Nutrients shape T cell exhaustion
Related Articles
Synthesis and characterization of soquelitinib a selective ITK inhibitor that modulates tumor immunity
ITK is a kinase involved in T cell activation, proliferation and differentiation. In mice, selective knock-out of the ITK gene produces Th1 skewing of T helper cell differentiation. Soquelitinib, a covalent ITK inhibitor, blocks ITK activity with greater than 100-fold selectivity compared to inhibition of a related kinase, RLK. We describe the chemistry and biologic effects of soquelitinib. In vitro studies with normal or malignant T cells demonstrated that soquelitinib suppresses Th2 cytokine production preferentially with relative sparing of Th1 cytokines. Soquelitinib inhibits the in vivo growth of several syngeneic murine tumors including those that do not express ITK. Treatment with soquelitinib leads to increased tumor infiltration of normal CD8+ cells that possess enhanced T effector function. Soquelitinib reduced expression of T cell exhaustion markers and was able to restore T effector function to exhausted cells. Pharmacologic selective ITK inhibition may represent a novel approach to cancer immunotherapy.
One-carbon metabolism is distinct metabolic signature for proliferative intermediate exhausted T cells of ICB-resistant cancer patients
One-carbon metabolism (1CM) has been reported to promote cancer progression across various malignancies. While 1CM is critical for cell proliferation by enhancing nucleotide synthesis, its physiological roles within different cell types in the tumor immune microenvironment (TIME) still remain unclear. In this study, we analyzed bulk-RNA sequencing and single-cell RNA sequencing (scRNA-seq) data from lung adenocarcinoma (LUAD) patients to elucidate the functional roles of 1CM within the TIME. Moreover, we examined scRNA-seq data from patients treated with immunotherapy across various cancers, including LUAD, glioblastoma, renal cell carcinoma, colorectal cancer, and triple-negative breast cancer. Compared to other cell types, 1CM gene profiles are significantly enriched in a specific subset of T cells. Intriguingly, these high-1CM T cells are identified as proliferative intermediate exhausted T cells (Texint). Furthermore, these proliferative Texint received the most robust CD137 signaling. Consistently, analysis of scRNA-seq data from LUAD patients undergoing anti-PD1 immunotherapy demonstrated that proliferative Texint exhibited higher 1CM scores and increased CD137 signaling. This observation was particularly pronounced in non-responders to immunotherapy, where the Texint population was significantly expanded. We further established that 1CM is a prominent signaling pathway in proliferative Texint in patients resistant to immunotherapy across multiple cancer types. Collectively, we identify CD137 signaling as a distinctive pathway in proliferative Texint of LUAD patients who do not respond to immunotherapy. These findings propose that targeting 1CM may represent a novel therapeutic strategy to enhance the efficacy of immunotherapy by mitigating Texint proliferation in diverse cancers.
Overall biomass yield on multiple nutrient sources
Microorganisms primarily utilize nutrients to generate biomass and replicate. When a single nutrient source is available, the produced biomass typically increases linearly with the initial amount of that nutrient. This linear trend can be accurately predicted by “black box models”, which conceptualize growth as a single chemical reaction, treating nutrients as substrates and biomass as a product. However, natural environments usually present multiple nutrient sources, prompting us to extend the black box framework to incorporate catabolism, anabolism, and biosynthesis of biomass precursors. This modification allows for the quantification of co-utilization effects among multiple nutrients on microbial biomass production. The extended model differentiates between different types of nutrients: non-degradable nutrients, which can only serve as a biomass precursor, and degradable nutrients, which can also be used as an energy source. We experimentally demonstrated using Escherichia coli that, in contrast to initial model predictions, different nutrients affect each other’s utilization in a mutually dependent manner; i.e., for some combinations, the produced biomass was no longer proportional to the initial amounts of nutrients present. To account for these mutual effects within a black box framework, we phenomenologically introduced an interaction between the metabolic processes involved in utilizing the nutrient sources. This phenomenological model qualitatively captures the experimental observations and, unexpectedly, predicts that the total produced biomass is influenced not only by the combination of nutrient sources but also by their relative initial amounts – a prediction we subsequently validated experimentally. Moreover, the model identifies which metabolic processes – catabolism, anabolism, or precursor biosynthesis—is affected in each specific nutrient combination, offering insights into microbial metabolic coordination.
Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS
Large-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.
Label-free live cell recognition and tracking for biological discoveries and translational applications
Label-free, live cell recognition (i.e. instance segmentation) and tracking using computer vision-aided recognition can be a powerful tool that rapidly generates multi-modal readouts of cell populations at single cell resolution. However, this technology remains hindered by the lack of accurate, universal algorithms. This review presents related biological and computer vision concepts to bridge these disciplines, paving the way for broad applications in cell-based diagnostics, drug discovery, and biomanufacturing.
Responses