Differential Glucocorticoid-Dependent Regulation and Function of the ERRFI1 Gene in Triple-Negative Breast Cancer

Inference of differential key regulatory networks and mechanistic drug repurposing candidates from scRNA-seq data with SCANet

MOTIVATION

The reconstruction of small key regulatory networks that explain the differences in the development of cell (sub)types from single-cell RNA sequencing is a yet unresolved computational problem.

RESULTS

To this end, we have developed SCANet, an all-in-one package for single-cell profiling that covers the whole differential mechanotyping workflow, from inference of trait/cell-type-specific gene co-expression modules, driver gene detection, and transcriptional gene regulatory network reconstruction to mechanistic drug repurposing candidate prediction. To illustrate the power of SCANet, we examined data from two studies. First, we identify the drivers of the mechanotype of a cytokine storm associated with increased mortality in patients with acute respiratory illness. Secondly, we find 20 drugs for eight potential pharmacological targets in cellular driver mechanisms in the intestinal stem cells of obese mice.

AVAILABILITY AND IMPLEMENTATION

SCANet is a free, open-source, and user-friendly Python package that can be seamlessly integrated into single-cell-based systems medicine research and mechanistic drug discovery.

The risk model construction of the genes regulated by H3K36me3 and H3K79me2 in breast cancer

Abnormal histone modifications (HMs) can promote the occurrence of breast cancer. To elucidate the relationship between HMs and gene expression, we analyzed HM binding patterns and calculated their signal changes between breast tumor cells and normal cells. On this basis, the influences of HM signal changes on the expression changes of breast cancer-related genes were estimated by three different methods. The results showed that H3K79me2 and H3K36me3 may contribute more to gene expression changes. Subsequently, 2109 genes with differential H3K79me2 or H3K36me3 levels during cancerogenesis were identified by the Shannon entropy and submitted to perform functional enrichment analyses. Enrichment analyses displayed that these genes were involved in pathways in cancer, human papillomavirus infection, and viral carcinogenesis. Univariate Cox, LASSO, and multivariate Cox regression analyses were then adopted, and nine potential breast cancer-related driver genes were extracted from the genes with differential H3K79me2/H3K36me3 levels in the TCGA cohort. To facilitate the application, the expression levels of nine driver genes were transformed into a risk score model, and its robustness was tested via time-dependent receiver operating characteristic curves in the TCGA dataset and an independent GEO dataset. At last, the distribution levels of H3K79me2 and H3K36me3 in the nine driver genes were reanalyzed in the two cell lines and the regions with significant signal changes were located.

Krüppel-like factor 9 (KLF9) links hormone dysregulation and circadian disruption to breast cancer pathogenesis

BACKGROUND

Circadian disruption is an emerging driver of breast cancer (BCa), with epidemiological studies linking shift work and chronic jet lag to increased BCa risk. Indeed, several clock genes participate in the gating of mitotic entry, regulation of DNA damage response, and epithelial-to-mesenchymal transition, thus impacting BCa etiology. Dysregulated estrogen (17β-estradiol, E2) and glucocorticoid (GC) signaling prevalent in BCa may further contribute to clock desynchrony by directly regulating the expression and cycling dynamics of genes comprising the local breast oscillator. In this study, we investigated the tumor suppressor gene, Krüppel-like factor 9 (KLF9), as an important point of crosstalk between hormone signaling and the circadian molecular network, and further examine its functional role in BCa.

METHODS

Through meta-analysis of publicly available RNA- and ChIP-sequencing datasets from BCa tumor samples and cell lines, and gene expression analysis by RT-qPCR and enhancer- reporter assays, we elucidated the molecular mechanism behind the clock and hormone regulation of KLF9. Lentiviral knockdown and overexpression of KLF9 in three distinct breast epithelial cell lines (MCF10A, MCF7 and MDA-MB-231) was generated to demonstrate the role of KLF9 in orthogonal assays on breast epithelial survival, proliferation, apoptosis, and migration.

RESULTS

We determined that KLF9 is a direct GC receptor target in mammary epithelial cells, and that induction is likely mediated through coordinate transcriptional activation from multiple GC-responsive enhancers in the KLF9 locus. More interestingly, rhythmic expression of KLF9 in MCF10A cells was abolished in the highly aggressive MDA-MB-231 line. In turn, forced expression of KLF9 altered the baseline and GC/E2-responsive expression of several clock genes, indicating that KLF9 may function as a regulator of the core clock machinery. Characterization of the role of KLF9 using complementary cancer hallmark assays in the context of the hormone-circadian axis revealed that KLF9 plays a tumor-suppressive role in BCa regardless of molecular subtype. KLF9 potentiated the anti-tumorigenic effects of GC in E2 receptor + luminal MCF7 cells, while it restrained GC-enhanced oncogenicity in triple-negative MCF10A and MDA-MB-231 cells.

CONCLUSIONS

Taken together, our findings support that dysregulation of KLF9 expression and oscillation in BCa impinges on circadian network dynamics, thus ultimately affecting the BCa oncogenic landscape.

The Role of Glucocorticoids in Breast Cancer Therapy

Glucocorticoids (GCs) are anti-inflammatory and immunosuppressive steroid molecules secreted by the adrenal gland and regulated by the hypothalamic-pituitary-adrenal (HPA) axis. GCs present a circadian release pattern under normal conditions; they increase their release under stress conditions. Their mechanism of action can be via the receptor-independent or receptor-dependent pathway. The receptor-dependent pathway translocates to the nucleus, where the ligand-receptor complex binds to specific sequences in the DNA to modulate the transcription of specific genes. The glucocorticoid receptor (GR) and its endogenous ligand cortisol (CORT) in humans, and corticosterone in rodents or its exogenous ligand, dexamethasone (DEX), have been extensively studied in breast cancer. Its clinical utility in oncology has mainly focused on using DEX as an antiemetic to prevent chemotherapy-induced nausea and vomiting. In this review, we compile the results reported in the literature in recent years, highlighting current trends and unresolved controversies in this field. Specifically, in breast cancer, GR is considered a marker of poor prognosis, and a therapeutic target for the triple-negative breast cancer (TNBC) subtype, and efforts are being made to develop better GR antagonists with fewer side effects. It is necessary to know the type of breast cancer to differentiate the treatment for estrogen receptor (ER)-positive, ER-negative, and TNBC, to implement therapies that include the use of GCs.

Identification of a 12-Gene Signature and Hub Genes Involved in Kidney Wilms Tumor via Integrated Bioinformatics Analysis

Wilms tumor (WT), also known as nephroblastoma, is a rare primary malignancy in all kinds of tumor. With the development of second-generation sequencing, the discovery of new tumor markers and potential therapeutic targets has become easier. This study aimed to explore new WT prognostic biomarkers. In this study, WT-miRNA datasets GSE57370 and GSE73209 were selected for expression profiling to identify differentially expressed genes. The key gene miRNA, namely hsa-miR-30c-5p, was identified by overlapping, and the target gene of candidate hsa-miR-30c-5p was predicted using an online database. Furthermore, 384 genes were obtained by intersecting them with differentially expressed genes in the TARGET-WT database, and the genes were analyzed for pathway and functional enrichment. Kaplan–Meier survival analysis of the 384 genes yielded a total of 25 key genes associated with WT prognosis. Subsequently, a prediction model with 12 gene signatures (BCL6, CCNA1, CTHRC1, DGKD, EPB41L4B, ERRFI1, LRRC40, NCEH1, NEBL, PDSS1, ROR1, and RTKN2) was developed. The model had good predictive power for the WT prognosis at 1, 3, and 5 years (AUC: 0.684, 0.762, and 0.774). Finally, ERRFI1 (hazard ratios [HR] = 1.858, 95% confidence intervals [CI]: 1.298–2.660) and ROR1 (HR = 0.780, 95% CI: 0.609–0.998) were obtained as independent predictors of prognosis in WT patients by single, multifactorial Cox analysis.

Gene 33/Mig6/ERRFI1, an Adapter Protein with Complex Functions in Cell Biology and Human Diseases

Gene 33 (also named Mig6, RALT, and ERRFI1) is an adapter/scaffold protein with a calculated molecular weight of about 50 kD. It contains multiple domains known to mediate protein–protein interaction, suggesting that it has the potential to interact with many cellular partners and have multiple cellular functions. The research over the last two decades has confirmed that it indeed regulates multiple cell signaling pathways and is involved in many pathophysiological processes. Gene 33 has long been viewed as an exclusively cytosolic protein. However, recent evidence suggests that it also has nuclear and chromatin-associated functions. These new findings highlight a significantly broader functional spectrum of this protein. In this review, we will discuss the function and regulation of Gene 33, as well as its association with human pathophysiological conditions in light of the recent research progress on this protein.

Association of steroid use with survival in solid tumours

BACKGROUND

Steroids are commonly used in patients with solid tumours for supportive therapy. In other cases, they are an essential part of cancer treatment such as prostate cancer. Some preclinical observations lead to the notion that glucocorticoids may modulate growth factors' pathways and may induce the progression of cancers. Glucocorticoids are associated with several side-effects on many organ systems (e.g. serious infections, diabetes, sepsis and thrombosis). We have performed a systematic review and meta-analysis to evaluate the outcome of cancer patients that assume or not steroids.

METHODS

Published articles that evaluated survival associated with steroids use in cancer patients from inception to June 2020 were identified by searching the PubMed, EMBASE and Cochrane Library databases. The primary outcome of interest was the risk of death, and the secondary end-point was the risk of progression in steroid versus non-steroid users.

RESULTS

Seventy-six studies were in quantitative synthesis for a total of 83,614 patients. Use of steroids was associated with a reduced survival (hazard ratios (HR) = 1.18, 95% confidence interval (CI): 1.1-1.26; P < .01). Progression-free survival was also decreased in steroid versus non-steroid users (HR = 1.13, 95% CI: 1.01-1.26; P = .03). In patients with lung cancer, advanced disease and supportive care indications were settings where the use of steroids increased the risk of death.

CONCLUSIONS

In patients with advanced cancers, use of steroids should be reduced and, at best, avoided because it may reduce survival, in particular, for patients with lung cancer and for palliative/supportive care purposes.

Differential Glucocorticoid-Dependent Regulation and Function of the ERRFI1 Gene in Triple-Negative Breast Cancer

Glucocorticoids (GCs; eg, hydrocortisone [CORT]) are routinely used as chemotherapeutic, anti-emetic, and palliative agents in breast cancer (BCa) therapy. The effects of GC signaling on BCa progression, however, remain a contentious topic as GC treatment seems to be beneficial for receptor-positive subtypes but elicits unfavorable responses in triple-negative BCa (TNBC). The mechanistic basis for these conflicting effects of GC in BCa is poorly understood. In this study, we sought to decipher the molecular mechanisms that govern the GC-dependent induction of the tumor suppressor ERRFI1 gene, an inhibitor of epidermal growth factor receptor (EGFR) signaling, and characterize the role of the GC-ERRFI1 regulatory axis in TNBC. Treatment of TNBC cell lines with a protein synthesis inhibitor or GC receptor (GR) antagonist followed by gene expression analysis suggests that ERRFI1 is a direct GR target. Using in silico analysis coupled with enhancer-reporter assays, we identified a putative ERRFI1 enhancer that supports CORT-dependent transactivation. In orthogonal assays for cell proliferation, survival, migration, and apoptosis, CORT mostly facilitated an oncogenic phenotype regardless of malignancy status. Lentiviral knockdown and overexpression of ERRFI1 showed that the CORT-enhanced oncogenic phenotype is restricted by ERRFI1 in the normal breast epithelial model MCF10A and to a lesser degree in the metastatic TNBC line MDA-MB-468. Conversely, ERRFI1 conferred pro-tumorigenic effects in the highly metastatic TNBC model MDA-MB-231. Taken together, our findings suggest that the progressive loss of the GC-dependent regulation and anti-tumorigenic function of ERRFI1 influences BCa progression and may contribute to the unfavorable effects of GC therapy in TNBC.