Computer methods and programs in biomedicine · 2026
Metabolic splicing subtypes elucidate metastatic trajectories and clinical biomarkers in adrenocortical carcinoma.
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Zou Min, Lan Rifang, Huo Zhengchun, Li Shaokang, Lv Yingli, Yang Lei
Аннотация
BACKGROUND AND OBJECTIVE: Adrenocortical carcinoma (ACC) is a rare but highly aggressive malignancy, and alternative splicing (AS) serves as a key post-transcriptional regulatory mechanism involved in its malignant progression. A prominent feature of ACC is metabolic reprogramming, which is closely associated with poor prognosis. However, the mechanism by which AS mediates metabolic abnormalities to promote ACC invasion and metastasis remains unclear.
METHODS: We identified three splicing subtypes based on metabolism-related splicing events, which were derived by correlating metabolic flux scores (inferred via the METAFlux algorithm) with AS PSI values using multi-omics data. A 9-gene AS-based metastatic prognostic signature was constructed using integrated computational models, and subtype-specific crosstalk between AS and metabolism was further explored to clarify the underlying mechanism.
RESULTS: Three splicing subtypes were identified, capturing the dynamic metabolic shift from catabolism to anabolism during ACC progression and a continuous trajectory from an immuno-metabolically active state to a proliferative and metastatic state. The 9-gene signature exhibits robust independent predictive value for ACC metastasis and prognosis. Mechanistically, activated acylglyceride metabolism in the metastasis-like ProgDiv subtype may up-regulate IGF2BP2 to modulate RPS11 exon skipping, suggesting a potential role in promoting ACC metastasis.
CONCLUSIONS: This study establishes an AS-centered framework for understanding metabolic reprogramming in ACC. The 9-gene signature is a promising tool for individualized prognostic stratification of ACC patients, while the delineated AS-metabolism crosstalk furnishes valuable insights for developing targeted therapies against aggressive ACC.
METHODS: We identified three splicing subtypes based on metabolism-related splicing events, which were derived by correlating metabolic flux scores (inferred via the METAFlux algorithm) with AS PSI values using multi-omics data. A 9-gene AS-based metastatic prognostic signature was constructed using integrated computational models, and subtype-specific crosstalk between AS and metabolism was further explored to clarify the underlying mechanism.
RESULTS: Three splicing subtypes were identified, capturing the dynamic metabolic shift from catabolism to anabolism during ACC progression and a continuous trajectory from an immuno-metabolically active state to a proliferative and metastatic state. The 9-gene signature exhibits robust independent predictive value for ACC metastasis and prognosis. Mechanistically, activated acylglyceride metabolism in the metastasis-like ProgDiv subtype may up-regulate IGF2BP2 to modulate RPS11 exon skipping, suggesting a potential role in promoting ACC metastasis.
CONCLUSIONS: This study establishes an AS-centered framework for understanding metabolic reprogramming in ACC. The 9-gene signature is a promising tool for individualized prognostic stratification of ACC patients, while the delineated AS-metabolism crosstalk furnishes valuable insights for developing targeted therapies against aggressive ACC.