Breast organoid suspension cultures maintain long-term estrogen receptor expression and responsiveness.

Organoid cultures offer a powerful technology to investigate many different aspects of development, physiology, and pathology of diverse tissues. Unlike standard tissue culture of primary breast epithelial cells, breast organoids preserve the epithelial lineages and architecture of the normal tissue. However, existing organoid culture methods are tedious, difficult to scale, and do not robustly retain estrogen receptor (ER) expression and responsiveness in long-term culture. Here, we describe a modified culture method to generate and maintain organoids as suspension cultures in reconstituted basement membrane (™Matrigel). This method improves organoid growth and uniformity compared to the conventional Matrigel dome embedding method, while maintaining the fidelity of the three major epithelial lineages. Using this adopted method, we are able to culture and passage purified hormone sensing (HS) cells that retain ER responsiveness upon estrogen stimulation in long-term culture. This culture system presents a valuable platform to study the events involved in initiation and evolution of ER-positive breast cancer.

Single-cell transcriptomics identifies a WNT7A-FZD5 signaling axis that maintains fallopian tube stem cells in patient-derived organoids.

The study of fallopian tube (FT) function in health and disease has been hampered by limited knowledge of FT stem cells and lack of in vitro models of stem cell renewal and differentiation. Using optimized organoid culture conditions to address these limitations, we find that FT stem cell renewal is highly dependent on WNT/ß-catenin signaling and engineer endogenous WNT/ß-catenin signaling reporter organoids to biomark, isolate, and characterize these cells. Using functional approaches, as well as bulk and single-cell transcriptomics analyses, we show that an endogenous hormonally regulated WNT7A-FZD5 signaling axis is critical for stem cell renewal and that WNT/ß-catenin pathway-activated cells form a distinct transcriptomic cluster of FT cells enriched in extracellular matrix (ECM) remodeling and integrin signaling pathways. Overall, we provide a deep characterization of FT stem cells and their molecular requirements for self-renewal, paving the way for mechanistic work investigating the role of stem cells in FT health and disease.

Parainfluenza viruses: A trigger for type 1 diabetes new onset?

Type 1 diabetes (T1DM) ethiopathogenesis is still being studied, since the role of environmental factors , especially viruses, is not yet clear. This study was conducted on 31 paediatric patients with T1DM at onset. We analysed: Coxsackieviruses A (CoxA), Coxsackieviruses B (CoxB), Echoviruses (Echo); Influenzavirus A and B (IV-A and IV-B); Adenovirus (AdV); Parainfluenza viruses 1-2 and 3 (PiV 1-2-3); Cytomegalovirus (CMV) and Respiratory Syncytial Virus (RSV). Enteroviruses, especially CoxB and Echo, are most represented. Unexpectedly, Parainfluenza viruses were detected in seasonal subgroups, with peaks in autumn and spring, and spread homogeneously in different age groups.

Distinguishing True Progression From Radionecrosis After Stereotactic Radiation Therapy for Brain Metastases With Machine Learning and Radiomics.

PURPOSE: Treatment effect or radiation necrosis after stereotactic radiosurgery (SRS) for brain metastases is a common phenomenon often indistinguishable from true progression. Radiomics is an emerging field that promises to improve on conventional imaging. In this study, we sought to apply a radiomics-based prediction model to the problem of diagnosing treatment effect after SRS. METHODS AND MATERIALS: We included patients in the Johns Hopkins Health System who were treated with SRS for brain metastases who subsequently underwent resection for symptomatic growth. We also included cases of likely treatment effect in which lesions grew but subsequently regressed spontaneously. Lesions were segmented semiautomatically on preoperative T1 postcontrast and T2 fluid-attenuated inversion recovery magnetic resonance imaging, and radiomic features were extracted with software developed in-house. Top-performing features on univariate logistic regression were entered into a hybrid feature selection/classification model, IsoSVM, with parameter optimization and further feature selection performed using leave-one-out cross-validation. Final model performance was assessed by 10-fold cross-validation with 100 repeats. All cases were independently reviewed by a board-certified neuroradiologist for comparison. RESULTS: We identified 82 treated lesions across 66 patients, with 77 lesions having pathologic confirmation. There were 51 radiomic features extracted per segmented lesion on each magnetic resonance imaging sequence. An optimized IsoSVM classifier based on top-ranked radiomic features had sensitivity and specificity of 65.38% and 86.67%, respectively, with an area under the curve of 0.81 on leave-one-out cross-validation. Only 73% of cases were classifiable by the neuroradiologist, with a sensitivity of 97% and specificity of 19%. CONCLUSIONS: Radiomics holds promise for differentiating between treatment effect and true progression in brain metastases treated with SRS. A predictive model built on radiomic features from an institutional cohort performed well on cross-validation testing. These results warrant further validation in independent datasets. Such work could prove invaluable for guiding management of individual patients and assessing outcomes of novel interventions.