Obesity is a risk factor for postmenopausal estrogen receptor alpha (ERα)-positive (ER+) breast cancer. Molecular mechanisms underlying factors from plasma that contribute to this risk and how these mechanisms affect ERα signaling have yet to be elucidated. To identify such mechanisms, we performed whole metabolite and protein profiling in plasma samples from women at high risk for breast cancer, which led us to focus on factors that were differentially present in plasma of obese versus nonobese postmenopausal women. These studies, combined with in vitro assays, identified free fatty acids (FFA) as circulating plasma factors that correlated with increased proliferation and aggressiveness in ER+ breast cancer cells. FFAs activated both the ERα and mTOR pathways and rewired metabolism in breast cancer cells. Pathway preferential estrogen-1 (PaPE-1), which targets ERα and mTOR signaling, was able to block changes induced by FFA and was more effective in the presence of FFA. Collectively, these data suggest a role for obesity-associated gene and metabolic rewiring in providing new targetable vulnerabilities for ER+ breast cancer in postmenopausal women. Furthermore, they provide a basis for preclinical and clinical trials where the impact of agents that target ERα and mTOR signaling cross-talk would be tested to prevent ER+ breast cancers in obese postmenopausal women.Significance: These findings show that obesity-associated changes in certain blood metabolites rewire metabolic programs in cancer cells, influence mammary epithelial cell tumorigenicity and aggressiveness, and increase breast cancer risk.

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.

Cholesterol has been implicated in the clinical progression of breast cancer, a disease that continues to be the most commonly diagnosed cancer in women. Previous work has identified the cholesterol metabolite 27-hydroxycholesterol (27HC) as a major mediator of the effects of cholesterol on breast tumor growth and progression. 27HC can act as an estrogen receptor (ER) modulator to promote the growth of ERα+ tumors, and as a liver X receptor (LXR) ligand in myeloid immune cells to establish an immune-suppressive program. In fact, the metastatic properties of 27HC require the presence of myeloid cells with neutrophils (polymorphonuclear neutrophils; PMNs) being essential for the increase in lung metastasis in murine models. In an effort to further elucidate the mechanisms by which 27HC alters breast cancer progression, we made the striking finding that 27HC promoted the secretion of extracellular vesicles (EVs), a diverse assortment of membrane bound particles that includes exosomes. The resulting EVs had a size distribution that was skewed slightly larger than EVs generated by treating cells with vehicle. The increase in EV secretion and size was consistent across 3 different subtypes: primary murine PMNs, RAW264.7 monocytic cells, and 4T1 murine mammary cancer cells. Label-free analysis of 27HC-EVs indicated that they had a different metabolite composition to those from vehicle-treated cells. Importantly, 27HC-EVs from primary PMNs promoted tumor growth and metastasis in 2 different syngeneic models, demonstrating the potential role of 27HC-induced EVs in the progression of breast cancer. EVs from PMNs were taken up by cancer cells, macrophages, and PMNs, but not T cells. Since EVs did not alter proliferation of cancer cells, it is likely that their protumor effects are mediated through interactions with myeloid cells. Interestingly, RNA-seq analysis of tumors from 27HC-EV-treated mice do not display significantly altered transcriptomes, suggesting that the effects of 27HC-EVs occur early on in tumor establishment and growth. Future work will be required to elucidate the mechanisms by which 27HC increases EV secretion, and how these EVs promote breast cancer progression. Collectively, however, our data indicate that EV secretion and content can be regulated by a cholesterol metabolite, which may have detrimental effects in terms of disease progression, important findings given the prevalence of both breast cancer and hypercholesterolemia.

Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming process. The identification and utilization of early exposure gene signatures and robust predictive models in regulatory toxicity testing has the potential to reduce time and costs substantially. In this study, comparative supervised machine learning approaches were applied to the rat liver TG-GATEs dataset to develop feature selection and predictive testing. We identified ten gene biomarkers using three different feature selection methods that predicted liver necrosis with high specificity and selectivity in an independent validation dataset from the Microarray Quality Control (MAQC)-II study. Nine of the ten genes that were selected with the supervised methods are involved in metabolism and detoxification (Car3, Crat, Cyp39a1, Dcd, Lbp, Scly, Slc23a1, and Tkfc) and transcriptional regulation (Ablim3). Several of these genes are also implicated in liver carcinogenesis, including Crat, Car3 and Slc23a1. Our biomarker gene signature provides high statistical accuracy and a manageable number of genes to study as indicators to potentially accelerate toxicity testing based on their ability to induce liver necrosis and, eventually, liver cancer.

The bazedoxifene and conjugated estrogens (CE+BZA) combination has been shown to prevent visceral adiposity and weight gain after ovariectomy. However, its impact on the liver transcriptomes associated with prevention of hepatosteatosis is yet to be determined. In the present study, we use liver transcriptomics and plasma metabolomics analysis to characterize the effects of various estrogens on liver. The CE+BZA combination was very effective at preventing ovariectomy-induced weight gain in mice fed a high-fat diet (HFD). In CE+BZA treated animals, liver weight and hepatic lipid deposition were significantly lower than in Vehicle (Veh) treated animals. Additionally, CE+BZA induced unique liver transcriptome and plasma metabolome profiles compared to estradiol, conjugated estrogens alone, and bazedoxifene alone. Blood plasma metabolite analysis identified several metabolites similar to and distinct from other estrogen treatments. Integrated pathway analysis showed that gene networks that were associated with inflammation, reactive oxygen species pathway and lipid metabolism and their relevant metabolites were regulated significantly by CE+BZA treatment. Thus, long-term CE+BZA treatment modulated hepatic metabolic gene networks and their associated metabolites and improves hepatic health without stimulating the uterus.