Brigham and Women's Hospital

Claims-based analyses can suffer from residual and unmeasured confounding due to factors that are poorly captured in claims. Some of these factors may be measured in other data sources, such as in structured fields of electronic health records (EHR), for example, laboratory test results, or in free-text physician notes. We conducted a proof-of-principle study to demonstrate a process for evaluating the potential risk of confounding-factors poorly captured in claims data but measurable in the EHR as part of drug safety surveillance activities. In future practical applications, this approach could be used along with other sensitivity analyses to evaluate potential residual confounding (e.g., E-values, negative controls). We used claims-EHR linked data from the Mass General Brigham site of the US Food and Drug Administration's (FDA) Sentinel Real World Evidence Data Enterprise. We extracted a cohort that was previously used in a prototypical Sentinel claims-based query that compared initiators of sacubitril-valsartan vs. angiotensin-converting enzyme inhibitors or angiotensin receptor blockers on the risk of angioedema. In this cohort, we used EHR data to characterize angioedema risk factors poorly captured in claims and observed that claims-based proxies balanced most risk factors that were measurable only in EHR data. While quantitative bias analysis methods can be used to adjust for residual confounding using external information on magnitude and direction of bias, this was deemed unnecessary for this example due to the observed balance achieved on risk factors for angioedema measured in the EHR. A robust linked EHR-claims data infrastructure is crucial for routine application of these methods to evaluate and mitigate residual confounding in drug safety surveillance studies.

Label-free and effective sorting of red and white blood cells based on their physical properties is crucial for subsequent single-cell analysis or immune cell engineering applications. However, cell sorting relying on the physical effects of one single physical property remains highly challenging. This paper proposes a cell sorting method based on a focused traveling surface acoustic wave (FTSAW)-based acoustofluidic chip, which leverages the ability of FTSAW acoustofluidics to comprehensively respond to multiple physical characteristics of cells (e.g., size, density, morphology, and deformability), and furthermore allows for precise setting of the action area range and adjustment of the action intensity. In experiments, a pair of focused interdigital transducers (FIDTs, characteristic frequency: 128.6 MHz) on the substrate of lithium niobate and a typical microchannel structure (single-side sheath flow focusing followed by bifurcated sorting, i.e., "two streams merging into one and then splitting into two") were designed and fabricated. Parameter optimization experiments for separation and sorting were conducted on 3 μm and 5 μm polystyrene (PS) beads, as well as red and white blood cell samples after sheath flow focusing. The results indicate that the FTSAW-based acoustofluidic chip enabled white blood cell sorting with high purity (∼90%) and high biological viability (∼98%). This study demonstrates the potential of the FTSAW-based acoustofluidic chip for cell sorting. Owing to its easy integration and advantages (non-contact operation, no sieve pore clogging, broad compatibility with cell culture media), it is expected to serve as a key pre-processing technology in microfluidic systems for single-cell analysis or cell engineering.

Mechanisms driving aggressive meningiomas remain poorly understood. Given the pivotal role of the immune microenvironment in tumor progression, we developed a comprehensive atlas of the meningioma microenvironment, with a view toward identifying modifiable opportunities. The immune microenvironment of 2,727 meningiomas was profiled using orthogonal methodologies, including 24 with mass cytometry, 24 single-cell RNAseq, 1,437 bulk RNAseq, 1,125 DNA methylation, 117 multiplex immunofluorescence, as well as that of 5 paired peripheral blood samples and 10 human meninges. Patient-derived organotypic tumor spheroids (PDOTS) were established to assess the effect of STING stimulation combined with anti-PD-1 treatment. We revealed a rich immune infiltration in meningioma, among the highest across 34 human cancer types (n = 12,188). Macrophages predominated in meningioma microenvironment, in contrast to the lymphoid dominance of peripheral blood, with meninges exhibiting an intermediate immune profile between meningiomas and peripheral blood. Cellular states and phenotypes of both immune and tumor cells shifted during tumor progression, with aggressive meningiomas possessing earlier-stage, immunosuppressive immune cells and proliferative tumor cells. Using ex vivo meningioma PDOTS, we demonstrated inducible responses to STING activation, marked by elevated cytokine release, which were synergistic when combined with PD-1 blockade. These findings offer an extensive resource on the cellular heterogeneity of the meningioma microenvironment and provide a framework for rational therapeutic modeling and strategy development.