Recently, a research team led by Prof. WANG Hongzhi at the Hefei Institutes of Physical Science, Chinese Academy of Sciences, has developed an auxiliary diagnostic strategy for lung cancer-associated pleural effusion based on volatile metabolites in pleural effusion.
The study was published in MedComm.
Lung cancer is one of the most serious malignant tumors affecting human health. During disease progression, some patients develop malignant pleural effusion. As it is closely associated with the tumor and its microenvironment, pleural effusion may contain metabolic information related to cancer. Identifying stable biomarkers in pleural effusion that reflect lung cancer metabolism is important for advancing liquid biopsy applications.
In this study, the researchers used headspace solid-phase microextraction combined with gas chromatography–mass spectrometry to analyze volatile metabolic profiles in malignant pleural effusion, benign pleural effusion, lung cancer tissues, and adjacent non-tumor tissues. Instead of simply comparing malignant and benign samples, they performed a cross-analysis between pleural effusion and tumor tissues, helping identify potential biomarkers that may better reflect metabolic changes in lung cancer.
Based on these results, the team proposed the concept of "gas biopsy of pleural effusion". Unlike conventional liquid biopsy methods that focus on cells, proteins, or nucleic acids, this approach targets volatile metabolic signals in pleural effusion. By capturing tumor-related “odor molecules” using mass spectrometry, the study offers a new way to explore lung cancer biomarkers.
The study found that hexanal showed consistent changes in both pleural effusion and lung cancer tissues, suggesting a link between tumor metabolism and volatile signals in pleural effusion. The team also developed a quantitative detection method for hexanal, supporting its potential use in lung cancer diagnosis.
Overall, the findings extend pleural effusion-based liquid biopsy by linking tumor tissue and pleural effusion data.
Gas chromatography–mass spectrometry-based “gas biopsy” workflow (Image by WANG Hongzhi)
