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Great strides have been made in recent years towards understanding the roles of natural killer (NK) cells in immunity to tumours and viruses. NK cells are cytotoxic innate lymphoid cells that produce inflammatory cytokines and chemokines. By lysing transformed or infected cells, they limit tumour growth and viral infections. Whereas T cells recognize peptides presented by MHC molecules, NK cells display receptors that recognize stress-induced autologous proteins on cancer cells. At the same time, their functional activity is inhibited by MHC molecules displayed on such cells. The enormous potential of NK cells for immunotherapy for cancer is illustrated by their broad recognition of stressed cells regardless of neoantigen presentation, and enhanced activity against tumours that have lost expression of MHC class I owing to acquired resistance mechanisms. As a result, many efforts are under way to mobilize endogenous NK cells with therapeutics, or to provide populations of ex vivo-expanded NK cells as a cellular therapy, in some cases by equipping the NK cells with chimeric antigen receptors. Here we consider the key features that underlie why NK cells are emerging as important new additions to the cancer therapeutic arsenal.
Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a "cells-to-peptides" automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography-mass spectrometry systems. The automated workflow was tested by preparing 96 <i>Escherichia coli</i> samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM-MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.