Gastrointestinal tumors are heterogeneous inherently. The heterogeneity of the tumor immune microenvironment is closely related to disease progression and responsiveness to treatment. In addition, malignant cells become increasingly diverse and heterogeneous during tumorigenesis and metastasis. These years, the development and application of large-scale databases provided a solid foundation for revealing the molecular mechanism of tumorigenesis and cancer development, exploring new diagnostic and therapeutic methods. Thus, research on the diagnosis and treatment of gastrointestinal tumors has entered the era of big data. Bioinformatics, multi-omics big data, tumor immunology and artificial intelligence are fully applied to realize accurate clinical risk assessment for patients with gastrointestinal tumors through the integration of clinical and molecular pathology information in this context of big-data science. Predictors of clinical outcomes for patients with gastrointestinal tumors are analyzed using large-sample real-world data, and individualized treatments are established based on large-sample omics data to find suitable biomarkers for precise diagnosis and treatment.
With the help of big data methods, such as multi-regional, omics sequencing and single-cell sequencing, an effective clinical model for predicting tumor immune heterogeneity is being established by understanding the complexity of tumor immune heterogeneity and its role in immunotherapy. It will provide more effective and personalized treatment to improve clinical efficacy.
This Research Topic provides a forum for researchers to publish scientific research on the risk assessment and intervention of gastrointestinal tumors, so as to contribute to clinical practices and benefit patients with gastrointestinal tumors. This Research Topic welcomes but is not limited to the followings:
? Clinical prediction models for accurately assessing the risk of gastrointestinal tumors based on bioinformatics analysis that can be widely used in clinical practice.
? Precise biomarkers and detection methods for gastrointestinal tumors based on tumor immune microenvironment (more precise exploration and optimization of biomarkers by combining proteomics, metabolomics, epigenetics and single-cell level studies etc.)
? Novel strategies and potential mechanisms of precision immunotherapy for gastrointestinal tumors (analysis of tumor immune microenvironment, prediction of patients' response to immunotherapy, exploration of new therapeutic targets, etc.)
NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
Gastrointestinal tumors are heterogeneous inherently. The heterogeneity of the tumor immune microenvironment is closely related to disease progression and responsiveness to treatment. In addition, malignant cells become increasingly diverse and heterogeneous during tumorigenesis and metastasis. These years, the development and application of large-scale databases provided a solid foundation for revealing the molecular mechanism of tumorigenesis and cancer development, exploring new diagnostic and therapeutic methods. Thus, research on the diagnosis and treatment of gastrointestinal tumors has entered the era of big data. Bioinformatics, multi-omics big data, tumor immunology and artificial intelligence are fully applied to realize accurate clinical risk assessment for patients with gastrointestinal tumors through the integration of clinical and molecular pathology information in this context of big-data science. Predictors of clinical outcomes for patients with gastrointestinal tumors are analyzed using large-sample real-world data, and individualized treatments are established based on large-sample omics data to find suitable biomarkers for precise diagnosis and treatment.
With the help of big data methods, such as multi-regional, omics sequencing and single-cell sequencing, an effective clinical model for predicting tumor immune heterogeneity is being established by understanding the complexity of tumor immune heterogeneity and its role in immunotherapy. It will provide more effective and personalized treatment to improve clinical efficacy.
This Research Topic provides a forum for researchers to publish scientific research on the risk assessment and intervention of gastrointestinal tumors, so as to contribute to clinical practices and benefit patients with gastrointestinal tumors. This Research Topic welcomes but is not limited to the followings:
? Clinical prediction models for accurately assessing the risk of gastrointestinal tumors based on bioinformatics analysis that can be widely used in clinical practice.
? Precise biomarkers and detection methods for gastrointestinal tumors based on tumor immune microenvironment (more precise exploration and optimization of biomarkers by combining proteomics, metabolomics, epigenetics and single-cell level studies etc.)
? Novel strategies and potential mechanisms of precision immunotherapy for gastrointestinal tumors (analysis of tumor immune microenvironment, prediction of patients' response to immunotherapy, exploration of new therapeutic targets, etc.)
NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
