Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is a highly lethal and heterogeneous liver cancer in which pathology-derived features such as microvascular invasion (MVI) and histologic growth pattern critically shape prognosis and treatment selection. Over the past two decades, numerous serum, tissue and liquid-biopsy biomarkers have been proposed, but their development is fragmented and poorly integrated with pathology-based staging. We hypothesized that systematic bibliometric mapping of HCC pathology-related biomarker research would clarify global structures, hotspots and gaps along the pathway from mechanistic discovery to clinical translation. This study aims to map and quantify global research patterns in pathology-related biomarkers for HCC from 2005 to 2025. METHODS: We performed a cross-sectional bibliometric study of HCC pathology-biomarker literature indexed in the Science Citation Index Expanded (SCIE) [Web of Science Core Collection (WoSCC)] between 1 January 2005 and 21 November 2025. English-language articles and reviews were retrieved using a combined pathology-biomarker-liver cancer topic search (TS). Descriptive indicators, collaboration networks, co-citation structures and keyword co-occurrence maps were generated using Bibliometrix (R), VOSviewer and CiteSpace. RESULTS: A total of 2,907 publications were identified, with annual output rising from 9 in 2005 to 280 in 2025; nearly half of all papers appeared during 2021-2025. China contributed ~48% of articles, followed by the USA, Japan and Italy, while a small group of high-impact hepatology and oncology journals formed the core co-citation backbone. Keyword and burst analyses showed an evolution from classical serum markers and gene-expression studies toward multimodal biomarker systems integrating histopathology, tissue genomics, tumour microenvironment, immune infiltration, radiomics and liquid-biopsy platforms. CONCLUSIONS: Bibliometric mapping shows that pathology-related HCC biomarker research is rapidly expanding and shifting toward multimodal, pathology-informed systems, underscoring the need for validated integrative models and broader international collaboration.