About this Research Topic
While a strict definition of rare cancers is elusive, they are generally categorized based on their public health impact in specific regions and the feasibility of obtaining sufficient samples for meaningful analysis. In general, these uncommon cancers account for around 25% of cancer-related deaths. Their low incidence rates and limited data availability significantly hinder drug development. Consequently, patients with rare cancers often receive supportive care for symptom management rather than achieving real disease-modifying clinical benefit.
In the meantime, the rapid advancement of Next-Generation Sequencing (NGS) has revolutionized cancer research, particularly in leveraging omics data to unravel immune variations and understand the molecular foundations of immune processes. Among over 500 omics types, genomics, epigenomics, transcriptomics, proteomics, and metabolomics are commonly explored. Beyond omics, studies focusing on multiomic analysis could further promote the identification of pathogenic and prognostic markers for rare cancers, as well as repurposing drugs by unveiling novel therapeutic targets in particular for cancer precision medicine.
Multi-omic data generated on rare cancers are substantially limited, where a multi-omic study was defined as one that includes two or more omic analyses types. Particularly, given the limitation of sample size caused by disease rarity, the recent advancement in single-cell multiomics methods, such as CITE-seq and DOGMA-seq, as well as spatial omics methods, such as Visium, Xenium and CODEX, hold great promise to achieve breakthrough in the field. The overall objective of this research topic is to summarize the latest breakthroughs in immune profiling and the identification of therapeutic targets within rare cancers using a multiomics approach. Hopefully, with deepened understanding of the underlying mechanisms of rare cancers, as well as deciphering the immune landscape within their microenvironments, potential therapeutic approaches can be implied for these largely unmet medical needs.
The scope of rare cancer should fit in at least one definition in various regions, such as a prevalence of <50/100,000 or incidence of <6 per 100,000 people per year in the U.S., a crude incidence rate of <6 per 100,000 people per year in Europe or Japan, and incidence of <2.5/100, 000 in China. Examples of rare cancers are listed as below:
- Sarcomas
- Nervous System Tumors
- Head and Neck Tumors
- Mesothelioma
- Thymic Tumors
- Rare gynecologic and breast tumors
- Blastomas
We welcome submissions that explore a wide range of topics related to rare cancers, including but not limited to:
- Integrated Omics Analyses: Studies integrating genomics, transcriptomics, proteomics, etc., to uncover immune profile and therapeutic targets.
- Data Integration and Computational Tools: Developing new statistical methods or computational tools for multiomics data analysis and interpretation in rare cancers.
- Predictive Modeling and Biomarker Discovery: Developing models and biomarker signatures for early detection and personalized treatment.
- Functional Genomics and Drug Repurposing: Characterizing genetic and epigenetic alterations to identify druggable targets and repurpose therapeutics.
- Immunogenomics and Immunotherapy Response Prediction: Assessing tumor-immune interactions to predict immunotherapy response and resistance.
The topic editors confirm that they have no conflicts of interest to declare in the organization and editorship of this collection.
In the meantime, the rapid advancement of Next-Generation Sequencing (NGS) has revolutionized cancer research, particularly in leveraging omics data to unravel immune variations and understand the molecular foundations of immune processes. Among over 500 omics types, genomics, epigenomics, transcriptomics, proteomics, and metabolomics are commonly explored. Beyond omics, studies focusing on multiomic analysis could further promote the identification of pathogenic and prognostic markers for rare cancers, as well as repurposing drugs by unveiling novel therapeutic targets in particular for cancer precision medicine.
Multi-omic data generated on rare cancers are substantially limited, where a multi-omic study was defined as one that includes two or more omic analyses types. Particularly, given the limitation of sample size caused by disease rarity, the recent advancement in single-cell multiomics methods, such as CITE-seq and DOGMA-seq, as well as spatial omics methods, such as Visium, Xenium and CODEX, hold great promise to achieve breakthrough in the field. The overall objective of this research topic is to summarize the latest breakthroughs in immune profiling and the identification of therapeutic targets within rare cancers using a multiomics approach. Hopefully, with deepened understanding of the underlying mechanisms of rare cancers, as well as deciphering the immune landscape within their microenvironments, potential therapeutic approaches can be implied for these largely unmet medical needs.
The scope of rare cancer should fit in at least one definition in various regions, such as a prevalence of <50/100,000 or incidence of <6 per 100,000 people per year in the U.S., a crude incidence rate of <6 per 100,000 people per year in Europe or Japan, and incidence of <2.5/100, 000 in China. Examples of rare cancers are listed as below:
- Sarcomas
- Nervous System Tumors
- Head and Neck Tumors
- Mesothelioma
- Thymic Tumors
- Rare gynecologic and breast tumors
- Blastomas
We welcome submissions that explore a wide range of topics related to rare cancers, including but not limited to:
- Integrated Omics Analyses: Studies integrating genomics, transcriptomics, proteomics, etc., to uncover immune profile and therapeutic targets.
- Data Integration and Computational Tools: Developing new statistical methods or computational tools for multiomics data analysis and interpretation in rare cancers.
- Predictive Modeling and Biomarker Discovery: Developing models and biomarker signatures for early detection and personalized treatment.
- Functional Genomics and Drug Repurposing: Characterizing genetic and epigenetic alterations to identify druggable targets and repurpose therapeutics.
- Immunogenomics and Immunotherapy Response Prediction: Assessing tumor-immune interactions to predict immunotherapy response and resistance.
The topic editors confirm that they have no conflicts of interest to declare in the organization and editorship of this collection.
Keywords: NGS, immunity, Therapeutics, Immunogenomics, Immunotherapy
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.
