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Abstract #2800

Combine radiomics models and multi-omics data stratified patients with AFPhigh - HCC Sensitivity to regorafenib.

Fan Tiantian1 and Zhou Yang2
1The Affiliated Cancer Hospital of Harbin Medical University, harbin, China, 2The Affiliated Cancer Hospital of Harbin Medical University, Harbin, China

Synopsis

Keywords: Cancer, Radiomics

Motivation: High expression of serum AFP (>400 ng/mL) in HCC patients predicts poor prognosis.

Goal(s): Identify AFP-high HCC patients who are responsive to regorafenib.

Approach: We developed a combined clinical-imaging-radiomics model to identify risk in AFP-high HCC patients post-surgery. Identify molecular differences between different risk groups through enrichment analysis and single-cell sequencing.Finally, validate the model using regorafenib treatment outcomes.

Results: The model stratified patients into high- and low-risk groups with significant OS differences (P < 0.001). Enrichment analysis showed PI3K-AKT pathway upregulation. Among 26 patients treated with regorafenib, the DCR was 61.5% in the low-risk group and 30.8% in the high-risk group.

Impact: The combined model based on clinical, imaging, and radiomics data can predict the postoperative survival status of patients. This model allows for the identification of a subgroup of patients who are at relatively low risk and responsive to regorafenib treatment.

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