Chronic diseases, such as cardiovascular ailments, diabetes, autoimmune disorders, and certain cancers, present a significant challenge to global public health. These conditions often involve persistent inflammatory responses, with immune cells playing a pivotal role in their pathogenesis. Immune cells orchestrate inflammatory responses and impact disease progression through a multifaceted communication network. This network, which includes cytokine secretion, chemokine action, and direct cell-to-cell interactions, influences inflammation intensity and duration. However, many questions remain unresolved about how immune cells engage via these channels and how they interact with stromal cells to alter tissue microenvironments. Emerging multi-omics technologies, such as single-cell sequencing, spatial transcriptomics, and metabolomics, are beginning to unravel these complex interactions, offering a more comprehensive understanding. Despite these advancements, a deeper exploration of immune cell communication mechanisms in chronic diseases is critical for developing novel therapeutic strategies.
This Research Topic aims to investigate immune cell communication in chronic diseases, focusing on the inflammatory effects induced by these cellular interactions. By integrating multi-omics technologies, the goal is to reveal complex immune cell interaction networks and their dynamic transformations in chronic inflammation, thus laying the groundwork for precision treatment strategies.
To gather further insights into immune cell communication in chronic conditions, we welcome articles addressing themes such as, but not limited to, the following:
• Utilization of single-cell multi-omics technologies for analyzing immune cell heterogeneity and interactions
• Spatial transcriptomics for uncovering spatiotemporal interaction traits between immune and stromal cells
• Investigations into the pathogenic mechanisms of ligand-receptor interaction networks in the immune system in conditions like tumors, autoimmune diseases, and fibrosis
• Development of machine learning models predicting disease prognosis from immune characteristics and interactions
• Novel therapeutic strategies targeting immune cell interactions, like cytokine inhibitors
• Personalized therapeutic approaches targeting the immune system to enhance chronic disease treatment efficacy and patient quality of life
We encourage authors to contribute to this Research Topic through original research articles, comprehensive reviews, and informative case reports that explore these and related themes.
Manuscripts consisting solely of bioinformatics or computational analysis of public databases without robust and relevant validation, for instance in an independent patient population or by PCR, are considered out of scope of this section. Studies based on indexes that are based simply on blood cell count or routine clinical tests are out of scope unless they investigate immunological mechanisms in depth.
Chronic diseases, such as cardiovascular ailments, diabetes, autoimmune disorders, and certain cancers, present a significant challenge to global public health. These conditions often involve persistent inflammatory responses, with immune cells playing a pivotal role in their pathogenesis. Immune cells orchestrate inflammatory responses and impact disease progression through a multifaceted communication network. This network, which includes cytokine secretion, chemokine action, and direct cell-to-cell interactions, influences inflammation intensity and duration. However, many questions remain unresolved about how immune cells engage via these channels and how they interact with stromal cells to alter tissue microenvironments. Emerging multi-omics technologies, such as single-cell sequencing, spatial transcriptomics, and metabolomics, are beginning to unravel these complex interactions, offering a more comprehensive understanding. Despite these advancements, a deeper exploration of immune cell communication mechanisms in chronic diseases is critical for developing novel therapeutic strategies.
This Research Topic aims to investigate immune cell communication in chronic diseases, focusing on the inflammatory effects induced by these cellular interactions. By integrating multi-omics technologies, the goal is to reveal complex immune cell interaction networks and their dynamic transformations in chronic inflammation, thus laying the groundwork for precision treatment strategies.
To gather further insights into immune cell communication in chronic conditions, we welcome articles addressing themes such as, but not limited to, the following:
• Utilization of single-cell multi-omics technologies for analyzing immune cell heterogeneity and interactions
• Spatial transcriptomics for uncovering spatiotemporal interaction traits between immune and stromal cells
• Investigations into the pathogenic mechanisms of ligand-receptor interaction networks in the immune system in conditions like tumors, autoimmune diseases, and fibrosis
• Development of machine learning models predicting disease prognosis from immune characteristics and interactions
• Novel therapeutic strategies targeting immune cell interactions, like cytokine inhibitors
• Personalized therapeutic approaches targeting the immune system to enhance chronic disease treatment efficacy and patient quality of life
We encourage authors to contribute to this Research Topic through original research articles, comprehensive reviews, and informative case reports that explore these and related themes.
Manuscripts consisting solely of bioinformatics or computational analysis of public databases without robust and relevant validation, for instance in an independent patient population or by PCR, are considered out of scope of this section. Studies based on indexes that are based simply on blood cell count or routine clinical tests are out of scope unless they investigate immunological mechanisms in depth.