FoxM1 is a promising candidate target in the treatment of breast cancer

A computational and structural approach to identify malignant non-synonymous FOXM1 single nucleotide polymorphisms in triple-negative breast cancer

The proliferation-specific oncogenic transcription factor, FOXM1 is overexpressed in primary and recurrent breast tumors across all breast cancer (BC) subtypes. Intriguingly, FOXM1 overexpression was found to be highest in Triple-negative breast cancer (TNBC), the most aggressive BC with the worst prognosis. However, FOXM1-mediated TNBC pathogenesis is not completely elucidated. Single nucleotide polymorphisms (SNPs) are the most common genetic variations causing functional and structural aberrations in proteins enhancing cancer susceptibility. This computational investigation attempted to identify the malignant FOXM1 non-synonymous SNPs (nsSNPs) and evaluate their role in affecting the conformational and functional stability, evolutionary conservation, post-translational modifications, and malignant susceptibility of the protein. Out of a huge data pool of 8826 FOXM1 SNPs using several in-silico sequence-based tools and structural approaches, four SNPs viz. E235Q, R256C, G429E and S756P were identified as pathogenic nsSNPs and among the shortlisted variants molecular dynamics simulations identified E235Q as the most damaging malignant SNP, followed by S756P. Additionally, the defective drug and DNA binding motif of E235Q and S756P were also determined in our study. Thus, although further in-vitro validations are awaited the findings of this in-silico work can be used as a blueprint for malignant nsSNP identification of FOXM1 aiding in clinical TNBC therapeutics.

DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways

SIGNIFICANCE

DeePathNet integrates cancer-specific biological pathways using transformer-based deep learning for enhanced cancer analysis. It outperforms existing models in predicting drug responses, cancer types, and subtypes. By enabling pathway-level biomarker discovery, DeePathNet represents a significant advancement in cancer research and could lead to more effective treatments.

EZH2 PROTACs target EZH2- and FOXM1-associated oncogenic nodes, suppressing breast cancer cell growth

Breast cancer (BC) remains the second leading cause of cancer-related mortalities in women. Resistance to hormone therapies such as tamoxifen, an estrogen receptor (ER) inhibitor, is a major hurdle in the treatment of BC. Enhancer of zeste homolog 2 (EZH2), the methyltransferase component of the Polycomb repressive complex 2 (PRC2), has been implicated in tamoxifen resistance. Evidence suggests that EZH2 often functions noncanonically, in a methyltransferase-independent manner, as a transcription coactivator through interacting with oncogenic transcription factors. Unlike methyltransferase inhibitors, proteolysis targeting chimeras (PROTAC) can suppress both activating and repressive functions of EZH2. Here, we find that EZH2 PROTACs, MS177 and MS8815, effectively inhibited the growth of BC cells, including those with acquired tamoxifen resistance, to a much greater degree when compared to methyltransferase inhibitors. Mechanistically, EZH2 associates with forkhead box M1 (FOXM1) and binds to the promoters of FOXM1 target genes. EZH2 PROTACs induce degradation of both EZH2 and FOXM1, leading to reduced expression of target genes involved in cell cycle progression and tamoxifen resistance. Together, this study supports that EZH2-targeted PROTACs represent a promising avenue of research for the future treatment of BC, including in the setting of tamoxifen resistance.

In silico identification and in vitro evaluation of MRPS30-DT lncRNA and MRPS30 gene expression in breast cancer

BACKGROUND

It has been reported that long non-coding RNAs (lncRNAs) can play important roles in a variety of biological processes and cancer regulatory networks, including breast cancer.

AIMS

This study aimed to identify a novel upregulated lncRNA in breast cancer and its associated gene using bioinformatics analysis, and then evaluate their potential roles in breast cancer.

METHODS AND RESULTS

Extensive in silico studies were performed using various bioinformatics databases and tools to identify a potential upregulated breast cancer-associated lncRNA and its co-expressed gene, and to predict their potential roles, functions, and interactions. The expression level of MRPS30-DT lncRNA and MRPS30 was assessed in both BC tissues and cell lines using qRT-PCR technology. MRPS30-DT lncRNA and MRPS30 were selected as target genes using bioinformatics analysis. We found that MRPS30-DT and MRPS30 were significantly overexpressed in BC tissues compared with normal tissues. Also, MRPS30 showed upregulation in all three BC cell lines compared with HDF. On the other hand, MRPS30-DT significantly increased in MDA-MB-231 compared with HDF. While the expression of MRPS30-DT was significantly dropped in the resistance cell line MCF/MX compared to HDF and MCF7. Moreover, bioinformatics analysis suggested that MRPS30-DT and MRPS30 may play a potential role in BC through their involvement in some cancer signaling pathways and processes, as well as through their interaction with TFs, genes, miRNAs, and proteins related to carcinogenesis.

CONCLUSIONS

Overall, our findings showed the dysregulation of MRPS30-DT lncRNA and MRPS30 may provide clues for exploring new therapeutic targets or molecular biomarkers in BC.

Biologically informed NeuralODEs for genome-wide regulatory dynamics

BACKGROUND

Gene regulatory network (GRN) models that are formulated as ordinary differential equations (ODEs) can accurately explain temporal gene expression patterns and promise to yield new insights into important cellular processes, disease progression, and intervention design. Learning such gene regulatory ODEs is challenging, since we want to predict the evolution of gene expression in a way that accurately encodes the underlying GRN governing the dynamics and the nonlinear functional relationships between genes. Most widely used ODE estimation methods either impose too many parametric restrictions or are not guided by meaningful biological insights, both of which impede either scalability, explainability, or both.

RESULTS

We developed PHOENIX, a modeling framework based on neural ordinary differential equations (NeuralODEs) and Hill-Langmuir kinetics, that overcomes limitations of other methods by flexibly incorporating prior domain knowledge and biological constraints to promote sparse, biologically interpretable representations of GRN ODEs. We tested the accuracy of PHOENIX in a series of in silico experiments, benchmarking it against several currently used tools. We demonstrated PHOENIX's flexibility by modeling regulation of oscillating expression profiles obtained from synchronized yeast cells. We also assessed the scalability of PHOENIX by modeling genome-scale GRNs for breast cancer samples ordered in pseudotime and for B cells treated with Rituximab.

CONCLUSIONS

PHOENIX uses a combination of user-defined prior knowledge and functional forms from systems biology to encode biological "first principles" as soft constraints on the GRN allowing us to predict subsequent gene expression patterns in a biologically explainable manner.

Biologically informed NeuralODEs for genome-wide regulatory dynamics

Modeling dynamics of gene regulatory networks using ordinary differential equations (ODEs) allow a deeper understanding of disease progression and response to therapy, thus aiding in intervention optimization. Although there exist methods to infer regulatory ODEs, these are generally limited to small networks, rely on dimensional reduction, or impose non-biological parametric restrictions - all impeding scalability and explainability. PHOENIX is a neural ODE framework incorporating prior domain knowledge as soft constraints to infer sparse, biologically interpretable dynamics. Extensive experiments - on simulated and real data - demonstrate PHOENIX's unique ability to learn key regulatory dynamics while scaling to the whole genome.

Role of Fork-Head Box Genes in Breast Cancer: From Drug Resistance to Therapeutic Targets

Breast cancer has been acknowledged as one of the most notorious cancers, responsible for millions of deaths around the globe. Understanding the various factors, genetic mutations, comprehensive pathways, etc., that are involved in the development of breast cancer and how these affect the development of the disease is very important for improving and revitalizing the treatment of this global health issue. The forkhead-box gene family, comprising 19 subfamilies, is known to have a significant impact on the growth and progression of this cancer. The article looks into the various forkhead genes and how they play a role in different types of cancer. It also covers their impact on cancer drug resistance, interaction with microRNAs, explores their potential as targets for drug therapies, and their association with stem cells.

Effective combination treatments for breast cancer inhibition by FOXM1 inhibitors with other targeted cancer drugs

PURPOSE

Few targeted treatment options currently exist for patients with advanced, often recurrent breast cancers, both triple-negative breast cancer (TNBC) and hormone receptor-positive breast cancer. Forkhead box M1 (FOXM1) is an oncogenic transcription factor that drives all cancer hallmarks in all subtypes of breast cancer. We previously developed small-molecule inhibitors of FOXM1 and to further exploit their potential as anti-proliferative agents, we investigated combining FOXM1 inhibitors with drugs currently used in the treatment of breast and other cancers and assessed the potential for enhanced inhibition of breast cancer.

METHODS

FOXM1 inhibitors alone and in combination with other cancer therapy drugs were assessed for their effects on suppression of cell viability and cell cycle progression, induction of apoptosis and caspase 3/7 activity, and changes in related gene expressions. Synergistic, additive, or antagonistic interactions were evaluated using ZIP (zero interaction potency) synergy scores and the Chou-Talalay interaction combination index.

RESULTS

The FOXM1 inhibitors displayed synergistic inhibition of proliferation, enhanced G2/M cell cycle arrest, and increased apoptosis and caspase 3/7 activity and associated changes in gene expression when combined with several drugs across different pharmacological classes. We found especially strong enhanced effectiveness of FOXM1 inhibitors in combination with drugs in the proteasome inhibitor class for ER-positive and TNBC cells and with CDK4/6 inhibitors (Palbociclib, Abemaciclib, and Ribociclib) in ER-positive cells.

CONCLUSION

The findings suggest that the combination of FOXM1 inhibitors with several other drugs might enable dose reduction in both agents and provide enhanced efficacy in treatment of breast cancer.

Biologically informed NeuralODEs for genome-wide regulatory dynamics

Models that are formulated as ordinary differential equations (ODEs) can accurately explain temporal gene expression patterns and promise to yield new insights into important cellular processes, disease progression, and intervention design. Learning such ODEs is challenging, since we want to predict the evolution of gene expression in a way that accurately encodes the causal gene-regulatory network (GRN) governing the dynamics and the nonlinear functional relationships between genes. Most widely used ODE estimation methods either impose too many parametric restrictions or are not guided by meaningful biological insights, both of which impedes scalability and/or explainability. To overcome these limitations, we developed PHOENIX, a modeling framework based on neural ordinary differential equations (NeuralODEs) and Hill-Langmuir kinetics, that can flexibly incorporate prior domain knowledge and biological constraints to promote sparse, biologically interpretable representations of ODEs. We test accuracy of PHOENIX in a series of in silico experiments benchmarking it against several currently used tools for ODE estimation. We also demonstrate PHOENIX's flexibility by studying oscillating expression data from synchronized yeast cells and assess its scalability by modelling genome-scale breast cancer expression for samples ordered in pseudotime. Finally, we show how the combination of user-defined prior knowledge and functional forms from systems biology allows PHOENIX to encode key properties of the underlying GRN, and subsequently predict expression patterns in a biologically explainable way.

Effects of thiostrepton alone or in combination with selumetinib on triple-negative breast cancer metastasis

OBJECTIVE

FoxM1 transcription factor contributes to tumor metastasis and poor prognosis in many cancers including triple-negative breast cancer (TNBC). In this study, we examined the effects of FoxM1 inhibitor Thiostrepton (THIO) alone or in combination with MEK inhibitor Selumetinib (SEL) on metastatic parameters in vitro and in vivo.

METHODS

Cell viability was determined by MTT assay. Immunoblotting and immunohistochemistry was used to assess metastasis-related protein expressions in 4T1 cells and its allograft tumor model in BALB/c mice. In vivo uPA activity was determined by enzymatic methods.

RESULTS

Both inhibitors were effective on the expressions of FoxM1, ERK, p-ERK, Twist, E-cadherin, and Vimentin alone or in combination in vitro. THIO significantly decreased 4T1 cell migration and changed the cell morphology from mesenchymal-like to epithelial-like structure. THIO was more effective than in combination with SEL in terms of metastatic protein expressions in vivo. THIO alone significantly inhibited mean tumor growth, decreased lung metastasis rate and tumor foci, however, no significant changes in these parameters were observed in the combined group. Immunohistochemically, FoxM1 expression intensity was decreased with THIO and its combination with SEL in the tumors.

CONCLUSIONS

This study suggests that inhibiting FoxM1 as a single target is more effective than combined treatment with MEK in theTNBC allograft model. The therapeutic efficacy of THIO should be investigated with further studies on appropriate drug delivery systems.

CDI Exerts Anti-Tumor Effects by Blocking the FoxM1-DNA Interaction

The Forkhead box protein M1 (FoxM1) is an appealing target for anti-cancer therapeutics as this cell proliferation-associated transcription factor is overexpressed in most human cancers. FoxM1 is involved in tumor invasion, angiogenesis, and metastasis. To discover novel inhibitors that disrupt the FoxM1-DNA interaction, we identified CDI, a small molecule that inhibits the FoxM1–DNA interaction. CDI was identified through an assay based on the time-resolved fluorescence energy transfer response of a labeled consensus oligonucleotide that was bound to a recombinant FoxM1-dsDNA binding domain (FoxM1-DBD) protein and exhibited potent inhibitory activity against FoxM1-DNA interaction. CDI suppressed cell proliferation and induced apoptosis in MDA-MB-231 cells obtained from a breast cancer patient. Furthermore, it decreased not only the mRNA and protein expression of FoxM1 but also that of downstream targets such as CDC25b. Additionally, global transcript profiling of MDA-MB-231 cells by RNA-Seq showed that CDI decreases the expression of FoxM1-regulated genes. The docking and MD simulation results indicated that CDI likely binds to the DNA interaction site of FoxM1-DBD and inhibits the function of FoxM1-DBD. These results of CDI being a possible effective inhibitor of FoxM1-DNA interaction will encourage its usage in pharmaceutical applications.

A novel HIF1α-STIL-FOXM1 axis regulates tumor metastasis

BACKGROUND

Metastasis is the major cause of morbidity and mortality in cancer that involves in multiple steps including epithelial-mesenchymal transition (EMT) process. Centrosome is an organelle that functions as the major microtubule organizing center (MTOC), and centrosome abnormalities are commonly correlated with tumor aggressiveness. However, the conclusive mechanisms indicating specific centrosomal proteins participated in tumor progression and metastasis remain largely unknown.

METHODS

The expression levels of centriolar/centrosomal genes in various types of cancers were first examined by in silico analysis of the data derived from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and European Bioinformatics Institute (EBI) datasets. The expression of STIL (SCL/TAL1-interrupting locus) protein in clinical specimens was further assessed by Immunohistochemistry (IHC) analysis and the oncogenic roles of STIL in tumorigenesis were analyzed using in vitro and in vivo assays, including cell migration, invasion, xenograft tumor formation, and metastasis assays. The transcriptome differences between low- and high-STIL expression cells were analyzed by RNA-seq to uncover candidate genes involved in oncogenic pathways. The quantitative polymerase chain reaction (qPCR) and reporter assays were performed to confirm the results. The chromatin immunoprecipitation (ChIP)-qPCR assay was applied to demonstrate the binding of transcriptional factors to the promoter.

RESULTS

The expression of STIL shows the most significant increase in lung and various other types of cancers, and is highly associated with patients' survival rate. Depletion of STIL inhibits tumor growth and metastasis. Interestingly, excess STIL activates the EMT pathway, and subsequently enhances cancer cell migration and invasion. Importantly, we reveal an unexpected role of STIL in tumor metastasis. A subset of STIL translocate into nucleus and associate with FOXM1 (Forkhead box protein M1) to promote tumor metastasis and stemness via FOXM1-mediated downstream target genes. Furthermore, we demonstrate that hypoxia-inducible factor 1α (HIF1α) directly binds to the STIL promoter and upregulates STIL expression under hypoxic condition.

CONCLUSIONS

Our findings indicate that STIL promotes tumor metastasis through the HIF1α-STIL-FOXM1 axis, and highlight the importance of STIL as a promising therapeutic target for lung cancer treatment.

Transcription Regulation and Genome Rewiring Governing Sensitivity and Resistance to FOXM1 Inhibition in Breast Cancer

Forkhead box M1 (FOXM1), an oncogenic transcription factor associated with aggressiveness and highly expressed in many cancers, is an emerging therapeutic target. Using novel 1,1-diarylethylene-diammonium small molecule FOXM1 inhibitors, we undertook transcriptomic, protein, and functional analyses to identify mechanisms by which these compounds impact breast cancer growth and survival, and the changes that occur in estrogen receptor (ERα)-positive and triple negative breast cancer cells that acquire resistance upon long-term treatment with the inhibitors. In sensitive cells, these compounds regulated FOXM1 gene networks controlling cell cycle progression, DNA damage repair, and apoptosis. Resistant cells showed transcriptional alterations that reversed the expression of many genes in the FOXM1 network and rewiring that enhanced inflammatory signaling and upregulated HER2 or EGFR growth factor pathways. ERα-positive breast cancer cells that developed resistance showed greatly reduced ERα levels and responsiveness to fulvestrant and a 10-fold increased sensitivity to lapatinib, suggesting that targeting rewired processes in the resistant state may provide benefits and prolong anticancer effectiveness. Improved understanding of how FOXM1 inhibitors suppress breast cancer and how cancer cells can defeat their effectiveness and acquire resistance should be helpful in directing further studies to move these agents towards translation into the clinic.

Nuclear Mechanisms Involved in Endocrine Resistance

Endocrine therapy is a standard treatment offered to patients with ERα (estrogen receptor α)-positive breast cancer. In endocrine therapy, ERα is either directly targeted by anti-estrogens or indirectly by aromatase inhibitors which cause estrogen deficiency. Resistance to these drugs (endocrine resistance) compromises the efficiency of this treatment and requires additional measures. Endocrine resistance is often caused by deregulation of the PI3K/AKT/mTOR pathway and/or cyclin-dependent kinase 4 and 6 activities allowing inhibitors of these factors to be used clinically to counteract endocrine resistance. The nuclear mechanisms involved in endocrine resistance are beginning to emerge. Exploring these mechanisms may reveal additional druggable targets, which could help to further improve patients' outcome in an endocrine resistance setting. This review intends to summarize our current knowledge on the nuclear mechanisms linked to endocrine resistance.

Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations

Luminal A is the most common breast cancer molecular subtype in women worldwide. These tumors have characteristic yet heterogeneous alterations at the genomic and transcriptomic level. Gene co-expression networks (GCNs) have contributed to better characterize the cancerous phenotype. We have previously shown an imbalance in the proportion of intra-chromosomal (cis-) over inter-chromosomal (trans-) interactions when comparing cancer and healthy tissue GCNs. In particular, for breast cancer molecular subtypes (Luminal A included), the majority of high co-expression interactions connect gene-pairs in the same chromosome, a phenomenon that we have called loss of trans- co-expression. Despite this phenomenon has been described, the functional implication of this specific network topology has not been studied yet. To understand the biological role that communities of co-expressed genes may have, we constructed GCNs for healthy and Luminal A phenotypes. Network modules were obtained based on their connectivity patterns and they were classified according to their chromosomal homophily (proportion of cis-/trans- interactions). A functional overrepresentation analysis was performed on communities in both networks to observe the significantly enriched processes for each community. We also investigated possible mechanisms for which the loss of trans- co-expression emerges in cancer GCN. To this end we evaluated transcription factor binding sites, CTCF binding sites, differential gene expression and copy number alterations (CNAs) in the cancer GCN. We found that trans- communities in Luminal A present more significantly enriched categories than cis- ones. Processes, such as angiogenesis, cell proliferation, or cell adhesion were found in trans- modules. The differential expression analysis showed that FOXM1, CENPA, and CIITA transcription factors, exert a major regulatory role on their communities by regulating expression of their target genes in other chromosomes. Finally, identification of CNAs, displayed a high enrichment of deletion peaks in cis- communities. With this approach, we demonstrate that network topology determine, to at certain extent, the function in Luminal A breast cancer network. Furthermore, several mechanisms seem to be acting together to avoid trans- co-expression. Since this phenomenon has been observed in other cancer tissues, a remaining question is whether the loss of long distance co-expression is a novel hallmark of cancer.

Mistletoe Extract Targets the STAT3-FOXM1 Pathway to Induce Apoptosis and Inhibits Metastasis in Breast Cancer Cells

Mistletoe extracts (Viscum album L.) have been widely used as complementary and alternative medicines for the treatment of cancer, and their cytotoxic effects have been reported on various types of cancer. However, the molecular targets of mistletoe extracts have not been well studied. Herein, we investigated molecules associated with the in vitro and in vivo anticancer effects of mistletoe extract using 4T1 murine breast cancer cells. Mistletoe extract induced apoptosis and inhibited the signal transducer and activator of transcription3 (STAT3) phosphorylation. This inhibition was accompanied by the downregulations of forkhead box M1 (FOXM1) and the DNA repair proteins, RAD51 and survivin. Mistletoe extract simultaneously increased the expression of the DNA damage marker proteins, phosphorylated H2A histone family member X (H2A.X), and phosphorylated p38. Furthermore, mistletoe extract effectively suppressed tumor growth in 4T1 tumor-bearing BALB/c mice. In addition to tumor growth inhibition, mistletoe extract inhibited lung metastasis in the tumor-bearing mice and cell invasiveness by downregulating the expressions of matrix metalloproteinases (MMPs), urokinase-type plasminogen activator (uPA), uPA receptor, and markers of epithelial-mesenchymal transition (snail and fibronectin). Taken together, our results suggest that mistletoe extract targets the STAT3-FOXM1 pathway for its cytotoxic effects, and that mistletoe extracts might be useful for the treatment of patients with cancers highly expressing the STAT3-FOXM1 pathway.

Metabolic Imaging Detects Resistance to PI3Kα Inhibition Mediated by Persistent FOXM1 Expression in ER+ Breast Cancer

PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor (ER)-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. FOXM1 drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II). The downstream metabolic changes can therefore be detected using MRI of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by positron emission tomography measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose. Rapid assessment of treatment response in breast cancer using this imaging method could help identify patients that benefit from PI3Kα inhibition and design drug combinations to counteract the emergence of resistance.

Oleanolic acid inhibits cell proliferation migration and invasion and induces SW579 thyroid cancer cell line apoptosis by targeting forkhead transcription factor A

Oleanolic acid (OA) is a naturally occurring triterpenoid that possesses antitumor activity against several tumor cell lines. However, the potential mechanism underlying OA-induced thyroid carcinoma cell death is poorly understood. We investigated the biological functions of OA by performing migration, invasion, colony formation, and apoptosis assays on SW579 cells. Forkhead box A1 (FOXA1) expression was used to predict poor prognosis in patients with thyroid carcinoma among the TCGA samples from the UALCAN and gene expression profiling interactive analysis databases. Western blot was used to detect protein expression level. Results revealed that OA inhibited the migration, colony formation, and invasion of thyroid carcinoma cells in a dose-dependent manner. Further investigation verified that OA treatment induced significant apoptosis of thyroid carcinoma cells. Moreover, high FOXA1 expression predicted the poor prognosis of patients with thyroid cancer. The proliferation, migration, and invasion of thyroid carcinoma cells were significantly decreased when FOXA1 was silenced. OA significantly increased Akt phosphorylation and reduced FOXA1 expression in SW579 cells, but only PI3K/Akt inhibitor LY294002 attenuated OA-induced FOXA1 downregulation. Furthermore, Akt overexpression suppressed the FOXA1 expression in SW579 cells. In addition, molecular docking assay revealed that OA possessed high affinity toward FOXA1 with a low binding energy. OA may be a potential chemotherapeutic agent against thyroid carcinoma cells.

Suppression of Tumor Growth, Metastasis, and Signaling Pathways by Reducing FOXM1 Activity in Triple Negative Breast Cancer

Simple Summary

Triple negative breast cancer is an aggressive subtype of breast cancer that frequently metastasizes. Because the transcription factor FOXM1 is highly upregulated in triple negative breast cancer and controls many cell activities that lead to cancer progression and metastasis, we sought to determine if FOXM1 inhibitory compounds could effectively suppress the invasiveness and progression of triple negative breast cancer cells and tumors. Our findings show that these compounds inhibit cell motility, invasiveness, and the expression of important proteins associated with epithelial to mesenchymal transition. These compounds also suppressed the proliferation and metastatic outgrowth of triple negative breast tumors. Thus, these findings highlight the crucial role of FOXM1 in promoting the progression and metastasis of these cancers, and suggest that FOXM1 inhibitory compounds may have therapeutic potential and prove beneficial in intervention against triple negative breast cancer.

Abstract

Metastasis-related complications account for the overwhelming majority of breast cancer mortalities. Triple negative breast cancer (TNBC), the most aggressive breast cancer subtype, has a high propensity to metastasize to distant organs, leading to poor patient survival. The forkhead transcription factor, FOXM1, is especially upregulated and overexpressed in TNBC and is known to regulate multiple signaling pathways that control many key cancer properties, including proliferation, invasiveness, stem cell renewal, and therapy resistance, making FOXM1 a critical therapeutic target for TNBC. In this study, we test the effectiveness of a novel class of 1,1-diarylethylene FOXM1 inhibitory compounds in suppressing TNBC cell migration, invasion, and metastasis using in vitro cell culture and in vivo tumor models. We show that these compounds inhibit the motility and invasiveness of TNBC MDA-MB-231 and DT28 cells, along with reducing the expression of important epithelial to mesenchymal transition (EMT) associated genes. Further, orthotopic tumor studies in NOD-SCID-gamma (NSG) mice demonstrate that these compounds reduce FOXM1 expression and suppress TNBC tumor growth as well as distant metastasis. Gene expression and protein analyses confirm the decreased levels of EMT factors and FOXM1-regulated target genes in tumors and metastatic lesions in the inhibitor-treated animals. The findings suggest that these FOXM1 suppressive compounds may have therapeutic potential in treating triple negative breast cancer, with the aim of reducing tumor progression and metastatic outgrowth.

Predicting FOXM1-Mediated Gene Regulation through the Analysis of Genome-Wide FOXM1 Binding Sites in MCF-7, K562, SK-N-SH, GM12878 and ECC-1 Cell Lines

Forkhead box protein M1 (FOXM1) is a key transcription factor (TF) that regulates a common set of genes related to the cell cycle in various cell types. However, the mechanism by which FOXM1 controls the common gene set in different cellular contexts is unclear. In this study, a comprehensive meta-analysis of genome-wide FOXM1 binding sites in ECC-1, GM12878, K562, MCF-7, and SK-N-SH cell lines was conducted to predict FOXM1-driven gene regulation. Consistent with previous studies, different TF binding motifs were identified at FOXM1 binding sites, while the NFY binding motif was found at 81% of common FOXM1 binding sites in promoters of cell cycle-related genes. The results indicated that FOXM1 might control the gene set through interaction with the NFY proteins, while cell type-specific genes were predicted to be regulated by enhancers with FOXM1 and cell type-specific TFs. We also found that the high expression level of FOXM1 was significantly associated with poor prognosis in nine types of cancer. Overall, these results suggest that FOXM1 is predicted to function as a master regulator of the cell cycle through the interaction of NFY-family proteins, and therefore the inhibition of FOXM1 could be an attractive strategy for cancer therapy.

Interpreting pathways to discover cancer driver genes with Moonlight

Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.

Suppression of FOXM1 activities and breast cancer growth in vitro and in vivo by a new class of compounds

The transcription factor FOXM1 is upregulated and overexpressed in aggressive, therapy-resistant forms of hormone receptor-positive and triple negative breast cancers, and is associated with less good patient survival. FOXM1 signaling is also a key driver in many other cancers. Here, we identify a new class of compounds effective in suppressing FOXM1 activity in breast cancers, and displaying good potency for antitumor efficacy. The compounds bind directly to FOXM1 and alter its proteolytic sensitivity, reduce the cellular level of FOXM1 protein by a proteasome- dependent process, and suppress breast cancer cell proliferation and cell cycle progression and increase apoptosis. RNA-seq and gene set enrichment analyses indicate that the compounds decrease expression of FOXM1-regulated genes and suppress gene ontologies under FOXM1 regulation. Several compounds have favorable pharmacokinetic properties and show good tumor suppression in preclinical breast tumor models. These compounds may be suitable for further clinical evaluation in targeting aggressive breast cancers driven by FOXM1.

Transcriptome and Network Dissection of Microsatellite Stable and Highly Instable Colorectal Cancer

Background:

Colorectal cancer (CRC) is one of the most common cancers worldwide with high number of mortality every year. Microsatellite instability (MSI) is a considerable feature of CRC which affects prognosis and treatment. High level of MSI or MSI-high (MSI-H) colorectal cancer has better prognosis and immunotherapy response, while microsatellite stable (MSS) CRC has better response to 5-fluorouracil (5-FU)-based chemotherapy. More studies are needed, specifically on MSS CRC which has worse prognosis, to further reveal biological differences and similarities between MSS and MSI colorectal cancer, which may equip us with the knowledge to develop more promising therapeutic approaches to target both types or be more effective for each type.

Methods:

We aimed to find affected biological processes and their regulators in both type, MSS and MSI-H, of CRC; as well as reveal specific ones in each type. We applied meta- and network analysis on freely available transcriptome data in MSS and MSI-H colorectal cancer from gene expression omnibus (GEO) database to detect common differentially expressed genes (DEGs) and critical biological processes and predict their most significant regulators.

Results:

Our results demonstrate considerable up and downregulation in cell cycle and lipid catabolism processes, respectively; and introduced MYC and FOXM1 as two central and up-stream regulators of DEGs in both type of CRC. Chemokine-mediated processes displayed up-regulation in MSI-H type, while metastasis-related processes showed more activation in MSS CRC. Additionally, DACH1 and TP53 were detected as two important transcription factors that differentially expressed just in MSS and MSI-H, respectively.

Conclusion:

Our results can explain why MSI and MSS CRC display different immunotherapy response, prognosis, and metastasis feature. Moreover, our predicted up-stream regulators in the regulatory networks may be promising therapeutic targets.

Single-cell RNA sequencing reveals novel gene expression signatures of trastuzumab treatment in HER2+ breast cancer: A pilot study

Human epidermal growth factor receptor 2-positive (HER2+) breast cancer accounts for ∼20% of invasive breast cancers and is associated with poor prognostics. The recent outcome of HER2+ breast cancer treatment has been vastly improved owing to the application of antibody-targeted therapies. Trastuzumab (Herceptin) is a monoclonal antibody designed to target HER2+ breast cancer cells. In addition to improved survival in the adjuvant treatment of HER2+ breast cancer, trastuzumab treatment has also been associated with cardiotoxicity side effect. However, the molecular mechanisms of trastuzumab action and trastuzumab-mediated cardiotoxicity are still not fully understood. Previous research utilized bulk transcriptomics analysis to study the underlining mechanisms, which relied on averaging molecular signals from bulk tumor samples and might have overlooked key expression features within breast cancer tumor. In contrast to previous research, we compared the single cancer cell level transcriptome profile between trastuzumab-treated and nontreated patients to reveal a more in-depth transcriptome profile. A total of 461 significantly differential expressed genes were identified, including previously defined and novel gene expression signatures. In addition, we found that trastuzumab-enhanced MGP gene expression could be used as prognostics marker for longer patient survival in breast invasive carcinoma patients, and validated our finding using TCGA (The Cancer Genome Atlas) breast cancer dataset. Moreover, our study revealed a 48-gene expression signature that is associated with cell death of cardiomyocytes, which could be used as early biomarkers for trastuzumab-mediated cardiotoxicity. This work is the first study to look at single cell level transcriptome profile of trastuzumab-treated patients, providing a new understanding of the molecular mechanism(s) of trastuzumab action and trastuzumab-induced cardiotoxicity side effects.

Overexpression of CKS2 is associated with a poor prognosis and promotes cell proliferation and invasion in breast cancer

Growing evidence indicates that cyclin dependent kinases regulatory subunit 2 (CKS2) serves an essential role in the regulation of multiple cellular processes in diverse human cancer types. The present study investigated the contribution of CKS2 to breast cancer (BC) progression. In the present study, CKS2 expression in BC was detected using Oncomine and The Cancer Genome Atlas database. The association between expression levels and clinical features was explored using Kaplan‑Meier plotter and the Breast Cancer Gene‑Expression Miner Version 4.0 (bc‑GenExMiner) online database. In addition, the roles of CKS2 in BC progression were examined. It was identified that CKS2 expression was significantly increased in BC tissues at the mRNA and protein levels. Bc‑GenExMiner demonstrated that high CKS2 expression was associated with a positive estrogen receptor status, progesterone receptor status, nodal status and basal‑like status. High CKS2 expression was markedly associated with poor overall survival, relapse‑free survival, and distant metastasis‑free survival in patients with BC. Moreover, functional assays revealed that CKS2 inhibition suppressed cell proliferation and invasion ability in vitro and reduced tumor growth in vivo. Thus, the present findings suggested that CKS2 may act as a potential biomarker and therapeutic target for the treatment of BC.

FOXM1 plays a role in autophagy by transcriptionally regulating Beclin-1 and LC3 genes in human triple-negative breast cancer cells

Triple-negative breast cancer (TNBC) is associated with poor prognosis owing to its aggressive and heterogeneous nature, and the lack of therapeutic targets. Although Forkhead Box M1 (FOXM1) is one of the most important oncogenes contributing to tumorigenesis, progression, and drug resistance in TNBC, the underlying molecular mechanisms are not well understood. Emerging evidence indicates that autophagy plays a critical role in cell survival and protective mechanism in TNBC. However, signaling pathways that are involved in the regulation of autophagy remain to be elucidated. In the present study, we examined the role of FOXM1 in regulating autophagy in TNBC cells and found that FOXM1 is upregulated during induction of autophagy. We found that inhibition of FOXM1 suppressed starvation and rapamycin-induced autophagy and expression of the major autophagy regulators, LC3 and Beclin-1. Further studies demonstrated that FOXM1 directly binds to the promotors of LC3 and Beclin-1 genes and transcriptionally regulates their expression by chromatin immunoprecipitation (ChIP) and luciferase gene reporter assays. In conclusion, our study provides the first evidence about the role of FOXM1 in regulating expression of LC3 and Beclin-1 and autophagy in TNBC cells. Our findings provide novel insight into the role of FOXM1 regulation of the autophagic survival pathway and potential molecular target for treating TNBC. KEY MESSAGES: • FOXM1 promotes tumorigenesis and progression of TNBC. However, the underlying molecular mechanism by which FOXM1 promotes TNBC tumorigenesis is unclear. The goal of our study was to determine the role of FOXM1 in the regulation of autophagy that plays a role in TNBC progression. Our findings show that FOXM1 binds to promoters of the genes encoding the major autophagy proteins, Beclin and LC3, and provide new insights into the regulation of autophagy, which is being targeted in many clinical trials.

MiR-216b inhibits osteosarcoma cell proliferation, migration, and invasion by targeting Forkhead Box M1

Osteosarcoma (OS) is considered the most common type of primary malignant bone tumor, which has a high rate of mortality in children and adolescents. However, the current treatment methods for OS are ineffective. Therefore, there is an urgent requirement to identify the critical targets. This study aimed to identify the roles and significance of microRNA-216b (miR-216b) in OS. To explore the cellular and molecular functions of miR-216b and Forkhead Box M1 (FoxM1) in OS, the expression of miR-216b and FoxM1 at the transcriptional level was measured using quantitative real-time PCR (qRT-PCR). Wound healing assay, 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyltetrazolium bromide assay (MTT) assay, flow cytometry, and transwell invasion assay were conducted to study the function of miR-216b and FoxM1 in OS cells. Dual luciferase reporter assay was performed to identify the relationships between miR-216b and FoxM1. qRT-PCR results revealed that miR-216b expression was significantly downregulated, and FoxM1 was observed to be significantly upregulated in human OS cell lines (MG-63) and tissues. MTT data showed that upregulation of miR-216b expression led to cell growth inhibition in MG-63 cells. The results of the invasion assay and wound healing assay illustrated that miR-216b upregulation or FoxM1 downregulation could inhibit the invasion and migration in MG-63 cells. In vivo, the tumor volume was significantly decreased by miR-194 mimic treatment compared with the control group. Furthermore, the results of the luciferase assay indicated that FoxM1 is a direct target of miR-216b. These findings may provide novel insights into the molecular mechanism of miR-216b and FoxM1 in the progression of OS, and suggested that miR-216b may serve as a potential tumor inhibitor of OS by targeting FoxM1.

Transcriptome mining of non-BRCA1/A2 and BRCA1/A2 familial breast cancer

About 10% of all breast cancer cases are the familial type. Mutations in two highly penetrance breast cancer susceptibility genes, BRCA1 and BRCA2, can only explain 20% to 25% of genetic susceptibility to breast cancer, and most familial breast cancer cases have intact BRCA1 and BRCA2 genes that refer to non-BRCA1/A2 or BRCAX familial breast cancer. Despite extensive studies, more than 50% of genetic susceptibility to breast cancer remained to be disclosed. Finding the differences between these two types of breast cancer (non-BRCA1/A2 and BRCA1/A2) at genomic, transcriptomic, and proteomic levels can help us to elucidate fundamental molecular processes and develope more promising therapeutic targets. Here, we used expression data of 391 patients with familial breast cancer including 195 non-BRCA1/A2 and 196 BRCA1 and/or BRCA2 cases from four independent studies by means of meta-analysis to find differences in gene expression signature between these two types of familial breast cancer. As well as, we applied comprehensive network analysis to find crucial protein complexes and regulators for each condition. Our results revealed significant overexpression of cell cycle processes in BRCA1/A2 patients and significant overexpression of estrogen axis in non-BRCA1/A2 patients. Moreover, we found FOXM1 as the central regulator of cell cycle processes and GATA3, FOXA1, and ESR1 as the main regulators of estrogen axis.

Targeting forkhead box M1 transcription factor in breast cancer

Breast cancer continues to be the most commonly diagnosed malignancy and second most common cause of cancer-related deaths among women in the United States. Improved understanding of the molecular heterogeneity of breast tumors and the approval of multiple targeted therapies have revolutionized the treatment landscape and long-term survival rates for patients with breast cancer. Despite the development of highly effective targeted agents, drug resistance and disease progression remain major clinical concerns. Improved understanding of the molecular mechanisms mediating drug resistance will allow new treatments to be developed. The forkhead box M1 (FoxM1) transcription factor is overexpressed in breast cancer and strongly associated with resistance to targeted therapies and chemotherapy. FoxM1 regulates all hallmarks of cancer, including proliferation, mitosis, EMT, invasion, and metastasis. Inhibition of FoxM1 transcription factor function is a potential strategy for overcoming breast cancer progression. In this research update, we review the role of FoxM1 in breast cancer and pharmacological approaches for blocking FoxM1 transcription factor function. Future preclinical studies should evaluate combination drug strategies to inhibit FoxM1 function and upstream kinase signaling pathways as potential strategies to treat resistant and metastatic breast cancers.