Dataset Information

Long Noncoding RNA Signature and Disease Outcome in Estrogen Receptor-Positive Breast Cancer Patients Treated with Tamoxifen.

ABSTRACT:

Purpose

Recent data have shown that the expression levels of long noncoding RNAs (lncRNAs) are associated with tamoxifen sensitivity in estrogen receptor (ER)-positive breast cancer. Herein, we constructed an lncRNA-based model to predict disease outcomes of ER-positive breast cancer patients treated with tamoxifen.

Methods

LncRNA expression information was acquired from Gene Expression Omnibus by re-mapping pre-existing microarrays of patients with ER-positive breast cancer treated with tamoxifen. The distant metastasis-free survival (DMFS) predictive signature was subsequently built based on a Cox proportional hazard regression model in discover cohort patients, which was further evaluated in another independent validation dataset.

Results

Six lncRNAs were found to be associated with DMFS in the discover cohort, which were used to construct a tamoxifen efficacy-related lncRNA signature (TLS). There were 133 and 362 patients with TLS high- and low-risk signatures in the discover cohort. Both univariate and multivariate analysis demonstrated that TLS was associated with DMFS. TLS high-risk patients had worse outcomes than low-risk patients, with a hazard ratio of 4.04 (95% confidence interval, 2.83-5.77; p<0.001). Both subgroup analysis and receiver operating characteristic analysis indicated that TLS performed better in lymph node-negative, luminal B, 21-gene recurrence score high-risk, and 70-gene prognosis signature high-risk patients. Moreover, in a comparison of the 21-gene recurrence score and 70-gene prognosis signature, TLS showed a similar area under receiver operating characteristic curve in all patients. Gene Set Enrichment Analysis indicated that TLS high-risk patients showed different gene expression patterns related to the cell cycle and nucleotide metabolism from those of low-risk patients.

Conclusion

This six-lncRNA signature was associated with disease outcome in ER-positive breast cancer patients treated with tamoxifen, which is comparable to previous messenger RNA signatures and requires further clinical evaluation.

SUBMITTER: Wang G

PROVIDER: S-EPMC6158153 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Publications

Long Noncoding RNA Signature and Disease Outcome in Estrogen Receptor-Positive Breast Cancer Patients Treated with Tamoxifen.

Wang Gen G Chen Xiaosong X Liang Yue Y Wang Wei W Fang Yan Y Shen Kunwei K

Journal of breast cancer 20180912 3

<h4>Purpose</h4>Recent data have shown that the expression levels of long noncoding RNAs (lncRNAs) are associated with tamoxifen sensitivity in estrogen receptor (ER)-positive breast cancer. Herein, we constructed an lncRNA-based model to predict disease outcomes of ER-positive breast cancer patients treated with tamoxifen.<h4>Methods</h4>LncRNA expression information was acquired from Gene Expression Omnibus by re-mapping pre-existing microarrays of patients with ER-positive breast cancer treat ...[more]

PMID: 30275856

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Project description:BackgroundTamoxifen resistance remains a clinical challenge for hormone receptor-positive breast cancer. Recently, dysregulations in autophagy have been suggested as a potential mechanism for tamoxifen resistance. Although the long noncoding RNA H19 is involved in various stages of tumorigenesis, its role in tamoxifen resistance remains unknown. Here, we assessed the role of H19 in the development of tamoxifen-resistant breast cancer.MethodsQuantitative real-time PCR analyzed expression of H19 in tamoxifen-resistant breast cancer tissues. Knockdown of H19 was used to assess the sensitivity to tamoxifen in vitro and in vivo. Both knockdown and overexpression of H19 were used to analyze the status of autophagy. Real-time quantitative methylation-specific polymerase chain reaction, chromatin immunoprecipitation, immunofluorescence, and Western blot were used to explore the tamoxifen resistance mechanism of H19.ResultsIn this study, we observed that the expression of H19 was substantially upregulated in tamoxifen-resistant breast cancer cell line and tumor tissues, and knockdown of H19 enhanced the sensitivity to tamoxifen both in vitro and in vivo. Furthermore, knockdown of H19 significantly inhibited autophagy in MCF7 tamoxifen-resistant (MCF7/TAMR) cells. Conversely, overexpression of H19 promoted autophagy. Interestingly, overexpression of H19 in MCF7 tamoxifen-sensitive cells could recapitulate tamoxifen resistance. Moreover, an increase in methylation in the promoter region of Beclin1 was observed in MCF7/TAMR-shH19 cells. In the double knockdown groups, both shH19+shSAHH and shH19+shDNMT3B rescued the Beclin1 promoter region methylation levels and reactivated autophagy functions. A chromatin immunoprecipitation assay further validated that DNMT3B binds to the Beclin1 promoter region and the knockdown of H19 increases this binding.ConclusionsOur findings demonstrate that H19 induces autophagy activation via the H19/SAHH/DNMT3B axis, which could contribute to tamoxifen resistance in breast cancer.

Project description:Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker.

Dataset Information

Long Noncoding RNA Signature and Disease Outcome in Estrogen Receptor-Positive Breast Cancer Patients Treated with Tamoxifen.

Purpose

Methods

Results

Conclusion

Publications

Long Noncoding RNA Signature and Disease Outcome in Estrogen Receptor-Positive Breast Cancer Patients Treated with Tamoxifen.

Similar Datasets

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