Multiple programmed cell death plays important role in tumor initiation and progression, including apoptosis, necroptosis, pyroptosis, ferroptosis, etc. New forms of programmed cell death are being discovered. It is worth mentioning that cuprotosis, a newly defined programmed cell death, was also involved in the progression of cancer. These forms of programmed cell death have different characteristics and complex driving mechanisms. For example, pyroptosis is defined as a GSDMD-dependent cell death with the release of inflammatory cytokines. These cytokines in turn will affect the dynamic balance between immune cells and tumor cells thus inducing tumor microenvironment reprogramming. Tumor microenvironment heterogeneity is the main reason for the low treatment responsiveness of cancer patients. The development of high-throughput technologies and increasing database resources could help us to obtain cancer-related big data of multi-omics. The application and integration of these data provide a comprehensive perspective on cancer. The comprehensively characterize programmed cell death-mediated tumor microenvironment heterogeneity would provide new insights into the identification of underlying cancer subtypes, the development of individualized cancer treatment, and the exploration of the immune microenvironment-specific anticancer drugs, thus supporting the clinic practice of precision medicine.
This research topic aims to provide new insights into the application of multi-omics data in the investigation of programmed cell death-mediated tumor microenvironment heterogeneity. Original research articles, methods, reviews, and mini reviews are welcome. Specific areas of interest for the Topic include, but are not limited to, the following:
• Identification of programmed cell death-related multi-biomarker for cancer diagnosis and prognosis
• The interactions among different types of programmed cell death in cancer
• The application and integration of multi-omics data in cancer diagnosis and prognosis
• Studies on the involvement of noncoding RNAs in the tumor microenvironment heterogeneity
• Machine learning-based methods for multi-omics data analysis
• The role of programmed cell death in mediating tumor microenvironment heterogeneity
• Single cell analysis in the investigation of tumor microenvironment heterogeneity
Please 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.
Multiple programmed cell death plays important role in tumor initiation and progression, including apoptosis, necroptosis, pyroptosis, ferroptosis, etc. New forms of programmed cell death are being discovered. It is worth mentioning that cuprotosis, a newly defined programmed cell death, was also involved in the progression of cancer. These forms of programmed cell death have different characteristics and complex driving mechanisms. For example, pyroptosis is defined as a GSDMD-dependent cell death with the release of inflammatory cytokines. These cytokines in turn will affect the dynamic balance between immune cells and tumor cells thus inducing tumor microenvironment reprogramming. Tumor microenvironment heterogeneity is the main reason for the low treatment responsiveness of cancer patients. The development of high-throughput technologies and increasing database resources could help us to obtain cancer-related big data of multi-omics. The application and integration of these data provide a comprehensive perspective on cancer. The comprehensively characterize programmed cell death-mediated tumor microenvironment heterogeneity would provide new insights into the identification of underlying cancer subtypes, the development of individualized cancer treatment, and the exploration of the immune microenvironment-specific anticancer drugs, thus supporting the clinic practice of precision medicine.
This research topic aims to provide new insights into the application of multi-omics data in the investigation of programmed cell death-mediated tumor microenvironment heterogeneity. Original research articles, methods, reviews, and mini reviews are welcome. Specific areas of interest for the Topic include, but are not limited to, the following:
• Identification of programmed cell death-related multi-biomarker for cancer diagnosis and prognosis
• The interactions among different types of programmed cell death in cancer
• The application and integration of multi-omics data in cancer diagnosis and prognosis
• Studies on the involvement of noncoding RNAs in the tumor microenvironment heterogeneity
• Machine learning-based methods for multi-omics data analysis
• The role of programmed cell death in mediating tumor microenvironment heterogeneity
• Single cell analysis in the investigation of tumor microenvironment heterogeneity
Please 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.
