Positioning circRNAs as multimodal regulatory hubs, this review provides a theoretical framework for developing circRNA-based immunotherapies to overcome resistance in lymphoma.
Abstract
Immune checkpoint inhibitors (ICIs) have revolutionized lymphoma treatment, yet resistance driven by complex regulatory networks remains a major hurdle. Circular RNAs (circRNAs) have emerged as central signaling hubs that integrate metabolic, inflammatory, and oncogenic cues to fine-tune immune checkpoints such as PD-L1 and CD47 in lymphoma. Here, we systematically dissect the molecular mechanisms by which circRNAs govern immune checkpoints in lymphoma, including nuclear transcriptional control, interactions with RNA-binding proteins (RBPs), competitive endogenous RNA (ceRNA) networks, and micropeptide translation. We differentiate between cell-extrinsic, exosome-mediated reprogramming of the tumor microenvironment and cell-intrinsic circRNA circuits within lymphoma cells spatially. Subtype-specific investigations demonstrate the importance of Epstein-Barr virus (EBV)-encoded circRNAs in immune evasion and the synergistic interactions between 9p24.1 amplification and circRNAs in classical Hodgkin lymphoma (cHL). While therapeutic approaches including antisense oligonucleotides, CRISPR-Cas13, and nanodelivery technologies demonstrate preclinical synergy with ICIs, circulating circRNAs show potential as dynamic indicators for predicting ICI responses. We also critically examine ongoing discussions about the flaws of current model systems, the technological constraints of current validation techniques, and the physiological significance of the ceRNA hypothesis. Positioning circRNAs as multimodal regulatory hubs, this review provides a theoretical framework for developing circRNA-based immunotherapies to overcome resistance in lymphoma.
Current discoveries defining the lncRNA-TIME nexus are synthesized and advances in high-throughput sequencing, single-cell transcriptomics, and computational modeling that enable the mapping of these complex networks are highlighted.
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PURPOSE
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