Protein arginine N-methyltransferase 2 plays a noncatalytic role in the histone methylation activity of PRMT1.

Protein arginine N-methyltransferases are a family of epigenetic enzymes responsible for monomethylation or dimethylation of arginine residues on histones. Dysregulation of protein arginine N-methyltransferase activity can lead to aberrant gene expression and cancer. Recent studies have shown that PRMT2 expression and histone H3 methylation at arginine 8 are correlated with disease severity in glioblastoma multiforme, hepatocellular carcinoma, and renal cell carcinoma. In this study, we explore a noncatalytic mechanistic role for PRMT2 in histone methylation by investigating interactions between PRMT2, histone peptides and proteins, and other PRMTs using analytical and enzymatic approaches. We quantify interactions between PRMT2, peptide ligands, and PRMT1 in a cofactor- and domain-dependent manner using differential scanning fluorimetry. We found that PRMT2 modulates the substrate specificity of PRMT1. Using calf thymus histones as substrates, we saw that a 10-fold excess of PRMT2 promotes PRMT1 methylation of both histone H4 and histone H2A. We found equimolar or a 10-fold excess of PRMT2 to PRMT1 can improve the catalytic efficiency of PRMT1 towards individual histone substrates H2A, H3, and H4. We further evaluated the effects of PRMT2 towards PRMT1 on unmodified histone octamers and mononucleosomes and found marginal PRMT1 activity improvements in histone octamers but significantly greater methylation of mononucleosomes in the presence of 10-fold excess of PRMT2. This work reveals the ability of PRMT2 to serve a noncatalytic role through its SH3 domain in driving site-specific histone methylation marks.

Protein arginine methyltransferase 1, a major regulator of biological processes.

Protein arginine methyltransferase 1 (PRMT1) is a major type I arginine methyltransferase that catalyzes the formation of monomethyl and asymmetric dimethylarginine in protein substrates. It was first identified to asymmetrically methylate histone H4 at the third arginine residue forming the H4R3me2a active histone mark. However, several protein substrates are now identified as being methylated by PRMT1. As a result of its association with diverse classes of substrates, PRMT1 regulates several biological processes like chromatin dynamics, transcription, RNA processing, and signal transduction. The review provides an overview of PRMT1 structure, biochemical features, specificity, regulation, and role in cellular functions. We discuss the genomic distribution of PRMT1 and its association with tRNA genes. Further, we explore the different substrates of PRMT1 involved in splicing. In the end, we discuss the proteins that interact with PRMT1 and their downstream effects in diseased states.

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.

Predicting breast cancer drug response using a multiple-layer cell line drug response network model.

BACKGROUND: Predicting patient drug response based on a patient's molecular profile is one of the key goals of precision medicine in breast cancer (BC). Multiple drug response prediction models have been developed to address this problem. However, most of them were developed to make sensitivity predictions for multiple single drugs within cell lines from various cancer types instead of a single cancer type, do not take into account drug properties, and have not been validated in cancer patient-derived data. Among the multi-omics data, gene expression profiles have been shown to be the most informative data for drug response prediction. However, these models were often developed with individual genes. Therefore, this study aimed to develop a drug response prediction model for BC using multiple data types from both cell lines and drugs. METHODS: We first collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values for 220 drugs tested in these cell lines from Genomics of Drug Sensitivity in Cancer (GDSC). Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on the drug structures, targets, and pan-cancer IC50 profiles. We further used ML-CDN2 to predict the drug response for new BC cell lines or patient-derived samples. RESULTS: ML-CDN2 demonstrated a good predictive performance, with the Pearson correlation coefficient between the observed and predicted IC50 values for all GDSC cell line-drug pairs of 0.873. Also, ML-CDN2 showed a good performance when used to predict drug response in new BC cell lines from the Cancer Cell Line Encyclopedia (CCLE), with a Pearson correlation coefficient of 0.718. Moreover, we found that the cell line-derived ML-CDN2 model could be applied to predict drug response in the BC patient-derived samples from The Cancer Genome Atlas (TCGA). CONCLUSIONS: The ML-CDN2 model was built to predict BC drug response using comprehensive information from both cell lines and drugs. Compared with existing methods, it has the potential to predict the drug response for BC patient-derived samples.

The treatment of SARS-CoV2 with antivirals and mitigation of the cytokine storm syndrome: the role of gene expression.

In the absence of a vaccine, the treatment of SARS-CoV2 has focused on eliminating the virus with antivirals or mitigating the cytokine storm syndrome (CSS) that leads to the most common cause of death: respiratory failure. Herein we discuss the mechanisms of antiviral treatments for SARS-CoV2 and treatment strategies for the CSS. Antivirals that have shown in vitro activity against SARS-CoV2, or the closely related SARS-CoV1 and MERS-CoV, are compared on the enzymatic level and by potency in cells. For treatment of the CSS, we discuss medications that reduce the effects or expression of cytokines involved in the CSS with an emphasis on those that reduce IL-6 because of its central role in the development of the CSS. We show that some of the medications covered influence the activity or expression of enzymes involved in epigenetic processes and specifically those that add or remove modifications to histones or DNA. Where available, the latest clinical data showing the efficacy of the medications is presented. With respect to their mechanisms, we explain why some medications are successful, why others have failed, and why some untested medications may yet prove useful.

SARS-CoV-2 multifaceted interaction with the human host. Part II: Innate immunity response, immunopathology, and epigenetics.

The SARS-CoV-2 makes its way into the cell via the ACE2 receptor and the proteolytic action of TMPRSS2. In response to the SARS-CoV-2 infection, the innate immune response is the first line of defense, triggering multiple signaling pathways to produce interferons, pro-inflammatory cytokines and chemokines, and initiating the adaptive immune response against the virus. Unsurprisingly, the virus has developed strategies to evade detection, which can result in delayed, excessive activation of the innate immune system. The response elicited by the host depends on multiple factors, including health status, age, and sex. An overactive innate immune response can lead to a cytokine storm, inflammation, and vascular disruption, leading to the vast array of symptoms exhibited by COVID-19 patients. What is known about the expression and epigenetic regulation of the ACE2 gene and the various players in the host response are explored in this review.

SARS-CoV-2 multifaceted interaction with human host. Part I: What we have learnt and done so far, and the still unknown realities.

SARS-CoV-2, the causing agent of the ongoing COVID-19 pandemic, is a beta-coronavirus which has 80% genetic homology with SARS-CoV, but displays increased virulence and transmissibility. Initially, SARS-CoV-2 was considered a respiratory virus generally causing a mild disease, only severe and fatal in the elderly and individuals with underlying conditions. Severe illnesses and fatalities were attributed to a cytokine storm, an excessive response from the host immune system. However, with the number of infections over 10 millions and still soaring, the insidious and stealthy nature of the virus has emerged, as it causes a vast array of diverse unexpected symptoms among infected individuals, including the young and healthy. It has become evident that besides infecting the respiratory tract, SARS-CoV-2 can affect many organs, possibly through the infection of the endothelium. This review presents an overview of our learning curve with the novel virus emergence, transmission, pathology, biological properties and host-interactions. It also briefly describes remedial measures taken until an effective vaccine is available, that is non-pharmaceutical interventions to reduce the viral spread and the repurposing of existing drugs, approved or in development for other conditions to eliminate the virus or mitigate the cytokine storm.

Selective DOT1L, LSD1, and HDAC Class I Inhibitors Reduce HOXA9 Expression in MLL-AF9 Rearranged Leukemia Cells, But Dysregulate the Expression of Many Histone-Modifying Enzymes.

Mixed lineage leukemia results from chromosomal rearrangements of the gene mixed lineage leukemia (MLL). MLL-AF9 is one such rearrangement that recruits the lysine methyltransferase, human disruptor of telomere silencing 1-like (DOT1L) and lysine specific demethylase 1 (LSD1), resulting in elevated expression of the Homeobox protein A9 (HOXA9), and leukemia. Inhibitors of LSD1 or DOT1L reduce HOXA9 expression, kill MLL-rearranged cells, and may treat leukemia. To quantify their effects on histone modifying enzyme activity and expression in MLL-rearranged leukemia, we tested inhibitors of DOT1L (EPZ-5676), LSD1 (GSK2879552), and HDAC (mocetinostat), in the MLL-AF9 cell line MOLM-13. All inhibitors reduced MOLM-13 viability but only mocetinostat induced apoptosis. EPZ-5676 increased total histone lysine dimethylation, which was attributed to a reduction in LSD1 expression, and was indistinguishable from direct LSD1 inhibition by GSK2879552. All compounds directly inhibit, or reduce the expression of, HOXA9, DOT1L and LSD1 by qPCR, increase total histone lysine methylation and acetylation by LC-MS/MS, and specifically reduce H3K79Me2 and increase H3K14Ac. Each inhibitor altered the expression of many histone modifying enzymes which may precipitate additional changes in expression. To the extent that this decreases HOXA9 expression it benefits mixed lineage leukemia treatment, all other expression changes are off-target effects.

Increased Post-Translational Lysine Acetylation of Myelin Basic Protein Is Associated with Peak Neurological Disability in a Mouse Experimental Autoimmune Encephalomyelitis Model of Multiple Sclerosis.

Citrullination of arginine residues is a post-translational modification (PTM) found on myelin basic protein (MBP), which neutralizes MBPs positive charge, and is implicated in myelin damage and multiple sclerosis (MS). Here we identify lysine acetylation as another neutralizing PTM to MBP that may be involved in myelin damage. We quantify changes in lysine and arginine PTMs on MBP derived from mice induced with an experimental autoimmune encephalomyelitis (EAE) model of MS using liquid chromatography tandem mass spectrometry. The changes in PTMs are correlated to changes in neurological disability scoring (NDS), as a marker of myelin damage. We found that lysine acetylation increased by 2-fold on MBP during peak NDS post-EAE induction. We also found that mono- and dimethyl-lysine, as well as asymmetric dimethyl-arginine residues on MBP were elevated at peak EAE disability. These findings suggest that the acetylation and methylation of lysine on MBP are PTMs associated with the neurological disability produced by EAE. Since histone deacetylase (HDAC) inhibitors have been previously shown to improve neurological disability, we also show that treatment with trichostatin A (a HDAC inhibitor) improves the NDS of EAE mice but does not change MBP acetylation.

Antimicrobial Prophylaxis for Patients Undergoing Cardiac Surgery: Intraoperative Cefazolin Concentrations and Sternal Wound Infections.

This study characterizes the pharmacodynamics of antimicrobial prophylaxis and sternal wound infections following cardiac surgery. Duration of surgery and cefazolin plasma concentration during wound closure were independently associated with surgical site infection at 30 days. Furthermore, a duration of surgery of >346 min and a total cefazolin closure concentration of <104 mg/liter were significant thresholds for an increased risk of infection. This study provides new data that informs dosing strategies for effective antimicrobial prophylaxis (AP) in patients undergoing cardiac surgery with cardiopulmonary bypass.

Evaluation of cefazolin antimicrobial prophylaxis during cardiac surgery with cardiopulmonary bypass.

Objectives: Although clinical practice guidelines recommend standard cefazolin antimicrobial prophylaxis (AP) dosing for cardiac surgery, limited data exist as to whether adequate concentrations are achieved in this patient population. The goal of our study was to characterize intraoperative cefazolin concentrations particularly at wound closure with regards to maintaining target cefazolin closure concentrations ≥40 mg/L. Methods: Adults undergoing cardiac surgery with cardiopulmonary bypass (CPB) and receiving cefazolin AP according to protocol were studied. Blood samples were collected after the preoperative cefazolin dose, prior to intraoperative cefazolin doses and at wound closure. Intraoperative trough and closure concentrations were characterized and evaluated against a target threshold of ≥ 40 mg/L (≥8 mg/L unbound, assuming 80% protein binding). Results: Fifty-five subjects (64.9 ±âŸ10.4 years, 89.7 ±âŸ16.5 kg, CLCR >50 mL/min/72 kg) completed the study. Total cefazolin concentrations were <40 mg/L in 40% (12 of 30) of intraoperative trough samples and 9.8% (5 of 51) of closure samples. Below-target concentrations at some time during surgery were documented in 30.9% (17 of 55) of subjects. In multivariate analyses, lower body weight (P = 0.027) and shorter duration of surgery (P = 0.045) were significant predictors of closure concentrations <40 mg/L. A total cefazolin exposure (preoperative and intraoperative doses) of ≥ 7.6 mg/kgdosing weight for every hour of surgery (intermittent dosing) was required to achieve target closure concentrations. Conclusions: The standard cefazolin AP regimen was not reliable in maintaining target closure concentrations ≥40 mg/L in patients with normal renal function undergoing elective cardiac surgery with CPB. The findings supported a cefazolin AP regimen consisting of at least 2 g preoperatively and every 3 h during surgery.

Arginine methylation in yeast proteins during stationary-phase growth and heat shock.

Arginine methyltransferases (RMTs) catalyze the methylation of arginine residues on proteins. We examined the effects of log-phase growth, stationary-phase growth, and heat shock on the formation of methylarginines on yeast proteins to determine if the conditions favor a particular type of methylation. Utilizing linear ion trap mass spectrometry, we identify methylarginines in wild-type and RMT deletion yeast strains using secondary product ion scans (MS(3)), and quantify the methylarginines using multiple reaction monitoring (MRM). Employing MS(3) and isotopic incorporation, we demonstrate for the first time that Nη1, Nη2-dimethylarginine (sDMA) is present on yeast proteins, and make a detailed structural determination of the fragment ions from the spectra. Nη-monomethylarginine (ηMMA), Nδ-monomethylarginine (δMMA), Nη1, Nη1-dimethylarginine (aDMA), and sDMA were detected in RMT deletion yeast using MS(3) and MRM with and without isotopic incorporation, suggesting that additional RMT enzymes remain to be discovered in yeast. The concentrations of ηMMA and δMMA decreased by half during heat shock and stationary phase compared to log-phase growth of wild-type yeast, whereas sDMA increased by as much as sevenfold and aDMA decreased by 11-fold. Therefore, upon entering stressful conditions like heat shock or stationary-phase growth, there is a net increase in sDMA and decreases in aDMA, ηMMA, and δMMA on yeast proteins.

Protein arginine N-methyltransferase substrate preferences for different nη-substituted arginyl peptides.

Protein arginine N-methyltransferases (PRMTs) catalyze methyl-group transfer from S-adenosyl-L-methionine onto arginine residues in proteins. In this study, modifications were introduced at the guanidine moiety of a peptidyl arginine residue to investigate how changes to the PRMT substrate can modulate enzyme activity. We found that peptides bearing Nη-hydroxy or Nη-amino substituted arginine showed higher apparent kcat values than for the monomethylated substrate when using PRMT1, whereas this catalytic preference was not observed for PRMT4 and PRMT6. Methylation by compromised PRMT1 variants E153Q and D51N further supports the finding that the N-hydroxy substitution facilitates methyl transfer by tuning the reactivity of the guanidine moiety. In contrast, Nη-nitro and Nη-canavanine substituted substrates inhibit PRMT activity. These findings demonstrate that methylation of these PRMT substrates is dependent on the nature of the modification at the guanidine moiety.

Enantiospecific analysis of 8-prenylnaringenin in biological fluids by liquid-chromatography-electrospray ionization mass spectrometry: application to preclinical pharmacokinetic investigations.

8-Prenylnaringenin (8PN) is a naturally occurring bioactive chiral prenylflavonoid found most commonly in the female flowers of hops (Humulus lupulus L.). A stereospecific method of analysis for 8PN in biological fluids is necessary to study the pharmacokinetic disposition of each enantiomer. A novel and simple liquid chromatographic-electrospray ionization-mass spectrometry (LC-ESI-MS) method was developed for the simultaneous determination of R- and S-8PN in rat serum and urine. Carbamazepine was used as the internal standard (IS). Enantiomeric resolution of 8PN was achieved on a Chiralpak(®) AD-RH column with an isocratic mobile phase consisting of 2-propanol and 10 mM ammonium formate (pH 8.5) (40:60, v/v) and a flow rate of 0.7 mL/min. Detection was achieved using negative selective ion monitoring (SIM) of 8PN at m/z 339.15 for both enantiomers and positive SIM m/z at 237.15 for the IS. The calibration curves for urine were linear over a range of 0.01-75 µg/mL and 0.05-75 µg/mL for serum with a limit of quantification of 0.05 µg/mL in serum and 0.01 µg/mL in urine. The method was successfully validated showing that it was sensitive, reproducible, and accurate for enantiospecific quantification of 8PN in biological matrices. The assay was successfully applied to a preliminary study of 8PN enantiomers in rat.

Bioinformatic Analyses of Broad H3K79me2 Domains in Different Leukemia Cell Line Data Sets.

A subset of expressed genes is associated with a broad H3K4me3 (histone H3 trimethylated at lysine 4) domain that extends throughout the gene body. Genes marked in this way in normal cells are involved in cell-identity and tumor-suppressor activities, whereas in cancer cells, genes driving the cancer phenotype (oncogenes) have this feature. Other histone modifications associated with expressed genes that display a broad domain have been less studied. Here, we identified genes with the broadest H3K79me2 (histone H3 dimethylated at lysine 79) domain in human leukemic cell lines representing different forms of leukemia. Taking a bioinformatic approach, we provide evidence that genes with the broadest H3K79me2 domain have known roles in leukemia (e.g., JMJD1C). In the mixed-lineage leukemia cell line MOLM-13, the HOXA9 gene is in a 100 kb broad H3K79me2 domain with other HOXA protein-coding and oncogenic long non-coding RNA genes. The genes in this domain contribute to leukemia. This broad H3K79me2 domain has an unstable chromatin structure, as was evident by enhanced chromatin accessibility throughout. Together, we provide evidence that identification of genes with the broadest H3K79me2 domain will aid in generating a panel of genes in the diagnosis and therapeutic treatment of leukemia in the future.

A protein arginine N-methyltransferase 1 (PRMT1) and 2 heteromeric interaction increases PRMT1 enzymatic activity.

Protein arginine N-methyltransferases (PRMTs) act in signaling pathways and gene expression by methylating arginine residues within target proteins. PRMT1 is responsible for most cellular arginine methylation activity and can work independently or in collaboration with other PRMTs. In this study, we demonstrate a direct interaction between PRMT1 and PRMT2 using co-immunoprecipitation, bimolecular fluorescence complementation, and enzymatic assays. As a result of this interaction, PRMT2 stimulated PRMT1 activity, affecting its apparent V(max) and K(M) values in vitro and increasing the production of methylarginines in cells. Active site mutations and regional deletions from PRMT1 and -2 were also investigated, which demonstrated that complex formation required full-length, active PRMT1. Although the inhibition of methylation by adenosine dialdehyde prevented the interaction between PRMT1 and -2, it did not prevent the interaction between PRMT1 and a truncation mutant of PRMT2 lacking its Src homology 3 (SH3) domain. This result suggests that the SH3 domain may mediate an interaction between PRMT1 and -2 in a methylation-dependent fashion. On the basis of our findings, we propose that PRMT1 serves as the major methyltransferase in cells by forming higher-order oligomers with itself, PRMT2, and possibly other PRMTs.

Sources of S-adenosyl-L-homocysteine background in measuring protein arginine N-methyltransferase activity using tandem mass spectrometry.

S-Adenosyl-L-homocysteine (AdoHcy) background signal in reactions with protein arginine N-methyltransferase 1 is investigated using an ultrahigh-performance liquid chromatography tandem mass spectrometry assay that measures AdoHcy. We identify three sources of AdoHcy background: enzymatic automethylation, AdoHcy contamination in commercial S-adenosyl-L-methionine (AdoMet), and nonenzymatic pseudo-first-order formation of AdoHcy from AdoMet. We propose a potential mechanism for the nonenzymatic production of AdoHcy and illustrate strategies for mitigating background AdoHcy that can be applied to any assay.

Kinetic analysis of human protein arginine N-methyltransferase 2: formation of monomethyl- and asymmetric dimethyl-arginine residues on histone H4.

Protein arginine N-methyltransferases (PRMTs) methylate arginine residues within proteins using S-adenosyl-L-methionine (AdoMet) to form S-adenosyl-L-homocysteine and methylarginine residues. All PRMTs produce omega-NG-monomethylarginine (MMA) residues and either asymmetric omega-N(G),N(G)-dimethylarginine (aDMA) or symmetric omega-N(G),N'(G)-dimethylarginine (sDMA) residues, referred to as Type I or Type II activity respectively. Here we report methylation activity from PRMT2 and compare it with PRMT1 activity using UPLC-MS/MS (ultra-performance liquid chromatography-tandem MS), gel electrophoresis, and thin-layer chromatography. We show that PRMT2 is a Type I enzyme and that the ratio of aDMA to MMA produced by PRMTs 1 and 2 is dependent on the substrate, regardless of rate or K(m), suggesting that the reactions for both enzymes are distributive rather than processive. Using UPLC-MS/MS we find that, for PRMT2, the dissociation constant (KAs) and K(m) of AdoMet and the Km of histone H4 are similar to values for PRMT1, whereas the PRMT2 k(cat) is 800-fold less than the PRMT1 k(cat). Although PRMT2 activity is substantially lower than PRMT1 in vitro, the fact that both enzymes selectively methylate histone H4 suggest that PRMT2, like PRMT1, may act as a transcription co-activator through this modification.

Deep graph embedding for prioritizing synergistic anticancer drug combinations.

Drug combinations are frequently used for the treatment of cancer patients in order to increase efficacy, decrease adverse side effects, or overcome drug resistance. Given the enormous number of drug combinations, it is cost- and time-consuming to screen all possible drug pairs experimentally. Currently, it has not been fully explored to integrate multiple networks to predict synergistic drug combinations using recently developed deep learning technologies. In this study, we proposed a Graph Convolutional Network (GCN) model to predict synergistic drug combinations in particular cancer cell lines. Specifically, the GCN method used a convolutional neural network model to do heterogeneous graph embedding, and thus solved a link prediction task. The graph in this study was a multimodal graph, which was constructed by integrating the drug-drug combination, drug-protein interaction, and protein-protein interaction networks. We found that the GCN model was able to correctly predict cell line-specific synergistic drug combinations from a large heterogonous network. The majority (30) of the 39 cell line-specific models show an area under the receiver operational characteristic curve (AUC) larger than 0.80, resulting in a mean AUC of 0.84. Moreover, we conducted an in-depth literature survey to investigate the top predicted drug combinations in specific cancer cell lines and found that many of them have been found to show synergistic antitumor activity against the same or other cancers in vitro or in vivo. Taken together, the results indicate that our study provides a promising way to better predict and optimize synergistic drug pairs in silico.

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

Different breast cancer (BC) subtypes have unique gene expression patterns, but their regulatory mechanisms have yet to be fully elucidated. We hypothesized that the top upregulated (Yin) and downregulated (Yang) genes determine the fate of cancer cells. To reveal the regulatory determinants of these Yin and Yang genes in different BC subtypes, we developed a lasso regression model integrating DNA methylation (DM), copy number variation (CNV) and microRNA (miRNA) expression of 391 BC patients, coupled with miRNA-target interactions and transcription factor (TF) binding sites. A total of 25, 20, 15 and 24 key regulators were identified for luminal A, luminal B, Her2-enriched, and triple negative (TN) subtypes, respectively. Many of the 24 TN regulators were found to regulate the PPARA and FOXM1 pathways. The Yin Yang gene expression mean ratio (YMR) and combined risk score (CRS) signatures built with either the targets of or the TN regulators were associated with the BC patients' survival. Previously, we identified FOXM1 and PPARA as the top Yin and Yang pathways in TN, respectively. These two pathways and their regulators could be further explored experimentally, which might help to identify potential therapeutic targets for TN.