Liver cancer is ranked as the sixth most commonly diagnosed malignant primary tumor and the fourth main reason for cancer-related death in the world. Countless metastatic cascade steps are concealed in the microenvironment composed of the pivotal facets of the liver immune system.
The immune microenvironment has a more crucial role than we thought it would. Current treatments may not only have difficulty achieving the desired therapeutic effect but also have obstacles with a higher recurrence rate. New thinking in hepatic carcinoma’s immune microenvironment is an urgent need.
Digital intelligence has not only deepened the understanding of liver cancer but has also perpetually amended the treatment and diagnosis solutions. Artificial intelligence (AI) has deeply affected the treatment of liver tumors, not only in diagnosis and treatment but also in rehabilitation. It brings incipient vitality to liver surgery. More importantly, it takes more preponderant rejuvenating opportunities for patients and a better individualized treatment experience. Utilizing integrated multi-omics approaches, AI could help to improve the detection and characterization of liver cancer with explosively complex datasets containing genomic and molecular data from tissues to single cells. This integrated algorithm is expected to inform disease diagnosis and staging as well as predict cancer relapse and treatment response. Finding more immune-targeting strategies that may help more patients shortly, such as adoptive T-cell transfer, vaccination, virotherapy, and more reliable biomarkers, could guide clinical decision-making about liver cancer.
This research topic aims to report on the latest progress in the immune microenvironment of liver cancer.
1. Utilizing artificial intelligence (including machine learning, deep learning, neural networks, etc.) or combining the "multi-omics" method to identify special molecules or cells that affect liver cancer and the immune microenvironment.
2. Exploring the interactional mechanism or specific manifestations of tumor heterogeneity between immune cells and the immune microenvironment in liver cancer by "stereo-seq" or "single cell" technology.
3. Novel molecules, cells, or pathways involved in the treatment of liver cancer by regulating the immune microenvironment.
Please NOTE: To uphold the focus of this Research Topic, manuscripts that solely consist of bioinformatics or computational analyses without being validated through independent cohorts or in vitro/in vivo investigations, are not within the scope of this Research Topic and will not be accepted.
Liver cancer is ranked as the sixth most commonly diagnosed malignant primary tumor and the fourth main reason for cancer-related death in the world. Countless metastatic cascade steps are concealed in the microenvironment composed of the pivotal facets of the liver immune system.
The immune microenvironment has a more crucial role than we thought it would. Current treatments may not only have difficulty achieving the desired therapeutic effect but also have obstacles with a higher recurrence rate. New thinking in hepatic carcinoma’s immune microenvironment is an urgent need.
Digital intelligence has not only deepened the understanding of liver cancer but has also perpetually amended the treatment and diagnosis solutions. Artificial intelligence (AI) has deeply affected the treatment of liver tumors, not only in diagnosis and treatment but also in rehabilitation. It brings incipient vitality to liver surgery. More importantly, it takes more preponderant rejuvenating opportunities for patients and a better individualized treatment experience. Utilizing integrated multi-omics approaches, AI could help to improve the detection and characterization of liver cancer with explosively complex datasets containing genomic and molecular data from tissues to single cells. This integrated algorithm is expected to inform disease diagnosis and staging as well as predict cancer relapse and treatment response. Finding more immune-targeting strategies that may help more patients shortly, such as adoptive T-cell transfer, vaccination, virotherapy, and more reliable biomarkers, could guide clinical decision-making about liver cancer.
This research topic aims to report on the latest progress in the immune microenvironment of liver cancer.
1. Utilizing artificial intelligence (including machine learning, deep learning, neural networks, etc.) or combining the "multi-omics" method to identify special molecules or cells that affect liver cancer and the immune microenvironment.
2. Exploring the interactional mechanism or specific manifestations of tumor heterogeneity between immune cells and the immune microenvironment in liver cancer by "stereo-seq" or "single cell" technology.
3. Novel molecules, cells, or pathways involved in the treatment of liver cancer by regulating the immune microenvironment.
Please NOTE: To uphold the focus of this Research Topic, manuscripts that solely consist of bioinformatics or computational analyses without being validated through independent cohorts or in vitro/in vivo investigations, are not within the scope of this Research Topic and will not be accepted.