Clinicopathological significance of oestrogen receptor expression in non-small cell lung cancer

Chen, Xiangqi; Zheng, Li-Xian; Li, Zhiying; Lin, Tong

doi:10.1177/0300060516666229

Cited by 17 publications

(10 citation statements)

References 15 publications

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“…In the present study, there were no significant associations between sex and the expression of ERα, or nuclear or cytoplasmic ERβ. ERβ expression has been demonstrated to be positively correlated with the degree of lung cancer differentiation ( 32 ), and a positive association between nuclear ERβ expression and tumor differentiation was also observed in the present study. This suggests that ERβ expression may, to a certain extent, reflect the degree of malignancy and therefore may be used as a predictor of prognosis.…”

Section: Discussionsupporting

confidence: 86%

Cytoplasmic expression of estrogen receptor β may predict poor outcome of EGFR‑TKI therapy in metastatic lung adenocarcinoma

Ding

Tang

et al. 2018

Oncol Lett

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There is growing evidence that estrogen receptors (ER) are expressed in lung cancer cells, and are able to interact with the epidermal growth factor receptor (EGFR) signaling pathway. However, data on the association between cytoplasmic ER expression and the response to EGFR-tyrosine kinase inhibitors (TKI) treatment are limited. The aim of the present study was to investigate the associations between ERα/ERβ expression and EGFR mutational status and response to TKI treatment in metastatic lung adenocarcinoma. A retrospective study of 126 consecutive patients with lung adenocarcinoma who were diagnosed with stage IV disease and had received EGFR-TKI treatment was conducted. ER expression was detected by immunohistochemistry. EGFR and GTPase KRas (KRAS) mutational statuses were evaluated by denaturing high performance liquid chromatography and PCR-restriction fragment length polymorphism, respectively. In the overall cohort of 126 lung adenocarcinoma samples analyzed, ERα expression in the nucleus of tumor cells was identified in 17 (18.9%) patients, whereas ERβ expression was identified in the nucleus (22/126, 17.5%) and cytoplasm (17/126, 13.5%). The nuclear expression of ERβ was positively associated with the degree of tumor differentiation (P=0.010). EGFR-sensitizing mutations were significantly associated with improved objective response rates (ORR), disease control rates (DCR), median progression-free survival (mPFS) and median overall survival (mOS) (P<0.001; P<0.001; P=0.003; and P=0.026, respectively). Patients with cytoplasmic ERβ expression exhibited non-significant poorer ORR, DCR, mPFS and mOS compared with patients without cytoplasmic ERβ expression (P=0.082; P=0.106; P=0.084; and P=0.119, respectively). However, the significant decrease of ORR, DCR and mPFS was observed in patients with coexisting cytoplasmic ERβ expression and EGFR-sensitizing mutations (P=0.030; P=0.009; and P=0.018, respectively) in comparison with the subgroup with EGFR sensitizing mutations but negative expression of cytoplasmic ERβ. A trend towards shorter mOS was also observed in patients with coexisting cytoplasmic ERβ expression and EGFR-sensitizing mutations (P=0.071). No KRAS mutations were identified in patients with cytoplasmic ERβ expression. Subsequent to adjusting for sex, smoking status and EGFR mutation status, the Cox repression analysis indicated that cytoplasmic expression of ERβ was a negative independent predictor for mPFS in the whole patient cohort (HR=1.870; 95% confidence interval 1.058–3.305; P=0.031). Cytoplasmic ERβ expression was negatively correlated with the efficacy of EGFR-TKI treatment for metastatic lung adenocarcinoma, particularly for patients with coexisting cytoplasmic ERβ expression and EGFR-sensitizing mutations. Cytoplasmic ERβ may be a promising marker to predict the outcome of EGFR-TKI treatment.

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Section: Discussionsupporting

confidence: 86%

Cytoplasmic expression of estrogen receptor β may predict poor outcome of EGFR‑TKI therapy in metastatic lung adenocarcinoma

Ding

Tang

et al. 2018

Oncol Lett

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“…No significant difference in the clinicopathological characteristic between the ERβ-positive and ERβ-negative lung adenocarcinoma has been mentioned, except some reported that the ER expression correlated with the tumor differentiation [ 111 ]. Detailed pathologic examination of the ERβ-positive adenocarcinoma may be necessary to show the genotype-phenotype correlations, similar to those found in the ALK-rearranged or the EGFR-mutated adenocarcinoma [ 112 , 113 ].…”

Section: Er As Targets For Lung Cancer Therapy and Relationship Wimentioning

confidence: 99%

Estrogen, Estrogen Receptor and Lung Cancer

Hsu

Chu

Kao

2017

IJMS

159

124

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Estrogen has been postulated as a contributor for lung cancer development and progression. We reviewed the current knowledge about the expression and prognostic implications of the estrogen receptors (ER) in lung cancer, the effect and signaling pathway of estrogen on lung cancer, the hormone replacement therapy and lung cancer risk and survival, the mechanistic relationship between the ER and the epidermal growth factor receptor (EGFR), and the relevant clinical trials combining the ER antagonist and the EGFR antagonist, to investigate the role of estrogen in lung cancer. Estrogen and its receptor have the potential to become a prognosticator and a therapeutic target in lung cancer. On the other hand, tobacco smoking aggravates the effect of estrogen and endocrine disruptive chemicals from the environment targeting ER may well contribute to the lung carcinogenesis. They have gradually become important issues in the course of preventive medicine.

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“… 51 TransPRECISE implicated the hormone receptor pathway in lung cancer, which is another known observation that is being studied for its translational potential. 52 Our sample-specific inference of pathway activity provided robust tumor stratification across model systems that include distinct prognostic information ( Fig 5 ). These robust edges and cross-signaling of pathways across model systems and cancer sites will potentially provide complementary information in terms of disease characterization and therapeutic targets.…”

Section: Discussionmentioning

confidence: 93%

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome

Bhattacharyya

Liu

et al. 2020

JCO Clinical Cancer Informatics

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PURPOSE Personalized network inference on diverse clinical and in vitro model systems across cancer types can be used to delineate specific regulatory mechanisms, uncover drug targets and pathways, and develop individualized predictive models in cancer. METHODS We developed TransPRECISE (personalized cancer-specific integrated network estimation model), a multiscale Bayesian network modeling framework, to analyze the pan-cancer patient and cell line interactome to identify differential and conserved intrapathway activities, to globally assess cell lines as representative models for patients, and to develop drug sensitivity prediction models. We assessed pan-cancer pathway activities for a large cohort of patient samples (> 7,700) from the Cancer Proteome Atlas across ≥ 30 tumor types, a set of 640 cancer cell lines from the MD Anderson Cell Lines Project spanning 16 lineages, and ≥ 250 cell lines’ response to > 400 drugs. RESULTS TransPRECISE captured differential and conserved proteomic network topologies and pathway circuitry between multiple patient and cell line lineages: ovarian and kidney cancers shared high levels of connectivity in the hormone receptor and receptor tyrosine kinase pathways, respectively, between the two model systems. Our tumor stratification approach found distinct clinical subtypes of the patients represented by different sets of cell lines: patients with head and neck tumors were classified into two different subtypes that are represented by head and neck and esophagus cell lines and had different prognostic patterns (456 v 654 days of median overall survival; P = .02). High predictive accuracy was observed for drug sensitivities in cell lines across multiple drugs (median area under the receiver operating characteristic curve > 0.8) using Bayesian additive regression tree models with TransPRECISE pathway scores. CONCLUSION Our study provides a generalizable analytic framework to assess the translational potential of preclinical model systems and to guide pathway-based personalized medical decision making, integrating genomic and molecular data across model systems.

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Clinicopathological significance of oestrogen receptor expression in non-small cell lung cancer

Cited by 17 publications

References 15 publications

Cytoplasmic expression of estrogen receptor β may predict poor outcome of EGFR‑TKI therapy in metastatic lung adenocarcinoma

Cytoplasmic expression of estrogen receptor β may predict poor outcome of EGFR‑TKI therapy in metastatic lung adenocarcinoma

Estrogen, Estrogen Receptor and Lung Cancer

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome

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