Region-specific glucocorticoid receptor promoter methylation has both positive and negative prognostic value in patients with estrogen receptor-positive breast cancer

Crosstalk of methylation and tamoxifen in breast cancer (Review)

Tamoxifen is a widely used anti‑estrogen drug in the endocrine therapy of breast cancer (BC). It blocks estrogen signaling by competitively binding to estrogen receptor α (ERα), thereby inhibiting the growth of BC cells. However, with the long‑term application of tamoxifen, a subset of patients with BC have shown resistance to tamoxifen, which leads to low overall survival and progression‑free survival. The molecular mechanism of resistance is mainly due to downregulation of ERα expression and abnormal activation of the PI3K/AKT/mTOR signaling pathway. Moreover, the downregulation of targeted gene expression mediated by DNA methylation is an important regulatory mode to control protein expression. In the present review, methylation and tamoxifen are briefly introduced, followed by a focus on the effect of methylation on tamoxifen resistance and sensitivity. Finally, the clinical application of methylation for tamoxifen is described, including its use as a prognostic indicator. Finally, it is hypothesized that when methylation is used in combination with tamoxifen, it could recover the resistance of tamoxifen.

SetQuence & SetOmic: Deep set transformers for whole genome and exome tumour analysis

In oncology, Deep Learning has shown great potential to personalise tasks such as tumour type classification, based on per-patient omics data-sets. Being high dimensional, incorporation of such data in one model is a challenge, often leading to one-dimensional studies and, therefore, information loss. Instead, we first propose relying on non-fixed sets of whole genome or whole exome variant-associated sequences, which can be used for supervised learning of oncology-relevant tasks by our Set Transformer based Deep Neural Network, SetQuence. We optimise this architecture to improve its efficiency. This allows for exploration of not just coding but also non-coding variants, from large datasets. Second, we extend the model to incorporate these representations together with multiple other sources of omics data in a flexible way with SetOmic. Evaluation, using these representations, shows improved robustness and reduced information loss compared to previous approaches, while still being computationally tractable. By means of Explainable Artificial Intelligence methods, our models are able to recapitulate the biological contribution of highly attributed features in the tumours studied. This validation opens the door to novel directions in multi-faceted genome and exome wide biomarker discovery and personalised treatment among other presently clinically relevant tasks.

Glucocorticoid receptor regulates the epithelial-mesenchymal transition process through GR/ZEB1/E-cad and is involved in breast cancer endocrine drug resistance-a bioinformatics analysis

Background

Studies have shown that there is a connection between estrogen receptor (ER) and glucocorticoid receptor (GR), which can impact the epithelial-mesenchymal transition (EMT) process and contribute to endocrine resistance in breast cancer. However, the specific mechanism is unclear. It is crucial to investigate this mechanism further.

Methods

This study aimed to confirm the role of GR in breast cancer endocrine resistance. Based on our hypothesis, GR is linked to a gene involved in the EMT process, and thus contributes to endocrine resistance in breast cancer. We obtained survival data and GR expression data from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Additionally, we gathered GR expression data from Gene Expression Omnibus (GEO). Using Cytoscape, we constructed a protein-protein interaction (PPI) network and identified key genes. Data of Vimentin, E-cad, and Wnt/β-catenin expression were obtained from The Cancer Genome Atlas (TCGA). We used the co-expression method to identify key proteins. UALCAN and cBioPortal were utilized to verify the function of the key protein.

Results

In ER+ breast cancer, GR (P=3.12780899271121E-08) and zinc finger E-box binding homeobox 1 (ZEB1) (P=1.716157E-01) were lowly expressed and down-regulated genes of GR differentially expressed genes were enriched in cell adhesion molecules. We screened for the key protein ZEB1 and found high levels of it was positively associated with prolonged recurrence-free survival (RFS) in patients receiving endocrine therapy (P=0.0024), while high levels of E-cad were negatively associated (P=0.0038). GR expression was positively associated with ZEB1 (Spearman =0.29, P=8.50e-21), negatively associated with E-cad (Spearman =-0.13, P=5.17e-5), and negatively associated with the SETD1B (Spearman =-0.14, P=1.527e-5), a gene downstream of ZEB1. In contrast, ZEB1 expression was negatively correlated with E-cad (Spearman =-0.081, P=3.132e-3) and negatively correlated with SET domain-containing 1B (SETD1B) (Spearman =-0.177, P=9.07e-11).

Conclusions

In ER+ breast cancers, GR expression is suppressed, and the EMT process is inhibited by suppressing ZEB1 expression and thus promoting E-cad expression. For the investigation of endocrine medication resistance in breast cancer, it is crucial to identify the mechanisms by how GR participates in the EMT process.

Somatic Super-Enhancer Epigenetic Signature for Overall Survival Prediction in Patients with Breast Invasive Carcinoma

To analyze genome-wide super-enhancers (SEs) methylation signature of breast invasive carcinoma (BRCA) and its clinical value. Differential methylation sites (DMS) between BRCA and adjacent tissues from The Cancer Genome Atlas (TCGA) database were identified by using ChAMP package in R software. Super-enhancers were identified sing ROSE software. Overlap analysis was used to assess the potential DMS in SEs region. Feature selection was performed by Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm based on TCGA training cohort. Prognosis model validation was performed in TCGA training cohort, TCGA validation cohort, and gene expression omnibus (GEO) test cohort. The gene ontology and KEGG analysis revealed that SEs target genes were significantly enriched in cell-migration-associated processes and pathways. A total of 83 654 DMS were identified between BRCA and adjacent tissues. Around 2397 DMS in SEs region were identified by overlap study and used to feature selection. By using Cox regression and LASSO algorithm, 42 features were selected to develop a clinical prediction model (CPM). Both training (TCGA) and validation cohorts (TCGA and GEO) show that the CPM has ideal discrimination and calibration. The CPM based on DMS at SE regions has ideal discrimination and calibration, which combined with tumor node metastasis (TNM) stage could improve prognostication, and thus contribute to individualized medicine.

Mechanisms behind context-dependent role of glucocorticoids in breast cancer progression

Glucocorticoids (GCs), mostly dexamethasone (dex), are routinely administered as adjuvant therapy to manage side effects in breast cancer. However, recently, it has been revealed that dex triggers different effects and correlates with opposite outcomes depending on the breast cancer molecular subtype. This has raised new concerns regarding the generalized use of GC and suggested that the context-dependent effects of GCs can be taken into potential consideration during treatment design. Based on this, attention has recently been drawn to the role of the glucocorticoid receptor (GR) in development and progression of breast cancer. Therefore, in this comprehensive review, we aimed to summarize the different mechanisms behind different context-dependent GC actions in breast cancer by applying a multilevel examination, starting from the association of variants of the GR-encoding gene to expression at the mRNA and protein level of the receptor, and its interactions with other factors influencing GC action in breast cancer. The role of GCs in chemosensitivity and chemoresistance observed during breast cancer therapy is discussed. In addition, experiences using GC targeting therapeutic options (already used and investigated in preclinical and clinical trials), such as classic GC dexamethasone, selective glucocorticoid receptor agonists and modulators, the GC antagonist mifepristone, and GR coregulators, are also summarized. Evidence presented can aid a better understanding of the biology of context-dependent GC action that can lead to further advances in the personalized therapy of breast cancer by the evaluation of GR along with the conventional estrogen receptor (ER) and progesterone receptor (PR) in the routine diagnostic procedure.

Stress sensing within the breast tumor microenvironment: how glucocorticoid receptors live in the moment

The classification and treatment of breast cancer is largely defined by the expression of steroid hormone receptors (HRs), namely estrogen receptor (ER) and progesterone receptor (PR), and gene amplification/overexpression of human epidermal growth factor receptor 2 (HER2). More recently, studies of androgen receptor (AR), glucocorticoid receptor (GR), and mineralocorticoid receptor (MR) have revealed that targeting these related HRs may be a promising strategy for a more personalized approach to the treatment of specific subtypes of HR+ breast cancer. For example, GR expression is associated with a good prognosis in ER+ breast cancer, but predicts poor prognosis in triple-negative breast cancer (TNBC). GR, like ER, PRs, and AR, is a ligand-activated transcription factor, but also has significant ligand-independent signaling activities. GR transcriptional activity is classically regulated by circulating glucocorticoids (GCs; ligand-dependent). Recent studies demonstrate that GR transcriptional activity is also regulated by a variety of cellular stress stimuli that input to GR Ser134 phosphorylation via rapid activation of the p38 mitogen activated protein kinase (MAPK) signaling pathway (ligand-independent). Furthermore, ligand-independent GR activation promotes feedforward signaling loops that mediate sustained activation of stress signaling pathways to drive advanced cancer biology (i.e. migration, invasion, chemoresistance, survival, and cellular growth). In this review, we will focus on the role of GR as a key sensor and mediator of physiologic and tumor microenvironment (TME)-derived cellular stress signaling in TNBC and discuss how targeting GR and/or associated signaling pathways may provide a strategy to inhibit deadly TNBC progression.

The clinical significance of the glucocorticoid receptors: Genetics and epigenetics

The impacts of glucocorticoids (GCs) are mainly mediated by a nuclear receptor (GR) existing in almost every tissue. The GR regulates a wide range of physiological functions, including inflammation, cell metabolism, and differentiation playing a major role in cellular responses to GCs and stress. Therefore, the dysregulation or disruption of GR can cause deficiencies in the adaptation to stress and the preservation of homeostasis. The number of GR polymorphisms associated with different diseases has been mounting per year. Tackling these clinical complications obliges a comprehensive understanding of the molecular network action of GCs at the level of the GR structure and its signaling pathways. Beyond genetic variation in the GR gene, epigenetic changes can enhance our understanding of causal factors involved in the development of diseases and identifying biomarkers. In this review, we highlight the relationships of GC receptor gene polymorphisms and epigenetics with different diseases.

A seven-nuclear receptor-based prognostic signature in breast cancer

BACKGROUND

Breast cancer (BRCA) is a malignant cancer that threatened the life of female with unsatisfactory prognosis. The aim of this study was to identify prognostic nuclear receptors (NRs) signature of BRCA.

METHODS

BRCA patient samples were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Consensus clustering analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed to evaluate, select NRs as prognostic factors and build Risk Score model. GSEA analysis was explored to check signaling differences between High- and Low-Risk group. Nomogram model basing on age and Risk Score was established to predict the 1-, 3- and 5-year survival. Model performance was assessed by a time-dependent receiver operating characteristic (ROC) curve and calibration plot. CIBERSORT, ESTIMATE and TIMER algorithm were introduced to evaluate the immune landscape.

RESULTS

NR3C1, NR4A3, THRA, RXRG, NR2F6, NR1D2 and RORB were optimized as a prognostic signature for BRCA. This seven-NR-based Risk Score could effectively predict overall survival status. The area under the curve (AUC) of 1-, 3- and 5-year overall survival are 0.702, 0.734 and 0.722 in TCGA training cohort, and 0.630, 0.721 and 0.823 in GEO validation cohort, respectively. Calibration plot demonstrated satisfactory agreement between predictive and observed outcomes. Nomogram model worked well on predicting survival probabilities. Multiple cancer-related pathways were highly enriched in High-Risk group. High- and Low-Risk groups showed significant differed immune cell infiltration. There exists an obvious connection between Risk Score and immune checkpoints LAG3, PD1 and TIM3.

CONCLUSION

The seven-NR-based Risk Score represents a promising signature for estimating overall survival in patients with BRCA, and is correlated with the immune microenvironment.

Glucocorticoid Receptor: A Multifaceted Actor in Breast Cancer

Breast cancer (BC) is one of the most common cancers in women worldwide. Even though the role of estrogen receptor alpha (ERα) is extensively documented in the development of breast tumors, other members of the nuclear receptor family have emerged as important players. Synthetic glucocorticoids (GCs) such as dexamethasone (dex) are commonly used in BC for their antiemetic, anti-inflammatory, as well as energy and appetite stimulating properties, and to manage the side effects of chemotherapy. However, dex triggers different effects depending on the BC subtype. The glucocorticoid receptor (GR) is also an important marker in BC, as high GR expression is correlated with a poor and good prognosis in ERα-negative and ERα-positive BCs, respectively. Indeed, though it drives the expression of pro-tumorigenic genes in ERα-negative BCs and is involved in resistance to chemotherapy and metastasis formation, dex inhibits estrogen-mediated cell proliferation in ERα-positive BCs. Recently, a new natural ligand for GR called OCDO was identified. OCDO is a cholesterol metabolite with oncogenic properties, triggering mammary cell proliferation in vitro and in vivo. In this review, we summarize recent data on GR signaling and its involvement in tumoral breast tissue, via its different ligands.

MicroRNA-19b Downregulates NR3C1 and Enhances Oxaliplatin Chemoresistance in Colon Cancer via the PI3K/AKT/mTOR Pathway

BACKGROUND

Identifying the genes and signaling pathways related to chemoresistance might facilitate the development of novel therapeutic strategies for colon cancer. In this study, we aimed to investigate the biological functions and underlying mechanisms of action of miR-19b and NR3C1, as well as their effects on chemosensitivity to oxaliplatin and prognosis of colon cancer patients.

METHODS

Reverse transcription-polymerase chain reaction (RT-PCR), Western blotting, and immunohistochemical staining were used to analyze the expression of miR-19b and NR3C1. Dual firefly luciferase reporter gene analysis was used to identify miR-19b target genes. Associations of miR-19b and NR3C1 with survival were estimated by the Kaplan-Meier method and Cox regression analyses. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and flow cytometric analysis were used to measure cell viability, cytotoxicity, cell cycle phase, and apoptosis, respectively. The effect of miR-19b on cell proliferation was investigated in vivo.

RESULTS

The miR-19b was overexpressed and NR3C1 was decreased in colon cancer tissue and cell lines (SW480 and DLD-1). The miR-19b inhibition and NR3C1 overexpression inhibited cell proliferation, and induced G1/S cell cycle blockade, apoptosis, and chemosensitivity to oxaliplatin in vitro. The miR-19b inhibition suppressed subcutaneous tumorigenesis in vivo. Increased miR-19b and decreased NR3C1 in colon cancer were correlated with poor prognosis. In addition, our results confirmed NR3C1 was directly targeted by miR-19b. Thus, miR-19b might inhibit apoptosis and enhance oxaliplatin chemoresistance via the PI3K/AKT/mTOR pathway.

CONCLUSIONS

Our study revealed that miR-19b promotes cell survival and chemoresistance to oxaliplatin via the PI3K/AKT/mTOR pathway by downregulating NR3C1 in colon cancer. miR-19b and NR3C1 might be potential intervention targets for chemoresistance of colon cancer.