The cell-cell communication (CCC), as a fundamental feature of tumor immune microenvironment (TIME), is crucial for deciphering the mechanisms of tumor initiation, metastasis and responses to various cancer therapies. The emergency of single-cell RNA sequencing (scRNA-seq) technology has sparked the inference of CCC at unprecedented high resolution and genomic coverage. Quite a few tools to estimate CCC from scRNA-seq data, mainly rely on the expression levels of pre-selected ligand-receptor pairs and explicitly defined functions, have been developed. However, these tools bear a major issue of significant false positive rate, given that CCC usually takes place within limited spatial distances that are not measured in scRNA-seq datasets. As the method of the year in 2020, the spatial transcriptomics (ST) technology, which provides the spatial locations of cells, offers a great opportunity to overcome this issue and further improve the accuracy of CCC inference.
This Research Topic aims to sharpen our tools to estimate, visualize and share CCC profiles, with a particular focus on immune microenvironment of tumor and other contexts. Currently only a few tools are available to infer CCC from ST data or in conjunction with scRNA-seq data, and most of them examine CCC locally and on cell pairs independently. As a result, there is still huge space for improvement in sensitivity, specificity and accuracy of CCC inference. With the growing availability of ST data, we seek new algorithms for applying ST data into CCC inference, new methods for evaluating and benchmarking currently available tools, and new tools to visualize and share CCC profiles. Through this Research Topic, we aspire to broaden our understanding of the roles of CCC and pave the road for innovative cancer therapeutics.
This Research Topic welcomes the articles of original research, reviews, and perspectives that provide deep insights into cell-cell communication in the context of tumour immune microenvironment and beyond. The sub-topics include, but not limited to, the flowing areas:
• New algorithms for estimating cell-cell communications that considering ST data solely or combined with the data of scRNA-seq or other modalities
• Benchmarking or best practice studies of currently available CCC inference tools
• Data portal and other platforms of CCC collection, analysis, visualization and sharing
• Role of CCC in immune oncology, like immune response, drug resistance, cancer metastasis, etc.
• Mechanism studies of particular ligand/receptor genes
Keywords:
Cell-cell communication, Spatial transcriptomics, Software development, Data portal, Immune response, Drug resistance, Benchmarking, Visualization, Sharing
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The cell-cell communication (CCC), as a fundamental feature of tumor immune microenvironment (TIME), is crucial for deciphering the mechanisms of tumor initiation, metastasis and responses to various cancer therapies. The emergency of single-cell RNA sequencing (scRNA-seq) technology has sparked the inference of CCC at unprecedented high resolution and genomic coverage. Quite a few tools to estimate CCC from scRNA-seq data, mainly rely on the expression levels of pre-selected ligand-receptor pairs and explicitly defined functions, have been developed. However, these tools bear a major issue of significant false positive rate, given that CCC usually takes place within limited spatial distances that are not measured in scRNA-seq datasets. As the method of the year in 2020, the spatial transcriptomics (ST) technology, which provides the spatial locations of cells, offers a great opportunity to overcome this issue and further improve the accuracy of CCC inference.
This Research Topic aims to sharpen our tools to estimate, visualize and share CCC profiles, with a particular focus on immune microenvironment of tumor and other contexts. Currently only a few tools are available to infer CCC from ST data or in conjunction with scRNA-seq data, and most of them examine CCC locally and on cell pairs independently. As a result, there is still huge space for improvement in sensitivity, specificity and accuracy of CCC inference. With the growing availability of ST data, we seek new algorithms for applying ST data into CCC inference, new methods for evaluating and benchmarking currently available tools, and new tools to visualize and share CCC profiles. Through this Research Topic, we aspire to broaden our understanding of the roles of CCC and pave the road for innovative cancer therapeutics.
This Research Topic welcomes the articles of original research, reviews, and perspectives that provide deep insights into cell-cell communication in the context of tumour immune microenvironment and beyond. The sub-topics include, but not limited to, the flowing areas:
• New algorithms for estimating cell-cell communications that considering ST data solely or combined with the data of scRNA-seq or other modalities
• Benchmarking or best practice studies of currently available CCC inference tools
• Data portal and other platforms of CCC collection, analysis, visualization and sharing
• Role of CCC in immune oncology, like immune response, drug resistance, cancer metastasis, etc.
• Mechanism studies of particular ligand/receptor genes
Keywords:
Cell-cell communication, Spatial transcriptomics, Software development, Data portal, Immune response, Drug resistance, Benchmarking, Visualization, Sharing
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.