No abstract

AXL is activated by its ligand GAS6 and is expressed in triple-negative breast cancer cells. In the current study, we report AXL expression in HER2-positive (HER2) breast cancers where it correlates with poor patient survival. Using murine models of HER2 breast cancer, Axl, but not its ligand Gas6, was found to be essential for metastasis. We determined that AXL is required for intravasation, extravasation, and growth at the metastatic site. We found that AXL is expressed in HER2 cancers displaying epithelial-to-mesenchymal transition (EMT) signatures where it contributes to sustain EMT. Interfering with AXL in a patient-derived xenograft (PDX) impaired transforming growth factor β (TGF-β)-induced cell invasion. Last, pharmacological inhibition of AXL specifically decreased the metastatic burden of mice developing HER2 breast cancer. Our data identify AXL as a potential anti-metastatic co-therapeutic target for the treatment of HER2 breast cancers.

Objective: This retrospective study was designed to assess the intensity of postoperative pain in relation to the location of craniotomy. Methods:After Research Ethics Board approval, data were collected from the charts of all patients who underwent a craniotomy at our institution between January 2004 and December 2005. The severity of post-craniotomy pain was assessed by collecting scores obtained using an 11-point verbal rating scale and calculating the cumulative analgesic requirements for the first 48 hr postoperatively. Data were compared according to the craniotomy location. Results:Data from 299 patients was available for analysis. On average, 76% of patients experienced moderate to severe postoperative pain. Frontal craniotomy was associated with lower pain scores than four of six craniotomy sites analyzed, with 49% of patients reporting mild pain, a significant difference (P < 0.05) compared with all other groups except for parietal craniotomies. Frontal craniotomy patients also had lower opioid analgesic requirements compared to patients who underwent posterior fossa craniotomy (P < 0.05). Logistic regression analysis showed that craniotomy location (P < 0.0001) and age (P = 0.004) were both independent predictors of the intensity of postoperative pain, with lower pain scores as age increased. Postoperative use of steroids, gender and presence of preoperative pain were not statistically linked to postoperative pain intensity. The prevalence of postoperative nausea and vomiting was 56% and it did not vary according to the location of craniotomy. Conclusion:This study shows that the intensity of postoperative pain in neurosurgery is affected by the site of craniotomy. Frontal craniotomy patients experienced the lowest pain scores, and required significantly less opioid than patients undergoing posterior fossa interventions.

Cancer cells exploit the epithelial-to-mesenchymal transition (EMT) program to become metastatic. Cytoskeletal regulators are required in mesenchymal cells where they promote EMT and EMT-induced migration. In a search for regulators of metastasis, we conducted shRNA screens targeting the microtubule plus-end tracking proteins (+TIPs). We show that the +TIP ACF7 is essential both for the maintenance of the EMT program and to promote migration. We find that the E3 ubiquitin ligase HectD1 promotes ACF7-proteasome-mediated degradation. Depletion of HectD1 stabilized ACF7, and this enhanced EMT and migration. Decreased HectD1 expression increased metastases in mouse models and conferred increased resistance to the cytotoxic drug cisplatin. A retrospective analysis of biopsies from breast cancer patients also reveals a correlation between higher ACF7 or lower HectD1 expression with poor clinical outcomes. Together, these results suggest that the control of ACF7 levels by HectD1 modulates EMT and the efficiency of metastasis.

Cyclin M (CNNM1-4) proteins maintain cellular and body magnesium (Mg2+) homeostasis. Using various biochemical approaches, we have identified members of the CNNM family as direct interacting partners of ADP-ribosylation factor-like GTPase 15 (ARL15), a small GTP-binding protein. ARL15 interacts with CNNMs at their carboxyl-terminal conserved cystathionine-β-synthase (CBS) domains. In silico modeling of the interaction between CNNM2 and ARL15 supports that the small GTPase specifically binds the CBS1 and CNBH domains. Immunocytochemical experiments demonstrate that CNNM2 and ARL15 co-localize in the kidney, with both proteins showing subcellular localization in the endoplasmic reticulum, Golgi apparatus and the plasma membrane. Most importantly, we found that ARL15 is required for forming complex N-glycosylation of CNNMs. Overexpression of ARL15 promotes complex N-glycosylation of CNNM3. Mg2+ uptake experiments with a stable isotope demonstrate that there is a significant increase of 25Mg2+ uptake upon knockdown of ARL15 in multiple kidney cancer cell lines. Altogether, our results establish ARL15 as a novel negative regulator of Mg2+ transport by promoting the complex N-glycosylation of CNNMs.

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Objectives The study sought to assess the clinical performance of a machine learning model aiming to identify unusual medication orders. Materials and Methods This prospective study was conducted at CHU Sainte-Justine, Canada, from April to August 2020. An unsupervised machine learning model based on GANomaly and 2 baselines were trained to learn medication order patterns from 10 years of data. Clinical pharmacists dichotomously (typical or atypical) labeled orders and pharmacological profiles (patients’ medication lists). Confusion matrices, areas under the precision-recall curve (AUPRs), and F1 scores were calculated. Results A total of 12 471 medication orders and 1356 profiles were labeled by 25 pharmacists. Medication order predictions showed a precision of 35%, recall (sensitivity) of 26%, and specificity of 97% as compared with pharmacist labels, with an AUPR of 0.25 and an F1 score of 0.30. Profile predictions showed a precision of 49%, recall of 75%, and specificity of 82%, with an AUPR of 0.60, and an F1 score of 0.59. The model performed better than the baselines. According to the pharmacists, the model was a useful screening tool, and 9 of 15 participants preferred predictions by medication, rather than by profile. Discussion Predictions for profiles had higher F1 scores and recall compared with medication order predictions. Although the performance was much better for profile predictions, pharmacists generally preferred medication order predictions. Conclusions Based on the AUPR, this model showed better performance for the identification of atypical pharmacological profiles than for medication orders. Pharmacists considered the model a useful screening tool. Improving these predictions should be prioritized in future research to maximize clinical impact.

This study suggests that all children admitted to hospital should have an evaluation of their NRS and NS, so that they can receive appropriate nutrition interventions provided by a multidisciplinary nutrition team.