Application of Integrated Proteomic and Serum Metabolomic Analysis in Assessing the Efficacy and Prognosis of TACE Combined With Targeted Immunotherapy in Unresectable Hepatocellular Carcinoma

Primary outcomes

1. Differences in Macroproteomics and Serum Metabolomics Expression between Effective and Ineffective Treatment Groups.

   Time frame: Starting from the completion of treatment and evaluation for all patients, up to 6 months

   Using two-dimensional liquid chromatography to separate proteins and perform data independent acquisition (DIA) for tissue and macro proteome analysis. Qualitative and quantitative analysis of DIA data was performed using data analysis software Spectronaut, and statistical algorithms were used to obtain differentially expressed proteins in HCC tissue and macro proteome between the effective and ineffective treatment groups. At the same time, non targeted metabolomics analysis methods were used to perform metabolomics analysis on serum samples from two groups of patients.

2. Model for predicting the efficacy and prognosis of advanced HCC treatment

   Time frame: Within six months after the completion of treatment and evaluation for all patients.

   Perform pathway and biological function enrichment analysis of differentially expressed proteins through IPA, analyze signal pathways and interaction networks of different bacterial strains through Unipept software, and perform pathway and functional analysis of differential metabolites through MetaboAnalyst to further screen important biomarkers. By using machine learning methods and combining ROC curves to construct efficacy prediction and prognosis judgment models, the optimal biomarker combination is obtained, and a prediction model is established.