Rare cancers, though not strictly defined, are generally characterized by their significant public health impact in specific regions and the challenges associated with obtaining sufficient samples for comprehensive analysis. These uncommon cancers account for approximately 25% of cancer-related deaths, yet their low incidence rates and limited data availability pose significant obstacles to drug development. As a result, patients with rare cancers often receive only supportive care aimed at symptom management, rather than treatments that offer substantial disease-modifying benefits. The advent of Next-Generation Sequencing (NGS) has transformed cancer research, particularly through the use of omics data to explore immune variations and understand the molecular underpinnings of immune processes. Despite the potential of multi-omics approaches, which include genomics, epigenomics, transcriptomics, proteomics, and metabolomics, the application of these methods to rare cancers remains limited. Recent advancements in single-cell multiomics and spatial omics methods, such as CITE-seq, DOGMA-seq, Visium, Xenium, and CODEX, offer promising avenues for breakthroughs in this field, yet there remains a critical need for further investigation.
This research topic aims to summarize the latest breakthroughs in immune profiling and the identification of therapeutic targets within rare cancers using a multiomics approach. The primary objective is to deepen the understanding of the underlying mechanisms of rare cancers and to decipher the immune landscape within their microenvironments. By achieving these goals, the research seeks to propose potential therapeutic approaches for these largely unmet medical needs, ultimately improving outcomes for patients with rare cancers.
To gather further insights in the realm of rare cancers, defined by specific regional prevalence and incidence criteria, we welcome articles addressing, but not limited to, the following themes:
- Integrated Omics Analyses: Studies integrating genomics, transcriptomics, proteomics, etc., to uncover immune profiles 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.
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.
