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Plasma proteomic signature for predicting survival in advanced HCC

ABSTRACT: Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality globally, with over 70% of patients diagnosed at intermediate or advanced stages (BCLC B/C) where curative treatments are no longer feasible. Conventional prognostic tools fail to capture this complexity, highlighting the urgent need for precise predictive models integrating molecular and clinical data. Methods: We conducted a retrospective cohort study of 242 patients with advanced HCC (BCLC B-D) treated with first-line systemic therapy (110 deaths and 152 survivors) at admitted to the Beijing Ditan Hospital of Capital Medical University between October 2021 and December 2023. Plasma proteomic analysis was obtained using DB4000 Deep Blood DIA Proteome combined with Data Independent Acquisition (DIA) and Astral Mass Spectrometry platform. Principal component analysis and differential protein abundance analysis are used to evaluate proteomic changes between two groups of patients. ELISA quantitative verification of protein biomarker phenological selection, single-cell transcriptome sequencing analysis of the expression of target protein in HCC tissue and its relationship with prognosis.

ORGANISM(S): Homo Sapiens

SUBMITTER: Yixin Hou

PROVIDER: PXD071115 | iProX | Sun Nov 23 00:00:00 GMT 2025

REPOSITORIES: iProX

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Project description:Introduction Immune checkpoint blockade (ICB) is a systemic therapeutic option for advanced hepatocellular carcinoma (HCC). However, low patient response rates necessitate the development of robust predictive biomarkers that identify individuals who will benefit from ICB. A 4-gene inflammatory signature, comprising CD8, PD-L1, LAG-3, and STAT1, was recently shown to be associated with a better overall response to ICB in various cancer types. Here, we examined whether tissue protein expression of CD8, PD-L1, LAG-3, and STAT1 predicts response to ICB in HCC. Methods HCC samples from 191 Asian patients, comprising resection specimens from 124 patients (ICB-naïve) and pre-treatment specimens from 67 advanced HCC patients treated with ICB (ICB-treated), were analyzed for CD8, PD-L1, LAG-3, and STAT1 tissue expression using multiplex immunohistochemistry followed by statistical and survival analyses. Results Immunohistochemical and survival analyses of ICB-naïve samples showed that high LAG-3 expression was associated with shorter median progression-free survival (mPFS) and overall survival (mOS). Analysis of ICB-treated samples revealed that high proportions of LAG-3+ and LAG-3+CD8+ cells pre-treatment were most closely associated with longer mPFS and mOS. Using a log-likelihood model, adding the total LAG-3+ cell proportion to the total CD8+ cell proportion significantly increased the predictive values for mPFS and mOS, compared with the total CD8+ cell proportion alone. Moreover, levels of CD8 and STAT1, but not PD-L1, were significantly correlated with better responses to ICB. After analyzing viral-related and non-viral HCC samples separately, only the LAG3+CD8+ cell proportion was significantly associated with responses to ICB regardless of viral status. Conclusion Immunohistochemical scoring of pre-treatment levels of LAG-3 and CD8 in the tumor microenvironment may help predict ICB benefits in HCC patients. Furthermore, immunohistochemistry-based techniques offer the advantage of being readily translatable in the clinical setting.

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Plasma proteomic signature for predicting survival in advanced HCC

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