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. 2023 Jul 25;33(1):45–52. doi: 10.1097/CEJ.0000000000000832

Comprehensive analysis of the clinical and prognostic significance of SFRP1 and PRKCB expression in non-small cell lung cancer: a retrospective analysis

GuoQiang Hu a, Juan Du b, Bin Wang c,d, PengTao Song c,d, ShunLin Liu c,d,✉
PMCID: PMC10702695  PMID: 37505453

Abstract

Objectives

Secreted frizzled-related protein 1 (SFRP1) and protein kinase C-B (PRKCB) contribute to cancer progression and angiogenesis. This study intended to detect SFRP1 and PRKCB expression in non-small-cell lung cancer (NSCLC) patients and analyze its association with clinicopathological features.

Methods

A total of 108 NSCLC patients who underwent surgical resection in our hospital between 2012 and 2017 were retrospectively analyzed. SFRP1 and PRKCB expression was detected using immunohistochemical staining. The relationships between SFRP1 and PRKCB expression and clinicopathological data were analyzed using the chi-square method. Kaplan–Meier analysis was used to investigate survival probability over time. The potential risk of NSCLC morbidity associated with SFRP1 and PRKCB levels was analyzed using univariate and multivariate Cox proportional risk models.

Results

SFRP1 and PRKCB expression was negative in 114 and 109 of the 180 NSCLC specimens, respectively. SFRP1 expression was significantly associated with TNM stage (P < 0.001) and tumor diameter (P < 0.001). PRKCB expression was significantly associated with the TNM stage (P < 0.001). The correlation between SFRP1 and PRKCB expression was evident (P = 0.023). SFRP1(−) or PRKCB(−) patients shows lower survival rates than SFRP1(+) or PRKCB(+) patients (P < 0.001). SFRP1(−)/PRKCB(−) patients had the worst prognosis (P < 0.001). Furthermore, the mortality of SFRP1(−) or PRKCB(−) patients was significantly higher than that of SFRP1(+) or PRKCB(+)

Conclusion

SFRP1 and PRKCB expression can be used to predict prognosis in patients with NSCLC.

Keywords: non-small cell lung cancer, protein kinase C-B, prognosis, secreted frizzled-related protein 1

Introduction

Lung cancer is a major health problem with high rates of incidence and mortality, often because of late diagnosis and early metastasis. The prognosis of this disease is typically not encouraging (Bray et al., 2018; Imyanitov et al., 2021). Non-small cell lung cancer (NSCLC) accounts for approximately 80–85% of all lung cancer cases (Imyanitov et al., 2021). Owing to the fact that lung cancer is often detected at an advanced stage (Lee and Kazerooni, 2022), even after receiving advanced treatments such as targeted therapy, chemoradiotherapy, and combination chemotherapy, the survival rates of patients are still unfavorable (Qi et al., 2022). Therefore, it is essential to explore the possible prognostic biomarkers for lung cancer.

The Wnt signaling pathway components are associated with the development and progression of NSCLC (Tang et al., 2017; Pan et al., 2020; Wang et al., 2021). Secreted frizzled-related protein (SFRP) family members (SFRP1–SFRP5) can be directly stimulated by Wnt signal molecules and Wnt pathway inhibition (Kawano and Kypta, 2003; Bovolenta et al., 2008; Surana et al., 2014). SFRP1, a secreted glycoprotein, is considered to be a subclass of Wnt pathway antagonists because a part of its structure is highly homologous to that of the FZD receptor of the Wnt signaling pathway. SFRP1 acts as a tumor suppressor gene by virtue of its ability to antagonize the Wnt signaling pathway (Krishnamurthy and Kurzrock, 2018). Protein kinase C-B (PRKCB) is a member of the protein kinase family. Its main function is to participate in the phosphorylation of proteins of various signal transduction pathways, including the Wnt signaling pathway (Kawano and Kypta, 2003). It has been reported that PRKCB is methylated in the early stages of lung adenocarcinoma development, which indicates that PRKCB plays a role in the progression of lung adenocarcinoma (Lee et al., 2010).

Considering the key role of Wnt inhibitors in cancer progression and prognosis, we hypothesized the SFRP1 and PRKCB have roles during NSCLC malignancy. Therefore, we evaluated the relationship between the tumor suppressor genes SFRP1 and PRKCB in the Wnt signaling pathway and the risk of NSCLC, as well as investigated their relationship with clinicopathological factors of NSCLC. In addition, we investigated whether immunohistochemical detection of these two genes can help determine the prognosis of NSCLC.

Methods

Patients and tissue samples

A total of 180 primary lung cancer tissue samples were retrospectively collected from 2012 to 2017 at Changxing Hospital of Traditional Chinese Medicine. None of the patients received chemotherapy or radiotherapy before surgery. Clinical data of all patients were completed. The clinical characteristics of the patients are summarized in Table 1. The tumor staging criteria were based on the 2009 TNM staging criteria for malignant tumors by the International Union against Cancer and the American Joint Committee on Cancer. This study was approved by the Research Ethics Committee of Changxing Hospital of Traditional Chinese Medicine (2019LL11). Informed consent was obtained from all patients before surgery.

Table 1.

Association between SFRP1 and PRKCB expression and clinicopathological variables in patients with NSCLC

Clinicopathological variable SFRP1 P PRKCB P-value
Negative, n = 114 Positive, n = 66 Negative, n = 109 Positive, n = 71
Age 60.96 ± 9.28 60.15 ± 9.49 0.575 61.73 ± 8.97 59.03 ± 9.71 0.057
Tumor diameter 2.79 ± 1.3 4.18 ± 1.74 <0.001 3.13 ± 1.71 3.57 ± 1.43 0.072
Sex Male 58 32 0.757 53 37 0.647
Female 56 34 56 34
Differentiation Poor 43 33 0.108 48 28 0.541
Well or moderate 71 33 61 43
TNM stage I 82 12 <0.001 74 20 <0.001
II 14 17 17 14
III 14 28 13 29
IV 4 9 5 8
Histology SCC 52 34 0.445 54 32 0.557
AC 62 32 55 39
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AC, adenocarcinoma; SCC, squamous-cell carcinoma.

Immunohistochemistry

The NSCLC tissue samples were fixed overnight in 4% paraformaldehyde solution at 4 °C–8 °C, embedded in paraffin wax, and cut into 4-mm-thick sections. Immunohistochemical analysis using the formalin fixation method was performed to detect SFRP1 and PRKCB expression in paraffin-embedded surgical specimens. The target search solution, which helps find antigens, was used for post-antigen retrieval. The activity of endogenous peroxidase was quenched by incubating the sections in 0.3% hydrogen peroxide. The sections were then blocked with 10% fetal bovine serum to prevent nonspecific binding, followed by preincubation with 10% fetal bovine serum in PBS containing 0.01% sodium azide. Subsequently, the sections were incubated with anti-SFRP1 (1:100; Santa Cruz Biotechnology, Dallas, Texas, USA) and PRKCB (1:50; Abcam, Cambridge, Massachusetts, USA) antibodies. Finally, the samples were incubated with peroxide-bound streptavidin. The sections were incubated for 30 min and counterstained with diaminobenzidine and hematoxylin. PBS was used as a negative control. An active control kit was used. Immunohistochemical staining was interpreted by two experienced pathologists using Image-Pro Plus 6.0 software (Media Cybernetics, Rockville, Maryland, USA). The mean staining density was calculated.

Evaluation of immunohistochemical staining

Positive expression of SFRP1 and PRKCB proteins was visualized as brownish-yellow or brown staining in the cytoplasm and cell membrane. Under high-power microscopy (SP 400×), five different visual fields were randomly selected for use in calculating the total number of positive cells, and the score was calculated according to the percentage of positive cells: 1 if positive cells accounted for <10%, 2 if positive cells accounted for >10% and ≤50%, 3 if positive cells accounted for >50% and ≤75%, and 4 if positive cells accounted for >75%. Moreover, scores were calculated according to different degrees of staining intensity: 1 point, negative; 2 points, weak staining; 3 points, medium staining; and 4 points, strong staining. The results were determined based on the sum of the abovementioned calculated scores: a score below 4 was considered (−); between 4 and 8 was considered (+); between 8 and 12 was considered (++); and between 12 and 16 was considered (+++). Samples were divided into high-expression [(++) and (+++)] and low-expression [(−) and (+)] groups (Yu et al., 2009).

Gene expression analysis

The Cancer Genome Atlas (https://www.cancer.gov/tcga) and Gene Expression Profiling Interactive Analysis (http://gepia2.cancer-pku.cn/) datasets were used to analyze SFRP1 and PRKCB expression in different cancer subtypes, including pan-cancer, lung adenocarcinoma, and lung squamous cell carcinoma.

Survival prognosis analysis

Based on the median values of the SFRP1 and PRKCB expression, patients were divided into high-expression and low-expression groups. The Kaplan–Meier plotter (http://kmplot.com/analysis/) was used to evaluate the effect of SFRP1 and PRKCB expression on patient outcomes. Overall survival (OS) was used for comparison. Follow-up for survival was performed for 5 years. Results with P < 0.05 were considered statistically significant. Some well-known confounders of survival in this context (e.g. age, sex, diagnosis, and prior medical history) were present in the data but others, such as cardiac function, were missing.

Statistical analysis

The differences between groups were statistically analyzed using the χ2 test and compared using the independent samples t-test. The classification indexes are described as N. Spearman’s correlation coefficient was used to analyze the correlation between SFRP1 and PRKCB. Kaplan–Meier survival curves were used to compare survival differences based on SFRP1 and PRKCB expression. Univariate and multivariate Cox regression analyses with propensity score models were performed to analyze the independent risk factors of survival and death. IBM SPSS Statistics 26 (IBM Corp., Armonk, New York, USA) and GraphPad 7.0 (GraphPad Software Inc., Boston, Massachusetts, USA) were used for the analyses. Most relevant results have been reported in this study, according to statistical and data reporting guidelines for the European Journal of Cardio-Thoracic Surgery and the Interactive CardioVascular and Thoracic Surgery journal. Results with P < 0.05 were considered statistically significant.

Results

Patient characteristics

This study involved 180 patients with NSCLC, including 90 men and 90 women. The average age of the participants was 60.5 years. Histological subtypes were squamous-cell carcinoma in 86 patients and adenocarcinoma in 94 patients. There were 94 patients with clinical stage I, 31 with stage II, 42 with stage III, and 13 with stage IV disease. According to the degree of tumor differentiation, 104 patients were categorized as moderately differentiated and 76 were categorized as poorly differentiated. Detailed characteristics of the patients are summarized in Table 1.

SFRP1 and PRKCB expression in NSCLC and its correlation with clinicopathological features

First, SFRP1 and PRKCB expression was evaluated via a public database. SFRP1 and PRKCB expression decreased across pan-cancer types (Figs. 1a–d and 2a–d) and in both lung adenocarcinoma and lung squamous cell carcinoma (Figs. 1e–h and 2e–h).

Fig. 1.

Fig. 1

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Expression of SFRP1 in non-small cell lung cancer (NSCLC). The expression of SFRP1 in NSCLC obtained via a public database (a–d). Immunohistochemical staining of SFRP1 in patients with NSCLC: (e) negative SFRP1 expression in patients with lung adenocarcinoma; (f) positive SFRP1 expression in patients with lung adenocarcinoma; (g) negative SFRP1 expression in patients with squamous-cell lung carcinoma; and (h) positive SFRP1 expression in patients with squamous-cell lung carcinoma. Original magnification 200×.

Fig. 2.

Fig. 2

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Expression of PRKCB in non-small cell lung cancer (NSCLC). The expression of PRKCB in NSCLC obtained via a public database (a–d). Immunohistochemical staining of PRKCB in patients with NSCLC: (e) negative PRKCB expression in patients with lung adenocarcinoma; (f) positive PRKCB expression in patients with lung adenocarcinoma; (g) negative PRKCB expression in patients with squamous-cell lung carcinoma; and (h) positive PRKCB expression in patients with squamous-cell lung carcinoma. Original magnification 200×.

Among the 180 NSCLC tissues, 114 (63.3%) were SFRP1-negative and 66 (36.7%) were SFRP1-positive. Moreover, 109 (60.6%) were PRKCB-negative, and the remaining 71 (39.41%) were PRKCB-positive. The immunohistochemical analysis results of SFRP1 and PRKCB are shown in Figs. 1e–h and 2e–h. According to clinical data analysis, SFRP1 expression correlated with tumor diameter (P < 0.001) and TNM stage (P < 0.001), but not with age, sex, smoking status, degree of tumor differentiation, or tumor tissue type (all P > 0.05, Table 1). Expression of PRKCB correlated with only the TNM stage (P < 0.001) and not with age, sex, degree of tumor differentiation, tumor diameter, tumor tissue type, or any other variable (all P > 0.05), as shown in Table 1. Among the 180 patients, 41 were positive for both SFRP1 and PRKCB, 73 were positive for SFRP1 and negative for PRKCB, 30 were positive for PRKCB and negative for SFRP1, and 36 were negative for both SFRP1 and PRKCB. There was a significant correlation between SFRP1 and PRKCB expression (P = 0.023, Table 2).

Table 2.

Correlation between SFRP1 and PRKCB

SFRP1 PRKCB P-value
Negative Positive
Negative 36 30 0.023
Positive 73 41
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Influence of SFRP1 and PRKCB expression on survival

To evaluate the effects of SFRP1 and PRKCB expression on patient survival, Kaplan–Meier analysis was performed. We observed that lower SFRP1 and PRKCB expression was associated with poorer OS (Fig. 3a–b). We then confirmed the finding with our collected data (Fig. 3c–e).

Fig. 3.

Fig. 3

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Relationship between SFRP1 and PRKCB and patient survival. The Kaplan–Meier database shows the effect of SFRP1 and PRKCB expression on patient survival (a and b). Kaplan–Meier analysis shows overall survival effect of (c) SFRP1, (d) PRKCB, and (e) both SFRP1 and PRKCB in patients with non-small cell lung cancer (NSCLC).

The survival analysis using the Kaplan–Meier plot showed that the 5-year OS rate of patients with positive SFRP1 expression was significantly higher than that of patients with negative SFRP1 expression (Fig. 3c, P < 0.001). Moreover, PRKCB expression was low in patients with poor survival and high in patients with high survival (Fig. 3d, P < 0.001). In addition, in the subsequent survival analyses performed to investigate patients at each stratification, namely SFRP1(+)/PRKCB(+), SFRP1(+)/PRKCB(−), and SFRP1(−)/PRKCB(−), SFRP1(−)/PRKCB(−) patients had the worst prognosis (Fig. 3e, P < 0.001) and SFRP1(+)/PRKCB(+) patients had the highest survival rate. According to Kaplan–Meier survival analysis, the 5-year OS rate of the SFRP1-positive group was significantly higher than that of the SFRP1-negative group (Fig. 3e, P < 0.001). Similarly, patients with high PRKCB expression had better prognosis than patients with low expression (Fig. 2, P < 0.001). SFRP1(+)/PRKCB(+) patients had the highest survival rate. The TNM stage significantly affected the survival of patients [hazard ratio (HR) = 2.211; 95% confidence interval (CI): 1.778–2.749; P < 0.001], which indicated that the later the TNM stage, the higher the probability of mortality. SFRP1 expression significantly affected the survival of patients (HR = 2.219; 95% CI: 1.471–3.346; P < 0.001), indicating that the mortality of SFRP1-negative patients was significantly higher than that of SFRP1-positive patients. PRKCB expression significantly affected the survival of patients (HR = 2.093; 95% CI: 1.446–3.030; P < 0.001), indicating that the mortality of PRKCB-negative patients was significantly higher than that of PRKCB-positive patients (Table 3).

Table 3.

Multivariate Cox analysis of survival

HR 95% CI P HR 95% CI P-value
Sex (male/female) 0.779 0.553–1.099 0.779
Age 0.983 0.964–1.002 0.072
Tumor diameter 1.443 1.308–1.592 <0.001 1.125 1.004–1.260 0.043
Differentiation 0.954 0.673–1.354 0.794
TNM stage 2.801 2.342–3.350 <0.001 2.211 1.778–2.749 <0.001
Histology (SCC/AC) 0.847 0.599–1.196 0.345
SFRP1(−/+) 4.874 3.395–6.995 <0.001 2.219 1.471–3.346 <0.001
PRKCB(−/+) 3.660 2.539–5.278 <0.001 2.093 1.446–3.030 <0.001
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AC, adenocarcinoma; CI, confidence interval; HR, hazard ratio; SCC, squamous-cell carcinoma.

Discussion

In this study, we found that SFRP1 expression significantly correlated with TNM stage and tumor diameter, and PRKCB expression significantly correlated with the TNM stage of the tumor. The survival analysis showed that patients with low SFRP1 and PRKCB expression had a poor clinical prognosis, and the worst prognosis was observed in patients who were SFRP1(−)/PRKCB(−). The multivariate analysis showed that SFRP1 and PRKCB expression had an independent prognostic value in patients with NSCLC. The results suggest that SFRP1 and PRKCB are potential clinical biomarkers for NSCLC.

The classical Wnt pathway plays a crucial role in embryonic development and tumorigenesis. Abnormal activation of this pathway can cause growth and developmental defects and is related to tumorigenesis. As a member of the SFRP family, SFRP1 contains a characteristic cysteine-rich region, which is homologous to the cysteine-rich region of the frizzled protein family of Wnt. Therefore, SFRP1 can also bind to Wnt via the cysteine-rich region to block its signal transduction (Yu et al., 2009). Indeed, inactivation of SFRP1 results in the activation of oncogenic Wnt signaling pathway in esophageal squamous cell carcinoma. It has been identified as a tumor suppressor in esophageal squamous cell carcinoma (Chen et al., 2022; Zhou et al., 2023). The tumor suppression function of SFRP1 has also been supported by the findings that gene silencing caused by methylation of the four members of this family weakens the inhibitory effect of SFRP on the Wnt pathway, leads to an abnormal activation of the pathway, and causes the occurrence and development of various tumors (Suzuki et al., 2002; Chung et al., 2009; Valencia et al., 2009; Mo et al., 2018; Baharudin et al., 2020; Rueda-Carrasco et al., 2021). In NSCLC, SFRP1 downregulation promotes cancer stem cell-like property and epithelial–mesenchymal transition, ultimately functions as a metastasis promoter (Ren et al., 2013; Taguchi et al., 2016; Yu et al., 2022). However, the prognostic role of SFRP1 in NSCLC remains unknown. Here, we found that SFRP1 expression significantly correlated with TNM stage and tumor diameter. The survival analysis showed that patients with low SFRP1 expression had a poor clinical prognosis, and the worst prognosis was observed in patients who were SFRP1(−). The multivariate analysis showed that SFRP1 expression had an independent prognostic value in patients with NSCLC.

PRKCB is a member of the protein kinase C (PRKC) family of enzymes, which are involved in signal transduction pathways. Previous studies have shown that PRKCB plays a role in cell survival and apoptosis (Roffey et al., 2009; Bononi et al., 2011). Methylation of the PRKCB promoter is common in adenocarcinomas, and this may lead to the dysregulation of PRKCB expression via the Wnt signaling pathway (Li et al., 2016; Wang et al., 2022). Liu et al. analyzed the clinical outcome of 111 patients with NSCLC and found it to be a favorable predictor of NSCLC risk (Liu et al., 2017). Consistently, we also found that PRKCB expression significantly correlated with the TNM stage of the tumor. The survival analysis showed that patients with low PRKCB expression had a poor clinical prognosis, and the worst prognosis was observed in patients who were PRKCB(−). The multivariate analysis showed that PRKCB expression had an independent prognostic value in patients with NSCLC.

Our study showed that SFRP1 and PRKCB expression had significant effects on the prognosis of patients with NSCLC. In both univariate and multivariate analyses, low SFRP1 and PRKCB expression was observed to be an independent prognostic factor for poor OS. Our data indicate that SFRP1 and PRKCB are potential therapeutic targets for NSCLC. This study has some limitations. First, this is a retrospective evaluation of a limited number of patients. Second, immunohistochemical staining was the only validated experiment method in this study; other methods should be used.

Acknowledgements

This research was supported by the Public Welfare Application Research Project of Huzhou Science and Technology, Zhejiang Province (No. 2019GY59).LSL designed the study, conducted immunohistochemical analysis, collected data, helped with statistical analyses, and wrote the manuscript. SPT and LSL conceptualized the study, evaluated immunohistochemical slices, and participated in data analysis and manuscript drafting. LSL performed statistical analysis and wrote the manuscript. HGQ and LSL reviewed the data and contributed to manuscript writing. All authors read and approved the final version of the manuscript.

Conflicts of interest

There are no conflicts of interest.

Footnotes

*

GuoQiang Hu, Juan Du and Bin Wang are the co-first authors.

References

  1. Baharudin R, Tieng FYF, Lee LH, Ab Mutalib NS. (2020). Epigenetics of SFRP1: the dual roles in human cancers. Cancers (Basel) 12:445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bononi A, Agnoletto C, de Marchi E, Marchi S, Patergnani S, Bonora M, et al. (2011). Protein kinases and phosphatases in the control of cell fate. Enzyme Res 2011:329098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bovolenta P, Esteve P, Ruiz JM, Cisneros E, Lopez-Rios J. (2008). Beyond Wnt inhibition: New functions of secreted frizzled-related proteins in development and disease. J Cell Sci 121:737–746. [DOI] [PubMed] [Google Scholar]
  4. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68:394–424. [DOI] [PubMed] [Google Scholar]
  5. Chen C, Zhang Y, Liu Y, Hang L, Yang J. (2022). Expression of tumor suppressor SFRP1 predicts biological behaviors and prognosis: a potential target for oral squamous cell carcinoma. Biomolecules 12:1034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chung MT, Lai HC, Sytwu HK, Yan MD, Shih YL, Chang CC, et al. (2009). SFRP1 and SFRP2 suppress the transformation and invasion abilities of cervical cancer cells through Wnt signal pathway. Gynecol Oncol 112:646–653. [DOI] [PubMed] [Google Scholar]
  7. Imyanitov EN, Iyevleva AG, Levchenko EV. (2021). Molecular testing and targeted therapy for non-small cell lung cancer: current status and perspectives. Crit Rev Oncol Hematol 157:103194. [DOI] [PubMed] [Google Scholar]
  8. Kawano Y, Kypta R. (2003). Secreted antagonists of the Wnt signalling pathway. J Cell Sci 116:2627–2634. [DOI] [PubMed] [Google Scholar]
  9. Krishnamurthy N, Kurzrock R. (2018). Targeting the Wnt/beta-catenin pathway in cancer: update on effectors and inhibitors. Cancer Treat Rev 62:50–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Lee E, Kazerooni EA. (2022). Lung cancer screening. Semin Respir Crit Care Med 43:839–850. [DOI] [PubMed] [Google Scholar]
  11. Lee SH, Chen T, Zhou J, Hofmann J, Bepler G. (2010). Protein kinase C-beta gene variants, pathway activation, and enzastaurin activity in lung cancer. Clin Lung Cancer 11:169–175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Li J, Huang KL, Zhang T, Li H, Zhao J, Wang H. (2016). Pan-cancer methylation and expression profiling of adenocarcinomas revealed epigenetic silencing in the WNT signaling pathway. Neoplasma 63:208–214. [DOI] [PubMed] [Google Scholar]
  13. Liu S, Chen X, Chen R, Wang J, Zhu G, Jiang J, et al. (2017). Diagnostic role of Wnt pathway gene promoter methylation in non small cell lung cancer. Oncotarget 8:36354–36367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Mo S, Su Z, Heng B, Chen WJ, Shi LP, Du XH, et al. (2018). SFRP1 promoter methylation and renal carcinoma risk: a systematic review and meta-analysis. J Nippon Med Sch 85:78–86. [DOI] [PubMed] [Google Scholar]
  15. Pan Y, Sun Y, Liu Z, Zhang C. (2020). miR-192-5p upregulation mediates the suppression of curcumin in human NSCLC cell proliferation, migration and invasion by targeting c-Myc and inactivating the Wnt/β-catenin signaling pathway. Mol Med Rep 22:1594–1604. [DOI] [PubMed] [Google Scholar]
  16. Qi C, Sun SW, Xiong XZ. (2022). From COPD to lung cancer: mechanisms linking, diagnosis, treatment, and prognosis. Int J Chron Obstruct Pulmon Dis 17:2603–2621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Ren J, Wang R, Huang G, Song H, Chen Y, Chen L. (2013). sFRP1 inhibits epithelial-mesenchymal transition in A549 human lung adenocarcinoma cell line. Cancer Biother Radiopharm 28:565–571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Roffey J, Rosse C, Linch M, Hibbert A, McDonald NQ, Parker PJ. (2009). Protein kinase C intervention: the state of play. Curr Opin Cell Biol 21:268–279. [DOI] [PubMed] [Google Scholar]
  19. Rueda-Carrasco J, Martin-Bermejo MJ, Pereyra G, Mateo MI, Borroto A, Brosseron F, et al. (2021). SFRP1 modulates astrocyte-to-microglia crosstalk in acute and chronic neuroinflammation. EMBO Rep 22:e51696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Surana R, Sikka S, Cai W, Shin EM, Warrier SR, Tan HJG, et al. (2014). Secreted frizzled related proteins: implications in cancers. Biochim Biophys Acta 1845:53–65. [DOI] [PubMed] [Google Scholar]
  21. Suzuki H, Gabrielson E, Chen W, Anbazhagan R, van Engeland M, Weijenberg MP, et al. (2002). A genomic screen for genes upregulated by demethylation and histone deacetylase inhibition in human colorectal cancer. Nat Genet 31:141–149. [DOI] [PubMed] [Google Scholar]
  22. Taguchi YH, Iwadate M, Umeyama H. (2016). SFRP1 is a possible candidate for epigenetic therapy in non-small cell lung cancer. BMC Med Genomics 9:28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Tang Q, Zhao H, Yang B, Li L, Shi Q, Jiang C, et al. (2017). WIF-1 gene inhibition and Wnt signal transduction pathway activation in NSCLC tumorigenesis. Oncol Lett 13:1183–1188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Valencia A, Román-Gómez J, Cervera J, Such E, Barragán E, Bolufer P, et al. (2009). Wnt signaling pathway is epigenetically regulated by methylation of Wnt antagonists in acute myeloid leukemia. Leukemia 23:1658–1666. [DOI] [PubMed] [Google Scholar]
  25. Wang R, Liu J, Li K, Yang G, Chen S, Wu J, et al. (2021). An SETD1A/Wnt/β-catenin feedback loop promotes NSCLC development. J Exp Clin Cancer Res 40:318. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Wang JJ, Shi MQ, Zhang HJ, Zhou H, Huang ZH, Zhou YL, et al. (2022). PRKCB is relevant to prognosis of lung adenocarcinoma through methylation and immune infiltration. Thorac Cancer 13:1837–1849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Yu C, Chen K, Zheng H, Guo X, Jia W, Li M, et al. (2009). Overexpression of astrocyte elevated gene-1 (AEG-1) is associated with esophageal squamous cell carcinoma (ESCC) progression and pathogenesis. Carcinogenesis 30:894–901. [DOI] [PubMed] [Google Scholar]
  28. Yu J, Ge Z, Chen S, Li S, Zhang X, Hu J, et al. (2022). miR-26a-5p suppresses Wnt/ β-catenin signaling pathway by inhibiting DNMT3A-mediated SFRP1 methylation and inhibits cancer stem cell-like properties of NSCLC. Dis Markers 2022:7926483. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Zhou M, Yu S, Liu Y, Shu S, Xu Y, Liu M, et al. (2023). H3K27me3 inactivates SFRP1 to promote cell proliferation via Wnt/β-catenin signaling pathway in esophageal squamous cell carcinoma. Dig Dis Sci 68:2463–2473. [DOI] [PubMed] [Google Scholar]

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