Hepatocellular Carcinoma Immunotherapy Biomarker Study

Figshare hosts a clinical proteomics dataset analyzing plasma protein biomarkers for patients with advanced hepatocellular carcinoma (HCC) receiving combination therapy. Jianing Wang authored the study, which includes data from 201 enrolled patients and proteomic analysis of 92 inflammatory proteins from 72 baseline plasma samples. The dataset was last updated in April 2026.

Use Cases

• Identify differentially expressed proteins, such as IL-17A, associated with poor overall survival in hyperbilirubinemia patients using Cox regression.
• Compare clinical outcomes like objective response rate (ORR) and disease control rate (DCR) between patient groups with normal and elevated bilirubin.
• Assess the interaction effect between hyperbilirubinemia and elevated IL-17A levels on patient survival via formal interaction tests.
• Analyze the proteomic profile of 92 inflammatory proteins to discover potential therapeutic targets for HCC with hyperbilirubinemia.

Strengths

• Clinical data from 201 enrolled patients with advanced hepatocellular carcinoma.
• Proteomic analysis quantified 92 inflammatory proteins from 72 baseline plasma samples.
• Identified 36 differentially expressed proteins between patient groups.

Limitations

• Small proteomic subset of 72 patients limits statistical power for biomarker discovery.
• Dataset scope is limited to a single study's patient cohort, reducing generalizability.
• Primary data is embedded in a DOCX file, requiring extraction for computational analysis.

Provenance

Source

Jianing Wang via figshare.

Collection Method

Clinical study with propensity score matching and Olink proteomics analysis of patient plasma.

Time Range

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Freshness

Last updated in April 2026.

Geography

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