Citations

Abstract Background Poor operating room (OR) ergonomics poses risk of injury to OR staff, worsening patient outcomes and threatening workforce wellness and sustainability. How OR staff navigate ergonomic barriers in the interdisciplinary team environment was examined in this qualitative study. Methods Semi-structured, open-ended interviews of surgeons, anaesthesiologists, and OR nurses were conducted at a single institution using a sociomaterial approach with interview-to-the-double. Transcripts were coded by two independent researchers. Themes in the data were outlined using the System Engineering Initiative for Patient Safety (SEIPS) 2.0 framework. Results Five major themes were identified. First, physical environment issues creating cognitive and physical frictions, such as tripping hazards and poor room layouts. Second, influence of social positionality, with hierarchy by role and experience and social dynamics leading to a differential capacity to adjust. Third, team collaboration, with lack of interdisciplinary work and communication and high staff turnover. Fourth, burden of self-initiated workarounds, outlining conflicts between system/organizational issues and individual solutions. Fifth, institutional support, with lack of leadership engagement. Participants suggested solutions including accommodations to foster a collaborative approach to managing discomfort in the OR and new team communication tools. Conclusion Ergonomic barriers were described within the work system of the SEIPS 2.0 framework. Social positionality and differential levels of agency, as well as lack of team collaboration and misperceptions of others’ roles, were central to ergonomic challenges. Conflicts between problems lying with the system/organization and solutions being left to individuals were also central to challenges to optimal OR ergonomics.

ABSTRACT Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method– independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

Abstract Early T-cell acute lymphoblastic leukemia (ETP-ALL) is an aggressive hematologic malignancy associated with early relapse and poor prognosis that is genetically, immunophenotypically, and transcriptionally distinct from more mature T-cell acute lymphoblastic leukemia (T-ALL) tumors. Here, we leveraged global metabolomic and transcriptomic profiling of primary ETP- and T-ALL leukemia samples to identify specific metabolic circuitries differentially active in this high-risk leukemia group. ETP-ALLs showed increased biosynthesis of phospholipids and sphingolipids and were specifically sensitive to inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase, the rate-limiting enzyme in the mevalonate pathway. Mechanistically, inhibition of cholesterol synthesis inhibited oncogenic AKT1 signaling and suppressed MYC expression via loss of chromatin accessibility at a leukemia stem cell–specific long-range MYC enhancer. In all, these results identify the mevalonate pathway as a druggable novel vulnerability in high-risk ETP-ALL cells and uncover an unanticipated critical role for cholesterol biosynthesis in signal transduction and epigenetic circuitries driving leukemia cell growth and survival. Significance: Overtly distinct cell metabolic pathways operate in ETP- and T-ALL pointing to specific metabolic vulnerabilities. Inhibition of mevalonate biosynthesis selectively blocks oncogenic AKT–MYC signaling in ETP-ALL and suppresses leukemia cell growth. Ultimately, these results will inform the development of novel tailored and more effective treatments for patients with high-risk ETP-ALL. This article is highlighted in the In This Issue feature, p. 587