Citations

Key Points HSCT after PD-1 blockade is feasible, although may be associated with increased early immune toxicity. PD-1 blockade may cause persistent depletion of PD1+ T cells and alterations in T-cell differentiation impacting subsequent treatment.

Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring “big data” applications in pediatric oncology. Computational strategies derived from big data science–network- and machine learning-based modeling and drug repositioning—hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which “big data” and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases.

BackgroundAutomated external defibrillators can provide life‐saving therapies to treat ventricular fibrillation. We developed a prototype unit that can deliver a unique shock waveform produced by four independent capacitors that is delivered through two shock vectors, with the rationale of providing more robust shock pathways during emergent defibrillation. We describe the initial testing and feasibility of this unique defibrillation unit, features of which may enable downsizing of current defibrillator devices.MethodsWe tested our defibrillation unit in four large animal models (two canine and two swine) under general anesthesia. Experimental defibrillation thresholds (DFT) were obtained by delivery of a unique waveform shock pulse via a dual‐vector pathway with four defibrillation pads (placed across the chest). DFTs were measured and compared with those of a commercially available biphasic defibrillator (Zoll M series, Zoll Medical, Chelmsford, MA, USA) tested in two different vectors. Shocks were delivered after 10 seconds of stable ventricular fibrillation and the output characteristics and shock outcome recorded. Each defibrillation series used a step‐down to failure protocol to define the defibrillation threshold.ResultsA total of 96 shocks were delivered during ventricular fibrillation in four large animals. In comparison to the Zoll M series, which delivered a single‐vector, biphasic shock, the energy required for successful defibrillation using the unique dual‐vector biphasic waveform did not differ significantly (P = 0.65).ConclusionsOur early findings support the feasibility of a unique external defibrillation unit using a dual‐vector biphasic waveform approach. This warrants further study to leverage this unique concept and work toward a miniaturized, portable shock delivery system.

AbstractAlzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive decline in memory and other aspects of cognitive function. Diffusion‐weighted imaging (DWI) offers a non‐invasive approach to delineate the effects of AD on white matter (WM) integrity. Previous studies calculated either some summary statistics over regions of interest (ROI analysis) or some statistics along mean skeleton lines (Tract Based Spatial Statistic [TBSS]), so they cannot quantify subtle local WM alterations along major tracts. Here, a comprehensive WM analysis framework to map disease effects on 3D tracts both locally and globally, based on a study of 200 subjects: 49 healthy elderly normal controls, 110 with mild cognitive impairment, and 41 AD patients has been presented. 18 major WM tracts were extracted with our automated clustering algorithm—autoMATE (automated Multi‐Atlas Tract Extraction); we then extracted multiple DWI‐derived parameters of WM integrity along the WM tracts across all subjects. A novel statistical functional analysis method—FADTTS (Functional Analysis for Diffusion Tensor Tract Statistics) was applied to quantify degenerative patterns along WM tracts across different stages of AD. Gradually increasing WM alterations were found in all tracts in successive stages of AD. Among all 18 WM tracts, the fornix was most adversely affected. Among all the parameters, mean diffusivity (MD) was the most sensitive to WM alterations in AD. This study provides a systematic workflow to examine WM integrity across automatically computed 3D tracts in AD and may be useful in studying other neurological and psychiatric disorders. Hum Brain Mapp 38:1191–1207, 2017. © 2016 Wiley Periodicals, Inc.

AbstractBackground.Preclinical and epidemiological data suggest that metformin might have antineoplastic properties against colon cancer (CC). However, the effect of metformin use on patient survival in stage III CC after curative resection is unknown. The survival outcomes were comparable regardless of the duration of metformin use.Patients and Methods.Before randomization to FOLFOX (folinic acid, 5-fluorouracil, oxaliplatin) with or without cetuximab, 1,958 patients with stage III CC enrolled in the N0147 study completed a questionnaire with information on diabetes mellitus (DM) and metformin use. Cox models were used to assess the association between metformin use and disease-free survival (DFS), overall survival (OS), and the time to recurrence (TTR), adjusting for clinical and/or pathological factors.Results.Of the 1,958 patients, 1,691 (86%) reported no history of DM, 115 reported DM with metformin use (6%), and 152 reported DM without metformin use (8%). The adjuvant treatment arms were pooled, because metformin use showed homogeneous effects on outcomes across the two arms. Among the patients with DM (n = 267), DFS (adjusted hazard ratio [aHR], 0.90; 95% confidence interval [CI], 0.59–1.35; p = .60), OS (aHR, 0.99; 95% CI, 0.65–1.49; p = .95), and TTR (aHR, 0.87; 95% CI, 0.56–1.35; p = .53) were not different for the metformin users compared with the nonusers after adjusting for tumor and patient factors. The survival outcomes were comparable regardless of the duration of metformin use (<1, 1–5, 6–10, ≥11 years) before randomization (ptrend = .64 for DFS, ptrend = .84 for OS, and ptrend = .87 for TTR). No interaction effects were observed between metformin use and KRAS, BRAF mutation status, tumor site, T/N stage, gender, or age.Conclusions.Patients with stage III CC undergoing adjuvant chemotherapy who used metformin before the diagnosis of CC experienced DFS, OS, and TTR similar to those for non-DM patients and DM patients without metformin use.

Purpose of reviewDetection of endometrial cancer at an early stage leads to better oncologic outcomes. To date, a screening test for endometrial cancer does not exist.Recent findingsEvolving knowledge of molecular changes involved in endometrial cancer carcinogenesis paired with sensitive and high-throughput technological advancements are a promising combination that can be leveraged to detect tumor DNA and proteins. These molecular biomarkers can be identified in biospecimens collected via minimally invasive and noninvasive approaches. Exploiting lower genital tract secretions as a biospecimen also allows for patient self-sampling.SummarySuccessful development of a screening test for endometrial cancer using self-collected lower genital tract biospecimens has the potential to increase accessibility to care and improve patient compliance.