Integrative analysis of bulk, single-cell, and spatial transcriptomes reveals a clinically relevant transcriptional program from hepatocellular carcinoma to pan-cancer

Abstract

Abstract Background Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, underscoring the urgent need for robust molecular signatures that support multiple clinical tasks and generalize across diverse transcriptomic platforms. Results We performed an integrative analysis of 1,300 HCC transcriptomic profiles spanning microarray (n = 869), bulk RNA sequencing (n = 370), spatial transcriptomics (n = 10), and single-cell RNA sequencing (n = 51). Using a multi-task machine learning framework, we distilled a foundational 284-gene program into a compact 25-gene transcriptional signature, including the under-characterized gene IPO9. This signature captured the core proliferative state of HCC while maintaining high diagnostic accuracy (AUC = 0.987–0.991) and served as an independent prognostic factor for both overall and progression-free survival, with activity levels that progressively scale with advancing tumor grade. Spatial and single-cell analyses localized the signature almost exclusively to malignant hepatocytes within the tumor core, confirming its cell-intrinsic nature. Extending beyond HCC, the signature demonstrated conserved oncogenic pathway alignment across 31 additional cancer types and prognostic relevance in nine of them, identifying it as a pan-cancer malignant proliferative-proteostatic marker. Conclusions This study defines a mechanistically interpretable 25-gene malignant axis that generalizes from HCC to multiple cancer types . Our findings suggest that this signature could serve as a reliable framework for clinical risk assessment and personalized management in HCC.