Temozolomide and cisplatin in relapsed/refractory acute leukemia

Cisplatin depletes MGMT and increases the sensitivity of leukemia cells to temozolomide. We performed a phase I study of cisplatin and temozolomide in patients with relapsed and refractory acute leukemia. Fifteen patients had AML, 3 had ALL, and 2 had biphenotypic leukemia. The median number of prior chemotherapy regimens was 3 (1–5). Treatment was well tolerated up to the maximal doses of temozolomide 200 mg/m2/d times 7 days and cisplatin 100 mg/m2 on day 1. There was one complete remission in this heavily pretreated patient population. Five of 20 (25%) patients demonstrated a significant reduction in bone marrow blasts

The responses of cancer cells to PLK1 inhibitors reveal a novel protective role for p53 in maintaining centrosome separation

Polo-like kinase-1 (PLK1) plays a major role in driving mitotic events, including centrosome disjunction and separation, and is frequently over-expressed in human cancers. PLK1 inhibition is a promising therapeutic strategy and works by arresting cells in mitosis due to monopolar spindles. The p53 tumour suppressor protein is a short-lived transcription factor that can inhibit the growth, or stimulate the death, of developing cancer cells. Curiously, although p53 normally acts in an anti-cancer capacity, it can offer significant protection against inhibitors of PLK1, but the events underpinning this effect are not known. Here, we show that functional p53 reduces the sensitivity to PLK1 inhibitors by permitting centrosome separation to occur, allowing cells to traverse mitosis and re-enter cycle with a normal complement of 2N chromosomes. Protection entails the activation of p53 through the DNA damage-response enzymes, ATM and ATR, and requires the phosphorylation of p53 at the key regulatory site, Ser15. These data highlight a previously unrecognised link between p53, PLK1 and centrosome separation that has therapeutic implications for the use of PLK1 inhibitors in the clinic

Bayesian Cue Integration as a Developmental Outcome of Reward Mediated Learning

Average human behavior in cue combination tasks is well predicted by Bayesian inference models. As this capability is acquired over developmental timescales, the question arises, how it is learned. Here we investigated whether reward dependent learning, that is well established at the computational, behavioral, and neuronal levels, could contribute to this development. It is shown that a model free reinforcement learning algorithm can indeed learn to do cue integration, i.e. weight uncertain cues according to their respective reliabilities and even do so if reliabilities are changing. We also consider the case of causal inference where multimodal signals can originate from one or multiple separate objects and should not always be integrated. In this case, the learner is shown to develop a behavior that is closest to Bayesian model averaging. We conclude that reward mediated learning could be a driving force for the development of cue integration and causal inference

Contemporary management of cancer of the oral cavity

Oral cancer represents a common entity comprising a third of all head and neck malignant tumors. The options for curative treatment of oral cavity cancer have not changed significantly in the last three decades; however, the work up, the approach to surveillance, and the options for reconstruction have evolved significantly. Because of the profound functional and cosmetic importance of the oral cavity, management of oral cavity cancers requires a thorough understanding of disease progression, approaches to management and options for reconstruction. The purpose of this review is to discuss the most current management options for oral cavity cancers