These observations demonstrate that splicing regulators modulate splice site selection allosterically.The majority of mouse and human genes are subject to alternative cleavage and polyadenylation (APA), which most often leads to the expression of two or more alternative length 3' untranslated region (3' UTR) mRNA isoforms. In neural tissues, there is enhanced expression of APA isoforms with longer 3' UTRs on a global scale, but the physiological relevance of these alternative 3' UTR isoforms is poorly understood. Calmodulin 1 (Calm1) is a key integrator of calcium signaling that generates short (Calm1-S) and long (Calm1-L) 3' UTR mRNA isoforms via APA. We found Calm1-L expression to be largely restricted to neural tissues in mice including the dorsal root ganglion (DRG) and hippocampus, whereas Calm1-S was more broadly expressed. smFISH revealed that both Calm1-S and Calm1-L were subcellularly localized to neural processes of primary hippocampal neurons. In contrast, cultured DRG showed restriction of Calm1-L to soma. To investigate the in vivo functions of Calm1-L, we implemented a CRISPR-Cas9 gene editing strategy to delete a small region encompassing the Calm1 distal polyA site. This eliminated Calm1-L expression while maintaining expression of Calm1-S. Mice lacking Calm1-L (Calm1ΔL/ΔL) exhibited disorganized DRG migration in embryos, and reduced experience-induced neuronal activation in the adult hippocampus. These data indicate that Calm1-L plays functional roles in the central and peripheral nervous systems.Purpose Natural killer (NK) cells exert antibody-dependent cell cytotoxicity (ADCC). We infused expanded, activated autologous NK cells to potentiate trastuzumab-mediated ADCC in patients with HER2-positive malignancies. Patients and methods In a Phase I trial, patients with treatment-refractory HER2-positive solid tumors received trastuzumab, with or without bevacizumab, and autologous NK cells expanded by 10-day co-culture with K562-mb15-41BBL cells. Primary objectives included safety and recommended phase II dose determination; secondary objectives included monitoring NK-cell activity and RECIST antitumor efficacy. Results In 60 cultures with cells from 31 subjects, median NK-cell expansion from peripheral blood was 340-fold (range, 91-603). NK cells expressed high levels of CD16, the mediator of ADCC, and exerted powerful killing of trastuzumab-targeted cells. In the 22 subjects enrolled in Phase I dose escalation, trastuzumab plus NK cells were well tolerated; maximum tolerated dose was not reached. Phase IB (n=9) included multiple cycles of NK cells (1x107/kg) and addition of bevacizumab. Although no objective response was observed, 6 of the 19 subjects who received at least 1x107/kg NK cells at cycle 1 had stable disease for ≥6 months (median, 8.8 months; range 6.0-12.0). One patient, the only one with the high affinity F158V CD16 variant, had a partial response. Peripheral blood NK cells progressively downregulated CD16 post-infusion; paired tumor biopsies showed increased NK cells, lymphocytic infiltrates, and apoptosis post-treatment. Discussion NK cell therapy in combination with trastuzumab was well tolerated, with target engagement and preliminary antitumor activity, supporting continued assessment of this approach in Phase II trials.Purpose The choice of therapy for breast cancer patients is often based on clinicopathological parameters, hormone receptor status, and HER2 amplification. To improve individual prognostication and tailored treatment decisions, we combined clinicopathological prognostic data with genome instabilty profiles established by quantitative measurements of the DNA content. Experimental design We retrospectively assessed clinical data of 4,003 breast cancer patients with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves and multivariable Cox proportional hazard models, to ascertain the potential of both, standard clinicopathological data and genome instability profiles, as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment. Results In Cox regression analyses, two parameters of the genome instability profiles, i.e., the S-phase fraction and the stemline scatter index emerged as independent predictors in premenopausal women, outperforming all clinicopathological parameters. In postmenopausal women, age and hormone receptor status were the predominant prognostic factors. However, by including S-phase fraction and 2.5c exceeding rate, we could improve disease outcome prediction in pT1 tumors irrespective of the lymph node status. In pT3-pT4 tumors, a higher S-phase fraction led to poorer prognosis. In patients who received adjuvant endocrine, chemo- or radiotherapy, or a combination, the ploidy profiles improved prognostication. Conclusions Genome instability profiles predict disease outcome in breast cancer patients independent of clinicopathological parameters. This applies especially to premenopausal patients.  https://www.selleckchem.com/products/azd9291.html  In patients receiving adjuvant therapy, the profiles improve identification of high-risk patients.Purpose Various biomarkers have been proposed for sunitinib therapy in GIST. However, the lack of 'real-life' comparative studies hampers the selection of the most appropriate one. We therefore set up a pharmacometric simulation framework to compare each proposed biomarker. Experimental design Models describing relations between sunitinib exposure, adverse events (HFS, fatigue, hypertension and neutropenia), sVEGFR-3 and overall survival were connected to evaluate the differences in survival and adverse events under different dosing algorithms. Various fixed dosing regimens (4/2 (weeks on/weeks off) or 2/1 (50 mg), and continuous daily dosing (37.5 mg)) and individualization approaches (concentration-adjusted dosing (CAD), toxicity-adjusted dosing (TAD) and sVEGFR-3-adjusted dosing (VAD)) were explored following earlier suggested blood sampling schedules and dose-reduction criteria. Model-based forecasts of biomarker changes were evaluated for predictive accuracy and the advantage of a model-based dosing algorithm was evaluated for clinical implementation.