RESUMO
We present a novel framework combining single-cell phenotypic data with single-cell transcriptomic analysis to identify factors underpinning heterogeneity in antitumor immune response. We developed a pairwise, tumor-immune discretized interaction assay between natural killer (NK-92MI) cells and patient-derived head and neck squamous cell carcinoma (HNSCC) cell lines on a microfluidic cell-trapping platform. Furthermore we generated a deep-learning computer vision algorithm that is capable of automating the acquisition and analysis of a large, live-cell imaging data set (>1 million) of paired tumor-immune interactions spanning a time course of 24 h across multiple HNSCC lines (n = 10). Finally, we combined the response data measured by Kaplan-Meier survival analysis against NK-mediated killing with downstream single-cell transcriptomic analysis to interrogate molecular signatures associated with NK-effector response. As proof-of-concept for the proposed framework, we efficiently identified MHC class I-driven cytotoxic resistance as a key mechanism for immune evasion in nonresponders, while enhanced expression of cell adhesion molecules was found to be correlated with sensitivity against NK-mediated cytotoxicity. We conclude that this integrated, data-driven phenotypic approach holds tremendous promise in advancing the rapid identification of new mechanisms and therapeutic targets related to immune evasion and response.
RESUMO
There are 0.6-1.9% of US children who were born with congenital heart malformations. Clinical and animal studies suggest that abnormal blood flow forces might play a role in causing these malformation, highlighting the importance of understanding the fetal cardiovascular fluid mechanics. We performed computational fluid dynamics simulations of the right ventricles, based on four-dimensional ultrasound scans of three 20-wk-old normal human fetuses, to characterize their flow and energy dynamics. Peak intraventricular pressure gradients were found to be 0.2-0.9 mmHg during systole, and 0.1-0.2 mmHg during diastole. Diastolic wall shear stresses were found to be around 1 Pa, which could elevate to 2-4 Pa during systole in the outflow tract. Fetal right ventricles have complex flow patterns featuring two interacting diastolic vortex rings, formed during diastolic E wave and A wave. These rings persisted through the end of systole and elevated wall shear stresses in their proximity. They were observed to conserve â¼25.0% of peak diastolic kinetic energy to be carried over into the subsequent systole. However, this carried-over kinetic energy did not significantly alter the work done by the heart for ejection. Thus, while diastolic vortexes played a significant role in determining spatial patterns and magnitudes of diastolic wall shear stresses, they did not have significant influence on systolic ejection. Our results can serve as a baseline for future comparison with diseased hearts.