• CHFR;
  • EGFR;
  • smoking;
  • hypermethylation;
  • mutation


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Aberrant promoter methylation of the checkpoint gene with forkhead-associated domain and ring finger (CHFR) gene is frequently detected in human cancer. We previously demonstrated that diminished CHFR expression was significantly correlated with both poor prognosis and heavy smoking in nonsmall cell lung cancer (NSCLC). Conversely, epidermal growth receptor (EGFR) mutation is detected in NSCLC among those who have never smoked or smoked lightly. To address the frequency of CHFR hypermethylation as well as differences in the distributions and clinicopathologic backgrounds against EGFR mutation in NSCLC, we investigated a large group of 208 NSCLC patients, including 165 with adenocarcinoma (ADC), 40 with squamous cell carcinoma and three others. We found that CHFR hypermethylation and EGFR mutation are mutually exclusive and have contrastive clinicopathologic backgrounds in NSCLC. Methylation-specific polymerase chain reaction (MSP) and direct DNA sequencing were performed to detect CHFR hypermethylation and EGFR mutation, respectively. CHFR hypermethylation was found in 29 cases (14%) (16 ADC (8%), 12 SCC (6%) and one adenosquamous carcinoma), while EGFR mutation was detected in 48 (23%) cases, all of which were ADC. CHFR hypermethylation and EGFR mutation were mutually exclusive (p = 0.004). NSCLC with altered CHFR was significantly correlated with smoking history, poor differentiation, lymphatic invasion, and poor prognosis; this contrasted sharply with EGFR mutation, which had statistically better clinical outcomes. Our results demonstrate that CHFR loss might be critical for the tumorigenesis of NSCLC in patients with a history of smoking and induces tumors of a more malignant phenotype than the EGFR mutation. Thus, CHFR alteration should be considered a therapeutic target against NSCLC in patients with poor prognoses.

Lung cancer is a leading cause of cancer mortality worldwide; it accounts for over a million deaths annually and still has a poor prognosis.1 Nonsmall cell lung cancer (NSCLC) is the main form of lung cancer, which has three major histologic types: squamous cell carcinoma (SCC), adenocarcinoma (ADC) and large cell carcinoma (LCC).2 Among these, ADC has become the most common type in Western countries.2 It is widely accepted that NSCLC is the result of a series of molecular changes, including oncogene activation and the loss of tumor suppressor genes. Recently, epidermal growth receptor (EGFR) mutation has been receiving increasing attention for its specific clinical response to the anticancer drug gefitinib.3EGFR mutations are found in 10–40% of NSCLC and are clinicopathologically characterized by female gender, no smoking history and ADC histology, especially with bronchioloalveolar features.4–6 In addition to these data, patients with EGFR mutation have fairly good survival rates.3 Plenty of knowledge has accumulated about EGFR mutation, but there is still no full understanding of the molecular abnormality that is a counterpart of NSCLC and that is associated with smoking and poor clinical outcome.

We previously reported that reduced checkpoint gene with forkhead-associated domain and ring finger (CHFR) expression was associated with a heavy smoking history, poorer differentiation and poor prognosis in NSCLC.7CHFR is a ubiquitin ligase of Plk1 and Aurora-A. It functions as a mitotic checkpoint by delaying entry into metaphase in response to mitotic stress induced by nocodazole or paclitaxel.8–10 The loss of CHFR messenger RNA and/or protein expression is observed in human cancers, partly due to hypermethylation of the CHFR promoter region or, in a few cases, to missense mutations. This suggests that CHFR is a candidate tumor suppressor.7, 11–15 Supporting this hypothesis, in addition to our previous results, it has been reported that tumor incidence was increased in CHFR knockout mice16 and that the specific knockdown of CHFR in immortalized human mammary cell lines resulted in the acquisition of malignant phenotypes associated with increased growth rates and high mitotic indices.17 Despite the knowledge that CHFR is a tumor suppressor, there is a paucity of informative data regarding the frequency and distribution of CHFR methylation against that for EGFR in NSCLC. With these findings in mind, we also paid attention to the striking contrasts in the clinicopathologic backgrounds and clinical outcomes between EGFR mutation and CHFR methylation in NSCLC. However, few data are available regarding the association between each genetic or epigenetic alteration in NSCLC with clinicopathologic data.

In this study, we performed an analysis of CHFR hypermethylation, EGFR mutation and KRAS mutation of 208 NSCLC to elucidate the frequency of CHFR methylation, as well as the distribution of each abnormality and the correlation of each with clinicopathologic data. We report that aberrant CHFR methylation and EGFR mutation do not occur simultaneously and contrast sharply in clinicopathologic backgrounds, including recurrence risk and survival of patients with NSCLC.

Material and Methods

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Lung cancer samples

Frozen tumor tissues, acquired from 208 Japanese patients with NSCLC who had undergone surgery at Kyushu University Hospital between 2003 and 2008, were used in this study. Informed consent was obtained for all patients, and use of the tissues was approved by the Ethics Committee of Kyushu University Hospital. The follow-up period ranged from 1 to 66 months, with a mean of 32 months. The patients ranged in age from 34 to 86 years (mean, 67 years) and included 124 males (60%) and 84 females (40%). Eighty-two patients were never-smokers, and the remaining 126 were past or current smokers. Histological diagnosis was made by hematoxylin and eosin staining essentially based on the WHO criteria,2 and was based on a consensus among three pathologists (T.K., M.T. and K.S.). The results revealed 165 ADC, 40 squamous cell carcinomas, two large cell carcinomas and one adenosquamous carcinoma. As for tumor differentiation, 71 tumors were well differentiated, 87 moderately differentiated and 48 poorly differentiated (excluding the two large cell carcinomas) based on the pathological criteria previously reported.2, 18, 19 Pathologic staging was classified according to the tumor-node-metastasis (TNM) classification system revised in 1997.20 Stages I, II, III and IV had 137, 46, 22 and three cases, respectively.

DNA and RNA extractions and bisulfite modification of genomic DNA

Prior to DNA or RNA extraction, tumor cells were enriched under light microscope–assisted gross dissection using Giemsa staining. Genomic DNAs were isolated using standard phenol and chloroform extraction. Sodium bisulfite conversion of genomic DNA was performed using the EZ DNA Methylation Kit (Zymo Research, Orange, CA), according to the manufacturer's standard protocol.

Total RNA was extracted from the specimens stained with Giemsa, using acid guanidinium thiocyanate–phenol–chloroform extraction methods.21 cDNA was synthesized with 0.3 μg total RNA using a first-strand cDNA Synthesis Kit (Invitrogen, Carlsbad, CA) and applied to direct sequencing.

Methylation analysis of the CHFR gene

The methylation status of the CHFR gene was analyzed by methylation-specific polymerase chain reaction (MSP) as previously described.7 The oligonucleotide primers were designed to be specific to either the methylated or unmethylated DNA sequence of the CHFR gene after sodium bisulfite conversion. Polymerase chain reaction (PCR) amplification was done with sodium bisulfite–treated DNA as a template and specific primers. The resultant PCR products were separated on 3% agarose gels. Each MSP was conducted at least twice.

Mutation analysis for EGFR and KRAS genes

EGFR and KRAS mutations were detected using PCR with tumor cDNA as a template, followed by direct sequencing, as described previously.4 Briefly, PCR amplification was done using specific primers for EGFR and KRAS cDNAs, which include exons 18–21 of the EGFR gene and exons 1–2 of the KRAS gene, and sequenced using the Applied Biosystems PRISM dye terminator cycle sequencing method (Perkin Elmer, Foster City, CA) with the ABI PRISM 3100 Analyzer (Applied Biosystems, Beverly, MA).

Statistical analysis

Fisher's exact probably test and Student's t-test were used to assess the association of variables properly. The overall survival and recurrence rates were analyzed using the Kaplan–Meier method with the log-rank test and Breslow test. The Cox proportional hazards multivariate regression model was used to select independently significant prognostic or recurrent factors. A p-value of less than 0.05 was regarded as statistically significant. Statistical analysis was done using SPSS software version 9.0.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

The frequency of CHFR, EGFR and KRAS alterations and the association with clinicopathologic data in NSCLC

Of 208 NSCLC, aberrant CHFR promoter methylation was identified in 29 cases (14%), including 16 ADC (8%), 12 SCC (6%) and one adenosquamous carcinoma (Table 1). No methylation of CHFR was found in two LCC. CHFR methylation was significantly associated with a greater number of clinicopathologic factors (Table 1), as shown by smoking habit (p = 0.039), histology of squamous cell carcinoma (p = 0.003), poorer differentiation (p = 0.011), lymphatic vessels and vascular invasion (p = 0.021, 0.040, respectively). No statistical differences were observed in pathologic stage, age, gender, tumor size (Table 1) or pleural invasion (data not shown). Typical lung ADC cases with CHFR hypermethylation demonstrated poorly differentiated carcinoma arranged mainly in nests or in a papillary and small tubular pattern with obvious destructive growth of alveoli (Fig. 1).

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Figure 1. (a) A typical lung adenocarcinoma with CHFR hypermethylation (H&E; ×100). The tumor consists of carcinoma cells with increased N/C ratios and bizarre nuclei, arranged in a papillary or tubular pattern or in nests. The natural structures of the alveoli are destroyed by tumor growth. (b) A case of adenocarcinoma with EGFR mutation (H&E; ×100). The tumor shows a papillary proliferation of malignant cells with fibrous alveolar septa. Generally in NSCLC with EGFR mutation compared to that with CHFR hypermethylation, destructive growth of carcinoma cells is not prominent and the nuclear atypia of tumor cells is relatively mild. (c) Methylation-specific PCR of the CHFR promoter region. U and M denote unmethylated DNA-specific amplification and methylated DNA-specific amplification, respectively. Aberrant methylation of the CHFR gene promoter is found in case 31. (d) Missense mutations in the EGFR gene exons 21 in NSCLC. L858R mutation in EGFR exon 21 is found in 27 cases. Since a reverse primer was used for sequencing, each nucleotide shows a comprehensive arrangement. (e) Kaplan–Meier curves with respect to recurrence. Patients with CHFR methylation in NSCLC show a significantly high recurrence rate (p = 0.0198 (log-rank test)), p = 0.0198 (Breslow test)). (f) Kaplan–Meier curves regarding overall survival. Survival curves are shown for patients with and without CHFR hypermethylation. Cases with CHFR methylation demonstrate poorer prognoses [p = 0.0029 (log-rank test), p = 0.0012 (Breslow test)]. (g) NSCLC cases with EGFR hypermethylation show better prognoses with a statistical tendency compared to those of EGFR wild-type cases [p = 0.2382 (log-rank test), p = 0.1401 (Breslow test)].

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Table 1. CHFR methylation and EGFR mutation, and correlations with clinicopathologic parameters
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EGFR mutations were detected in 48 (23%) of the 208 NSCLC in exons 18–21, the tyrosine kinase domain; no EGFR mutation was seen in SCC or the others (Table 1). The 48 mutations consisted of 21 deletion mutations and 27 missense mutations. Besides these, 12 silent mutations were also detected. In the 48 tumors with EGFR deletion or missense mutation, we resequenced the tumors to confirm that these mutations were actually present. We also resequenced the corresponding cDNA from noncancerous lung tissue and confirmed that all these mutations were somatic. All of the 21 deletion mutations occurred around codons 746–750 in exon 19 and were simple deletions of five amino acid residues, ELREA, from codons 746 to 750. All of the 27 missense mutations were from a T- to a G-transversion at the second nucleotide of codon 858 in exon 21, resulting in the substitution of leucine with arginine residue. All 12 silent mutations were at codon 787 (Q787Q) in exon 20. EGFR deletion and missense mutations were also correlated with a good number of clinicopathologic factors (Table 1), such as female gender (p < 0.001), never having smoked (p < 0.001), ADC histology (p < 0.001), good differentiation (p = 0.002), smaller tumor size (p = 0.039) and no vascular invasion (p = 0.007). No difference was observed in age, lymphatic invasion or pathologic stage (Table 1) or in pleural invasion (data not shown). It is noteworthy that CHFR methylation was correlated with many clinicopathologic factors toward poor prognosis, but EGFR mutation was linked to the factors for good prognosis. Histologic characteristics of typical ADC with EGFR mutation have an inclination to differentiate well with carcinoma cells proliferating in a lepidic or papillary fashion (Fig. 1). Generally, the destructive growth of alveoli is less prominent in ADC with EGFR mutation than in that with CHFR hypermethylation. Case No. 143 possessed both CHFR methylation and EGFR mutation (Table 2). This case was well-differentiated ADC with lymphatic and vascular invasions.

Table 2. Distribution of EGFR and KRAS mutations and CHFR methylation in NSCLC
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Of the 208 NSCLC, 13 (6%) had the KRAS mutation in exon 2. No KRAS mutation was seen in any of the SCC or other cases. No statistical significance regarding clinicopathologic data was observed (data not shown).

Distribution of EGFR or KRAS mutations and aberrant CHFR promoter hypermethylation in NSCLC

The distribution of EGFR mutation and that of CHFR methylation were significantly exclusive in NSCLC (p = 0.004; Table 2). Although the frequency of CHFR methylation was significantly higher in SCC than in ADC (Table 1), statistical significance between EGFR mutation and CHFR methylation was also observed only in ADC (p = 0.041, data not shown). EGFR and KRAS mutations were also mutually independent (p = 0.042, Table 2), but no statistical correlation was found between KRAS mutation and CHFR methylation (p = 0.796, Table 2).

Risk factors for recurrence

Background factors for recurrence and patient survival are shown in Table 3. A statistically significant difference was observed between the recurrence rate of patients with CHFR methylation and that of those without it by the Kaplan–Meier method in the log-rank and Breslow tests (p = 0.0198, 0.0116, respectively; Fig. 1).

Table 3. Background factors for recurrence and patient survival
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Univariate analyses of recurrence by age, gender, smoking habit, EGFR or KRAS mutation, CHFR methylation, tumor histology, tumor differentiation and lymphatic or vascular invasion were performed (Table 4). Gender (p = 0.0075), smoking habit (p = 0.0207), CHFR methylation (p = 0.0229), tumor differentiation (p = 0.0030) and lymphatic (p = 0.0002) or vascular invasion (p = 0.0001) were significant. There was no significance in age (p = 0.1251), EGFR or KRAS mutation (p = 0.3984, 0.6014, respectively) or tumor histology (p = 0.3814, Table 4). We applied age, which showed a p-value of 0.3 or less, in addition to gender, smoking habit, CHFR methylation, tumor differentiation and lymphatic or vascular invasion, to logistic multivariate analysis. The results showed CHFR methylation and lymphatic invasion to be independent risk factors for recurrence, with hazard ratios of 2.00 and 2.62, respectively (p = 0.0421, 0.0026, respectively, Table 5).

Table 4. Univariate analysis for recurrence risk factors and over all survival
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Table 5. Multivariate analysis for recurrence risk factors and over all survival
inline image

Univariate and multivariate analyses of prognostic parameters

The overall survival rate of patients with CHFR methylation was significantly correlated with poor prognosis by the log-rank and Breslow tests (p = 0.0029, 0.0012, respectively; Fig. 1). As for EGFR mutation, patients with the mutation showed better prognosis with a statistically significant tendency than patients with wild-type EGFR (p = 0.2382, 0.1401; Fig. 1).

Univariate analyses of survival according to age, gender, smoking habit, EGFR and KRAS mutations, CHFR methylation, tumor histology and differentiation and lymphatic or vascular invasion for survival were performed. CHFR methylation and lymphatic or vascular invasion were significant factors (p = 0.0061, 0.0034, 0.0288, respectively), but there was no significance in age (p = 0.6927), gender (p = 0.1075), smoking habit (p = 0.4355), EGFR and KRAS mutations (p = 0.2799, 0.8678, respectively) or tumor histology or differentiation (p = 0.3700, 0.1025, respectively; Table 4). We applied gender, EGFR mutation and tumor differentiation, which showed p-values of 0.3 or less, in addition to CHFR methylation and lymphatic or vascular invasion, to logistic multivariate analysis. The results showed CHFR methylation and lymphatic invasion to be independent prognostic factors, with hazard ratios of 3.44 and 4.02, respectively (p = 0.0274, 0.0134, respectively, Table 5). These two factors for prognosis coincided with that for recurrence.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

EGFR gene mutation has received much attention, because patients with NSCLC harboring specific mutations in the EGFR gene show excellent clinical responsiveness to the tyrosine kinase inhibitor gefitinib.22, 23EGFR mutations are found in ∼40% of NSCLC, and NSCLC with the mutation is clinicopathologically characterized by female gender, never having smoked, ADC histology especially with bronchioloalveolar features and fairly good survival rates.1, 3, 4, 6 To our knowledge, however, few molecular abnormalities, which were associated concurrently with smoking habit, clinicopathologic data correlated with tumor malignant potential and poor clinical outcomes, have been found in NSCLC without EGFR mutation. In this study, we performed an analysis of 208 NSCLC regarding promoter methylation of CHFR, a putative tumor suppressor, as well as EGFR and KRAS mutations, and obtained the following key findings: (i) CHFR methylation was found at relatively low frequency, but the distribution was exclusive against that for EGFR mutation in NSCLC; (ii) the genetic or epigenetic abnormalities had sharply contrasting clinicopathologic backgrounds, such as smoking habit, tumor differentiation and lymphatic or vascular invasion; CHFR methylation, rather than EGFR mutation, was positively associated with such clinicopathologic data concerning tumor invasiveness and (iii) CHFR hypermethylation, in addition to lymphatic invasion, was an independent risk factor for recurrence rate and prognosis, whereas EGFR mutation was associated with a better prognosis compared with the wild-type EGFR genotype in NSCLC.

EGFR activation triggers several signaling cascades, including the Ras/Raf/MAPK, Janus-activated kinase/signal transducers and activators of transcription and PI3K/Akt pathways. These cascades promote cell survival, migration, proliferation and angiogenesis. In contrast, CHFR functions as a cell-cycle checkpoint molecule and has been thought to be a tumor suppressor because the silencing of CHFR is frequently observed in human cancers.7, 11–15 Several pieces of evidence support this hypothesis that CHFR is a tumor suppressor: CHFR knockout mice had an increased tumor incidence13 and CHFR knockdown in immortalized human mammary cell lines resulted in the acquisition of malignant phenotypes.17 In addition, several target molecules of CHFR have been found recently. CHFR downregulates histone deacetylase 1 (HDAC1) through its ectopic expression, leading to the upregulation of p21CIP1/WAF1 as well as of metastasis suppressors KAI1 and E-cadherin.24CHFR also negatively regulates NF-κB and p65.25 These data might indicate that CHFR functions not only as a cell-cycle checkpoint component but also possibly as a regulator of downstream oncogenic molecules. However, it remains unknown whether or not CHFR affects the signaling cascades activated by EGFR mutation. In this study, CHFR methylation and EGFR mutation were mutually exclusive, and EGFR and KRAS mutations did not occur simultaneously in NSCLC. In comparison to EGFR mutation, CHFR methylation and KRAS mutation had relatively low frequencies in NSCLC (14 and 6%, respectively). Through this extensive research into NSCLC, the rates of CHFR hypermethylation was found to be approximately identical with that of a previous report,15 but the rate of KRAS mutation was approximately the same frequency as in previous reports in Asian countries, although somewhat lower than those in Western countries.26, 27 We have no explanation for this difference yet, but the low incidence appears not to be based on the sensitivity of our assay (data not shown). Although mutations in genes functioning in different pathways frequently occur together in the same cancer, mutations in the same pathway tend to be mutually exclusive.28 Thus, CHFR alteration may be involved in the EGFR signaling pathway. Further examination is necessary to confirm this. We also demonstrated that CHFR hypermethylation was associated with smoking habit, whereas EGFR mutation occurred in never-smokers. It is evident that tobacco smoking is a cause of lung carcinogenesis; indeed, approximately 90 and 70% of male and female cases of lung cancer, respectively, have been considered smoking related.29 Several reports have associated tobacco smoking with alterations of oncogenes and/or tumor suppressor genes in lung cancer, including KRAS and p53 mutations, loss of heterozygosity, or promoter hypermethylation of fragile histidine triad (FHIT) and p16 genes.30–33 These data might suggest that smoking, fundamentally independently of EGFR mutation, triggers CHFR hypermethylation. In the future, the mechanisms that abolish CHFR functions by smoking should be elucidated.

Interestingly, our data revealed sharp contrasts in clinicopathologic background characteristics—such as tumor differentiation, lymphatic or vascular invasion and smoking habit—between CHFR methylation and EGFR mutation. It is worth noting that CHFR loss, in contrast to EGFR mutation, was positively associated with these factors concerning tumor invasiveness in NSCLC. These data suggest that CHFR loss is closely related to the tumor malignant phenotype, but thus far no mechanisms have been elucidated at all. Meanwhile, EGFR mutation was negatively correlated with those factors. Thus, patients with EGFR mutation might exhibit rather good prognoses.

Alterations of many cell-cycle checkpoint proteins, including the INK4 family (p16) and the Cip/Kip family (p21, p27 and p57), have been reported to predict prognosis in NSCLC,34–37 but this is the first study to report CHFR methylation as an independent risk factor for recurrence rate and prognosis in NSCLC. As described above, the reason for this may involve the positive relationship between CHFR methylation and several risk factors for patient survival, but the overall mechanisms underlying the potential for CHFR to influence the recurrence rates or prognoses of patients with malignant tumors remain poorly understood.

In conclusion, our results suggest that CHFR hypermethylation might be critical for tumorigenesis of NSCLC in patients with a history of heavy smoking. Although the frequency of this abnormal methylation is relatively low, it has more potential than EGFR mutation to harm the clinical outcomes of patients with NSCLC. Thus, CHFR, including the upstream and targeting molecules, might be a promising therapeutic target against NSCLC.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

The authors thank Mr. Hiroshi Fujii and Mrs. Yuko Nishimura-Ikeda for their excellent technical assistance, and Ms. Noriya Taki for her technical statistical advice.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
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