Abstract Background Immunotherapies targeting immune checkpoints have gained increasing attention in cancer treatment, emphasizing the need for predictive biomarkers. Circular RNAs (circRNAs) have emerged as critical regulators of tumor immunity, particularly in the PD- 1/PD-L1 pathway, and have shown potential in predicting the efficacy of immunotherapies. However, the precise roles of circRNAs in cancer immunotherapy remain incompletely understood. While existing databases focus on either circRNA profiles or immunotherapy cohorts, there is currently no platform that enables the exploration of the intricate interplay between circRNAs and anti-tumor immunotherapy. Therefore, the development of a comprehensive resource that integrates circRNA profiles, immunotherapy response data, and clinical benefits is crucial for advancing our understanding of circRNA-mediated tumor-immune interactions and developing effective immunotherapy biomarkers. Methods To address these gaps, we constructed the Cancer CircRNA Immunome Atlas (TCCIA), the first database that combines circRNA profiles, immunotherapy response data, and clinical outcomes across multi-cancer types. The construction of TCCIA involved applying standardized preprocessing to the raw sequencing FASTQ files, characterizing circRNA profiles using CIRCexplorer2, analyzing tumor immunophenotypes through IOBR, and compiling immunotherapy response data from diverse cohorts treated with immune-checkpoint blockades (ICBs). Results TCCIA encompasses over 3,700 clinical samples obtained from 18 cohorts treated with ICBs, including PD-1/PD-L1 and CTLA-4 inhibitors, along with other treatment modalities. The database provides researchers and clinicians with a cloud-based platform that enables interactive exploration of circRNA data in the context of ICB. The platform offers a range of analytical tools, including visualization of circRNA abundance and correlation, association analysis between circRNAs and clinical variables, assessment of the tumor immune microenvironment, exploration of tumor molecular signatures, evaluation of treatment response or prognosis, and identification of altered circRNAs in immunotherapy-sensitive and resistant tumors. To illustrate the utility of TCCIA, we performed a re-analysis on a melanoma cohort with TCCIA, and found that an isoform of circTMTC3, TMTC3:+:chr12:88148287:88176319, played a significant role in predicting unfavorable survival outcomes and treatment nonresponse. Conclusions TCCIA represents a significant advancement over existing resources, providing a comprehensive platform to investigate the role of circRNAs in immune oncology. What is already known on this topic Prior knowledge indicated that circRNAs are involved in tumor immunity and have potential as predictive biomarkers for immunotherapy efficacy. However, there lacked a comprehensive database that integrated circRNA profiles and immunotherapy response data, necessitating this study. What this study adds This study introduces TCCIA, a database that combines circRNA profiles, immunotherapy response data, and clinical outcomes. It provides a diverse collection of clinical samples and an interactive platform, enabling in-depth exploration of circRNAs in the context of checkpoint-blockade immunotherapy. How this study might affect research, practice or policy The findings of this study offer valuable insights into the roles of circRNAs in tumor-immune interactions and provide a resource for researchers and clinicians in the field of immune-oncology. TCCIA has the potential to guide personalized immunotherapeutic strategies and contribute to future research, clinical practice, and policy decisions in checkpoint-blockade immunotherapy and biomarker development.
