Back

T cell polarization and NFAT translocation are stiffness-dependent and are differentially regulated by Piezo1 and Orai1

Zhao, R.; Zhang, J.; Schwarz, E. C.; Campo, A. d.; Hoth, M.; Qu, B.

2024-03-11 immunology
10.1101/2024.03.06.583253 bioRxiv
Show abstract

Effective T cell responses against tumor cells require diverse effector functions including polarization towards tumor cells to form immunological synapses and nuclear factor of activated T-cells (NFAT)-dependent gene transcription. While the role of tumor cell softening has been associated with malignancy, stemness, and metastasis, potentially contributing to immune evasion, its impact on cellular processes in T cells is not well understood. Here, we show that both T cell polarization and NFAT nuclear translocation are modulated by target stiffness in a Ca2+ dependent manner. Using both anti-CD3 antibody-functionalized substrates with varying stiffness as surrogates for target cells or softened tumor cells, we found that both, reorientation of microtubule organizing center (MTOC) towards the tumor cells, a hallmark for T cell polarization, and NFAT translocation were impaired on softer hydrogels or following contact with softer cancer cells. The amplitudes of intracellular Ca2+ signals were dependent on stiffness, and removal of extracellular Ca2+ inhibited stiffness-dependent T cell responsiveness. While stiffness-dependent Ca2+ signaling was crucial for both, T cell polarization and NFAT translocation, Ca2+ influx through Piezo1, a mechanosensitive ion channel, mediated stiffness-dependent MTOC reorientation but not NFAT translocation. In contrast, Ca2+ influx through store-operated Orai channels mediated NFAT translocation but not MTOC reorientation. Our results demonstrate that tumor cell stiffness directly influences T cell functionality through distinct Ca2+ influx pathways, revealing cell softening as an essential mechanism employed by malignant cells to evade immune surveillance.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.