What does this research mean for the field?

Lung cancer biomarker research has evolved towards multimodal, intelligent screening approaches, with future priorities focusing on DNA methylation, circulating microRNAs, and artificial intelligence-assisted diagnostics. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The aim is to analyze global research trends and collaborative frameworks in lung cancer biomarker studies that enhance screening processes.

May 28, 2026Open Access

A visual analysis of the research dynamics of biomarkers for lung cancer screening

Key Points

The aim is to analyze global research trends and collaborative frameworks in lung cancer biomarker studies that enhance screening processes.
Performed bibliometric analysis of 3636 publications from Web of Science Core Collection.
Utilized Citespace, VOSviewer, and other platforms for data visualization and topic modeling.
Conducted burst detection analysis to project future research trends.
Research output on lung cancer biomarkers showed exponential growth since 2014.
Identified four emerging research areas, including DNA methylation and liquid biopsy technologies.
Found a dual-core research structure focused on China and the United States with differing publication and citation impacts.

Abstract

BACKGROUND: Non-invasive biomarkers offer potential to improve risk stratification and early diagnosis of lung cancer, complementing low-dose computed tomography (LDCT) screening. This study employed bibliometric analysis to identify global research trends, collaborative networks, and future directions in lung cancer biomarker research. Publications on lung cancer biomarkers for screening were retrieved from the Web of Science Core Collection (WoSCC). Data processing and visualisation were performed using Citespace, VOSviewer, KH Coder, Latent Dirichlet Allocation (LDA) topic modelling, and the online bibliometric analysis platform. Burst detection analysis was performed to predict emerging research trends. RESULTS: Analysis of 3636 publications revealed exponential growth in research output since 2014. International collaboration demonstrated a dual-core structure centred on China and the United States, with Chinese institutions showing high publication volumes and American institutions demonstrating greater citation influence. Journal citation mapping revealed three evolutionary phases: basic mechanisms-clinical translation-intelligent integration. LDA topic modelling identified 22 topics grouped into five core research directions: imaging and pathological diagnostic techniques; molecular and omics marker research; liquid biopsy and new detection technologies; clinical and translational medicine research; and tumour biology and treatment mechanisms. Burst detection analysis predicted future four priority areas: epigenetic studies centred on DNA methylation for risk prediction; treatment resistance and invasion mechanisms; liquid biopsy technology development; and targeted therapy clinical trials. CONCLUSIONS: Lung cancer biomarker research has evolved towards multimodal, intelligent screening approaches. Future research priorities include DNA methylation-based markers, circulating microRNA signatures, and artificial intelligence-assisted diagnostic platforms to improve early detection accuracy and complement LDCT screening.

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