MELK Inhibition Effectively Suppresses Growth of Glioblastoma and Cancer Stem-Like Cells by Blocking AKT and FOXM1 Pathways

CPI203, a BET inhibitor, down-regulates a consistent set of DNA synthesis genes across a wide array of glioblastoma lines

INTRODUCTION

Glioblastomas utilize malignant gene expression pathways to drive growth. Many of these gene pathways are not directly accessible with molecularly targeted pharmacological agents. Chromatin-modifying compounds can alter gene expression and target glioblastoma growth pathways. In this study, we utilize a systematic screen of chromatin-modifying compounds on a panel of patient-derived glioblastoma lines to identify promising compounds and their associated gene targets.

METHODS

Five glioblastoma cell lines were subjected to a drug screen of 106 chromatin-modifying compounds representing 36 unique drug classes to determine the twelve most promising drug classes and the best candidate inhibitors in each class. These twelve drugs were then tested with a panel of twelve patient-derived gliomasphere lines to identify growth inhibition and corresponding gene expression patterns. Overlap analysis and weighted co-expression network analysis (WCGNA) were utilized to determine potential target genes and gene pathways.

RESULTS

The initial drug screen identified twelve candidate pharmacologic agents for further testing. Drug sensitivity testing indicated an overall high degree of variability between gliomasphere lines. However, CPI203 was the most consistently effective compound, and the BET inhibitor class was the most consistently effective class of compounds across the gliomasphere panel. Correspondingly, most of the compounds tested had highly variable effects on gene expression between gliomasphere lines. CPI203 stood out as the only compound to induce a consistent effect on gene expression across different gliomasphere lines, specifically down-regulation of DNA-synthesis genes. Amongst the twelve tested cell lines, high expression of CDKN2A and CDKN2B distinguished more drug sensitive from more drug resistant lines. WCGNA identified two oncogenic gene modules (FBXO5 and MELK) that were effectively downregulated by CPI203 (FBXO5) and ML228 (FBXO5 and MELK).

CONCLUSIONS

The bromodomain inhibitor CPI203 induced relatively consistent effects on gene expression and growth across a variety of glioblastoma lines, specifically down-regulating genes associated with DNA replication. We propose that clinically effective BET inhibitors have the potential to induce consistent beneficial effects across a spectrum of glioblastomas.

N-Glycoside of Indolo[2,3-a]pyrrolo[3,4-c]carbazole LCS1269 Exerts Anti-Glioblastoma Effects by G2 Cell Cycle Arrest and CDK1 Activity Modulation: Molecular Docking Studies, Biological Investigations, and ADMET Prediction

Background/Objectives: Indolo[2,3-a]pyrrolo[3,4-c]carbazole scaffold is successfully used as an efficient structural motif for the design and development of different antitumor agents. In this study, we investigated the anti-glioblastoma therapeutic potential of glycosylated indolocarbazole analog LCS1269 utilizing in vitro, in vivo, and in silico approaches. Methods: Cell viability was estimated by an MTT assay. The distribution of cell cycle phases was monitored using flow cytometry. Mitotic figures were visualized by fluorescence microscopy. Quantitative RT-PCR was used to evaluate the gene expression. The protein expression was assessed by Western blotting. Molecular docking and computational ADMET were approved for the probable protein target simulations and predicted pharmacological assessments, respectively. Results: Our findings clearly suggest that LCS1269 displayed a significant cytotoxic effect against diverse glioblastoma cell lines and patient-derived glioblastoma cultures as well as strongly suppressed xenograft growth in nude mice. LCS1269 exhibited more potent anti-proliferative activity toward glioblastoma cell lines and patient-derived glioblastoma cultures compared to conventional drug temozolomide. We further demonstrated that LCS1269 treatment caused the severe G2 phase arrest of cell cycle in a dose-dependent manner. Mechanistically, we proposed that LCS1269 could affect the CDK1 activity both by targeting active site of this enzyme and indirectly, in particular through the modulation of the Wee1/Myt1 and FOXM1/Plk1 signaling pathways, and via p21 up-regulation. LCS1269 also showed favorable pharmacological characteristics in in silico ADME prediction in comparison with staurosporine, rebeccamycin, and becatecarin as reference drugs. Conclusions: Further investigations of LCS1269 as an anti-glioblastoma medicinal agent could be very promising.

DDX56 promotes EMT and cancer stemness via MELK-FOXM1 axis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major global cause of death, with epithelial-mesenchymal transition (EMT) and cancer stem cell (CSC)-like properties contributing to its metastasis. DEAD box helicase 56 (DDX56) is involved in carcinogenesis, but its role in EMT induction and stem phenotype maintenance is unclear. This study assessed the impact of DDX56 absence on HCC cell stemness and EMT. DDX56 was found to be overexpressed in HCC tissues, correlating with disease stage and prognosis. In vitro, DDX56 stimulated tumor cell proliferation, migration, invasion, EMT, and stemness. It also enhanced maternal embryonic leucine-zipper kinase (MELK)-mediated forkhead box protein M1 (FOXM1) expression, regulating cancer stemness and malignant traits. In vivo, DDX56 knockdown in tumor-bearing mice reduced tumorigenicity and lung metastasis by modulating the MELK-FOXM1 signaling pathway. Collectively, DDX56 initiates stem cell-like traits in HCC and promotes EMT via MELK-FOXM1 activation, shedding light on HCC pathogenesis and suggesting a potential anti-cancer therapeutic target.

AI identifies potent inducers of breast cancer stem cell differentiation based on adversarial learning from gene expression data

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

Role of N6-methyladenosine methylation in glioma: recent insights and future directions

Glioma is the most pervasive intracranial tumor in the central nervous system (CNS), with glioblastoma (GBM) being the most malignant type having a highly heterogeneous cancer cell population. There is a significantly high mortality rate in GBM patients. Molecular biomarkers related to GBM malignancy may have prognostic values in predicting survival outcomes and therapeutic responses, especially in patients with high-grade gliomas. In particular, N6-methyladenine (m6A) mRNA modification is the most abundant form of post-transcriptional RNA modification in mammals and is involved in regulating mRNA translation and degradation. Cumulative findings indicate that m6A methylation plays a crucial part in neurogenesis and glioma pathogenesis. In this review, we summarize recent advances regarding the functional significance of m6A modification and its regulatory factors in glioma occurrence and progression. Significant advancement of m6A methylation-associated regulators as potential therapeutic targets is also discussed.

Forkhead box transcription factors (FOXOs and FOXM1) in glioma: from molecular mechanisms to therapeutics

Glioma is the most aggressive and malignant type of primary brain tumor, comprises the majority of central nervous system deaths, and is categorized into different subgroups according to its histological characteristics, including astrocytomas, oligodendrogliomas, glioblastoma multiforme (GBM), and mixed tumors. The forkhead box (FOX) transcription factors comprise a collection of proteins that play various roles in numerous complex molecular cascades and have been discovered to be differentially expressed in distinct glioma subtypes. FOXM1 and FOXOs have been recognized as crucial transcription factors in tumor cells, including glioma cells. Accumulating data indicates that FOXM1 acts as an oncogene in various types of cancers, and a significant part of studies has investigated its function in glioma. Although recent studies considered FOXO subgroups as tumor suppressors, there are pieces of evidence that they may have an oncogenic role. This review will discuss the subtle functions of FOXOs and FOXM1 in gliomas, dissecting their regulatory network with other proteins, microRNAs and their role in glioma progression, including stem cell differentiation and therapy resistance/sensitivity, alongside highlighting recent pharmacological progress for modulating their expression.

Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation, especially synovitis, leading to joint damage. It is important to explore potential biomarkers and therapeutic targets to improve the clinical treatment of RA. However, the potential underlying mechanisms of action of available treatments for RA have not yet been fully elucidated. The present study investigated the potential biomarkers of RA and identified specific targets for therapeutic intervention. A comprehensive analysis was performed using mRNA files downloaded from the Gene Expression Omnibus. Differences in gene expression were analyzed and compared between the normal and RA groups. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on differentially expressed genes (DEGs). A protein-protein interaction network, Molecular Complex Detection and cytoHubba network were evaluated to identify hub genes. Finally, using an experimental RA rat model induced by Freund's complete adjuvant (FCA), the expression of potential biomarkers or target genes in RA were verified through reverse transcription-quantitative PCR. The results of the mRNA dataset processing revealed 195 DEGs in patients with RA when compared with the healthy controls. Moreover, 10 hub genes were identified in patients with RA and four candidate mRNAs were identified, as follows: Discs large homolog-associated protein 5 (DLGAP5), kinesin family member 20A (KIF20A), maternal embryonic leucine zipper kinase (MELK) and nuclear division cycle 80 (NDC80). Finally, the bioinformatics analysis results were validated by quantifying the expression of the DLGAP5, KIF20A, MELK and NDC80 genes in the FCA-induced experimental RA rat model. The findings of the present study suggested that the treatment of RA may be successful through the inhibition of DLGAP5, KIF20A, MELK and NDC80 expression. Therefore, the targeting of these genes may result in more effective treatments for patients with RA.

Differential expression of the circadian clock network correlates with tumour progression in gliomas

BACKGROUND

Gliomas are tumours arising mostly from astrocytic or oligodendrocytic precursor cells. These tumours are classified according to the updated WHO classification from 2021 in 4 grades depending on molecular and histopathological criteria. Despite novel multimodal therapeutic approaches, the vast majority of gliomas (WHO grade III and IV) are not curable. The circadian clock is an important regulator of numerous cellular processes and its dysregulation had been found during the progression of many cancers, including gliomas.

RESULTS

In this study, we explore expression patterns of clock-controlled genes in low-grade glioma (LGG) and glioblastoma multiforme (GBM) and show that a set of 45 clock-controlled genes can be used to distinguish GBM from normal tissue. Subsequent analysis identified 17 clock-controlled genes with a significant association with survival. The results point to a loss of correlation strength within elements of the circadian clock network in GBM compared to LGG. We further explored the progression patterns of mutations in LGG and GBM, and showed that tumour suppressor APC is lost late both in LGG and GBM. Moreover, HIF1A, involved in cellular response to hypoxia, exhibits subclonal losses in LGG, and TERT, involved in the formation of telomerase, is lost late in the GBM progression. By examining multi-sample LGG data, we find that the clock-controlled driver genes APC, HIF1A, TERT and TP53 experience frequent subclonal gains and losses.

CONCLUSIONS

Our results show a higher level of disrgulation at the gene expression level in GBM compared to LGG, and indicate an association between the differentially expressed clock-regulated genes and patient survival in both LGG and GBM. By reconstructing the patterns of progression in LGG and GBM, our data reveals the relatively late gains and losses of clock-regulated glioma drivers. Our analysis emphasizes the role of clock-regulated genes in glioma development and progression. Yet, further research is needed to asses their value in the development of new treatments.

Identification, characterization, and prognosis investigation of pivotal genes shared in different stages of breast cancer

One of the leading causes of death (20.1 per 100,000 women per year), breast cancer is the most prevalent cancer in females. Statistically, 95% of breast cancer are categorized as adenocarcinomas, and 55% of all patients may go into invasive phases; however, it can be successfully treated in approximately 70-80% of cases if diagnosed in the nascent stages. The emergence of breast tumor cells which are intensely resistant to conventional therapies, along with the high rate of metastasis occurrence, has highlighted the importance of finding novel strategies and treatments. One of the most advantageous schemes to alleviate this complication is to identify the common differentially expressed genes (DEGs) among primary and metastatic cancerous cells to use resultants for designing new therapeutic agents which are able to target both primary and metastatic breast tumor cells. In this study, the gene expression dataset with accession number GSE55715 was analyzed containing two primary tumor samples, three bone-metastatic samples, and three normal samples to distinguish the up- and down regulated genes in each stage compared to normal cells as control. In the next step, the common upregulated genes between the two experimental groups were detected by Venny online tool. Moreover, gene ontology, functions and pathways, gene-targeting microRNA, and influential metabolites were determined using EnrichR 2021 GO, KEGG pathways miRTarbase 2017, and HMDB 2021, respectively. Furthermore, elicited from STRING protein-protein interaction networks were imported to Cytoscape software to identify the hub genes. Then, identified hub genes were checked to validate the study using oncological databases. The results of the present article disclosed 1263 critical common DEGs (573 upregulated + 690 downregulated), including 35 hub genes that can be broadly used as new targets for cancer treatment and as biomarkers for cancer detection by evaluation of expression level. Besides, this study opens a new horizon to reveal unknown aspects of cancer signaling pathways by providing raw data evoked from in silico experiments. This study's outcomes can also be widely utilized in further lab research since it contains diverse information on common DEGs of varied stages and metastases of breast cancer, their functions, structures, interactions, and associations.

Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if it reaches the metastatic phase. The novelty of the present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was conducted using RNA-seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. A promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability, leading to improper chromosome segregation, causing aneuploidy. A 13-gene predictive model was obtained and validated using a KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis.

UBA1 inhibition contributes radiosensitization of glioblastoma cells via blocking DNA damage repair

Glioblastoma multiforme (GBM) is a brain tumor with high mortality and recurrence rate. Radiotherapy and chemotherapy after surgery are the main treatment options available for GBM. However, patients with glioblastoma have a grave prognosis. The major reason is that most GBM patients are resistant to radiotherapy. UBA1 is considered an attractive potential anti-tumor therapeutic target and a key regulator of DNA double-strand break repair and genome replication in human cells. Therefore, we hypothesized that TAK-243, the first-in-class UBA1 inhibitor, might increase GBM sensitivity to radiation. The combined effect of TAK-243 and ionizing radiation on GBM cell proliferation, and colony formation ability was detected using CCK-8, colony formation, and EdU assays. The efficacy of TAK-243 combined with ionizing radiation for GBM was further evaluated in vivo, and the mechanism of TAK-243 sensitizing radiotherapy was preliminarily discussed. The results showed that TAK-243, in combination with ionizing radiation, significantly inhibited GBM cell proliferation, colony formation, cell cycle arrest in the G2/M phase, and increased the proportion of apoptosis. In addition, UBA1 inhibition by TAK-243 substantially increased the radiation-induced γ-H2AX expression and impaired the recruitment of the downstream effector molecule 53BP1. Therefore, TAK-243 inhibited the radiation-induced DNA double-strand break repair and thus inhibited the growth of GBM cells. Our results provided a new therapeutic strategy for improving the radiation sensitivity of GBM and laid a theoretical foundation and experimental basis for further clinical trials.

Comprehensive Analyses of MELK-Associated ceRNA Networks Reveal a Potential Biomarker for Predicting Poor Prognosis and Immunotherapy Efficacy in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with high morbidity and mortality. Identifying specific molecular markers that can predict HCC prognosis is extremely important. MELK has been reported to play key roles in several types of human cancers and predict poor prognosis. This study was aimed to explore the impact of MELK on HCC.

Methods: A pan-cancer analysis of MELK was conducted by The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) data. The prognosis of MELK in various cancers was analyzed in GEPIA. Then, a ceRNA network of MELK was constructed based on the comprehensive consideration of the expression analysis, the correlation analysis, and the survival analysis by R software. The correlation of MELK and immune cell infiltration was analyzed by TIMER and CIBERSORT. Then, the overall survival of differentially expressed immune cells was conducted. The correlation of MELK and immune checkpoints expression was analyzed by GEPIA.

Results: MELK was overexpressed in 14 types of human cancers, and its expression was significantly higher than that in both unmatched and paired normal samples in HCC. Higher MELK expression was correlated with poorer survival and advanced clinical stage, topography (T) stage, and histological grade. The univariate and multivariate Cox regression analyses showed that MELK was an independent risk factor for poor prognosis in HCC. Then, we constructed a ceRNA network consisting of MELK, miR-101-3p, and two lncRNAs (SNHG1 and SNHG6) after evaluating the expression and impact on prognosis in HCC of these RNAs. TIMER and CIBERSORT databases indicated that MELK was correlated with various immune cells including B cells, CD8+ T cells, CD4+ T cells, macrophage, neutrophil, and dendritic cells in HCC. Of them, B cells, CD4+ T cells, macrophage, and neutrophil were related to the prognosis of HCC. In addition, MELK was significantly positively correlated with the immune checkpoint genes.

Conclusions: MELK may be a novel potential biomarker for predicting prognosis and immunotherapy efficacy in patients with HCC. Our study may provide new molecular and therapeutic strategies for the treatment of HCC patients.

xCT contributes to colorectal cancer tumorigenesis through upregulation of the MELK oncogene and activation of the AKT/mTOR cascade

Colorectal cancer (CRC) is one of the most commonly diagnosed and deadly malignant tumors globally, and its occurrence and progression are closely related to the poor histological features and complex molecular characteristics among patients. It is urgent to identify specific biomarkers for effective treatment of CRC. In this study, we performed comprehensive experiments to validate the role of xCT expression in CRC tumorigenesis and stemness and confirmed xCT knockdown significantly suppressed the proliferation, migration, and stemness of CRC cells in vitro and effectively inhibited CRC tumorigenesis and metastasis in vivo. In addition, bioinformatic analysis and luciferase assays were used to identify E2F1 as a critical upstream transcription factor of SLC7A11 (the gene encoding for xCT) that facilitated CRC progression and cell stemness. Subsequent RNA sequencing, western blotting, rescue assay, and immunofluorescence assays revealed MELK directly co-expressed with xCT in CRC cells, and its upregulation significantly attenuated E2F1/xCT-mediated tumorigenesis and stemness in CRC. Further molecular mechanism exploration confirmed that xCT knockdown may exert an antitumor effect by controlling the activation of MELK-mediated Akt/mTOR signaling. Erastin, a specific inhibitor of xCT, was also proven to effectively inhibit CRC tumorigenesis and cell stemness. Altogether, our study showed that E2F1/xCT is a promising therapeutic target of CRC that promotes tumorigenesis and cell stemness. Erastin is also an effective antitumoral agent for CRC.

Csnk1a1 inhibition modulates the inflammatory secretome and enhances response to radiotherapy in glioma

Glioblastoma multiforme (GBM), a fatal brain tumour with no available targeted therapies, has a poor prognosis. At present, radiotherapy is one of the main methods to treat glioma, but it leads to an obvious increase in inflammatory factors in the tumour microenvironment, especially IL-6 and CXCL1, which plays a role in tumour to resistance radiotherapy and tumorigenesis. Casein kinase 1 alpha 1 (CK1α) (encoded on chromosome 5q by Csnk1a1) is considered an attractive target for Tp53 wild-type acute myeloid leukaemia (AML) treatment. In this study, we evaluated the anti-tumour effect of Csnk1a1 suppression in GBM cells in vitro and in vivo. We found that down-regulation of Csnk1a1 or inhibition by D4476, a Csnk1a1 inhibitor, reduced GBM cell proliferation efficiently in both Tp53 wild-type and Tp53-mutant GBM cells. On the contrary, overexpression of Csnk1a1 promoted cell proliferation and colony formation. Csnk1a1 inhibition improved the sensitivity to radiotherapy. Furthermore, down-regulation of Csnk1a1 reduced the production and secretion of pro-inflammatory factors. In the preclinical GBM model, treatment with D4476 significantly inhibited the increase in pro-inflammatory factors caused by radiotherapy and improved radiotherapy sensitivity, thus inhibiting tumour growth and prolonging animal survival time. These results suggest targeting Csnk1a1 exert an anti-tumour role as an inhibitor of inflammatory factors, providing a new strategy for the treatment of glioma.

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

Background

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.

Methods

We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.

Results

With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.

Conclusions

In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08173-0.