Dataset Information

An estrogen receptor (ER)-related signature in predicting prognosis of ER-positive breast cancer following endocrine treatment.

ABSTRACT: Quite a few estrogen receptor (ER)-positive breast cancer patients receiving endocrine therapy are at risk of disease recurrence and death. ER-related genes are involved in the progression and chemoresistance of breast cancer. In this study, we identified an ER-related gene signature that can predict the prognosis of ER-positive breast cancer patient receiving endocrine therapy. We collected RNA expression profiling from Gene Expression Omnibus database. An ER-related signature was developed to separate patients into high-risk and low-risk groups. Patients in the low-risk group had significantly better survival than those in the high-risk group. ROC analysis indicated that this signature exhibited good diagnostic efficiency for the 1-, 3- and 5-year disease-relapse events. Moreover, multivariate Cox regression analysis demonstrated that the ER-related signature was an independent risk factor when adjusting for several clinical signatures. The prognostic value of this signature was validated in the validation sets. In addition, a nomogram was built and the calibration plots analysis indicated the good performance of this nomogram. In conclusion, combining with ER status, our results demonstrated that the ER-related prognostic signature is a promising method for predicting the prognosis of ER-positive breast cancer patients receiving endocrine therapy.

SUBMITTER: Tang J

PROVIDER: S-EPMC6652714 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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An estrogen receptor (ER)-related signature in predicting prognosis of ER-positive breast cancer following endocrine treatment.

Tang Jianing J Cui Qiuxia Q Zhang Dan D Liao Xing X Zhu Jian J Wu Gaosong G

Journal of cellular and molecular medicine 20190523 8

Quite a few estrogen receptor (ER)-positive breast cancer patients receiving endocrine therapy are at risk of disease recurrence and death. ER-related genes are involved in the progression and chemoresistance of breast cancer. In this study, we identified an ER-related gene signature that can predict the prognosis of ER-positive breast cancer patient receiving endocrine therapy. We collected RNA expression profiling from Gene Expression Omnibus database. An ER-related signature was developed to ...[more]

PMID: 31124293

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Project description:BackgroundBreast cancer is one of the most serious and prevalent malignancies. Zinc is commonly known to play a crucial role in the development and progression of breast cancer; however, the detailed mechanisms underlying this role are not well understood. This study aimed to develop a zinc metabolism-related gene (ZMRG) signature based on a multi-database study to predict patient prognosis and investigate the relationship between drug therapy response and immune enrichment.MethodsData for breast cancer samples from The Cancer Genome Atlas and Gene Expression Omnibus databases were screened for zinc metabolism-related genes using the Molecular Signature Database. Cox and Least Absolute Shrinkage and Selection Operator regressions were performed to construct a ZMRG signature. To assess the predictive performance of the gene signature, Kaplan-Meier analysis and receiver operating characteristic curves were used. Additionally, we utilised single-sample gene set enrichment analysis, the Tumour Immune Estimation Resource, the Genomics of Drug Sensitivity in Cancer database, and the Cancer Therapeutics Response Portal to investigate the association between the tumour microenvironment and drug sensitivity. Quantitative PCR was used to assess the expression of each gene in the signature in breast cancer cell lines and patient samples.ResultsFive ZMRGs were identified (ATP7B, BGLAP, P2RX4, SLC39A11, and TH) and a risk profile was constructed for each. Two risk groups, high- and low-risk, were identified in this way, and the high-risk score subgroups were found to have worse prognosis. This risk profile was validated using the GSE42568 dataset. Tumour microenvironment and drug sensitivity analyses showed that the expression of these five ZMRGs was significantly associated with immune response. The high-risk group showed substantial immune cell infiltration and enrichment of immune pathways, and patients were more sensitive to drugs commonly used in breast cancer.ConclusionThe ZMRG signature represents a new prognostic predictor for patients with breast cancer, and may also provide new insights into individualised treatment of breast cancer.

Project description:BackgroundTumor heterogeneity is widely recognized as a crucial factor impacting the prognosis of breast cancer (BC) patients. However, there remains an insufficient understanding of the underlying impact of anoikis on the prognosis of BC patients.MethodsThe researchers utilized the TCGA-BRCA dataset to screen and analyze the differentially expressed genes of anoikis-related genes (ARGs) in BC and normal breast tissue. Prognostic gene signatures were established through univariate, LASSO, and multivariate Cox regression analyses. These signatures were evaluated using Kaplan-Meier curve and receiver operating characteristic (ROC) analyses, resulting in the development of an anoikis-related index (ACI). The training dataset was TCGA-BRCA, while METABRIC and GSE96058 were used for external validation. Additionally, nomograms were developed by combining risk scores and clinical parameters, enabling gene set enrichment analysis (GSEA) and tumor immunoassay. Furthermore, an exploration of small molecule compounds was conducted to identify potential therapeutic benefits.ResultsA six-gene anoikis-related signature was constructed, which divided BC patients into high- and low-ACI groups based on median ACI scores. The ACI accurately predicted prognosis and acted as an independent prognostic factor for BC patients. Patients in the high-ACI group exhibited poorer overall survival (OS) across all cohorts and showed more severe clinical manifestations compared to the low-ACI group. The study also explored the potential impacts of anoikis on immune cells infiltrating tumors, immune checkpoints, growth factors, and cytokine levels. Additionally, the potential implications of anoikis in BC immunotherapy were discussed, along with highlighting small molecule compounds that could offer therapeutic benefits.ConclusionsAnoikis was found to hold significant prognostic value in breast cancer, providing a novel approach for managing patients with different prognoses and implementing more precise immunotherapy strategies.

Dataset Information

An estrogen receptor (ER)-related signature in predicting prognosis of ER-positive breast cancer following endocrine treatment.

Publications

An estrogen receptor (ER)-related signature in predicting prognosis of ER-positive breast cancer following endocrine treatment.

Similar Datasets

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