squamous cell carcinoma (SCC) and adenocarcinoma of the lung are currently subject to similar treatment regimens despite distinct differences in histology and epidemiology. The aim of this study is to identify a molecular target with diagnostic and therapeutic values for SCC.

Experimental Design: Genes specifically up-regulated in SCC were explored through microarray analysis of 5 SCCs, 5 adenocarcinomas, 10 small cell lung carcinomas, 27 normal tissues, and 40 cancer cell lines. Clinical usefulness of these genes was subsequently examined mainly by immunohistochemical analysis.

Results: Seven genes, including aldo-keto reductase family 1, member B10 (AKR1B10), were identified as SCC-specific genes. AKR1B10 was further examined by immunohistochemical analysis of 101 non–small cell lung carcinomas (NSCLC) and its overexpression was observed in 27 of 32 (84.4%) SCCs and 19 of 65 (29.2%) adenocarcinomas. Multiple regression analysis showed that smoking was an independent variable responsible for AKR1B10 overexpression in NSCLCs (P < 0.01) and adenocarcinomas (P < 0.01). AKR1B10 staining was occasionally observed even in squamous metaplasia, a precancerous lesion of SCC.

Conclusion: AKR1B10 was overexpressed in most cases with SCC, which is closely associated with smoking, and many adenocarcinoma cases of smokers. These results suggest that AKR1B10 is a potential diagnostic marker specific to smokers' NSCLCs and might be involved in tobacco-related carcinogenesis.

Key Words: microarray • squamous cell lung carcinoma • tobacco • retinoic acid • metaplasia


   INTRODUCTION
Top
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Lung cancer is the leading cause of cancer death among all types of cancers and continues to increase in frequency worldwide (1). There are two major types of lung cancer, small cell lung carcinoma (SCLC) and non–small cell lung carcinoma (NSCLC), which account for 20% and 80% of all cases (2), respectively. NSCLC is further classified into squamous cell lung carcinoma (SCC) and lung adenocarcinoma. Despite distinct differences in histologic and epidemiologic features, adenocarcinoma and SCC are similarly treated in clinical practice (3) partly because underlying molecular mechanisms are largely unknown. Even the most recent therapeutic innovations for NSCLC have yielded little improvement to prognosis with overall 5-year survival rates still <15% (4).

We reported previously the clinical relevance of expression of G1-S transition regulatory molecules in prognosis, such as p53, retinoblastoma protein, p16INK4A, and p27 in NSCLCs (5–8). We further showed that Ki-67-positive, high-level cyclin E, low-level N-acetylgalactosaminyl transferase-3 (GalNAcT3) and low-level N-acetylglucosaminyltransferase (GnT-V) are associated with shorter survival in NSCLCs (8–12). However, we did not observe any differences between SCC and adenocarcinoma.

SCC accumulates a series of genetic alterations in the progression from a normal bronchial epithelium, metaplasia, dysplasia, and carcinoma in situ to invasive carcinoma (13). Because most SCC develops in smokers and tobacco smoking reversibly induces metaplasia, smoking has been regarded as a major cause of SCCs (14). As diagnostic markers for SCC, SCC antigen and cytokeratin 19 fragment (CYFRA 21.1) have been widely used (15). Despite their usefulness in distinguishing between SCC and adenocarcinoma, these two molecules are hardly adequate for early detection of cancer (15). Moreover, their expression in normal squamous cell suggests that these two molecules are not involved in carcinogenesis and inappropriate as therapeutic targets. Thus, search for genes specific to SCC alone will lead to identification of a novel molecular target of SCC, which may help developing both early detection of SCC and personalized therapeutics of SCC.

Microarray analysis has been applied to several aspects of cancer research, including classification, mechanistic elucidation, discovery of therapeutic targets, and development of tumor makers (16–21). For example, we recently explored potential diagnostic or therapeutic markers of hepatocellular carcinoma using microarray analysis and showed that soluble glypican-3 is a novel serologic marker essential for early detection of hepatocellular carcinoma (19). Recent reports on microarray analysis of lung cancer have shown that SCC and adenocarcinoma have different gene expression signatures, suggesting involvement of distinct pathways in carcinogenesis (22, 23). In the present study, we searched for genes specifically overexpressed in SCC through microarray analysis and identified seven genes, including aldo-keto reductase family 1, member B10 (AKR1B10). We investigated potential relevance of AKR1B10 in NSCLCs with a newly generated monoclonal antibody and found that it is overexpressed in smokers' NSCLCs, including most cases with SCC.


   MATERIALS AND METHODS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Tissue Samples and Cell Lines. Forty-five primary lung cancers (15 SCCs, 20 adenocarcinomas, and 10 SCLCs) were obtained with informed consent from patients who underwent lobectomy at Jichi Medical School Hospital (Tochigi, Japan), Cancer Institute Hospital, Japanese Foundation for Cancer Research (Tokyo, Japan), and Hokkaido University Medical Hospital (Hokkaido, Japan). All samples were immediately frozen after resection and stored at –80°C until RNA or protein was extracted. Adenocarcinoma cell lines A549, H23, H522, H1648, and H2347 were purchased from the American Type Culture Collection (Manassas, VA). SCLC cell line Lu130 and SCC cell line H157 were obtained from Cell Resource Center for Biomedical Research, Tohoku University (Miyagi, Japan).

RNA Extraction and Microarray Analysis. Tissues or cells were directly lysed in Isogen reagent (Nippon Gene, Osaka, Japan) and homogenized. Total RNA was extracted according to manufacturer's instructions. Surgically resected lung tissues and lung cancers, including 5 SCCs, 10 SCLCs, a pooled sample made up of 12 adenocarcinomas, other 5 adenocarcinomas, and 1 normal lung, were analyzed on GeneChip HG U133 oligonucleotide arrays (Affymetrix, Santa Clara, CA) containing probes for ~40,000 human genes. Further information on the source of other RNA from normal tissues analyzed here is provided on request or is available at http://www.lsbm.org/db/index.html. Microarray analysis was done essentially as described previously (24). For global normalization, the average signal in an array was made equal to 100.

Systematic Selection of SCC-Specific Genes Based on Microarray Analysis. We systematically explored SCC-specific genes that were defined as follows: its expression level is (a) up-regulated in SCC but minimal in (b) normal lung and bronchial epithelia, (c) adenocarcinoma and SCLC, and (d) normal squamous epithelia, such as skin. Briefly, genes with a median signal score across 5 SCCs of >150 and >10 times that of normal lung were first selected. Among the 136 genes selected, genes with signal score of >150 in skin and small airway epithelial cell were omitted. We subsequently eliminated genes with signal >150 in SCLCs, adenocarcinomas, and most other normal tissues and various primary culture cells. Among 12 genes selected thus far, we additionally eliminated 5 genes that showed low expression throughout all of 40 cancer cell lines, suggesting expression by surrounding stromal cells but not by cancer cells (Table 1).


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  		Table 1 Genes with SCC-specific overexpression

 
Quantitative Real-time Reverse Transcription-PCR. After digesting genomic DNA using DNase I (Invitrogen, Carlsbad, CA) cDNA was synthesized from 1 µg total RNA using SuperScript First-Strand Synthesis System for reverse transcription-PCR (Invitrogen) in 24 µL volume and diluted up to 80 µL. Quantitative real-time PCR for AKR1B10 were done using an iCycler iQ Detection System (Bio-Rad, Hercules, CA). Reaction mixtures contained SYBR Green I nucleic acid gel stain (BMA, Rockland, ME) and primers 5'-CCCAAAGATGATAAAGGTAATGCCATCGGT-3' and 5'-CGATCTGGAAGTGGCTGAAATTGGAGA-3' for AKR1B10 or 5'-AGAAGGAGATCACTGCCCTGGCACC-3' and 5'-CCTGCTTGCTGATCCACATCTGCTG-3' for ß-actin. PCR condition was 1 cycle of 94°C for 3 minutes followed by 40 cycles at 94°C for 30 seconds, 65°C for 30 seconds, and 72°C for 1 minute. All the samples were run in triplicate, and the results were averaged. Specific amplification of AKR1B10 was confirmed by the gel electrophoresis and melting curve analysis after PCR. The expression level of AKR1B10 was indicated as a relative ratio of its signal to that of ß-actin to normalize the starting amount of template cDNA. We also did semiquantitative PCR using the same condition for six pair-samples of SCC and corresponding noncancerous lung tissues.

Generation of Anti-AKR1B10 Monoclonal Antibodies. Monoclonal antibodies against AKR1B10 were generated as described previously (25). Briefly, glutathione S-transferase–fused full-length AKR1B10 produced in Escherichia coli was immunized to female BALB/c mice. Nine clones of monoclonal hybridomas were selected by immunoblotting against recombinant AKR1B10 transiently expressed in COS-7 cells. We selected H4025 as a specific antibody in this study because a single band at around Mr 36,000 was observed only in AKR1B10-expressing cell lines as revealed by microarray analysis of 37 cell lines.

Immunoblot Analysis. Immunoblot analysis was done as described previously (25). Briefly, cells or tissues were lysed by 10 mmol/L Tris (pH 7.4), 150 mmol/L NaCl, 5 mmol/L EDTA, 1.0% Triton X-100, 1.0% sodium deoxycholate, 0.1% SDS with protease inhibitor cocktail (Sigma, St. Louis, MO) at 4°C. H4025 (5 µg/mL) or anti-ß-actin antibody (0.3 µg/mL, Sigma) was used as primary antibodies.

Immunocytochemistry and Confocal Microscopy Analysis. Immunostaining of culture cells were done after fixation in 4% paraformaldehyde and permeabilization in 0.2% Triton X-100 followed by incubation with 2% nonfat milk in TBS. An antibody H4025 (50 µg/mL) was applied as a primary antibody and incubated in a moist chamber at room temperature for 1 hour. The secondary staining was done with FITC-labeled anti-mouse IgG antibody (Sigma) as secondary antibody at room temperature for 1 hour. Dual-color detection by confocal laser scan microscopy (TCS SP2 system, Leica, Bensheim, Germany) was done after treatment with a 0.5 µmol/L solution of the mitochondrial stain MitoTracker Red CMXRos (Invitrogen) or the intercalator of double-strand nucleic acid stain propidium iodide (Invitrogen).

Immunostaining Analysis. Immunohistochemical analysis for AKR1B10 was done with the formalin-fixed, paraffin-embedded tissue archive at the University of Tokyo. The sections were deparaffinized in xylene, washed in ethanol, and rehydrated in TBS. Antigen retrieval was done in 10 mmol/L citrate buffer (pH 6.0) at 120°C for 10 minutes following incubation with TBS with 2% nonfat dried milk. Then, H4025 (50 µg/mL) or cytokeratin 5/6 (1:500, DAKO Ltd., Cambridge, United Kingdom) was applied for 1 hour followed by the secondary staining with DAKO Envision+ reagent. All sections were counterstained with Mayer's hematoxylin. We defined AKR1B10 positive if >10% of tumor cells displayed immunoreactivity.

We first examined archival samples of the University of Tokyo to compare expression of AKR1B10 and that of keratin 5/6 in NSCLCs, squamous epithelia of skin and esophagus, alveolar epithelium, and bronchus. We have analyzed previously 217 primary NSCLC specimens for expression of cyclin E, Ki-67, Bcl-2, p53, retinoblastoma protein, p27, GalNAcT3, and GnT-V (8, 9, 11, 12). Among these, we next examined 101 NSCLCs, which were classified into 32 SCCs, 65 adenocarcinomas, and 4 adenosquamous cell carcinomas according to WHO criteria (26). Clinicopathologic features are summarized in Table 3. The postsurgical pathologic tumor-node-metastasis stage was determined according to the guidelines of the American Joint Committee on Cancer (27). The Medical Ethical Committee of Hokkaido University School of Medicine approved this immunohistochemical study.


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  		Table 3 Clinicopathologic features correlated to AKR1B10 overexpression

 
Statistical Analysis. We analyzed the statistical significance of the relationship between the expression of AKR1B10 and clinicopathologic variables by {chi}2 test, Yates {chi}2 test, or Fisher's exact test as appropriate. We also analyzed the associations between AKR1B10 expressions and the cyclin E or Ki-67 labeling index (%; refs. 8, 9) by Student's t test. We additionally used multiple regression analysis to extract factors responsible for AKR1B10 expression in NSCLCs and adenocarcinomas alone. Sex, age, smoking history, differentiation, pT classification, pN classification, survival time, histology, cyclin E, Ki-67, GalNAcT3, and GnT-V were used as independent variables and AKR1B10 expression as a dependent variable. Differences were considered significant at P < 0.05. We simultaneously examined the correlation coefficient and the partial correlation coefficient between AKR1B10 expression and smoking or sex.


   RESULTS
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Microarray Analysis Identifies Seven Genes Specifically Up-Regulated in SCC. We selected seven potential SCC-specific genes (see Materials and Methods) using microarray analysis (Table 1). Tissue-wide expression profiles of these genes showed their high specificity compared with two widely used diagnostic markers of SCC, SCC antigen and CYFRA 21.1, suggesting robustness of our selection for SCC-specific genes (Fig. 1; Supplementary Fig. 1). Among these seven genes, AKR1C1, ELAFIN, NQO1, and UGT1A9 were reported previously as potential target genes for detection or therapy against lung cancer (28–31); SPRR3 is overexpressed in epidermal SCC (32); and ALDH3A1 was reported to be involved in metabolism of tobacco carcinogens (33). Overexpression of AKR1B10 has not been reported previously in lung cancer; then, we investigated whether it represents a good molecular target of SCC.



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  		Fig. 1 Expression profiles of AKR1B10. A tissue-wide expression of AKR1B10 was displayed with CYFRA and SCCAg as references. Signal denotes gene expression level obtained from microarray analysis: (a) 27 normal tissues, (b) 5 fetal tissues, (c) 7 cultured normal cells, (d) 5 adenocarcinomas, (e) 10 SCLCs, (f) 5 SCCs, and (g) 7 lung cancer cell lines. Filled columns, SCC.

 
Overexpression of AKR1B10 in SCC. To confirm array data, we first did semiquantitative PCR. Overexpression of AKR1B10 in SCC was observed in six pair-samples analysis (Fig. 2A). We subsequently investigated expression level of AKR1B10 across lung cancer tissues by quantitative reverse transcription-PCR. Overexpression of AKR1B10 was observed in 6 of 9 (67%) SCCs but not in SCLCs or normal lung tissues (Fig. 2B). Expression of AKR1B10 was also observed in 4 of 12 (33%), adenocarcinomas although its level was not so high as in SCC (Fig. 2B).



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  		Fig. 2 Overexpression of AKR1B10 in SCC. A, semiquantitative PCR using six pairs of SCC and noncancerous lung tissues. Note that AKR1B10 was up-regulated in all paired samples. B, quantitative real-time PCR. Examined samples were 9 SCCs, 12 adenocarcinomas, 10 SCLCs, 6 lung cancer cell lines, and 5 normal lung tissues. Note expression level of AKR1B10 was remarkably high in 6 SCCs compared with 4 adenocarcinomas. C, immunoblot analysis of AKR1B10. A 36-kDa protein was detected in SCCs and AKR1B10-expressing cell lines H1648 and A549. N, normal lung tissues; C, cancer tissues; CL, cell line.

 
Next, we investigated expression of AKR1B10 protein by immunoblot analysis with a newly generated monoclonal anti-AKR1B10 antibody, H4025. As for three pair-samples of SCC used in semiquantitative PCR above, AKR1B10 was observed only in cancerous tissues, whereas AKR1B10 was negative in 3 adenocarcinomas (Fig. 2C).

Comparison of AKR1B10 with Pan-Squamous Cell Marker Keratin 5/6. As a SCC marker, keratin 5/6 is widely used based on its specificity to squamous cells. Unique feature of AKR1B10 as we identified in our selection is that it is not a merely squamous cell–specific marker unlike keratin 5/6 but a SCC-specific marker. To highlight the difference in "specificity" of these two molecules, we compared their expression in NSCLCs and normal tissues, including squamous epithelia of skin and esophagus, alveolar epithelium, and columnar epithelia of bronchus (Table 2). Keratin 5/6 staining was observed in normal squamous epithelia, columnar epithelia, and 83% of SCCs but not in adenocarcinoma. In contrast, AKR1B10 staining was observed in 64% of SCC and 30% of adenocarcinoma but not in normal epithelia (Table 2).


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  		Table 2 Expression of AKR1B10 and keratin 5/6 in NSCLCs and normal epithelia

 
Distinct Localization of AKR1B10 in SCC and Adenocarcinoma. As we described above, analysis in larger number of samples revealed that AKR1B10 was expressed not only in most cases of SCC but also in a subset of adenocarcinoma. To investigate relevance of AKR1B10 in NSCLCs, we subsequently did immunohistochemical analysis in 101 primary NSCLCs, including 65 adenocarcinoma (Table 3). AKR1B10 staining was observed in 27 of 32 (84.4%) SCCs but also in 19 of 65 (29.2%) adenocarcinomas (Table 3). In adenosquamous cell carcinomas, AKR1B10 staining was observed in 2 of 4 cases and restricted to SCC components of these 2 cases (data not shown). AKR1B10 was preferentially observed in cancer cells with obvious squamous differentiation in SCC (Fig. 3A-E), whereas with lower differentiation grade in adenocarcinoma (Fig. 3G). Interestingly, we occasionally observed AKR1B10 staining in lesions with metaplasia: squamous metaplasia (Fig. 3I) and transitional cell metaplasia (Fig. 3J) in noncancerous areas (Fig. 3K) of one smoker's SCC specimen. We seldom detected positive staining in noncancerous portion of lung tissue, except two cases in normal bronchial epithelia of smokers (Supplementary Fig. 2A and B).




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  		Fig. 3 Immunohistochemical analysis of AKR1B10. A-E, two representative cases in SCC. H&E staining, (A) x20 and (C) x100. Cancerous regions with obvious (red line) and no (blue line) squamous differentiation. Corresponding staining of the same sample (B and D) and another sample (E) by H4025. Note that AKR1B10 is stained in regions with squamous differentiation. F and G, two representative cases in adenocarcinoma. Homogenous staining was observed in some cases (F), whereas preferential staining in regions with lower differentiation was observed in most cases (G). H, typical case with nuclear staining in SCC (x100). I-K, AKR1B10 staining in metaplasia of a smoker. I, squamous metaplasia: (left) x20 and (right) x100. J, transitional cell metaplasia: (left) x20 and (right) x100. Note that these metaplastic regions are observed successively in noncancerous regions of a case with SCC (K). L-N, subcellular localization of endogenous AKR1B10 in A549 cells in 70% (L and M) and 100% (N) confluency. Left, AKR1B10; middle, MitoTracker (L) or propidium iodide (M and N); right, merged image. Note nuclear staining (L and M) has disappeared in 100% confluency (N).

 
AKR1B10 staining was mainly observed in cytoplasm of cancer cells but also in nucleus in a subset of cells (Fig. 3E and F). Notably, two cases had apparent AKR1B10 staining mainly in nuclei (Fig. 3M). These results were essentially confirmed in confocal microscopy analysis of A549 cells. AKR1B10 was generally localized in cytoplasm, neither in nucleus nor in mitochondria in most cells. However, a subset of cells had additional staining in nucleus in 70% confluency (Fig. 3L and M) but not in full confluency (Fig. 3N).

Correlation between AKR1B10 Overexpression and Smoking History in NSCLC and Adenocarcinoma. To clarify the factors that correlate with AKR1B10 immunostaining, we carried out a statistical analysis that examined a variety of clinicopathologic variables and the expression of molecules that we reported previously (refs. 8, 9, 11, 12 ; Table 3). We observed positive correlations between AKR1B10 overexpression and SCCs ({chi}2 test, P < 0.0001) and smoking ({chi}2 test, P < 0.0001) in NSCLCs. AKR1B10 overexpression was observed in 40 of 61 (65.6%) smokers' NSCLCs. The correlation coefficient between AKR1B10 overexpression and smoking was 0.47 in NSCLCs. Partial correlation coefficient was 0.41 even after removing the effect of positive correlation between AKR1B10 overexpression and male (P < 0.05). These results indicate the significant correlation between AKR1B10 overexpression and smoking.

Univariate analysis in NSCLCs also showed that AKR1B10 was overexpressed in tumors with high pT classification (P < 0.05). Additionally, AKR1B10-positive cases had a higher Ki-67 expression (P < 0.001), higher cyclin E expression (P < 0.01), lower GalNAcT3 expression (P < 0.01), and lower GnT-V expression (P < 0.05) than negative cases in NSCLCs. Student's t test revealed that there was a significant difference between AKR1B10 expression and Ki-67 expression (P < 0.005) and cyclin E expression (P < 0.05) in NSCLCs.

Multiple regression analysis showed that smoking (P < 0.01), SCC (P < 0.01), and lower GalNAcT3 (P < 0.05) were important independent variables responsible for AKR1B10 overexpression in NSCLCs (Table 4). We subsequently analyzed only adenocarcinomas (n = 65) because most SCCs were AKR1B10 positive (84.4%) and smokers (96.9%). Interestingly, there was still a remarkable correlation ({chi}2 test, P < 0.01) between AKR1B10 overexpression and smoking in adenocarcinomas (Table 3). Moreover, it was also shown that smoking was the only important independent variable responsible for AKR1B10 expression in adenocarcinomas (P < 0.01; Table 4).


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  		Table 4 Multiple regression analysis for AKR1B10

 

   DISCUSSION
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Aldo-keto reductases are NAD(P)H-dependent oxidoreductases that catalyze the reduction of a variety of carbonyl compounds (34). AKR1B10 is a member of this superfamily and reduces aromatic and aliphatic aldehyde substrates (34). Reportedly, AKR1B10 mRNA shows expression in adrenal gland, small intestine, and colon, consistent with its putative physiologic roles in steroid metabolism or detoxification of reactive aldehydes in the digested food in intestinal tract (34–36).

Initial goal of our study was to identify SCC-specific molecules, distinct from currently used SCC markers that are specific to squamous cell in general. We eliminated these squamous cell marker genes through our selection and identified AKR1B10 as a gene highly specific to SCC but not to squamous cells in general. AKR1B10 was expressed in as many as 90% of SCC of the lung but not in normal bronchial epithelium and squamous epithelium from skin and esophagus. This unique feature of AKR1B10 is highlighted when we compared the results of immunohistochemical analysis using AKR1B10 and keratin 5/6 (Table 2). AKR1B10 was highly specific to SCC when SCC and normal epithelia were analyzed by immunohistochemistry, although its specificity and sensitivity for SCC among NSCLCs were lower than those of keratin 5/6.

In the present study, we showed that AKR1B10 is overexpressed in SCC, which is closely associated with smoking. Additionally, we found AKR1B10 expression even in metaplasia, which is also associated with smoking and regarded as precancerous lesions of SCC (37, 38). Unexpectedly, nearly one third of the cases of adenocarcinomas expressed AKR1B10, but it was revealed by multiple regression analysis that smoking was the most important determinant of AKR1B10 expression in adenocarcinomas. Adenocarcinomas can be clustered into several subclasses based on reported expression profiling (22, 23). Together with recent reports that ~40% of adenocarcinomas occur in smokers (39), there is a possibility that AKR1B10 could characterize a subset of adenocarcinoma associated with smoking. Based on our results, AKR1B10 immunostaining could be applied to the early detection of cancer cells or atypical cells in sputum, especially in heavy smokers.

Then, what could be potential roles of AKR1B10 in multistep carcinogenesis of SCCs? There are two possibilities as follows: one is that AKR1B10 may be related to cell proliferation. There was a positive correlation between AKR1B10 expression and putative poor prognosis factors, such as high Ki-67, high cyclin E, low GalNAcT3, and low GnT-V in NSCLCs (8, 9, 11, 12). Moreover, AKR1B10 was localized in nucleus in a fraction of cancer cells in subconfluent culture conditions, which disappeared under confluent culture, suggesting that AKR1B10 translocates during cell cycle and is involved in the regulation of cell cycle in a fashion yet identified.

Another possibility is that AKR1B10 promotes carcinogenesis of SCC through its enzymatic activity that counteracts the conversion of ß-carotene to retinoic acid (40). Retinoic acid induces potent differentiation and growth-suppressive effects in diverse premalignant and malignant cells (41). In lung, deficiencies of retinoids are reported to cause hyperplasia and squamous metaplasia of airway epithelium (42) that can be suppressed by retinoic acid (43). Through the analysis of many cancer samples, we noticed positive staining of AKR1B10 even in some cases with metaplasia, precancerous lesion of SCC. Because the number of samples that contained metaplasia was small in the present study, this result was further investigated by another study focusing on idiopathic pulmonary fibrosis, which showed that squamous metaplasia was positive for AKR1B10 in 23 cases of 56 squamous metaplasia lesions.10 These results strongly suggest that AKR1B10 expression is positive in precancerous lesions and may down-regulate retinoic acid, which could lead to carcinogenesis of SCC. Considering that AKR1B10 is an enzyme related to detoxification and that some smokers' bronchial epithelia without metaplasia were positive for AKR1B10 staining, AKR1B10 may be directly induced by some chemical compounds in tobacco, which should be further investigated. Interestingly, we also observed frequent overexpression of AKR1B10 in SCC of the laryngopharynx and esophagus that is closely associated with smoking and occasional overexpression of esophageal dysplasia and hyperplasia.10 Remarkably high frequency of its up-regulation specific to SCC warrants further investigation of AKR1B10 in carcinogenesis of SCC.

Various retinoids, including ß-carotene, have been shown previously effective for the treatment and prevention of several cancers, including carcinoma of the breast, skin, and kidney (44–49). However, clinical chemoprevention trials of lung cancer by ß-carotene have failed to show its effectiveness. Moreover, administration of ß-carotene unexpectedly promoted tumorigenesis in smokers (50, 51). Molecular mechanism underlying these adverse effects is currently unknown, but up-regulation of AKR1B10 in precancerous lesions in the bronchial epithelium of smokers may partly explain ineffectiveness of ß-carotene observed in the lung.

AKR1B10 was also overexpressed in adenocarcinoma of smokers. Its staining was observed in undifferentiated region in contrast to SCC with staining in differentiated region. Together with its overexpression in hepatocellular carcinomas (34, 36), AKR1B10 may be related to another carcinogenic pathway distinct from that of SCC.

In summary, we showed that AKR1B10 is overexpressed in most SCCs and in adenocarcinomas that developed in the lung of smokers. Considering its involvement in retinoic acid metabolic pathway, AKR1B10 could be not a mere surrogate marker but a molecule relevant in smoking-related NSCLCs. Elucidation of its roles in carcinogenesis will be required to evaluate AKR1B10 as a therapeutic target in addition to a potential marker of SCC for diagnosis as shown in this study.


   ACKNOWLEDGMENTS
 
We thank Dr. S. Tsutsumi and Y. Midorikawa for useful comments and H. Meguro, S. Kawanabe, J. Yagi, K. Shiina, and E. Ashihara for excellent technical assistance.


   FOOTNOTES
 
Grant support: Ministry of Education, Culture, Sports, Science and Technology Grants-in-Aid for Scientific Research (B) 12557051 and 13218019 and Uehara Memorial Foundation (H. Aburatani).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: This study was carried out as a part of the Technology Development for Analysis of Protein Expression and Interaction in Bioconsortia on R&D of New Industrial Science and Technology Frontiers that was overseen by the Industrial Science, Technology and Environmental Policy Bureau, Ministry of Economy, Trade & Industry, and delegated to New Energy Development Organization.

Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

10 Fukayama et al., in preparation. Back

Received 6/25/04; revised 10/26/04; accepted 11/ 4/04.


   REFERENCES
Top
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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