Abstract Background Immune checkpoint inhibitors (CPI) have transformed cancer outcomes, but frequently trigger autoimmune- like events, including life-threatening colitis. Current immunosuppressive treatments for CPI- colitis (CPI-c) incur significant side effects and may compromise CPI efficacy, highlighting the need for new therapies. Methods RNA sequencing was performed on colonic biopsies from patients with CPI-c (n=12), CPI (no colitis, n=6), healthy controls (n=13), and UC (n=12). Gene expression, pathway level (GSEA) and cellular composition were analysed. Cell-cell communication were analysed using a single-cell RNA sequencing reposited dataset. Colonic organoids from CPI-c and controls were cultured and treated with IFNg ± JAK1-STAT inhibition with Upadacitinib . The impact of JAK1 blockade was evaluated in vivo using pre-clinical models of CPI-c1. Colonic leukocytes were analysed by flow cytometry. Clinical and endoscopic outcomes were defined in five patients with treatment-refractory CPI-c, following treatment with Upadacitinib 45mg for 8 weeks. Results Gene expression profiling of colonic biopsies highlighted overactivity of the JAK1-dependent cytokine IFNg in CPI-c. IFNg responsive transcripts, including CXCL9, CXCL10, IDO1, GZMB and STAT1, were among the most upregulated transcripts, with IFNg signalling identified as the top enriched pathway. Cellular deconvolution revealed enrichment of TH1 and CD8+ memory cells. Cell-cell communication analysis indicated distinct dialogue mediated by IFNg between T-cell subsets in CPI-c, including TH17+PD1+ and epithelial cells, and inflammatory enterocytes. Colonic organoids from CPI-c patients retained high baseline expression of IFNg-responsive transcripts, and significantly over-expressed these following ex vivo stimulation with IFNg, which was corroborated at protein level. Upadacitinib treatment of stimulated organoids reversed these changes. In vivo administration of Upadacitinib significantly reduced pathological features and severity of CPI-c in preclinical models of disease. Encouraged by these findings, we treated 5 patients with severe, treatment refractory CPI-c with Upadacitinib. All achieved rapidly resolution of disease with complete mucosal healing, no adverse events, and favourable 9-month cancer outcomes were sustained. Conclusion IFNg signalling was highly upregulated in CPI-colitis patients, which was recapitulated in a novel CPI-c derived colonic organoid model and in vivo models of disease. Upadacitinib improved organoid morphology, reduced IFNg targets, and ameliorated CPI-c in mice. Moreover, Upadacitinib rapidly rescued treatment refractory patients highlighting its potential as a promising therapeutic approach in patients with severe disease. References 1. Lo J, Cozzetto D, Liu Z, et al. Immune checkpoint inhibitor-induced colitis is mediated by CXCR6+ polyfunctional lymphocytes and is dependent on the IL23/IFNγ axis. Nat Commun. 2022;13(1)41798. doi:10.1038/s41467-023-41798-2
Despite its role in cancer surveillance, adoptive immunotherapy using γδ T cells has achieved limited efficacy. To enhance trafficking to bone marrow, circulating Vγ9Vδ2 T cells are expanded in serum-free medium containing TGF-β1 and IL-2 (γδ[T2] cells) or medium containing IL-2 alone (γδ[2] cells, as the control). Unexpectedly, the yield and viability of γδ[T2] cells are also increased by TGF-β1, when compared to γδ[2] controls. γδ[T2] cells are less differentiated and yet display increased cytolytic activity, cytokine release, and antitumor activity in several leukemic and solid tumor models. Efficacy is further enhanced by cancer cell sensitization using aminobisphosphonates or Ara-C. A number of contributory effects of TGF-β are described, including prostaglandin E
Abstract Background Cytokines are small peptides that signal between a variety of cell types and are one of the fundamental communication elements of the immune system. A variety of cytokine—cytokine interactions have previously been investigated in the literature, describing cytokines activating or inhibiting other cytokines in target cell types, and thus progressing the immune response to infection and illness. Disruption of cytokine communication is often an important goal in drug development as these compounds allow quelling and managing an overactive immune response in chronic diseases, such as Inflammatory Bowel Disease (IBD). In our previous work, we have introduced CytokineLink, a novel computational framework developed to establish cytokine—cytokine interactions from transcriptomics data (Olbei et al., Cells, 2021). Methods In this project, we generated a global network of cytokine—cytokine interactions based on cytokine response transcriptomics data from over 2000 datasets deposited in the CytoSig database. Using CytoSig’s significance analysis protocol, we established statistically significant cytokine—cytokine interactions, and determined the likely intracellular pathways connecting upstream and target cytokines using the OmniPath interaction resource. Results The resulting network is a signed, directed network of cytokine communication, containing 488 cytokine—cytokine interactions of 91 cytokines. The interactions in the network are annotated with the intracellular pathways that the included cytokines are anticipated to utilise, as well as the stimulatory and inhibitory effects that the cytokines have on one another. The resource captures the cytokine—cytokine networks of cytokines crucial in the pathophysiology of IBD, such as TNF, IL2, IL21, and OSM, which may grant novel insights into the cytokine pathways important in the molecular mechanisms underlying chronic diseases like IBD. The resource can be used by the community as a knowledge base for hypothesis generation, and is freely available through the NDEx platform. Conclusion In our work, we generated a novel computational framework collating how cytokines differentially regulate the expression of one another based on cytokine response transcriptomics data. The resulting interactions are signed, highlighting the inhibitory or stimulatory nature of the associations, and the change in expression associated with each link. The resource could be used to identify previously unknown network pharmacology targets, and to better understand the cytokine dysregulation in chronic diseases such as IBD by illustrating the interplay of the most influential IBD associated cytokines with other cytokines.
Abstract The maintenance of intestinal homeostasis is a fundamental process critical for organismal integrity. Sitting at the interface of the gut microbiome and mucosal immunity, adaptive and innate lymphoid populations regulate the balance between commensal micro-organisms and pathogens. Checkpoint inhibitors, particularly those targeting the CTLA-4 pathway, disrupt this fine balance and can lead to inflammatory bowel disease and immune checkpoint colitis. Here, we show that CTLA-4 is expressed by innate lymphoid cells and that its expression is regulated by ILC subset-specific cytokine cues in a microbiota-dependent manner. Genetic deletion or antibody blockade of CTLA-4 in multiple in vivo models of colitis demonstrates that this pathway plays a key role in intestinal homeostasis. Lastly, we have found that this observation is conserved in human IBD. We propose that this population of CTLA-4-positive ILC may serve as an important target for the treatment of idiopathic and iatrogenic intestinal inflammation.
Genome3D (http://www.genome3d.eu) is a collaborative resource that provides predicted domain annotations and structural models for key sequences. Since introducing Genome3D in a previous NAR paper, we have substantially extended and improved the resource. We have annotated representatives from Pfam families to improve coverage of diverse sequences and added a fast sequence search to the website to allow users to find Genome3D-annotated sequences similar to their own. We have improved and extended the Genome3D data, enlarging the source data set from three model organisms to 10, and adding VIVACE, a resource new to Genome3D. We have analysed and updated Genome3D's SCOP/CATH mapping. Finally, we have improved the superposition tools, which now give users a more powerful interface for investigating similarities and differences between structural models.
Abstract The tumour microenvironment plays a crucial role in the growth and progression of cancer, and the presence of tumour-associated macrophages (TAMs) is associated with poor prognosis. Recent studies have demonstrated that TAMs display transcriptomic, phenotypic, functional and geographical diversity. Here we show that a sialylated tumour-associated glycoform of the mucin MUC1, MUC1-ST, through the engagement of Siglec-9 can specifically and independently induce the differentiation of monocytes into TAMs with a unique phenotype that to the best of our knowledge has not previously been described. These TAMs can recruit and prolong the lifespan of neutrophils, inhibit the function of T cells, degrade basement membrane allowing for invasion, are inefficient at phagocytosis, and can induce plasma clotting. This macrophage phenotype is enriched in the stroma at the edge of breast cancer nests and their presence is associated with poor prognosis in breast cancer patients.
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
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