Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer
<b>Background/Objectives</b>: The current staging of non-small cell lung cancer (NSCLC) relies on conventional imaging, which lacks the sensitivity to detect micrometastatic disease. The functional assessment of NSCLC progression may provide independent information to enhance the predict...
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2025-05-01
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| author | Manlu Liu Yanlong Zhu Sean J. McIlwain Haotian Deng Allan R. Brasier Ying Ge Michelle E. Kimple Andrew M. Baschnagel |
| author_facet | Manlu Liu Yanlong Zhu Sean J. McIlwain Haotian Deng Allan R. Brasier Ying Ge Michelle E. Kimple Andrew M. Baschnagel |
| author_sort | Manlu Liu |
| collection | DOAJ |
| description | <b>Background/Objectives</b>: The current staging of non-small cell lung cancer (NSCLC) relies on conventional imaging, which lacks the sensitivity to detect micrometastatic disease. The functional assessment of NSCLC progression may provide independent information to enhance the prediction of metastatic risk. The objective of this study was to determine if we could identify a metabolomic signature predictive of metastasis in patients with NSCLC treated with definitive radiation. <b>Methods</b>: Plasma samples were collected prospectively from patients enrolled in a clinical trial with non-metastatic NSCLC treated with definitive radiation. Metabolites were extracted, and mass spectrometry-based analysis was performed using a flow injection electrospray (FIE)–Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) method. Early metastasis was defined as metastasis within 1 year of radiation treatment. <b>Results</b>: The study cohort included 28 patients. FIE-FITCR produced highly reproducible profiles in technical replicates. A total of 51 metabolic features were identified to be different in patients with early metastasis compared to patients without early metastasis (all adjusted <i>p</i>-values < 0.05, Welch’s <i>t</i>-test), including glycerophospholipids, sphingolipids, and fatty acyls. In the follow-up samples collected after the initiation of chemotherapy and radiation treatment, a total of 174 metabolic features were significantly altered in patients who developed early metastasis compared to those who did not. <b>Conclusions</b>: We identified several distinct changes in the metabolic profiles of patients with NSCLC who developed metastatic disease within 1 year of definitive radiation. These findings highlight the potential of metabolomic profiling as a predictive tool for assessing metastatic risk in NSCLC. |
| format | Article |
| id | doaj-art-cba2a7e6f81348169e57f8e2a80ed19e |
| institution | DOAJ |
| issn | 2218-1989 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metabolites |
| spelling | doaj-art-cba2a7e6f81348169e57f8e2a80ed19e2025-08-20T03:14:39ZengMDPI AGMetabolites2218-19892025-05-0115534010.3390/metabo15050340Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung CancerManlu Liu0Yanlong Zhu1Sean J. McIlwain2Haotian Deng3Allan R. Brasier4Ying Ge5Michelle E. Kimple6Andrew M. Baschnagel7Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USAHuman Proteomics Program, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USADepartment of Human Oncology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USA<b>Background/Objectives</b>: The current staging of non-small cell lung cancer (NSCLC) relies on conventional imaging, which lacks the sensitivity to detect micrometastatic disease. The functional assessment of NSCLC progression may provide independent information to enhance the prediction of metastatic risk. The objective of this study was to determine if we could identify a metabolomic signature predictive of metastasis in patients with NSCLC treated with definitive radiation. <b>Methods</b>: Plasma samples were collected prospectively from patients enrolled in a clinical trial with non-metastatic NSCLC treated with definitive radiation. Metabolites were extracted, and mass spectrometry-based analysis was performed using a flow injection electrospray (FIE)–Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) method. Early metastasis was defined as metastasis within 1 year of radiation treatment. <b>Results</b>: The study cohort included 28 patients. FIE-FITCR produced highly reproducible profiles in technical replicates. A total of 51 metabolic features were identified to be different in patients with early metastasis compared to patients without early metastasis (all adjusted <i>p</i>-values < 0.05, Welch’s <i>t</i>-test), including glycerophospholipids, sphingolipids, and fatty acyls. In the follow-up samples collected after the initiation of chemotherapy and radiation treatment, a total of 174 metabolic features were significantly altered in patients who developed early metastasis compared to those who did not. <b>Conclusions</b>: We identified several distinct changes in the metabolic profiles of patients with NSCLC who developed metastatic disease within 1 year of definitive radiation. These findings highlight the potential of metabolomic profiling as a predictive tool for assessing metastatic risk in NSCLC.https://www.mdpi.com/2218-1989/15/5/340lung cancermetabolomicsbiomarkersclinical study |
| spellingShingle | Manlu Liu Yanlong Zhu Sean J. McIlwain Haotian Deng Allan R. Brasier Ying Ge Michelle E. Kimple Andrew M. Baschnagel Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer Metabolites lung cancer metabolomics biomarkers clinical study |
| title | Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer |
| title_full | Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer |
| title_fullStr | Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer |
| title_full_unstemmed | Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer |
| title_short | Characterizing Plasma-Based Metabolomic Signatures for Metastasis in Non-Small Cell Lung Cancer |
| title_sort | characterizing plasma based metabolomic signatures for metastasis in non small cell lung cancer |
| topic | lung cancer metabolomics biomarkers clinical study |
| url | https://www.mdpi.com/2218-1989/15/5/340 |
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