AZD1775 sensitizes T cell acute lymphoblastic leukemia cells to cytarabine by promoting apoptosis over DNA repair

While some children with acute lymphoblastic leukemia (ALL) have excellent prognoses, the prognosis for adults and children with T cell ALL is more guarded. Treatment for T-ALL is heavily dependent upon antimetabolite chemotherapeutics, including cytarabine. Targeted inhibition of WEE1 with AZD1775 has emerged as a strategy to sensitize cancer cells to cytarabine and other chemotherapeutics. We sought to determine if this strategy would be effective for T-ALL with clinically relevant anti-leukemia agents. We found that AZD1775 sensitizes T-ALL cells to several traditional anti-leukemia agents, acting synergistically with cytarabine by enhancing DNA damage and apoptosis. In addition to increased phosphorylation of H2AX at serine 139 (γH2AX), AZD1775 led to increased phosphorylation of H2AX at tyrosine 142, a signaling event associated with promotion of apoptosis over DNA repair. In a xenograft model of T-ALL, the addition of AZD1775 to cytarabine slowed leukemia progression and prolonged survival. Inhibition of WEE1 with AZD1775 sensitizes T-ALL to several anti-leukemia agents, particularly cytarabine. Mechanistically, AZD1775 promotes apoptosis over DNA repair in cells treated with cytarabine. These data support the development of clinical trials including AZD1775 in combination with conventional chemotherapy for acute leukemia.     

Hierarchical non‐negative matrix factorization to characterize brain tumor heterogeneity using multi‐parametric MRI

Tissue characterization in brain tumors and, in particular, in high‐grade gliomas is challenging as a result of the co‐existence of several intra‐tumoral tissue types within the same region and the high spatial heterogeneity. This study presents a method for the detection of the relevant tumor substructures (i.e. viable tumor, necrosis and edema), which could be of added value for the diagnosis, treatment planning and follow‐up of individual patients. Twenty‐four patients with glioma [10 low‐grade gliomas (LGGs), 14 high‐grade gliomas (HGGs)] underwent a multi‐parametric MRI (MP‐MRI) scheme, including conventional MRI (cMRI), perfusion‐weighted imaging (PWI), diffusion kurtosis imaging (DKI) and short‐TE ¹H MRSI. MP‐MRI parameters were derived: T₂, T₁ + contrast, fluid‐attenuated inversion recovery (FLAIR), relative cerebral blood volume (rCBV), mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and the principal metabolites lipids (Lip), lactate (Lac), N‐acetyl‐aspartate (NAA), total choline (Cho), etc. Hierarchical non‐negative matrix factorization (hNMF) was applied to the MP‐MRI parameters, providing tissue characterization on a patient‐by‐patient and voxel‐by‐voxel basis. Tissue‐specific patterns were obtained and the spatial distribution of each tissue type was visualized by means of abundance maps. Dice scores were calculated by comparing tissue segmentation derived from hNMF with the manual segmentation by a radiologist. Correlation coefficients were calculated between each pathologic tissue source and the average feature vector within the corresponding tissue region. For the patients with HGG, mean Dice scores of 78%, 85% and 83% were obtained for viable tumor, the tumor core and the complete tumor region. The mean correlation coefficients were 0.91 for tumor, 0.97 for necrosis and 0.96 for edema. For the patients with LGG, a mean Dice score of 85% and mean correlation coefficient of 0.95 were found for the tumor region. hNMF was also applied to reduced MRI datasets, showing the added value of individual MRI modalities. Copyright © 2015 John Wiley & Sons, Ltd.