Silencing of ELK3 Induces S-M Phase Arrest and Apoptosis and Upregulates SERPINE1 Expression Reducing Migration in Prostate Cancer Cells

ELK3 destabilization by speckle-type POZ protein suppresses prostate cancer progression and docetaxel resistance

Accumulating evidence demonstrates that the activity regulation of ELK3, a member of the E26 transformation-specific oncogene family, is critical to regulating cell proliferation, migration, and survival in human cancers. However, the molecular mechanisms of how ELK3 induces chemoresistance in prostate cancer (PCa) have not been elucidated. In this study, we found that SPOP and ELK3 are an interacting partner. The interaction between SPOP and ELK3 resulted in increased ELK3 ubiquitination and destruction, assisted by checkpoint kinase-mediated ELK3 phosphorylation. Notably, the modulation of SPOP-mediated ELK3 protein stability affected the c-Fos-induced cell proliferation and invasion of PCa cells. The clinical involvement of the SPOP-ELK3 axis in PCa development was confirmed by an immunohistochemical assay on 123 PCa tissues, with an inverse correlation between increased ELK3 and decreased SPOP being present in ~80% of the specimens. This observation was supported by immunohistochemistry analysis using a SPOP-mutant PCa specimen. Finally, docetaxel treatment induced cell death by activating checkpoint kinase- and SPOP-mediated ELK3 degradation, while SPOP-depleted or SPOP-mutated PCa cells showed cell death resistance. Notably, this observation was correlated with the protein levels of ELK3. Taken together, our study reveals the precise mechanism of SPOP-mediated degradation of ELK3 and provides evidence that SPOP mutations contribute to docetaxel resistance in PCa.

Construction of gastric cancer prognostic signature based on the E26 transcription factor and the identification of novel oncogene ELK3

The aim of the present study was to investigate the function of 29 E26 (ETS) transcription factor families in gastric cancer (GC) and determine their association with prognosis. Our analysis of the expression of the ETS family revealed that 28 genes were dysregulated in GC, and that their expression was associated with multiple clinicopathological features (P<0.05). Based on the expression signature of the ETS family, consensus clustering was performed to generate two gastric cancer subtypes. These subtypes exhibited differences in overall survival (OS, P = 0.161), disease-free survival (DFS, P<0.05) and GC grade (P<0.01). Functional enrichment analysis of the target genes associated with the ETS family indicated that these genes primarily contribute to functions that facilitate tumor progression. A systematic statistical analysis was used to construct a prognostic model related to OS and DFS in association with the ETS family. This model demonstrated that the maximum area under the curve (AUC) values for predicting OS and DFS were 0.729 and 0.670, respectively, establishing ETS as an independent prognostic factor for GC Furthermore, a nomogram was created from the prognostic signature, and its predictive accuracy was confirmed by a calibration curve. Finally, the expression and prognostic significance of the six genes comprising the model were also examined. Among these, ELK3 was found to be significantly overexpressed in GC clinical samples. Subsequent in vitro and in vivo studies verified that ELK3 regulates GC proliferation and metastasis, highlighting its potential as a therapeutic target for gastric cancer.

The Effect of HMGB1 and HMGB2 on Transcriptional Regulation Differs in Neuroendocrine and Adenocarcinoma Models of Prostate Cancer

Human high-mobility group-B (HMGB) proteins regulate gene expression in prostate cancer (PCa), a leading cause of oncological death in men. Their role in aggressive PCa cancers, which do not respond to hormonal treatment, was analyzed. The effects of HMGB1 and HMGB2 silencing upon the expression of genes previously related to PCa were studied in the PCa cell line PC-3 (selected as a small cell neuroendocrine carcinoma, SCNC, PCa model not responding to hormonal treatment). A total of 72% of genes analyzed, using pre-designed primer panels, were affected. HMGB1 behaved mostly as a repressor, but HMGB2 as an activator. Changes in SERPINE1, CDK1, ZWINT, and FN1 expression were validated using qRT-PCR after HMGB1 silencing or overexpression in PC-3 and LNCaP (selected as an adenocarcinoma model of PCa responding to hormonal treatment) cell lines. Similarly, the regulatory role of HMGB2 upon SERPINE1, ZWINT, FN1, IGFPB3, and TYMS expression was validated, finding differences between cell lines. The correlation between the expression of HMGB1, HMGB2, and their targets was analyzed in PCa patient samples and also in PCa subgroups, classified as neuroendocrine positive or negative, in public databases. These results allow a better understanding of the role of HMGB proteins in PCa and contribute to find specific biomarkers for aggressive PCa.

ETS transcription factor ELK3 in human cancers: An emerging therapeutic target

Cancer is a genetic and complex disorder, resulting from several events associated with onset, development, and metastasis. Tumor suppressors and oncogenes are among the main regulators of tumor progression, contributing to various cancer-related behaviors like cell proliferation, invasion, migration, epithelial-mesenchymal transition (EMT), cell cycle, and apoptosis. Transcription factors (TFs) could act as tumor suppressors or oncogenes in cancer progression. E-twenty-six/E26 (ETS) family of TFs have a winged helix-turn-helix (HLH) motif, which interacted with specific DNA regions with high levels of purines and GGA core. ETS proteins act as transcriptional repressors or activators to modulate the expression of target genes. ETS transcription factor ELK3 (ELK3), as a type of ETS protein, was shown to enhance in various cancers, suggesting that it may have an oncogenic role. These studies indicated that ELK3 promoted invasion, migration, cell cycle, proliferation, and EMT, and suppressed cell apoptosis. In addition, these studies demonstrated that ELK3 could be a promising diagnostic and prognostic biomarker in human cancer. Moreover, accumulating data proved that ELK3 could be a novel chemoresistance mediator in human cancer. Here, we aimed to explore the overall change of ELK3 and its underlying molecular mechanism in human cancers. Moreover, we aimed to investigate the potential role of ELK3 as a prognostic and diagnostic biomarker as well as its capability as a chemoresistance mediator in cancer.

Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer

Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors (TF). TraRe was applied to transcriptomic data from 46 patients with mCRPC with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared with Abi-resistant patients. These modules were replicated in an independent mCRPC study. Furthermore, key rewiring predictions and their associated TFs were experimentally validated in two prostate cancer cell lines with different Abi-resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving Abi response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions.

SIGNIFICANCE

The computational method TraRe built on Bayesian machine learning models for investigating transcriptional network structures shows that disruption of ELK3, MXD1, and MYB signaling cascades impacts abiraterone resistance in prostate cancer.

Identification of target and pathway of aspirin combined with Lipitor treatment in prostate cancer through integrated bioinformatics analysis

PURPOSE

Our previous studies have confirmed that aspirin combined with Lipitor inhibited the development of prostate cancer (PCa), but the mechanisms need to be comprehensively expounded. The study aims to screen out the hub genes of combination therapy and to explore their association with the pathogenesis and prognosis of PCa.

METHODS

Gene expressions were quantified by RNA sequencing (RNA-seq). Altered biological function, pathways of differentially expressed genes (DEGs), protein-protein interaction network, the filtering of hub genes, gene co-expression and the pathogenesis and prognosis were revealed by bioinformatics analysis. The correlation between hub gene expression and patient survival was validated by Kaplan-Meier. The effects of silent DNA replication and sister chromatid cohesion 1 (siDSCC1) combined with Lipitor and aspirin on DSCC1 expression, viability, invasion and migration of PCa cells were detected by qRT-PCR, Wound healing and transwell assays.

RESULTS

157 overlapped DEGs involved in FoxO, PI3K-Akt and p53 signaling pathways were identified. Ten hub genes (NEIL3, CDC7, DSCC1, CDC25C, PRIM1, MCM10, FBXO5, DTL, SERPINE1, EXO1) were verified to be correlated with the pathology and prognosis of PCa. DSCC1 silencing not only inhibited the viability, migration and invasion of PCa cells, but also strengthened the suppressing effects of Lipitor and aspirin alone or in combination on PCa cells.

CONCLUSION

The enrichment pathways and targets of Lipitor combined with aspirin in PCa are discovered, and DSCC1 silencing can potentiate the effect of Lipitor combined with aspirin in the treatment of PCa.

Molecular and clinical features of a potential immunotherapy target ELK3 in glioma

Glioma represents the most prevalent malignant primary brain cancer, and its treatment remains a tremendous challenge. Novel and efficient molecular targets are therefore required for improving diagnosis, survival prediction, and treatment outcomes. Additionally, some studies have shown that immunity is highly associated with glioma progression. Our study aimed to investigate the clinicopathological features, prognostic significance, and immunotherapeutic targetability of ELK3, a member of the erythroblast transformation-specific transcription factor family, in glioma using bioinformatics analyses. ELK3 transcript levels in glioma tissues were evaluated using the Gene Expression Omnibus and The Cancer Genome Atlas databases. Clinical and transcriptomic data of The Cancer Genome Atlas glioma patients were analyzed to identify the molecular and clinical characterizations of ELK3. The prognostic significance of ELK3 was assessed using Cox regression and Kaplan-Meier analysis. The biological pathways related to ELK3 expression were identified by gene set enrichment analysis. The relationships between ELK3 and inflammatory responses, immune cell infiltration, and immune checkpoints were explored using canonical correlation analysis and gene set variation analysis. ELK3 was upregulated in gliomas, and its high expression was correlated with advanced clinicopathologic features and unfavorable prognosis. Gene set enrichment analysis revealed that several immune-related pathways were tightly linked to high ELK3 expression. gene set variation analysis and correlograms demonstrated that ELK3 was robustly associated with inflammatory and immune responses. Correlation analyses indicated that ELK3 was positively associated with infiltrating immune cells and synergistic with several immune checkpoints. ELK3 may serve as a novel marker of poor prognosis and a potential immunotherapeutic target in glioma.

Platelet-Related Molecular Subtype to Predict Prognosis in Hepatocellular Carcinoma

Purpose

Complex crosstalk between tumor cells and platelets is closely related to the development, relapse, and drug resistance of hepatocellular carcinoma (HCC). Therefore, an intensive analysis of the relationship between platelet-related genes and the effectiveness of immunotherapy is necessary for improving the poor prognosis of HCC patients.

Methods

Genes associated with platelets in the GeneCards database were collected and were used to identify molecular subtypes using a non-negative matrix decomposition algorithm (NMF) and constructed a platelet-related genes-based prognostic stratification model by the LASSO-Cox regression and stepwise Cox regression analysis. The effect of this feature on the immune microenvironment of HCC and the response to immune checkpoint inhibitors was also explored.

Results

After identifying two molecular subtypes, we constructed a platelet-related genes-based prognostic stratification model that can be effectively used for immune checkpoint inhibitor (PD1, PD-L1, PD-L2, and CTLA4) efficacy and prognosis prediction in HCC patients, which was subsequently validated using patient samples from ICGC, GSE14520 and a small sample size clinical cohort. We also found downregulation of PAFAH1B3 remarkably inhibited the proliferation and migration ability of Hep3B cells by cytological experiments.

Conclusion

We constructed a prognostic classifier based on platelet-related genes that could effectively classify HCC patients for prognostic prediction and provide new light on the selection of optimal individualized antiplatelet therapy for HCC patients in future clinical practice.

ELK3 Controls Gastric Cancer Cell Migration and Invasion by Regulating ECM Remodeling-Related Genes

Current therapeutic strategies for gastric cancer, including surgery and chemotherapy improve patient survival; however, the survival rate of patients with metastatic gastric cancer is very low. The molecular mechanisms underlying the dissemination of gastric cancer cells to distant organs are currently unknown. Here, we demonstrate that the E26 transformation-specific (ETS) transcription factor ELK3 (ELK3) gene is required for the migration and invasion of gastric cancer cells. The ELK3 gene modulates the expression of extracellular matrix (ECM) remodeling-related genes, such as bone morphogenetic protein (BMP1), lysyl oxidase like 2 (LOXL2), Snail family transcriptional repressor 1 (SNAI1), serpin family F member 1 (SERPINF1), decorin (DCN), and nidogen 1 (NID1) to facilitate cancer cell dissemination. Our in silico analyses indicated that ELK3 expression was positively associated with these ECM remodeling-related genes in gastric cancer cells and patient samples. The high expressions of ELK3 and other ECM remodeling-related genes were also closely associated with a worse prognosis of patients with gastric cancer. Collectively, these findings suggest that ELK3 acts as an important regulator of gastric cancer cell dissemination by regulating ECM remodeling.

ELK3: A New Molecular Marker for the Diagnosis and Prognosis of Glioma

ETS transcription factor ELK3 (ELK3), a novel oncogene, affects pathological processes and progression of many cancers in human tissues. However, it remains unclear whether ELK3, as a key gene, affects the pathological process of gliomas and the prognosis of patients with gliomas. This study aimed to comprehensively and systematically reveal the correlation between ELK3 and the malignant progression of gliomas by analyzing clinical sample information stored in multiple databases. We revealed the putative mechanism of ELK3 involvement in malignant gliomas progression and identified a new and efficient biomarker for glioma diagnosis and targeted therapy. Based on the sample data from multiple databases and real-time quantitative polymerase chain reaction (RT-qPCR), the abnormally high expression of ELK3 in gliomas was confirmed. Kaplan-Meier and Cox regression analyses demonstrated that a high ELK3 expression was markedly associated with low patient survival and served as an independent biomarker of gliomas. Wilcox and Kruskal-Wallis tests revealed that expression of ELK3 was positively correlated with several clinical characteristics of patients with gliomas, such as age, WHO classification, and recurrence. Moreover, Cell Counting Kit‐8 (CCK-8), immunofluorescence, and wound healing assays confirmed that ELK3 overexpression markedly promoted the proliferation and migration of glioma cells. Finally, gene set enrichment analysis (GSEA) and western blotting confirmed that overexpression of ELK3 regulated the JAK–STAT signaling pathway and upregulate the expression of signal transducer and activator of transcription 3 (STAT3) and phosphorylated STAT3 (P-STAT3) to promote the malignant transition of gliomas. Therefore, ELK3 may serve as an efficient biomarker for the diagnosis and prognosis of gliomas and it can also be used as a therapeutic target to improve the poor prognosis of patients with gliomas.

Prognostic signature composed of transcription factors accurately predicts the prognosis of gastric cancer patients

BACKGROUND

Transcription factors (TFs) are involved in important molecular biological processes of tumor cells and play an essential role in the occurrence and development of gastric cancer (GC).

METHODS

Combined The Cancer Genome Atlas Program and Genotype-Tissue Expression database to extract the expression of TFs in GC, analyzed the differences, and weighted gene co-expression network analysis to extract TFs related to GC. The cohort including the training and validation cohort. Univariate Cox, least absolute contraction and selection operator (LASSO) regression, and multivariate Cox analysis was used for screening hub TFs to construct the prognostic signature in the training cohort. The Kaplan-Meier (K-M) and the receiver operating characteristic curve (ROC) was drawn to evaluate the predictive ability of the prognostic signature. A nomogram combining clinical information and prognostic signatures of TFs was constructed and its prediction accuracy was evaluated through various methods. The target genes of the hub TFs was predicted and enrichment analysis was performed to understand its molecular biological mechanism. Clinical samples and public data of GC was collected to verify its expression and prognosis. 5-Ethynyl-2'-deoxyuridine and Acridine Orange/Ethidium Bromide staining, flow cytometry and Western-Blot detection were used to analyze the effects of hub-TF ELK3 on the proliferation and apoptosis of gastric cancer in vitro.

RESULTS

A total of 511 misaligned TFs were obtained and 200 GC-related TFs were exposed from them. After systematic analysis, a prognostic signature composed of 4 TFs (ZNF300, ELK3, SP6, MEF2B) were constructed. The KM and ROC curves demonstrated the good predictive ability in training, verification, and complete cohort. The areas under the ROC curve are respectively 0.737, 0.705, 0.700. The calibration chart verified that the predictive ability of the nomogram constructed by combining the prognostic signature of TFs and clinical information was accurate, with a C-index of 0.714. Enriching the target genes of hub TFs showed that it plays an vital role in tumor progression, and its expression and prognostic verification were consistent with the previous analysis. Among them, ELK3 was proved in vitro, and downregulation of its expression inhibited the proliferation of gastric cancer cells, induced proliferation, and exerted anti-tumor effects.

CONCLUSIONS

The 4-TFs prognostic signature accurately predicted the overall survival of GC, and ELK3 may be potential therapeutic targets for GC.

LINC01106 post-transcriptionally regulates ELK3 and HOXD8 to promote bladder cancer progression

Bladder cancer (BCa) is a kind of common urogenital malignancy worldwide. Emerging evidence indicated that long noncoding RNAs (lncRNAs) play critical roles in the progression of BCa. In this study, we discovered a novel lncRNA LINC01116 whose expression increased with stages in BCa patients and closely related to the survival rate of BCa patients. However, the molecular mechanism dictating the role of LINC01116 in BCa has not been well elucidated so far. In our study, we detected that the expression of LINC01116 was boosted in BCa cells. Moreover, the results of a series of functional assays showed that LINC01116 knockdown suppressed the proliferation, migration, and invasion of BCa cells. Thereafter, GEPIA indicated the closest correlation of LINC01116 with two protein-coding genes, ELK3 and HOXD8. Interestingly, LINC01116 was mainly a cytoplasmic lncRNA in BCa cells, and it could modulate ELK3 and HOXD8 at post-transcriptional level. Mechanically, LINC01116 increased the expression of ELK3 by adsorbing miR-3612, and also stabilized HOXD8 mRNA by binding with DKC1. Rescue experiments further demonstrated that the restraining influence of LINC01116 knockdown on the progression of BCa, was partly rescued by ELK3 promotion, but absolutely reversed by the co-enhancement of ELK3 and HOXD8. More intriguingly, HOXD8 acted as a transcription factor to activate LINC01116 in BCa. In conclusion, HOXD8-enhanced LINC01116 contributes to the progression of BCa via targeting ELK3 and HOXD8, which might provide new targets for treating patients with BCa.

Advances in Targeting Cancer-Associated Genes by Designed siRNA in Prostate Cancer

Short interfering RNAs (siRNAs) have provided novel insights into the field of cancer treatment in light of their ability to specifically target and silence cancer-associated genes. In recent years, numerous studies focus on determining genes that actively participate in tumor formation, invasion, and metastasis in order to establish new targets for cancer treatment. In spite of great advances in designing various siRNAs with diverse targets, efficient delivery of siRNAs to cancer cells is still the main challenge in siRNA-mediated cancer treatment. Recent advancements in the field of nanotechnology and nanomedicine hold great promise to meet this challenge. This review focuses on recent findings in cancer-associated genes and the application of siRNAs to successfully silence them in prostate cancer, as well as recent progress for effectual delivery of siRNAs to cancer cells.