Different from traditional treatment modalities, immunotherapy kills cells by activating the body’s immune system and has been placed with great expectations and potential in the treatment of cancer. Nevertheless, in the decades of clinical application of immunotherapy, only a part of patients obtained different degrees of benefit. Identifying the sensitivity to immunotherapy is conducive to the personalized management of patients in clinical practice, which is an urgent problem to be solved. Omics data including genomics, proteomics, transcriptomics, and metabolomics have proliferated over the past decades as sequencing technology has innovated and costs have fallen. The development of multi-omics has made the study of medicine enter the era of big data. Compared with the single omics signatures, the integrated analysis of multi-omics facilitates a more comprehensive and in-depth dissection of the development and dynamic changes of tumor immunity by investigators. The role of multidimensional biomarkers in improving the benefit of immunotherapy in patients has been gradually highlighted. Therefore, with the rapid increase in the volume of omics data and the diversified development of analysis methods, exploring the role of multi-omics variants in tumor immunity and immunotherapy is of tremendous help in improving the clinical benefits of immunotherapy in patients.
To improve the clinical benefit of immunotherapy, exploring immune-related predictive biomarkers from a multidimensional point of view is always the hotspot of cancer research. In this Research Topic, we look forward to publishing high-quality Original Research papers and Reviews on the combination of multi-omics analysis and immunotherapy. We welcome submissions on the following subtopics:
1. Exploring the influence of tumor immune microenvironment on patient prognosis through multi-omics data analysis
2. Development and validation of tumor prognosis-related immune molecular markers
3. Multi-omics analysis identifies immunotherapy vulnerabilities in cancers.
4. Improving the benefits of immunotherapy in cancer patients through multi-omics analysis
5. Investigating the underlying mechanisms of tumor immune resistance at the pan-cancer level through multi-omics data
6. Integrating multi-omics data to identify tumor immune-related subtypes
NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation are considered out of the scope of this section.
Different from traditional treatment modalities, immunotherapy kills cells by activating the body’s immune system and has been placed with great expectations and potential in the treatment of cancer. Nevertheless, in the decades of clinical application of immunotherapy, only a part of patients obtained different degrees of benefit. Identifying the sensitivity to immunotherapy is conducive to the personalized management of patients in clinical practice, which is an urgent problem to be solved. Omics data including genomics, proteomics, transcriptomics, and metabolomics have proliferated over the past decades as sequencing technology has innovated and costs have fallen. The development of multi-omics has made the study of medicine enter the era of big data. Compared with the single omics signatures, the integrated analysis of multi-omics facilitates a more comprehensive and in-depth dissection of the development and dynamic changes of tumor immunity by investigators. The role of multidimensional biomarkers in improving the benefit of immunotherapy in patients has been gradually highlighted. Therefore, with the rapid increase in the volume of omics data and the diversified development of analysis methods, exploring the role of multi-omics variants in tumor immunity and immunotherapy is of tremendous help in improving the clinical benefits of immunotherapy in patients.
To improve the clinical benefit of immunotherapy, exploring immune-related predictive biomarkers from a multidimensional point of view is always the hotspot of cancer research. In this Research Topic, we look forward to publishing high-quality Original Research papers and Reviews on the combination of multi-omics analysis and immunotherapy. We welcome submissions on the following subtopics:
1. Exploring the influence of tumor immune microenvironment on patient prognosis through multi-omics data analysis
2. Development and validation of tumor prognosis-related immune molecular markers
3. Multi-omics analysis identifies immunotherapy vulnerabilities in cancers.
4. Improving the benefits of immunotherapy in cancer patients through multi-omics analysis
5. Investigating the underlying mechanisms of tumor immune resistance at the pan-cancer level through multi-omics data
6. Integrating multi-omics data to identify tumor immune-related subtypes
NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation are considered out of the scope of this section.
