Prognostic role of EGR1 in breast cancer: a systematic review

Potential involvement of KANK1 haploinsufficiency in centrosome aberrations

KANK1 was found as a tumor suppressor gene based on frequent deletions in renal cell carcinoma and the inhibitory activity of tumor cell proliferation. Previously, we reported that knockdown of KANK1 induced centrosomal amplification, leading to abnormal cell division, through the hyperactivation of RhoA small GTPase. Here, we investigated the loss of KANK1 function by performing CRISPR/Cas9-based genome editing to knockout the gene. After several rounds of genome editing, however, there were no cell lines with complete loss of KANK1, and the less the wild-type KANK1 dosage, the greater the number of cells with abnormal numbers of centrosomes and rates of cell-doubling and apoptosis, suggesting the involvement of KANK1 haploinsufficiency in centrosome aberrations. The rescue of KANK1-knockdown cells with a KANK1-expressing plasmid restored the rates of cells exhibiting centrosomal amplification to the control level. RNA-sequencing analysis of the cells with reduced dosages of functional KANK1 revealed potential involvement of other cell proliferation-related genes, such as EGR1, MDGA2, and BMP3, which have been reported to show haploinsufficiency when they function. When EGR1 protein expression was reduced by siRNA technology, the number of cells exhibiting centrosomal amplification increased, along with the reduction of KANK1 protein expression, suggesting their functional relationship. Thus, KANK1 haploinsufficiency may contribute to centrosome aberrations through the network of haploinsufficiency-related genes.

Toxoplasma gondii suppresses proliferation and migration of breast cancer cells by regulating their transcriptome

BACKGROUND

Breast cancer is the most common cancer in women worldwide. Toxoplasma gondii (T. gondii) has shown anticancer activity in breast cancer mouse models, and exerted beneficial effect on the survival of breast cancer patients, but the mechanism was unclear.

METHODS

The effect of tachyzoites of T. gondii (RH and ME49 strains) on human breast cancer cells (MCF-7 and MDA-MB-231 cells) proliferation and migration was assessed using cell growth curve and wound healing assays. Dual RNA-seq was performed for T. gondii-infected and non-infected cells to determine the differentially expressed genes (DEGs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction Networks analysis (PPI) were performed to explore the related signaling pathway and hub genes. Hub genes were validated using the Kaplan-Meier plotter database, and Pathogen Host Interaction (PHI-base) database. The results were verified by qRT-PCR.

RESULTS

The tachyzoites of T. gondii decreased the expression of Ki67 and increased the expression of E-cadherin, resulting in suppressing the proliferation and migration of infected human breast cancer cells. The inhibitory effect of T. gondii on breast cancer cells showed a significant dose-response relationship. Compared with the control group, 2321 genes were transcriptionally regulated in MCF-7 cells infected with T. gondii, while 169 genes were transcriptionally regulated in infected MDA-MB-231 cells. Among these genes, 698 genes in infected MCF-7 cells and 67 genes in infected MDA-MB-231 cells were validated by the publicly available database. GO and KEGG analyses suggested that several pathways were involved in anticancer function of T. gondii, such as ribosome, interleukin-17 signaling, coronavirus disease pathway, and breast cancer pathway. BRCA1, MYC and IL-6 were identified as the top three hub genes in infected-breast cancer cells based on the connectivity of PPI analysis. In addition, after interacting with breast cancer cells, the expression of ROP16 and ROP18 in T. gondii increased, while the expression of crt, TgIST, GRA15, GRA24 and MIC13 decreased.

CONCLUSIONS

T. gondii transcriptionally regulates several signaling pathways by altering the hub genes such as BRCA1, MYC and IL-6, which can inhibit the breast tumor growth and migration, hinting at a potential therapeutic strategy.

Transcriptome Profiling of Cardiac Glycoside Treatment Reveals EGR1 and Downstream Proteins of MAPK/ERK Signaling Pathway in Human Breast Cancer Cells

Cardiac glycosides (CGs) constitute a group of steroid-like compounds renowned for their effectiveness in treating cardiovascular ailments. In recent times, there has been growing recognition of their potential use as drug leads in cancer treatment. In our prior research, we identified three highly promising CG compounds, namely lanatoside C (LC), peruvoside (PS), and strophanthidin (STR), which exhibited significant antitumor effects in lung, liver, and breast cancer cell lines. In this study, we investigated the therapeutic response of these CGs, with a particular focus on the MCF-7 breast cancer cell line. We conducted transcriptomic profiling and further validated the gene and protein expression changes induced by treatment through qRT-PCR, immunoblotting, and immunocytochemical analysis. Additionally, we demonstrated the interactions between the ligands and target proteins using the molecular docking approach. The transcriptome analysis revealed a cluster of genes with potential therapeutic targets involved in cytotoxicity, immunomodulation, and tumor-suppressor pathways. Subsequently, we focused on cross-validating the ten most significantly expressed genes, EGR1, MAPK1, p53, CCNK, CASP9, BCL2L1, CDK7, CDK2, CDK2AP1, and CDKN1A, through qRT-PCR, and their by confirming the consistent expression pattern with RNA-Seq data. Notably, among the most variable genes, we identified EGR1, the downstream effector of the MAPK signaling pathway, which performs the regulatory function in cell proliferation, tumor invasion, and immune regulation. Furthermore, we substantiated the influence of CG compounds on translational processes, resulting in an alteration in protein expression upon treatment. An additional analysis of ligand-protein interactions provided further evidence of the robust binding affinity between LC, PS, and STR and their respective protein targets. These findings underscore the intense anticancer activity of the investigated CGs, shedding light on potential target genes and elucidating the probable mechanism of action of CGs in breast cancer.

Major regulators of the multi-step metastatic process are potential therapeutic targets for breast cancer management

Metastasis is a multi-step process that leads to the dissemination of tumor cells to new sites and, consequently, to multi-organ neoplasia. Although most lethal breast cancer cases are related to metastasis occurrence, little is known about the dysregulation of each step, and clinicians still lack reliable therapeutic targets for metastasis impairment. To fill these gaps, we constructed and analyzed gene regulatory networks for each metastasis step (cell adhesion loss, epithelial-to-mesenchymal transition, and angiogenesis). Through topological analysis, we identified E2F1, EGR1, EZH2, JUN, TP63, and miR-200c-3p as general hub-regulators, FLI1 for cell-adhesion loss specifically, and TRIM28, TCF3, and miR-429 for angiogenesis. Applying the FANMOD algorithm, we identified 60 coherent feed-forward loops regulating metastasis-related genes associated with distant metastasis-free survival prediction. miR-139-5p, miR-200c-3p, miR-454-3p, and miR-1301-3p, among others, were the FFL's mediators. The expression of the regulators and mediators was observed to impact overall survival and to go along with metastasis occurrence. Lastly, we selected 12 key regulators and observed that they are potential therapeutic targets for canonical and candidate antineoplastics and immunomodulatory drugs, like trastuzumab, goserelin, and calcitriol. Our results highlight the relevance of miRNAs in mediating feed-forward loops and regulating the expression of metastasis-related genes. Altogether, our results contribute to understanding the multi-step metastasis complexity and identifying novel therapeutic targets and drugs for breast cancer management.

Identification of Three Circulating MicroRNAs in Plasma as Clinical Biomarkers for Breast Cancer Detection

The diagnostic value of microRNAs (miRNAs) for breast cancer (BC) is largely unknown. Here, our research aim was to explore new circulating miRNAs for BC diagnosis. First, we identified 14 common differentially expressed miRNAs in tissues by TCGA_BRCA and GSE97811 datasets and preliminarily validated them in serum by the GSE73002 dataset. Furthermore, we examined three plasma miRNAs in BC patients (n = 108) and healthy subjects (n = 103) by RT−PCR, namely, hsa-miR-100-5p, hsa-miR-191-5p and hsa-miR-342-3p. The levels of these three miRNAs in BC patients were higher than those in healthy controls (p < 0.05). The ROC curve analysis revealed that these three miRNAs had high diagnostic efficacy for BC and early-stage BC. The combination of hsa-miR-100-5p and hsa-miR-191-5p was the optimal combination for the diagnosis of BC and early-stage BC. Additionally, hsa-miR-100-5p was correlated with stage I−II, T1 stage, N0 stage and Luminal A subtype (p < 0.05). Hsa-miR-191-5p and hsa-miR-342-3p were irrelevant to TNM stage, T stage, N stage and molecular subtypes. Meanwhile, the biological function analysis indicated that these three miRNAs are mainly involved in the calcium signaling pathway, MAPK signaling pathway and microRNAs in cancer. In conclusion, these three miRNAs demonstrate a positive effect on detection and discovery in BC.

Integrated spatial analysis of gene mutation and gene expression for understanding tumor diversity in formalin-fixed paraffin-embedded lung adenocarcinoma

Introduction

A deeper understanding of intratumoral heterogeneity is essential for prognosis prediction or accurate treatment plan decisions in clinical practice. However, due to the cross-links and degradation of biomolecules within formalin-fixed paraffin-embedded (FFPE) specimens, it is challenging to analyze them. In this study, we aimed to optimize the simultaneous extraction of mRNA and DNA from microdissected FFPE tissues (φ = 100 µm) and apply the method to analyze tumor diversity in lung adenocarcinoma before and after erlotinib administration.

Method

Two magnetic beads were used for the simultaneous extraction of mRNA and DNA. The decross-linking conditions were evaluated for gene mutation and gene expression analyses of microdissected FFPE tissues. Lung lymph nodes before treatment and lung adenocarcinoma after erlotinib administration were collected from the same patient and were preserved as FFPE specimens for 4 years. Gene expression and gene mutations between histologically classified regions of lung adenocarcinoma (pre-treatment tumor in lung lymph node biopsies and post-treatment tumor, normal lung, tumor stroma, and remission stroma, in resected lung tissue) were compared in a microdissection-based approach.

Results

Using the optimized simultaneous extraction of DNA and mRNA and whole-genome amplification, we detected approximately 4,000-10,000 expressed genes and the epidermal growth factor receptor (EGFR) driver gene mutations from microdissected FFPE tissues. We found the differences in the highly expressed cancer-associated genes and the positive rate of EGFR exon 19 deletions among the tumor before and after treatment and tumor stroma, even though they were collected from tumors of the same patient or close regions of the same specimen.

Conclusion

Our integrated spatial analysis method would be applied to various FFPE pathology specimens providing area-specific gene expression and gene mutation information.

Assessment of Early Growth Response 1 in Tumor Suppression of Esophageal Squamous Cell Carcinoma

Background: Esophageal squamous cell carcinoma (ESCC) is associated with poor survival despite surgical resection, and its pathogenesis has been broadly investigated in the past decade. Early growth response 1 (EGR-1) could involve regulating tumor development in ESCC cells. Methods: An attempt was made to examine the molecular and cellular influence of EGR-1 in esophageal cancer cells by RNA extraction, real-time PCR (qRT-PCR), cell culture, small interfering RNA (siRNA) knockdown, western blot, migration assay, and cell viability assay. One hundred and forty-four samples of ESCC were collected from our hospital and analyzed. Significantly higher EGR-1 expression was noted in tumor-adjacent normal tissue compared with tumor lesions. Results: The univariate analysis showed no significant impacts of EGR-1 expression on patients’ survival. However, after adjusting for the pathological stage, patients with EGR-1 expression > 68th percentile had lower risks of cancer-related death. Moreover, knockdown of EGR-1 significantly enhanced cell migration, invasion, and resistance to chemotherapeutic agents in two ESCC cell lines. Conclusions: EGR-1 plays a key role in tumor suppression involving tumor viability suppression and reflects the treatment effect of current chemotherapy for ESCC.

Integrated bioinformatical analysis, machine learning and in vitro experiment-identified m6A subtype, and predictive drug target signatures for diagnosing renal fibrosis

Renal biopsy is the gold standard for defining renal fibrosis which causes calcium deposits in the kidneys. Persistent calcium deposition leads to kidney inflammation, cell necrosis, and is related to serious kidney diseases. However, it is invasive and involves the risk of complications such as bleeding, especially in patients with end-stage renal diseases. Therefore, it is necessary to identify specific diagnostic biomarkers for renal fibrosis. This study aimed to develop a predictive drug target signature to diagnose renal fibrosis based on m6A subtypes. We then performed an unsupervised consensus clustering analysis to identify three different m6A subtypes of renal fibrosis based on the expressions of 21 m6A regulators. We evaluated the immune infiltration characteristics and expression of canonical immune checkpoints and immune-related genes with distinct m6A modification patterns. Subsequently, we performed the WGCNA analysis using the expression data of 1,611 drug targets to identify 474 genes associated with the m6A modification. 92 overlapping drug targets between WGCNA and DEGs (renal fibrosis vs. normal samples) were defined as key drug targets. A five target gene predictive model was developed through the combination of LASSO regression and stepwise logistic regression (LASSO-SLR) to diagnose renal fibrosis. We further performed drug sensitivity analysis and extracellular matrix analysis on model genes. The ROC curve showed that the risk score (AUC = 0.863) performed well in diagnosing renal fibrosis in the training dataset. In addition, the external validation dataset further confirmed the outstanding predictive performance of the risk score (AUC = 0.755). These results indicate that the risk model has an excellent predictive performance for diagnosing the disease. Furthermore, our results show that this 5-target gene model is significantly associated with many drugs and extracellular matrix activities. Finally, the expression levels of both predictive signature genes EGR1 and PLA2G4A were validated in renal fibrosis and adjacent normal tissues by using qRT-PCR and Western blot method.

The Landscape of Early Growth Response Family Members 1-4 in Hepatocellular Carcinoma: Their Biological Roles and Diagnostic Utility

The incidence of hepatocellular carcinoma (HCC), which is one of the most frequent types of cancer seen all over the world, is steadily growing from year to year. EGR genes are members of the early growth response (EGR) gene family. It has been shown that EGR genes play an increasingly essential role in the development of tumors and the progression of numerous malignancies. However, the possible diagnostic and prognostic roles of EGR genes in HCC have only been examined in a limited number of studies. Expression and methylation data on EGR family members were obtained from TCGA datasets. The prognostic values of EGR members were studied. Additionally, the correlations of EGR members with immune cells were assessed through the single-sample gene set enrichment analysis (ssGSEA). In this study, we found that the expression of EGR1, EGR2, EGR3, and EGR4 was distinctly decreased in HCC specimens compared with nontumor specimens. ROC assays confirmed that they have a strong ability in screening HCC specimens from nontumor specimens. According to the findings of Pearson's correlation, EGR1, EGR2, EGR3, and EGR4 were found to have a negative association with the methylation level. Survival study revealed that EGR1, EGR2, and EGR3 were associated with the clinical outcome of HCC patients. Immune cell enrichment analysis demonstrated that the expressions of all EGR members were positively related to the levels of most types of immune cells, such as macrophages, NK cells, B cells, T cells, eosinophils, and CD8 T cells. Overall, the current work demonstrated the expression mode and prognostic value of EGR members in HCC in a comprehensive manner, offering insights for further research of the EGR family as possible clinical biomarkers in HCC.

The Effect of EGR1 on the Proliferation of Dermal Papilla Cells

Early growth response factor 1 (EGR1) is a zinc-finger transcription factor that plays a vital role in the development of hair follicles. According to our previous studies, EGR1 is a transcriptional promoter of the bone morphogenetic protein 7 (BMP7), a candidate gene involved in the proliferation of dermal papilla cells. Since hair follicles are the basis of lambskin pattern formation and dermal papilla cells (DPCs) act on hair follicle growth, in order to elucidate the role of EGR1 and hair follicles, this study aimed to investigate the biological role of EGR1 in DPCs. In our study, the EGR1 coding sequence (CDS) region was firstly cloned by polymerase chain reaction, and bioinformatics analysis was performed. Then, the function of EGR1 was detected by 5-ethynyl-2’-deoxyuridine (EDU) and Cell Counting Kit-8 (CCK8), and Western blot (WB) was conducted to analyze the cellular effect of EGR1 on DPCs. The proliferative effect of EGR1 on DPCs was also further confirmed by detecting its expression by qPCR and WB on marker genes of proliferation, including PCNA and CDK2. The sequence of the EGR1 CDS region of a lamb was successfully cloned, and its nucleic acid sequence was analyzed and found to be highly homologous to Rattus norvegicus, Mus musculus, Bos taurus and Homo sapiens. Predictive analysis of the protein encoded by EGR1 revealed that it is an extra-membrane protein, and not a secretory protein, with subcellular localization in the nucleus and cytoplasm. The proliferative effect of DPCs was significantly stronger (p < 0.01) in EGR1 up-regulated DPCs compared to the controls, while the opposite result was observed in EGR1 down-regulated DPCs. Markers of proliferation including PCNA and CDK2 also appeared to be differentially upregulated in EGR1 gene overexpression compared to the controls, with the opposite result in EGR1 gene downregulation. In summary, our study revealed that EGR1 promotes the proliferation of DPCs, and we speculate that EGR1 may be closely associated with hair follicle growth and development.

Computational Recognition of a Regulatory T-cell-specific Signature With Potential Implications in Prognosis, Immunotherapy, and Therapeutic Resistance of Prostate Cancer

Prostate cancer, recognized as a "cold" tumor, has an immunosuppressive microenvironment in which regulatory T cells (Tregs) usually play a major role. Therefore, identifying a prognostic signature of Tregs has promising benefits of improving survival of prostate cancer patients. However, the traditional methods of Treg quantification usually suffer from bias and variability. Transcriptional characteristics have recently been found to have a predictive power for the infiltration of Tregs. Thus, a novel machine learning-based computational framework has been presented using Tregs and 19 other immune cell types using 42 purified immune cell datasets from GEO to identify Treg-specific mRNAs, and a prognostic signature of Tregs (named "TILTregSig") consisting of five mRNAs (SOCS2, EGR1, RRM2, TPP1, and C11orf54) was developed and validated to monitor the prognosis of prostate cancer using the TCGA and ICGC datasets. The TILTregSig showed a stronger predictive power for tumor immunity compared with tumor mutation burden and glycolytic activity, which have been reported as immune predictors. Further analyses indicate that the TILTregSig might influence tumor immunity mainly by mediating tumor-infiltrating Tregs and could be a powerful predictor for Tregs in prostate cancer. Moreover, the TILTregSig showed a promising potential for predicting cancer immunotherapy (CIT) response in five CIT response datasets and therapeutic resistance in the GSCALite dataset in multiple cancers. Our TILTregSig derived from PBMCs makes it possible to achieve a straightforward, noninvasive, and inexpensive detection assay for prostate cancer compared with the current histopathological examination that requires invasive tissue puncture, which lays the foundation for the future development of a panel of different molecules in peripheral blood comprising a biomarker of prostate cancer.

Early Growth Response 1 Strengthens Pol-III-Directed Transcription and Transformed Cell Proliferation by Controlling PTEN/AKT Signalling Activity

RNA polymerase III (Pol III) products play essential roles in ribosome assembly, protein synthesis, and cell survival. Deregulation of Pol-III-directed transcription is closely associated with tumorigenesis. However, the regulatory pathways or factors controlling Pol-III-directed transcription remain to be investigated. In this study, we identified a novel role of EGR1 in Pol-III-directed transcription. We found that Filamin A (FLNA) silencing stimulated EGR1 expression at both RNA and protein levels. EGR1 expression positively correlated with Pol III product levels and cell proliferation activity. Mechanistically, EGR1 downregulation dampened the occupancies of Pol III transcription machinery factors at the loci of Pol III target genes. Alteration of EGR1 expression did not affect the expression of p53, c-MYC, and Pol III general transcription factors. Instead, EGR1 activated RhoA expression and inhibited PTEN expression in several transformed cell lines. We found that PTEN silencing, rather than RhoA overexpression, could reverse the inhibition of Pol-III-dependent transcription and cell proliferation caused by EGR1 downregulation. EGR1 could positively regulate AKT phosphorylation levels and is required for the inhibition of Pol-III-directed transcription mediated by FLNA. The findings from this study indicate that EGR1 can promote Pol-III-directed transcription and cell proliferation by controlling the PTEN/AKT signalling pathway.