Sage Journals: Discover world-class research

Abstract

Overall survival of non-small cell lung cancer (NSCLC) patients remains disappointingly low. The estrogen receptor (ER) was considered a promising therapeutic target for NSCLC. Numerous studies have linked expression of ERβ to lung cancer outcome. However, results are conflicting regarding the association of ERβ with surviving lung cancer. The aim of this meta-analysis was to evaluate the prognostic aspect of ERβ expression on survival among NSCLC patients. We performed a final analysis of prognostic value of overexpression ERβ on 3500 patients from 18 evaluable studies (from January 1, 2000 to May 1, 2021). The reference category is specified as low ERβ expression levels. Summarized hazard ratios were calculated. Our study showed that the pooled hazard ratios of ERβ overexpression for overall survival in NSCLC was 0.81 (95% confidence interval (CI): 0.64–1.02, P = 0.07) by univariate analysis and 1.06 (95% CI: 0.83–1.36, P = 0.63) by multivariate analysis. Pooled hazard ratio by univariate analysis in Asian studies was 0.73 (95%CI: 0.59–0.89, P = 0.002). Pooled hazard ratio by univariate analysis was 0.75 (95% CI: 0.61–0.93, P = 0.009) from seven studies reported for nuclear ERβ. No significant results were found in subgroups by multivariate analysis. No significant results were found in studies outside Asia or in studies reported for cytoplasmic ERβ. Our results suggested that expression of ERβ might not be a direct prognostic factor for NSCLC patients. More detailed prospective studies are needed to identify direct prognostic factors in these patients.

Keywords

Estrogen receptor beta overall survival non-small cell lung cancer

Introduction

Lung cancer is the leading cause of cancer-related deaths among males and the second leading cause among females worldwide.^1,2 Modern advances in genomics allow development of therapies that target oncogenic driver mutations or translocations in genes such as EGFR and ALK.³ More recently, immune checkpoint inhibitors have shown efficacy in the metastatic and locally advanced settings.⁴ Small molecule tyrosine kinase inhibitors and immunotherapy have brought very good survival benefits in some patients. However, the overall survival (OS) rate of non-small cell lung cancer (NSCLC) is still very low, especially in metastatic NSCLC.⁵ The estrogen receptor (ER) is another promising target.⁶ Many studies have demonstrated that estrogens and estrogen signaling play significant roles not only in normal lung development but also in lung cancer pathophysiology.^7,8 Cell lines derived from lung tumors of both men and women express ERs and respond to estrogens. Estrogen can be synthesized in the lung by the enzyme aromatase (CYP19A1). Aromatase present in NSCLC cells and tumor tissues is functional. Estrogens are known to stimulate NSCLC cell proliferation, whereas the antiestrogen fulvestrant inhibits this effect.⁹ Cellular responses to estrogen and its analogues are mediated by two distinct receptors, ERα and ERβ. In lung cancer cells, ERβ is sufficient to induce the full-range of estrogenic responses when no detectable full-length ERα protein is present.¹⁰ In addition, ERβ appears to be the predominant form in lung cancer in the literature.^11,13

Consequently, numerous studies have linked ERβ expression to lung cancer outcome.^9,10, Some studies suggested that high expression of ERβ was unfavorable to the prognosis of lung cancer patients.^19,20,24 However, some studies found that high expression of ERβ was beneficial for lung cancer survival.^21,23 There were even two meta-analyses of these studies with opposite conclusions: Luo et al.²⁶ suggested high expression of ERβ was significantly associated with improved OS in NSCLC patients based on univariate analysis, while Ma et al.²⁷ concluded that ERβ overexpression was not associated with NSCLC prognosis based on univariate analysis. Based on the discordant results, we conducted this meta-analysis in order to evaluate the prognostic impact of ERβ expression on survival among NSCLC patients.

Luo et al.²⁶ published their meta-analysis in 2015, which included 13 studies, including 3 Chinese studies. Ma et al.²⁷ published the meta-analysis in 2016, which included 11 studies. Until now, at least 4 new studies have been published.^25,28–30 Therefore, we considered our systematic review to be an extension and update of the meta-analyses by Luo et al.²⁶ and Ma et al.²⁷

Materials and methods

We conducted the systematic review of cohort studies on the effect of ERβ expression on survival among NSCLC patients based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) statements.^31,32

Literature search

We performed extensive literature searches in 15 databases: PubMed, Web of Science, EMBASE, Cochrane Library, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL, Open-Grey, metaRegister of Controlled Trials, Clinical-Trials.gov, WHO Clinical Trials Database, WanFangData, CQVIP, COMPENDEX, and China National Knowledge Infrastructure. We searched the following keywords in the above databases: (“estrogen receptor” OR “ER” OR “ERβ” OR “estrogen receptor beta”) AND (“non-small cell lung cancer” OR “NSCLC” OR “lung cancer” OR “lung carcinoma” OR “carcinoma of lung”) AND (outcome OR survival OR prognosis OR OS). We included articles published from January 1, 2000 to May 1, 2021. We searched the citations and references of the identified literature for more potentially relevant studies to ensure literature saturation. Since this meta-analysis is an extension and update of Luo et al.²⁶ and Ma et al.,²⁷ we also searched for articles considered by them, to avoid missing any existing literature.

Study selection

We restricted publications to be in either English or Chinese. We searched for observational studies (study design criteria) conducted in NSCLC patients (setting criteria) and studies reporting the OS (outcome criteria) in at least two different ERβ expression levels using comparable methods (design criteria). In order to assess the quality of individual studies and methodological differences between studies, we included only studies that reported ERβ testing and assessment methods. We included primary NSCLC patients and excluded those with other cancers, severe organ dysfunction, or severe infections. Two reviewers independently identified potentially eligible articles by screening all titles and abstracts; in cases of disagreement, a third researcher was involved.

Data extraction and quality assessment

The following data were collected from included studies using a predesigned abstraction form: name of first author, year of publication, country, sample size, average age, sex ratio, pathological type, laboratory methodology, follow-up period, number of people with high ERβ expression, number of smoking people, study year, and univariate analysis hazard ratio (HR) and 95% confidence interval (CI), multivariate analysis HR and 95% CI. Data from each study were collected independently and in duplicate by two reviewers; in cases of disagreement, a third researcher was involved. Two reviewers independently scored the quality of included studies using the Newcastle–Ottawa Scale (NOS).³³ In cases of disagreement, a third researcher was involved.

Statistical methods

The intensity of the relationship between the expression levels of ERβ and OS was described as HR. The reference category was specified as low ERβ expression levels, and an HR greater than 1 implied a greater rate of mortality of high ERβ compared with low ERβ, and vice versa. HR and 95% CI were obtained from published papers or calculated by Kaplan–Meier survival curves using the software Engauge Digitizer Version 4.1 (http://digitizer.sourceforge.net/) and the method previously presented by Parmar et al and used by Zhang et al.^34,35 The pooled HR and corresponding 95% CI were used to assess the prognostic value of ERβ in NSCLC patients. According to the Cochrane Handbook, we supposed a moderate level of heterogeneity between studies for I² values ranging from 30% to 60%.³⁶ If I² was equal or less than 60%, the fixed effects model was used to estimate the pooled HR; if I² exceeded 60% for the pooled analysis, we explored sources of heterogeneity in subgroups of studies and used a random effects model. We used a funnel plot and Egger's test³⁷ to evaluate reports for publication bias. A P-value less than 0.05 was considered statistically significant. Review Manager 5.3³⁸ and STATA 15³⁹ were used to perform statistical analysis.

Results

Study selection and characteristics

A total of 208 articles were retrieved from the 15 electronic databases according to our defined search terms. Then, 87 duplicates were removed. Through careful reading the abstracts, 49 studies that focused on the association between ERβ expression and NSCLC survival were included in our full-text review process. After reading the full-text studies, 31 papers had to be excluded because the data were not extractable or could not provide enough information about OS. As a result, 18 eligible studies comprising 3500 patients were included in this meta-analysis.^13,^19,^25,^29,^40–53 The process of literature screening is shown in the PRISMA Flow Diagram. (Figure 1) Among all the included studies, the individual characteristics and HRs are summarized in Table 1. The quality of studies with a NOS score of 7 or more was considered high. All of the included studies had NOS scores of 8–9 (as shown in Table 2 in the supplementary file).

Figure 1.

PRISMA flow diagram.

Table 1.

Characteristics of the included studies.

First author	Publish year	Country	ERβ location	Sample size	ERβ over-expression	Age	Gender (male: female)	ADC/SCC/others	Laboratory methodology
Kawai	2005¹³	Japan	nucleus	132	66	67	76/56	102/28/2	IHC
Schwartz	2005⁴²	America	nucleus	278	170	53	64/214	231/13/35	IHC
Wu	2005⁴³	China	nucleus	301	138	63	174/127	194/90/17	IHC
Skov	2008⁴⁴	Denmark	nucleus	104	72	NA	71/33	40/56/8	IHC
Mauro	2010⁴⁵	Argentina	nucleus	58	23	64	40/18	33/18/6	IHC
Karlsson	2012⁴⁶	Sweden	Cytoplasm	68	NA	65.7	32/36	68/0/0	IHC
Mah	2011¹⁹	America	Nucleus or cytoplasm	377	189	65.4	185/192	226/93/58	IHC
Stabile	2011⁴⁷	America	Cytoplasm	183	64	66.78	91/92	103/62/18	IHC
Verma	2012⁴¹	Japan	nucleus	169	148	> 60	103/66	129/36/4	IHC
Verma a	2012⁴⁰	Japan	Cytoplasm	162	62	45–82	98/64	120/38/4	IHC
Navaratnam	2012⁴⁸	Canada	Cytoplasm	79	40	69.2	32/47	NA	IHC
Monica	2012⁴⁹	Italy	nucleus	79	NA	68	79/0	57/34/15	IHC
Jian	2013⁵⁰	China	nucleus	144	75	57.6	49/95	109/0/35	IHC
Liu	2013⁵¹	China	Cytoplasm ERβ2	112	66	55	58/54	NA	IHC
Aresti	2014⁵²	Spain	Nucleus or cytoplasm	96	NA	NA	81/15	41/42/13	RT-PCR/ELISA
He	2015⁵³	China	Nucleus or cytoplasm	46	36	58	31/15	33/13/0	IHC
Cheng	2018²⁹	America and Canada	Nucleus or cytoplasm	813	407	65–74	363/450	200/465/148	IHC
Enwere	2020²⁵	Canada	nucleus	299	34	65	150/149	162/94/43	IHC
First author	follow up period (months)	cut-off value	univariate analysis HR	95%CI	multivariate analysis HR	95%CI	smoking patients Y/N	study year
Kawai¹³	60	≥5%	1.49	0.76–2.93	1.9	1.1–3.4	71/61	1991–1995
Schwartz⁴²	50	≥10%	1.01	0.65–1.57	NA	NA	247/30	1990–2004
Wu⁴³	180	≥50%	0.672	0.478–0.945	0.719	0.504–1.026	131/159	1990–0001
Skova⁴⁴	180	≥10%	NA	NA	0.97	0.76–1.26	NA	1989 to 1992
Mauro⁴⁵	120	≥5%	0.57	0.13–0.8	NA	NA	41/16	1997–2004
Karlsson⁴⁶	60	>30%	0.47	0.22–1.01	NA	NA	42/13	1990–1995
Mah¹⁹	120	>3 score	1.6	0.84–2.09	2.17	1.46–3.21	330/47	NA
Stabile⁴⁷	55	>7 score	1.05	1.0–1.1	1.67	1.14–2.14	157/26	1992–2006
Verma⁴¹	140	≥10%	0.721	0.3–0.98	NA	NA	NA	1993–2003
Verma a⁴⁰	140	≥10%	1.16	0.75–1.82	NA	NA	NA	NA
Navaratnam⁴⁸	36	>60 score (median)	0.41	0.21–0.80	0.4	0.20–0.79	NA	1999
Monica⁴⁹	30	NA	1.75	1.00–3.03	NA	NA	NA	2008 --2010
Jian⁵⁰	50	≥10%	0.58	0.35–0.96	0.819	0.43–1.56	0/144	2009–2010
Liu⁵¹	40	>3 score	0.19	0.04–0.97	NA	NA	52/60	2008–2011
Aresti⁵²	NA	NA	0.7	0.38–1.29	NA	NA	82/14	NA
He⁵³	24	NA	NA	NA	0.396	0.167–0.939	23/23	2010–2012
Cheng²⁹	62	Median H-score	NA	NA	1.59	1.08–2.33	606/207	2005–2011
Enwere²⁵	NA	Cut points were obtained using X-Tile	NA	NA	1.16	0.77–1.76	258/41	2003–2006

ADC: adenocarcinoma; ELISA: enzyme-linked immunosorbent assay; ERβ: estrogen receptor beta; IHC: immunohistochemistry; RT-PCR: reverse transcription-polymerase chain reaction; SCC: squamous cell carcinoma.

Table 2.

NOS score of included studies.

Author	Year published	Selection				Comparability	Outcome			TOTAL
Author	Year published	Representativeness of the exposed cohort	Selection of the non-exposed cohort	Ascertainment of exposure	Demonstration that outcome of interest was not present at start of study	Comparability of cohorts on the basis of the design or analysis	Assessment of outcome	Was follow-up long enough for outcomes to occur?	Adequacy of follow-up of cohorts	TOTAL
Kawai	2005¹³	1	1	1	1	2	1	1	1	9
Schwartz	2005⁴²	1	1	1	1	2	1	1	1	9
Wu	2005⁴³	1	1	1	1	2	1	1	1	9
Skova	2008⁴⁴	1	1	1	1	2	1	1	1	9
Mauro	2010⁴⁵	1	1	1	1	1	1	1	1	8
Karlsson	2012⁴⁶	1	1	1	1	1	1	1	1	8
Mah	2011¹⁹	1	1	1	1	2	1	1	1	9
Stabile	2011⁴⁷	1	1	1	1	2	1	1	1	9
Verma	2012⁴¹	1	1	1	1	1	1	1	1	8
Verma a	2012⁴⁰	1	1	1	1	1	1	1	1	8
Navaratnam	2012⁴⁸	1	1	1	1	2	1	1	1	9
Monica	2012⁴⁹	1	1	1	1	1	1	1	1	8
Jian	2013⁵⁰	1	1	1	1	2	1	1	1	9
Liu	2013⁵¹	1	1	1	1	1	1	1	1	8
Aresti	2014⁵²	1	1	1	1	1	1	1	1	8
He	2015⁵³	1	1	1	1	2	1	1	1	9
Cheng	2018²⁹	1	1	1	1	2	1	1	1	9
Enwere	2020²⁵	1	1	1	1	2	1	1	1	9

NOS: Newcastle–Ottawa Scale.

Meta-analysis

Of the 18 studies, 14 (including 2238 patients)^{13,19,40–43}^45–52 were included in a univariate meta-analysis and 10 (including 2478 patients)^{13,19,25,29,43,44,47,48,50,53} were included in a multivariate meta-analysis. Among the 10 studies that conducted the multivariate analysis, age, sex, and stage were taken as covariables in 9 studies,^{13,19,25,29,43,44,47,48,53} and smoking status and pathological type were taken as covariables in 8 studies.^{13,19,25,29,43,,47,53} Univariate and multivariate analyses showed no significant relationship between ERβ expression and NSCLC OS, with a pooled HR of 0.81 (95% CI: 0.64–1.02, P = 0.07, I² = 69%, random-effect) by univariate analysis and a pooled HR of 1.06 (95% CI: 0.83–1.36, P = 0.63, I² = 77%, random-effect) by multivariate analysis. (Figure 2(a) and (b))

Figure 2.

(a) Univariate meta-analysis of 14 studies (2238 patients). (b) Multivariate meta-analysis of 10 studies (2478 patients).

Subgroup analysis

After reading all the included literature, we found that the effect of ERβ on lung cancer prognosis was different among different races or different ERβ distribution locations, so we performed a subgroup analysis.

Asian patients

To assess the factor of race, we conducted a subgroup analysis for Asian patients. Six Asian studies (including 1020 patients) reported univariate analysis results—three from China and three from Japan—and the pooled HR was 0.73 (95% CI: 0.59–0.89, P = 0.002, I² = 37%, fixed-effect) (Figure 3(a)).

Figure 3.

(a) Subgroup analysis for Asian patients (six studies including 1020 patients for univariate analysis). (b) Subgroup analysis for Asian patients (four studies including 623 patients for multivariate analysis).

Four Asian studies (including 623 patients) reported multivariate analysis results—three from China and one from Japan—and the pooled HR was 0.85 (95% CI: 0.48–1.50, P = 0.57, I² = 74%, random-effect) (Figure 3(b)). There was no significant result for studies out of Asia.

Nuclear ERβ

To assess the factor of ERβ location, we conducted a subgroup analysis. 7 studies (including 1161 patients) conducted a univariate analysis for the effect of nuclear ERβ on lung cancer prognosis, and the pooled HR was 0.75 (95% CI: 0.61–0.93, P = 0.009, I² = 46%, fixed-effect) (Figure 4(a)). Five studies (including 980 patients) conducted a multivariate analysis for the effect of nuclear ERβ on lung cancer prognosis, and the pooled HR was 1.03 (95%CI: 0.80—1.32, P = 0.84, I² = 61%, random-effect) (Figure 4(b)). There were no significant results for cytoplasmic ERβ.

Figure 4.

(a) Subgroup analysis for nuclear ERβ (seven studies including 1161 patients for univariate analysis). (b) Subgroup analysis for nuclear ERβ (five studies including 980 patients for multivariate analysis).

Publication bias

The 14 studies for the univariate meta-analysis yielded the funnel plot in Figure 5(a) and an Egger's test score of P = 0.138, while the 10 studies for the multivariate meta-analysis yielded the funnel plot in Figure 5(b) and an Egger's test score of P = 0.202. Publication bias was within acceptable limits.

Figure 5.

(a) Funnel plot of 14 studies included in univariate analysis. (b) Funnel plot of 10 studies included in multivariate analysis.

Sensitivity analysis

Sensitivity analysis was performed for the 18 included studies to investigate the effect of every study on the overall meta-analysis by omitting one study each time. The omission of any study made no significant difference, and I² was greater than 60%.

Discussion

We performed extensive literature searches in 15 databases from January 1, 2000 to May 1, 2021, and included 18 cohort studies incorporating 3500 patients to evaluate the relationship between ERβ expression and NSCLC OS. ERβ expression failed to yield a significant association with NSCLC OS by univariate analysis or multivariate analysis. Then we conducted a subgroup analysis of Asians, and the pooled HR of univariate analysis was 0.73 (P = 0.002). Inspired by Verma et al.,^40,41 who obtained different results from his experiment on nuclear ERβ and cytoplasmic ERβ, we further analyzed the subgroup of nuclear ERβ, and the pooled HR of univariate analysis was 0.75 (P = 0.009). However, in multivariate analyses, neither ethnicity nor ERβ position was an important independent factor affecting the OS of NSCLC. Our conclusion was in accordance with Ma et al.,²⁷ who suggested ERβ that overexpression indicated no relationship of prognosis for patients with NSCLC. We included seven more studies than Ma et al. and performed both univariate and multivariate analyses to estimate the HR and 95% CI, while Ma et al.²⁷ only performed univariate analyses.

Monica et al.⁴⁹ suggested ERβ expression was significantly higher in patients with metastatic disease compared with all other disease stages (P = 0.02). Enwere et al.²⁵ also claimed that higher ERβ expression levels in stage IV disease were apparent in the tumor as well as the surrounding stroma, and in both nuclei and cytoplasmic compartments. However, most studies—such as Schwartz et al.⁴² and Skov et al.⁴⁴—reported that there was no statistically significant correlation between ERβ positivity and age, gender, stage, or histology. Researchers have conflicting conclusions on whether tumor stage has an effect on the prognosis of NSCLC, and the literature was insufficient for meta-analysis.

Whether the effect of ERβ expression level on NSCLC prognosis is different for male and female patients remains controversial. Schwartz et al.⁴² and Skov et al.⁴⁴ found men with ERβ-positive tumors had a significantly reduced mortality compared to men with ERβ-negative tumors, while women with ERβ-negative tumors had a non-significant change in mortality compared with women with Erβ-positive tumors. However, other researchers—such as Enwere et al.²⁵—found no differences in ERβ expression between male and female patients. Unfortunately, there were too little data in the literature to draw definitive conclusions.

The expression of ERβ may be closely related to some clinical characteristics, such as gender, stage, race, etc. More observational clinical studies are needed to confirm these possibly-related factors, to provide accurate prognostic prediction for patients with NSCLC, and to then explore corresponding treatment methods.

There were some limitations to our study. First, the presence of heterogeneity could be explained to a great extent by the different population selected, such as sex ratio, age composition, tumor stage, and histological subtypes, which were different in the 18 selected studies. Second, we searched only English and Chinese literature, and thus introduced somewhat of a selection bias. Third, reporting bias existed. For example, Monica et al.⁴⁹ reported only significant results for men but not for women, and we didn't have access to the raw data. Another potential source of bias was related to the method used to extrapolate the HR, which was extracted from the data included in the article directly or calculated from the survival curves. Finally, the heterogeneity could be explained by the differences in the laboratory tests of ERβ, such as the different antibodies used for staining and the different criteria for defining stain positivity.

Conclusion

Our results suggested that the expression of ERβ might not be a direct prognostic factor for NSCLC patients. Although high ERβ expression in nuclear and Asian subgroups was significantly associated with improved OS in univariate analysis, it was not in multivariate analysis. More detailed prospective studies are needed to identify direct prognostic factors in NSCLC patients.

Footnotes

Acknowledgments

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

Project development: Yuguo Liu and Hui Li. Data collection or management: Haisheng Chen, Jing Shi, and Qing Fan. Data analysis: Hui Li, Zhongxia Zhou, Xiufeng Tang. Manuscript writing/editing: Zhongxia Zhou, Xiufeng Tang, and Yanhong Wang.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China, (grant number 82104051).

ORCID iD

Hui Li

Supplemental material

Supplemental material for this article is available online.

References

Novaes

Cataneo

Ruiz Junior

, et al. Lung cancer: histology, staging, treatment and survival. J Bras Pneumol 2008; 34: 595–600.

Mattiuzzi

Lippi

. Current cancer epidemiology. J Epidemiol Glob Health 2019; 4: 217–222.

Aleksakhina

Imyanitov

. Cancer therapy guided by mutation tests: current status and perspectives. Int J Mol Sci 2021; 22: 10931.

Mencoboni

Ceppi

Bruzzone

, et al. Effectiveness and safety of immune checkpoint inhibitors for patients with advanced non-small-cell lung cancer in real-world: review and meta-analysis. Cancers (Basel) 2021; 13: 1388.

Herbst

Morgensztern

Boshoff

. The biology and management of non-small cell lung cancer. Nature 2018; 553: 446–454.

Weinberg

Marquez-Garban

Fishbein

, et al. Aromatase inhibitors in human lung cancer therapy. Cancer Res 2005; 65: 11287–11291.

Stabile

Rothstein

Cunningham

, et al. Prevention of tobacco carcinogen-induced lung cancer in female mice using antiestrogens. Carcinogenesis 2012; 33: 2181–2189.

Siegfried

Lin

Dacic

, et al. Prediction of NSCLC survival with the PAM50 breast cancer signature. Int J Radiat Oncol Biol Phys 2014; 90: S71–S72.

Stabile

Davis

Gubish

, et al. Human non-small cell lung tumors and cells derived from normal lung express both estrogen receptor alpha and beta and show biological responses to estrogen. Cancer Res 2002; 62: 2141–2150.

10.

Hershberger

Stabile

Kanterewicz

, et al. Estrogen receptor beta (ERbeta) subtype-specific ligands increase transcription, p44/p42 mitogen activated protein kinase (MAPK) activation and growth in human non-small cell lung cancer cells. J Steroid Biochem Mol Biol 2009; 116: 102–109.

11.

Zhang

Liu

Farkas

, et al. Estrogen receptor beta functions through nongenomic mechanisms in lung cancer cells. Mol Endocrinol 2009; 23: 146–156.

12.

Stabile

Siegfried

JM.

Estrogen receptor pathways in lung cancer. Curr Oncol Rep 2004; 6: 259–267.

13.

Kawai

Ishii

Washiya

, et al. Estrogen receptor alpha and beta are prognostic factors in non-small cell lung cancer. Clin Cancer Res 2005; 11: 5084–5089.

14.

Chlebowski

Schwartz

Wakelee

, et al. Oestrogen plus progestin and lung cancer in postmenopausal women (women’s health initiative trial): a post-hoc analysis of a randomised controlled trial. Lancet 2009; 374: 1243–1251.

15.

Omoto

Kobayashi

Nishida

, et al. Expression, function, and clinical implications of the estrogen receptor beta in human lung cancers. Biochem Biophys Res Commun 2001; 285: 340–347.

16.

Ganti

Sahmoun

Panwalkar

, et al. Hormone replacement therapy is associated with decreased survival in women with lung cancer. J Clin Oncol 2006; 24: 59–63.

17.

Niikawa

Suzuki

Miki

, et al. Intratumoral estrogens and estrogen receptors in human non-small cell lung carcinoma. Clin Cancer Res 2008; 14: 4417–4426.

18.

Zhang

Yanamala

Lathrop

, et al. Ligand-independent antiapoptotic function of estrogen receptor-beta in lung cancer cells. Mol Endocrinol 2010; 24: 1737–1747.

19.

Mah

Marquez

Alavi

, et al. Expression levels of estrogen receptor beta in conjunction with aromatase predict survival in non-small cell lung cancer. Lung Cancer 2011; 74: 318–325.

20.

Slatore

Chien

, et al. Lung cancer and hormone replacement therapy: association in the vitamins and lifestyle study. J Clin Oncol 2010; 28: 1540–1546.

21.

Schabath

Vassilopoulou-Sellin

, et al. Hormone replacement therapy and lung cancer risk: a case-control analysis. Clin Cancer Res 2004; 10: 113–123.

22.

Schwartz

Wenzlaff

Prysak

, et al. Reproductive factors, hormone use, estrogen receptor expression and risk of non-small-cell lung cancer in women. J Clin Oncol 2007; 25: 5785–5792.

23.

Huang

Carloss

Wyatt

, et al. Hormone replacement therapy and survival in lung cancer in postmenopausal women in a rural population. Cancer 2009; 115: 4167–4175.

24.

Liu

Inoue

Sobue

, et al. Reproductive factors, hormone use and the risk of lung cancer among middle-aged never-smoking Japanese women: a large-scale population-based cohort study. Int J Cancer 2005; 117: 662–666.

25.

Enwere

Dean

, et al. The prevalence and prognostic significance of estrogen receptor beta expression in non-small cell lung cancer. Transl Lung Cancer Res 2020; 9: 496–506.

26.

Luo

Jiang

, et al. Overexpression of estrogen receptor beta is a prognostic marker in non-small cell lung cancer: a meta-analysis. Int J Clin Exp Med 2015; 8: 8686–8697.

27.

Zhan

Liu

, et al. Prognostic value of the expression of estrogen receptor beta in patients with non-small cell lung cancer: a meta-analysis. Transl Lung Cancer Res 2016; 5: 202–207.

28.

Liu

Nie

Lei

, et al. The expression of ER beta 2, bcl-xl and bax in non-small cell lung cancer and associated with prognosis. Int J Clin Exp Pathol 2017; 10: 10040–10046.

29.

Cheng

T-YD

Darke

Redman

, et al. Smoking, sex, and non-small cell lung cancer: steroid hormone receptors in tumor tissue (S0424). J Natl Cancer Inst 2018; 110: 734–742.

30.

Ding

, et al. Estrogen receptor beta promotes the vasculogenic mimicry (VM) and cell invasion via altering the lncRNA-MALAT1/miR-145–5p/NEDD9 signals in lung cancer. Oncogene 2019; 38: 1225–1238.

31.

Stroup

Berlin

Morton

, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. Jama 2000; 283: 2008–2012.

32.

Moher

Altman

Liberati

, et al. PRISMA Statement. Epidemiology 2011; 22: 128; author reply 128.

33.

Wells GA

O’Connell

Peterson

, et al. The Newcastle-Ottawa scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp 2014

34.

Parmar

Torri

, Stewart L: extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 1998; 17: 2815–2834.

35.

Zhang

Wang

Zhou

, et al. The prognostic value of MGMT promoter methylation in glioblastoma multiforme: a meta-analysis. Fam Cancer 2013; 12: 449–458.

36.

Higgins

JPT

. Chapter 9.5.2 Identifying and measuring heterogeneity. Green

(ed.) Cochrane Handbook for Systematic Reviews of Interventions. Version 5.1.0. The Cochrane Collaboration.2011.Available from www.cochrane-handbook.org..

37.

Egger

Davey Smith

Schneider

, et al.

Bias in meta-analysis detected by a simple, graphical test.

Br Med J 1997; 315: 629–634.

38.

Higgins

JPT

Thomas

Chandler

, et al. Cochrane handbook for systematic reviews of interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.

39.

Wang

Mou

Zhai

, et al. Application of STATA software to test heterogeneity in meta-analysis method. Zhonghua Liu Xing Bing Xue Za Zhi 2008; 29: 726–729.

40.

Verma

Miki

Abe

, et al. Cytoplasmic estrogen receptor beta as a potential marker in human non-small cell lung carcinoma. Expert Opin Ther Targets 2012; 16: S91–S102.

41.

Verma

Miki

Abe

, et al. Co-expression of estrogen receptor beta and aromatase in Japanese lung cancer patients: gender-dependent clinical outcome. Life Sci 2012; 91: 800–808.

42.

Schwartz

A G

Prysak

G M

Murphy

. Nuclear estrogen receptor beta in lung cancer: expression and survival differences by sex. Clin Cancer Res 2005; 11: 7280–7287.

43.

Chang

Shih

, et al. The significance of estrogen receptor beta in 301 surgically treated non-small cell lung cancers. J Thorac Cardiovasc Surg 2005; 130: 979–986.

44.

Skov

Fischer

, Pappot H. Oestrogen receptor beta over expression in males with non-small cell lung cancer is associated with better survival. Lung Cancer 2008; 59: 88–94.

45.

Mauro

Dalurzo

Carlini

, et al. Estrogen receptor beta and epidermal growth factor receptor as early-stage prognostic biomarkers of non-small cell lung cancer. Oncol Rep 2010; 24: 1331–1338.

46.

Karlsson

Helenius

Fernandes

, et al. Oestrogen receptor beta in NSCLC - prevalence, proliferative influence, prognostic impact and smoking. Apmis 2012; 120: 451–458.

47.

Stabile

Dacic

Land

, et al. Combined analysis of estrogen receptor beta-1 and progesterone receptor expression identifies lung cancer patients with poor outcome. Clin Cancer Res 2011; 17: 154–164.

48.

Navaratnam

Skliris

Qing

, et al. Differential role of estrogen receptor beta in early versus metastatic non-small cell lung cancer. Hormones and Cancer 2012; 3: 93–100.

49.

Monica

Longo

Felice

, et al. Role of hormone receptor expression in patients with advanced-stage lung cancer treated with chemotherapy. Clin Lung Cancer 2012; 13: 416–423.

50.

Jian

Zhu

Shao

, et al. Relationships between survival and expressions of estrogen receptor alpha and beta in non-smoking non- small cell lung cancer patients. China Oncology 2013; 23: 910–916.

51.

Liu

Liao

Tang

, et al. The expression of estrogen receptors beta2, 5 identifies and is associated with prognosis in non-small cell lung cancer. Endocrine 2013; 44: 517–524.

52.

Aresti

Carrera

Iruarrizaga

, et al. Estrogen receptor 1 gene expression and its combination with estrogen receptor 2 or aromatase expression predicts survival in non-small cell lung cancer. PLoS One 2014; 9: e109659.

53.

Y-F

Luo

H-Q

Wang

, et al. Clinical features and prognosis-associated factors of non-small cell lung cancer exhibiting symptoms of bone metastasis at the time of diagnosis. Oncol Lett 2015; 9: 2706–2712.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.01 MB

ERβ overexpression may not be a direct prognostic factor in patients with NSCLC: A meta-analysis

Abstract

Keywords

Introduction

Materials and methods

Literature search

Study selection

Data extraction and quality assessment

Statistical methods

Results

Study selection and characteristics

Meta-analysis

Subgroup analysis

Asian patients

Nuclear ERβ

Publication bias

Sensitivity analysis

Discussion

Conclusion

Footnotes

Acknowledgments

Availability of data and materials

Ethics approval and consent to participate

Consent for publication

Competing interests

Authors’ contributions

Declaration of conflicting interests

Funding

ORCID iD

Supplemental material

References

Supplementary Material