Obesity is associated with an increased risk of developing breast cancer and is also associated with worse clinical prognosis. The mechanistic link between obesity and breast cancer progression remains unclear, and there has been no development of specific treatments to improve the outcome of obese cancer patients. Here we show that obesity-associated NLRC4 inflammasome activation/ interleukin (IL)-1 signalling promotes breast cancer progression. The tumour microenvironment in the context of obesity induces an increase in tumour-infiltrating myeloid cells with an activated NLRC4 inflammasome that in turn activates IL-1β, which drives disease progression through adipocyte-mediated vascular endothelial growth factor A (VEGFA) expression and angiogenesis. Further studies show that treatment of mice with metformin inhibits obesity-associated tumour progression associated with a marked decrease in angiogenesis. This report provides a causal mechanism by which obesity promotes breast cancer progression and lays out a foundation to block NLRC4 inflammasome activation or IL-1β signalling transduction that may be useful for the treatment of obese cancer patients.

Aurora B is a mitotic checkpoint kinase that plays a pivotal role in the cell cycle, ensuring correct chromosome segregation and normal progression through mitosis. Aurora B is overexpressed in many types of human cancers, which has made it an attractive target for cancer therapies. Tumor suppressor p53 is a genome guardian and important negative regulator of the cell cycle. Whether Aurora B and p53 are coordinately regulated during the cell cycle is not known. We report that Aurora B directly interacts with p53 at different subcellular localizations and during different phases of the cell cycle (for instance, at the nucleus in interphase and the centromeres in prometaphase of mitosis). We show that Aurora B phosphorylates p53 at S183, T211, and S215 to accelerate the degradation of p53 through the polyubiquitination–proteasome pathway, thus functionally suppressing the expression of p53 target genes involved in cell cycle inhibition and apoptosis (e.g., p21 and PUMA). Pharmacologic inhibition of Aurora B in cancer cells with WT p53 increased p53 protein level and expression of p53 target genes to inhibit tumor growth. Together, these results define a mechanism of p53 inactivation during the cell cycle and imply that oncogenic hyperactivation or overexpression of Aurora B may compromise the tumor suppressor function of p53. We have elucidated the antineoplastic mechanism for Aurora B kinase inhibitors in cancer cells with WT p53.

In genome and transcriptome analyses of HCC samples, we found mutations in genes in the TGF-β signaling pathway in almost 40% of samples. These correlated with changes in expression of genes in the pathways; up-regulation of genes in this pathway would contribute to inflammation and fibrosis, whereas down-regulation would indicate loss of TGF-β tumor suppressor activity. Our findings indicate that therapeutic agents for HCCs can be effective, based on genetic features of the TGF-β pathway; agents that block TGF-β should be used only in patients with specific types of HCCs.

Hyperpolarized [1-13C]-pyruvate has shown tremendous promise as an agent for imaging tumor metabolism with unprecedented sensitivity and specificity. Imaging hyperpolarized substrates by magnetic resonance is unlike traditional MRI because signals are highly transient and their spatial distribution varies continuously over their observable lifetime. Therefore, new imaging approaches are needed to ensure optimal measurement under these circumstances. Constrained reconstruction algorithms can integrate prior information, including biophysical models of the substrate/target interaction, to reduce the amount of data that is required for image analysis and reconstruction. In this study, we show that metabolic MRI with hyperpolarized pyruvate is biased by tumor perfusion, and present a new pharmacokinetic model for hyperpolarized substrates that accounts for these effects. The suitability of this model is confirmed by statistical comparison to alternates using data from 55 dynamic spectroscopic measurements in normal animals and murine models of anaplastic thyroid cancer, glioblastoma, and triple-negative breast cancer. The kinetic model was then integrated into a constrained reconstruction algorithm and feasibility was tested using significantly under-sampled imaging data from tumor-bearing animals. Compared to naïve image reconstruction, this approach requires far fewer signal-depleting excitations and focuses analysis and reconstruction on new information that is uniquely available from hyperpolarized pyruvate and its metabolites, thus improving the reproducibility and accuracy of metabolic imaging measurements.