Integrative Analysis Reveals Subtype-Specific Regulatory Determinants in Triple Negative Breast Cancer

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.

Dynamic tumor microenvironment, molecular heterogeneity, and distinct immunologic portrait of triple-negative breast cancer: an impact on classification and treatment approaches

Heterogeneity of the tumor microenvironment (TME) and the lack of a definite targetable receptor in triple-negative breast cancer (TNBC) has carved a niche for this cancer as a particularly therapeutically challenging form of breast cancer. However, recent advances in high-throughput genomic analysis have provided new insights into the unique microenvironment and defining characteristics of various subsets of TNBC. This improved understanding has contributed to the development of novel therapeutic strategies including targeted therapies such as PARP inhibitors and CDK inhibitors. Moreover, the recent FDA approval of the immune checkpoint inhibitor against programmed cell death protein 1 (PD-1), pembrolizumab and atezolizumab, holds the promise of improving the quality of life and increasing the overall survival of TNBC patients. This recent approval is one of the many therapeutically novel strategies that are currently being exploited in clinical trials toward eventual contribution to the oncologist's toolbox against TNBC. In this review, we comprehensively discuss TNBC's distinct TME and its immunophenotype. Furthermore, we highlight the histological and molecular classification of this cancer. More importantly, we describe how these characteristics and classifications contribute to the current standards of care and how they steer the development of newer and more targeted therapies toward achieving peak therapeutic goals in the treatment of TNBC.

Functional impact of multi-omic interactions in breast cancer subtypes

Multi-omic approaches are expected to deliver a broader molecular view of cancer. However, the promised mechanistic explanations have not quite settled yet. Here, we propose a theoretical and computational analysis framework to semi-automatically produce network models of the regulatory constraints influencing a biological function. This way, we identified functions significantly enriched on the analyzed omics and described associated features, for each of the four breast cancer molecular subtypes. For instance, we identified functions sustaining over-representation of invasion-related processes in the basal subtype and DNA modification processes in the normal tissue. We found limited overlap on the omics-associated functions between subtypes; however, a startling feature intersection within subtype functions also emerged. The examples presented highlight new, potentially regulatory features, with sound biological reasons to expect a connection with the functions. Multi-omic regulatory networks thus constitute reliable models of the way omics are connected, demonstrating a capability for systematic generation of mechanistic hypothesis.

Bioinformatics driven discovery of small molecule compounds that modulate the FOXM1 and PPARA pathway activities in breast cancer

Our previous studies demonstrated that the FOXM1 pathway is upregulated and the PPARA pathway downregulated in breast cancer (BC), and especially in the triple negative breast cancer (TNBC) subtype. Targeting the two pathways may offer potential therapeutic strategies to treat BC, especially TNBC which has the fewest effective therapies available among all BC subtypes. In this study we identified small molecule compounds that could modulate the PPARA and FOXM1 pathways in BC using two methods. In the first method, data were initially curated from the Connectivity Map (CMAP) database, which provides the gene expression profiles of MCF7 cells treated with different compounds as well as paired controls. We then calculated the changes in the FOXM1 and PPARA pathway activities from the compound-induced gene expression profiles under each treatment to identify compounds that produced a decreased activity in the FOXM1 pathway or an increased activity in the PPARA pathway. In the second method, the CMAP database tool was used to identify compounds that could reverse the expression pattern of the two pathways in MCF7 cells. Compounds identified as repressing the FOXM1 pathway or activating the PPARA pathway by the two methods were compared. We identified 19 common compounds that could decrease the FOXM1 pathway activity scores and reverse the FOXM1 pathway expression pattern, and 13 common compounds that could increase the PPARA pathway activity scores and reverse the PPARA pathway expression pattern. It may be of interest to validate these compounds experimentally to further investigate their effects on TNBCs.

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.

Multi-Omic Regulation of the PAM50 Gene Signature in Breast Cancer Molecular Subtypes

Breast cancer is a disease that exhibits heterogeneity that goes from the genomic to the clinical levels. This heterogeneity is thought to be captured (at least partially) by the so-called breast cancer molecular subtypes. These molecular subtypes were initially defined based on the unsupervised clustering of gene expression and its correlate with histological, morphological, phenotypic and clinical features already known. Later, a 50-gene signature, PAM50, was defined in order to identify the biological subtype of a given sample within the clinical setting. The PAM50 signature was obtained by the use of unsupervised statistical methods, and therefore no limitation was set on the biological relevance (or lack of) of the selected genes beyond its predictive capacity. An open question that remains is what are the regulatory elements that drive the various expression behaviors of this set of genes in the different molecular subtypes. This question becomes more relevant as the measurement of more biological layers of regulation becomes accessible. In this work, we analyzed the gene expression regulation of the 50 genes in the PAM50 signature, in terms of (a) gene co-expression, (b) transcription factors, (c) micro-RNAs, and (d) methylation. Using data from the Cancer Genome Atlas (TCGA) for the Luminal A and B, Basal, and HER2-enriched molecular subtypes as well as normal tumor adjacent tissue, we identified predictors for gene expression through the use of an elastic net model. We compare and contrast the sets of identified regulators for the gene signature in each molecular subtype, and systematically compare them to current literature. We also identified a unique set of predictors for the expression of genes in the PAM50 signature associated with each of the molecular subtypes. Most selected predictors are exclusive for a PAM50 gene and predictors are not shared across subtypes. There are only 13 coding transcripts and 2 miRNAs selected for the four subtypes. MiR-21 and miR-10b connect almost all the PAM50 genes in all the subtypes and normal tissue, but do it in an exclusive manner, suggesting a cancer switch from miR-10b coordination in normal tissue to miR-21. The PAM50 gene sets of selected predictors that enrich for a function across subtypes, support that different regulatory molecular mechanisms are taking place. With this study we aim to a wider understanding of the regulatory mechanisms that differentiate the expression of the PAM50 signature, which in turn could perhaps help understand the molecular basis of the differences between the molecular subtypes.

Antiproliferative and Carbonic Anhydrase II Inhibitory Potential of Chemical Constituents from Lycium shawii and Aloe vera: Evidence from In Silico Target Fishing and In Vitro Testing

Lycium shawii Roem. & Schult and resin of Aloe vera (L.) BURM. F. are commonly used in Omani traditional medication against various ailments. Herein, their antiproliferative and antioxidant potential was explored. Bioassay-guided fractionation of the methanol extract of both plants led to the isolation of 14 known compounds, viz., 1-9 from L. shawii and 10-20 from A. vera. Their structures were confirmed by combined spectroscopic techniques including 1D (1H and 13C) and 2D (HMBC, HSQC, COSY) nuclear magnetic resonance (NMR), and electrospray ionization-mass spectrometry (ESI-MS). The cytotoxic potential of isolates was tested against the triple-negative breast cancer cell line (MDA-MB-231). Compound 5 exhibited excellent antiproliferative activity in a range of 31 μM, followed by compounds 1-3, 7, and 12, which depicted IC50 values in the range of 35-60 μM, while 8, 6, and 9 also demonstrated IC50 values >72 μM. Subsequently, in silico target fishing was applied to predict the most potential cellular drug targets of the active compounds, using pharmacophore modeling and inverse molecular docking approach. The extensive in silico analysis suggests that our compounds may target carbonic anhydrase II (CA-II) to exert their anticancer activities. When tested on CA-II, compounds 5 (IC50 = 14.4 µM), 12 (IC50 = 23.3), and 2 (IC50 = 24.4 µM) showed excellent biological activities in vitro. Additionally, the ethyl acetate fraction of both plants showed promising antioxidant activity. Among the isolated compounds, 4 possesses the highest antioxidant (55 μM) activity followed by 14 (241 μM). The results indicated that compound 4 can be a promising candidate for antioxidant drugs, while compound 5 is a potential candidate for anticancer drugs.

The Many Faces of Gene Regulation in Cancer: A Computational Oncogenomics Outlook

Cancer is a complex disease at many different levels. The molecular phenomenology of cancer is also quite rich. The mutational and genomic origins of cancer and their downstream effects on processes such as the reprogramming of the gene regulatory control and the molecular pathways depending on such control have been recognized as central to the characterization of the disease. More important though is the understanding of their causes, prognosis, and therapeutics. There is a multitude of factors associated with anomalous control of gene expression in cancer. Many of these factors are now amenable to be studied comprehensively by means of experiments based on diverse omic technologies. However, characterizing each dimension of the phenomenon individually has proven to fall short in presenting a clear picture of expression regulation as a whole. In this review article, we discuss some of the more relevant factors affecting gene expression control both, under normal conditions and in tumor settings. We describe the different omic approaches that we can use as well as the computational genomic analysis needed to track down these factors. Then we present theoretical and computational frameworks developed to integrate the amount of diverse information provided by such single-omic analyses. We contextualize this within a systems biology-based multi-omic regulation setting, aimed at better understanding the complex interplay of gene expression deregulation in cancer.