ELF5 inhibits the proliferation and invasion of breast cancer cells by regulating CD24

LINC00525 enhances ZNF460-regulated CD24 expression through the sponge miR-125a-5p to promote malignant progression of breast cancer

INTRODUCTION

CD24 is a highly glycosylated glycosylphosphatidylinositol anchored membrane protein that plays an important role in tumor progression. The aim of this study was to investigate the effect of abnormal expression of CD24 on the proliferation, migration and invasion of breast cancer (BC) cells, and the molecular mechanism of regulating CD24 expression in breast cancer.

METHODOLOGY

The bioinformatics method was used to predict the expression level of CD24 in BC and its relationship with the occurrence and development of BC. IHC, RT-qPCR and WB were used to detect the expression of CD24 in BC tissues and cells. The proliferation of CD24 was evaluated by CCK-8 and colony formation assay, and the migration and invasion of CD24 were evaluated by wound healing and transwell. In addition, the effect of CD24 on the malignancy of BC in vivo was further evaluated by subcutaneous tumorigenesis assay. Molecular mechanisms were measured by luciferase reporter assays, biotin-labeled miRNA pull-down assay, RIP, and western blotting.

RESULTS

The results show that CD24 is highly expressed in breast cancer tissues and cell lines, and knockdown of CD24 in vivo and in vitro can inhibit the proliferation, migration and invasion of BC cells. Mechanistically, the transcription factor ZNF460 promotes its expression by binding to the CD24 promoter, and the expression of ZNF460 is regulated by miR-125a-5p, which inhibits its expression by targeting the 3'UTR of ZNF460. In addition, LINC00525 acts as a ceRNA sponge to adsorb miR-125a-5p and regulate its expression.

CONCLUSIONS

Overexpression of CD24 is involved in the development and poor prognosis of BC, which can be used as a potential target for the treatment of BC and provide a theoretical basis for the treatment of BC.

RNA biomarkers in cancer therapeutics: The promise of personalized oncology

Cancer therapy is a rapidly evolving and constantly expanding field. Current approaches include surgery, conventional chemotherapy and novel biologic agents as in immunotherapy, that together compose a wide armamentarium. The plethora of choices can, however, be clinically challenging in prescribing the most suitable treatment for any given patient. Fortunately, biomarkers can greatly facilitate the most appropriate selection. In recent years, RNA-based biomarkers have proven most promising. These molecules that range from small noncoding RNAs to protein coding gene transcripts can be valuable in cancer management and especially in cancer therapeutics. Compared to their DNA counterparts which are stable throughout treatment, RNA-biomarkers are dynamic. This allows prediction of success prior to treatment start and can identify alterations in expression that could reflect response. Moreover, improved nucleic acid technology allows RNA to be extracted from practically every biofluid/matrix and evaluated with exceedingly high analytic sensitivity. In addition, samples are largely obtained by minimally invasive procedures and as such can be used serially to assess treatment response real-time. This chapter provides the reader insight on currently known RNA biomarkers, the latest research employing Artificial Intelligence in the identification of such molecules and in clinical decisions driving forward the era of personalized oncology.

From mechanism to therapy: the journey of CD24 in cancer

CD24 is a glycosylphosphatidylinositol-anchored protein that is expressed in a wide range of tissues and cell types. It is involved in a variety of physiological and pathological processes, including cell adhesion, migration, differentiation, and apoptosis. Additionally, CD24 has been studied extensively in the context of cancer, where it has been found to play a role in tumor growth, invasion, and metastasis. In recent years, there has been growing interest in CD24 as a potential therapeutic target for cancer treatment. This review summarizes the current knowledge of CD24, including its structure, function, and its role in cancer. Finally, we provide insights into potential clinical application of CD24 and discuss possible approaches for the development of targeted cancer therapies.

EpCAM-CD24+ circulating cells associated with poor prognosis in breast cancer patients

Following the discovery of circulating tumor cells (CTCs) in the peripheral blood of cancer patients, CTCs were initially postulated to hold promise as a valuable prognostic tool through liquid biopsy. However, a decade and a half of accumulated data have revealed significant complexities in the investigation of CTCs. A challenging aspect lies in the reduced expression or complete loss of key epithelial markers during the epithelial-mesenchymal transition (EMT). This likely hampers the identification of a pathogenetically significant subset of CTCs. Nevertheless, there is a growing body of evidence regarding the prognostic value of such molecules as CD24 expressing in the primary breast tumor. Herewith, the exact relevance of CD24 expression on CTCs remains unclear. We used two epithelial markers (EpCAM and cytokeratin 7/8) to assess the count of CTCs in 57 breast cancer patients, both with (M0mts) and without metastasis (M0) during the follow-up period, as well as in M1 breast cancer patients. However, the investigation of these epithelial markers proved ineffective in identifying cell population expressing different combinations of EpCAM and cytokeratin 7/8 with prognostic significance for breast cancer metastases. Surprisingly, we found CD24+ circulating cells (CCs) in peripheral blood of breast cancer patients which have no epithelial markers (EpCAM and cytokeratin 7/8) but was strongly associated with distant metastasis. Namely, the count of CD45-EpCAM-CK7/8-CD24+ N-cadherin-CCs was elevated in both groups of patients, those with existing metastasis and those who developed metastases during the follow-up period. Simultaneously, an elevation in these cell counts beyond the established threshold of 218.3 cells per 1 mL of blood in patients prior to any treatment predicted a 12-fold risk of metastases, along with a threefold decrease in distant metastasis-free survival over a 90-month follow-up period. The origin of CD45-EpCAM-CK7/8-CD24+ N-cadherin-CCs remains unclear. In our opinion their existence can be explained by two most probable hypotheses. These cells could exhibit a terminal EMT phenotype, or it might be immature cells originating from the bone marrow. Nonetheless, if this hypothesis holds true, it's worth noting that the mentioned CCs do not align with any of the recognized stages of monocyte or neutrophil maturation, primarily due to the presence of CD45 expression in the myeloid cells. The results suggest the presence in the peripheral blood of patients with metastasis (both during the follow-up period and prior to inclusion in the study) of a cell population with a currently unspecified origin, possibly arising from both myeloid and tumor sources, as confirmed by the presence of aneuploidy.

An atlas of causal and mechanistic drivers of interpatient heterogeneity in glioma

Grade IV glioma, formerly known as glioblastoma multiforme (GBM) is the most aggressive and lethal type of brain tumor, and its treatment remains challenging in part due to extensive interpatient heterogeneity in disease driving mechanisms and lack of prognostic and predictive biomarkers. Using mechanistic inference of node-edge relationship (MINER), we have analyzed multiomics profiles from 516 patients and constructed an atlas of causal and mechanistic drivers of interpatient heterogeneity in GBM (gbmMINER). The atlas has delineated how 30 driver mutations act in a combinatorial scheme to causally influence a network of regulators (306 transcription factors and 73 miRNAs) of 179 transcriptional "programs", influencing disease progression in patients across 23 disease states. Through extensive testing on independent patient cohorts, we share evidence that a machine learning model trained on activity profiles of programs within gbmMINER significantly augments risk stratification, identifying patients who are super-responders to standard of care and those that would benefit from 2 nd line treatments. In addition to providing mechanistic hypotheses regarding disease prognosis, the activity of programs containing targets of 2 nd line treatments accurately predicted efficacy of 28 drugs in killing glioma stem-like cells from 43 patients. Our findings demonstrate that interpatient heterogeneity manifests from differential activities of transcriptional programs, providing actionable strategies for mechanistically characterizing GBM from a systems perspective and developing better prognostic and predictive biomarkers for personalized medicine.

Oleanolic acid inhibits the tumor progression by regulating Lactobacillus through the cytokine-cytokine receptor interaction pathway in 4T1-induced mice breast cancer model

The therapeutic mechanism of oleanolic acid (OA) in breast cancer has been widely reported, but little has been known about the combined effects of transcriptome and gut microbiome. In this study, the phenotypic effect of oleanolic acid on mice was tested at the end of the administration cycle, and RNA sequencing on murine tumor tissue and 16S-rRNA sequencing on intestinal contents were conducted to analyze gene expression profiles and microbial diversity between the control group and OA treated group using 4T1-induced mice breast cancer model. As a result, it has been confirmed that oleanolic acid would play a significant inhibitory effect on the development of breast tumors in mice. Based on the integrative analysis of the transcriptomic and metagenomic data, it was found that the abundance of Lactobacillus in the intestinal flora of mice significantly increased in the OA group. Moreover, the up-regulation of Il10 had a significant effect on inhibiting the tumor progression, which played a role through cytokine-cytokine receptor interaction pathway.

ELF5: A Molecular Clock for Breast Aging and Cancer Susceptibility

Breast cancer is predominantly an age-related disease, with aging serving as the most significant risk factor, compounded by germline mutations in high-risk genes like BRCA1/2. Aging induces architectural changes in breast tissue, particularly affecting luminal epithelial cells by diminishing lineage-specific molecular profiles and adopting myoepithelial-like characteristics. ELF5 is an important transcription factor for both normal breast and breast cancer development. This review focuses on the role of ELF5 in normal breast development, its altered expression throughout aging, and its implications in cancer. It discusses the lineage-specific expression of ELF5, its regulatory mechanisms, and its potential as a biomarker for breast-specific biological age and cancer risk.

ELF5 drives angiogenesis suppression though stabilizing WDTC1 in renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is a common malignant tumor of the urinary system. Angiogenesis is a main contributing factor for tumorigenesis. E74-like transcription factor 5 (ELF5) has been verified to participate in the progression of different cancers and can regulate angiogenesis. This study was aimed to explore the functions of ELF5 in RCC.

METHODS

Bioinformatics tools were used to predict the expression of ELF5 in RCC. RT-qPCR was applied for testing ELF5 expression in RCC cells. Cell behaviors were evaluated by colony formation, CCK-8, and transwell assays. The tube formation assay was used for determining angiogenesis. Methylation-specific PCR (MSP) was utilized for measuring the methylation level of ELF5 in RCC cells. ChIP and luciferase reporter assays were applied for assessing the binding of ELF5 and ubiquitin-specific protease 3 (USP3). Co-IP and GST pull-down were utilized for detecting the interaction of WD40 and tetratricopeptide repeats 1 (WDTC1) and USP3. Ubiquitination level of WDTC1 was determined by ubiquitination assay.

RESULTS

ELF5 was lowly expressed in RCC cells and tissues. High expression of ELF5 expression notably suppressed RCC cell proliferative, migratory, and invasive capabilities, and inhibited angiogenesis. The tumor growth in mice was inhibited by ELF5 overexpression. ELF5 was highly methylated in RCC samples, and DNA methyltransferases (DNMTs) can promote hypermethylation level of ELF5 in RCC cells. ELF5 was further proved to transcriptionally activate USP3 in RCC. Moreover, USP3 inhibited WDTC1 ubiquitination. ELF5 can promote USP3-mediated WDTC1 stabilization. Additionally, WDTC1 silencing reversed the functions of ELF5 overexpression on RCC progression.

CONCLUSION

Downregulation of ELF5 due to DNA hypermethylation inhibits RCC development though the USP3/WDTC1axis in RCC.

Targeting CD24 as a novel immunotherapy for solid cancers

Cluster of differentiation 24 (CD24), a mucin-like highly glycosylated molecule has been extensively studied as a cancer stem cell marker in a variety of solid cancers. The functional role of CD24 is either fulfilled by combining with ligands or participating in signal transduction, which mediate the initiation and progression of neoplasms. Recently, CD24 was also described as an innate immune checkpoint with apparent significance in several types of solid cancers. Herein, we review the current understanding of the molecular fundamentals of CD24, the role of CD24 in tumorigenesis and cancer progression, the possibility as a promising therapeutic target and summarized different therapeutic agents or strategies targeting CD24 in solid cancers. Video Abstract.

TF-Prioritizer: a Java pipeline to prioritize condition-specific transcription factors

BACKGROUND

Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic datasets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multimodal datasets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., chromatin immunoprecipitation [ChIP], ATAC, or DNase sequencing) and RNA sequencing data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.

RESULTS

We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multimodal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE datasets for cell lines K562 and MCF-7, including 12 histone modification ChIP sequencing as well as ATAC and DNase sequencing datasets, where we observe and discuss assay-specific differences.

CONCLUSION

TF-Prioritizer accepts ATAC, DNase, or ChIP sequencing and RNA sequencing data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.