Publications

<div>Abstract<p>Novel therapeutic strategies are urgently needed for patients with high-risk Ewing sarcoma and for the reduction of severe side effects for all patients. Immunotherapy may fill this need, but its successful application has been hampered by a lack of knowledge on the composition and function of the Ewing sarcoma immune microenvironment. Here, we explore the immune microenvironment of Ewing sarcoma, by single-cell RNA sequencing of 18 Ewing sarcoma primary tissue samples. Ewing sarcoma is infiltrated by natural killer, T, and B cells, dendritic cells, and immunosuppressive macrophages. Ewing sarcoma–associated T cells show various degrees of dysfunction. The antigen-presenting cells found in Ewing sarcoma lack costimulatory gene expression, implying functional impairment. Interaction analysis reveals a clear role for Ewing sarcoma tumor cells in turning the Ewing sarcoma immune microenvironment into an immunosuppressive niche. These results provide novel insights into the functional state of immune cells in the Ewing sarcoma tumor microenvironment and suggest mechanisms by which Ewing sarcoma tumor cells interact with, and shape, the immune microenvironment.</p>Significance:<p>This study is the first presenting a detailed analysis of the Ewing sarcoma microenvironment using single-cell RNA sequencing. We provide novel insight into the functional state of immune cells and suggests mechanisms by which Ewing tumor cells interact with, and shape, their immune microenvironment. These insights provide help in understanding the failures and successes of immunotherapy in Ewing sarcoma and may guide novel targeted (immuno) therapeutic approaches.</p></div>

Air-liquid interface (ALI) cultures are frequently used in lung research but require substantial cell numbers that cannot readily be obtained from patients. We explored whether organoid expansion [three-dimensional (3D)] can be used to establish ALI cultures from clinical samples with low epithelial cell numbers. Airway epithelial cells were obtained from tracheal aspirates (TA) from preterm newborns and from bronchoalveolar lavage (BAL) or bronchial tissue (BT) from adults. TA and BAL cells were 3D-expanded, whereas cells from BT were expanded in 3D and 2D. Following expansion, cells were cultured at ALI to induce differentiation. The impact of cell origin and 2D or 3D expansion was assessed with respect to 1) cellular composition, 2) response to cigarette smoke exposure, and 3) effect of Notch inhibition or IL-13 stimulation on cellular differentiation. We established well-differentiated ALI cultures from all samples. Cellular compositions (basal, ciliated, and goblet cells) were comparable. All 3D-expanded cultures showed a similar stress response following cigarette smoke exposure but differed from the 2D-expanded cultures. Higher peak levels of antioxidant genes HMOX1 and NQO1 and a more rapid return to baseline, and a lower unfolded protein response was observed after cigarette smoke exposure in 3D-derived cultures compared to 2D-derived cultures. In addition, TA- and BAL-derived cultures were less sensitive to modulation by DAPT or IL-13 than BT-derived cultures. Organoid-based expansion of clinical samples with low cell numbers, such as TA from preterm newborns is a valid method and tool to establish ALI cultures.

Background Despite large amounts of research on determinants of burnout, research on its treatment is scarce. In the Netherlands, occupational physicians (OPs) can officially diagnose burnout and have to offer return-to-work (RTW) guidance to employees on sick leave, which includes referral to treatment. This research aimed to explore 1) characteristics of treatment for burnout and 2) how employee-, complaint- and employer characteristics relate to referral to treatment by the OP and to employee RTW expectation. Methods All 212 employees (45% male, 42.5 years of age, 35% high educated) diagnosed with burnout at one occupational health service during February-June 2020 were included. Register data (gender, age (years), education, organization size) and self-reported data collected online (living situation; Burnout Assessment Tool (BAT) score; cause of absence mainly work-related (0/1); treatment (0/1); on waiting list (0/1); type of treatment; treatment focused on RTW (0/1); employee RTW expectation high (0/1)) were tested with Chi2, ANOVA and logistic regression analyses. Results Of all employees, 75.9% (n = 161) were referred to treatment by their OP, of which 25.5% (n = 41) were currently on a waiting list. The majority received treatment from a nurse practitioner (51.7%) or psychologist (23.3%) These practitioners focused on RTW less often (51.6%-60.7%) than the other practitioners (81.5-100%) (p = 0.042). Multivariate tests showed age to relate to referral to treatment (OR 0.956; 95% CI 0.928-0.986) and BAT score to employee RTW expectation (OR 0.635; 95% CI 0.407-0.991). Conclusions OPs referred three quarters of the employees on sick leave with burnout to treatment. Referral by OPs related only to younger age and employee RTW expectation only to BAT score. The practitioners that were referred to most often, focused less on RTW. As burnout is a work-related syndrome, these findings suggest room for improving the treatment's focus on (returning to) work. Key messages OPs referred 75.9% of the burned out employees on sick leave to treatment, particularly younger employees. The practitioners that were referred to most often, focused less on RTW.

No abstract is provided for this article.

<div>Abstract<p>Increasing knowledge about signal transduction pathways as drivers of cancer growth has elicited the development of “targeted drugs,” which inhibit aberrant signaling pathways. They require a companion diagnostic test that identifies the tumor-driving pathway; however, currently available tests like estrogen receptor (ER) protein expression for hormonal treatment of breast cancer do not reliably predict therapy response, at least in part because they do not adequately assess functional pathway activity. We describe a novel approach to predict signaling pathway activity based on knowledge-based Bayesian computational models, which interpret quantitative transcriptome data as the functional output of an active signaling pathway, by using expression levels of transcriptional target genes. Following calibration on only a small number of cell lines or cohorts of patient data, they provide a reliable assessment of signaling pathway activity in tumors of different tissue origin. As proof of principle, models for the canonical Wnt and ER pathways are presented, including initial clinical validation on independent datasets from various cancer types. <i>Cancer Res; 74(11); 2936–45. ©2014 AACR</i>.</p></div>