Purpose Neuroblastoma is a pediatric cancer that continues to exact significant morbidity and mortality. Recently, a number of cell cycle proteins, particularly those within the Cyclin D/CDK4/CDK6/RB network, have been shown to exert oncogenic roles in neuroblastoma, suggesting that their therapeutic exploitation might improve patient outcomes. Experimental Procedures We evaluated the effect of dual CDK4/CDK6 inhibition on neuroblastoma viability using LEE011, a highly specific CDK4/6 inhibitor. Results Treatment with LEE011 significantly reduced proliferation in 12 of 17 human neuroblastoma-derived cell lines by inducing cytostasis at nanomolar concentrations (mean IC50 = 307 ± 68 nM in sensitive lines). LEE011 caused cell cycle arrest and cellular senescence that was attributed to dose-dependent decreases in phosphorylated RB and FOXM1, respectively. In addition, responsiveness of neuroblastoma xenografts to LEE011 translated to the in vivo setting in that there was a direct correlation of in vitro IC50 values with degree of subcutaneous xenograft growth delay. While our data indicate that neuroblastomas sensitive to LEE011 were more likely to contain genomic amplification of MYCN (p = 0.01), the identification of additional clinically accessible biomarkers is of high importance. Conclusions Taken together, our data show that LEE011 is active in a large subset of neuroblastoma cell line and xenograft models, and supports the clinical development of this CDK4/6 inhibitor as a therapy for patients with this disease.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor