Pan-Cancer Profiling of Intron Retention and Its Clinical Significance in Diagnosis and Prognosis

Simple Summary Alternative splicing generates transcripts that can promote tumorigenesis, but intron retention (IR), a form of alternative splicing, remains understudied. We investigated the role of IR in tumorigenesis and its potential clinical applications at the pan-cancer level. We identified IR events from The Cancer Genome Atlas (TCGA) that differ between tumor and normal samples, as well as IR events associated with patient survival. These IR events may modulate the expression of host genes, including those that play a role in cancer biology. For example, we experimentally validated a novel IR event within the STN1 5 ' UTR. The excellent performance of IR-based diagnostic and prognostic models and their biological importance in cancer suggest that IR is a potential biomarker and drug target.Abstract Alternative splicing can produce transcripts that affect cancer development and thus shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been studied less in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention inside the 5 ' UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification in certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets.