Peripheral Blood Biomarkers and Response to Atezolizumab Plus Bevacizumab in Hepatocellular Carcinoma

Overview

This single-center prospective observational cohort study aims to evaluate the predictive value of peripheral blood-based biomarkers for treatment response in patients with hepatocellular carcinoma (HCC) receiving first-line atezolizumab plus bevacizumab (T+A) therapy. Residual peripheral blood samples obtained during routine clinical testing will be analyzed without additional blood draws. The study hypothesizes that baseline and longitudinal peripheral blood biomarkers are associated with treatment response and can be used to identify patients more likely to benefit from T+A therapy. Treatment response will be evaluated based on the best overall response (BOR) during treatment. The primary efficacy assessment will be performed according to RECIST 1.1, while modified RECIST (mRECIST) will be used as a supportive assessment. Predictive models based on peripheral blood biomarkers will be developed using RECIST 1.1-defined treatment response as the primary analysis, with mRECIST used for supportive and sensitivity analyses.

This is a single-center prospective observational cohort study designed to evaluate the predictive value of peripheral blood-based biomarkers for treatment response in patients with hepatocellular carcinoma (HCC) receiving first-line atezolizumab plus bevacizumab (T+A) therapy. T+A therapy has become a standard first-line treatment for advanced HCC; however, the objective response rate remains limited, and reliable non-invasive biomarkers for predicting treatment response are lacking. Consequently, accurate patient stratification and individualized prediction of treatment benefit remain challenging in clinical practice. We hypothesize that peripheral blood-based biomarkers, including serum-derived indicators such as secreted proteins, metabolites, and extracellular vesicle-related components, as well as peripheral blood cell-related markers, are associated with treatment response to T+A therapy and may help identify patients more likely to benefit from treatment. These biomarkers will be analyzed using approaches including proteomic and metabolomic analyses, extracellular vesicle-related assays, enzyme-linked immunosorbent assays (ELISAs), and peripheral blood cell-related analyses. Eligible patients scheduled to receive first-line T+A therapy will be consecutively enrolled at Zhongshan Hospital, Fudan University. When available, residual peripheral blood samples obtained during routine clinical testing will be collected at baseline, at routine treatment visits approximately every 3 weeks, and at the time of first documented disease progression. All participants will provide written informed consent for the use of residual biospecimens and clinical data. Participants may withdraw from the study at any time without affecting their subsequent medical care. Biospecimens and clinical data will be assigned unique study identification numbers and managed in a de-identified manner. Personally identifiable information will be stored separately with restricted access. Biospecimens and study data will be stored, managed, and destroyed in accordance with applicable institutional policies and ethical requirements. The study is expected to involve minimal additional risk because it does not require additional blood draws or alter standard clinical care. Treatment response will be evaluated based on the best overall response (BOR) during T+A therapy. The primary efficacy assessment will be performed according to RECIST 1.1, while modified RECIST (mRECIST) will be used as a supportive assessment for HCC-specific response evaluation. Participants will be categorized as responders if their BOR is complete response (CR) or partial response (PR), and as non-responders if their BOR is stable disease (SD) or progressive disease (PD). The primary objective is to compare baseline peripheral blood biomarker levels between responders and non-responders, as defined by RECIST 1.1, and to identify biomarkers associated with treatment benefit. Secondary objectives include evaluating longitudinal biomarker changes from baseline throughout T+A therapy, including fold changes and potential time windows associated with treatment response. Treatment response according to mRECIST will be evaluated as a supportive analysis, and sensitivity analyses based on mRECIST-defined response will be performed to assess the consistency and robustness of biomarker associations and predictive model performance. Predictive models will be developed using least absolute shrinkage and selection operator (LASSO)-based feature selection, with treatment response defined according to RECIST 1.1 as the primary endpoint. Model discrimination will be evaluated using receiver operating characteristic (ROC) curve analysis, including the area under the ROC curve (AUC), sensitivity, and specificity. Predictive performance based on mRECIST-defined response will be explored as a supportive analysis.