Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer
BackgroundTo construct a prediction model consisting of metabolites and proteins in peripheral blood plasma to predict whether patients with unresectable stage III and IV non-small cell lung cancer can benefit from immunotherapy before it is administered.MethodsPeripheral blood plasma was collected...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1479550/full |
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| author | Rui Wu Kunchen Wei Xingshuai Huang Yinge Zhou Xiao Feng Xin Dong Hao Tang |
| author_facet | Rui Wu Kunchen Wei Xingshuai Huang Yinge Zhou Xiao Feng Xin Dong Hao Tang |
| author_sort | Rui Wu |
| collection | DOAJ |
| description | BackgroundTo construct a prediction model consisting of metabolites and proteins in peripheral blood plasma to predict whether patients with unresectable stage III and IV non-small cell lung cancer can benefit from immunotherapy before it is administered.MethodsPeripheral blood plasma was collected from unresectable stage III and IV non-small cell lung cancer patients who were negative for driver mutations before receiving immunotherapy. Then we classified samples according to the follow-up results after two courses of immunotherapy and non-targeted metabolomics and proteomics analyses were performed to select different metabolites and proteins. Finally, potential biomarkers were picked out by applying machine learning methods including random forest and stepwise regression and prediction models were constructed by logistic regression.ResultsThe presence of metabolites and proteins in peripheral blood plasma was causally associated with both non-small cell lung cancer and PD-L1/PD-1 expression levels. A total of 2 differential metabolites including 5-sulfooxymethylfurfural and Anthranilic acid and 2 differential proteins including Immunoglobulin heavy variable 1-45 and Microfibril-associated glycoprotein 4 were selected as reliable biomarkers. The area under the curve (AUC) of the prediction model built on clinical risks was merely 0.659. The AUC of metabolomics prediction model was 0.977 and the AUC of proteomics was 0.875 while the AUC of the integrative-omics prediction model was 0.955.ConclusionsMetabolic and protein biomarkers in peripheral blood both have high efficacy and reliability in the prediction of immunotherapy sensitivity in unresectable stage III and IV non-small cell lung cancer, but validation in larger population-based cohorts is still needed. |
| format | Article |
| id | doaj-art-27288d1a5042451199b609c064ed496a |
| institution | Kabale University |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Immunology |
| spelling | doaj-art-27288d1a5042451199b609c064ed496a2025-02-07T06:49:33ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-02-011610.3389/fimmu.2025.14795501479550Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancerRui Wu0Kunchen Wei1Xingshuai Huang2Yinge Zhou3Xiao Feng4Xin Dong5Hao Tang6Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Surgery II, Peking University Cancer Hospital & Institute, Beijing, ChinaDepartment of Respiratory and Critical Care Medicine, Changzheng Hospital, Navy Medical University, Shanghai, ChinaDepartment of Anesthesiology, Changzheng Hospital, Navy Medical University, Shanghai, ChinaSchool of Medicine, Shanghai University, Shanghai, ChinaDepartment of Respiratory and Critical Care Medicine, Changzheng Hospital, Navy Medical University, Shanghai, ChinaSchool of Medicine, Shanghai University, Shanghai, ChinaDepartment of Respiratory and Critical Care Medicine, Changzheng Hospital, Navy Medical University, Shanghai, ChinaBackgroundTo construct a prediction model consisting of metabolites and proteins in peripheral blood plasma to predict whether patients with unresectable stage III and IV non-small cell lung cancer can benefit from immunotherapy before it is administered.MethodsPeripheral blood plasma was collected from unresectable stage III and IV non-small cell lung cancer patients who were negative for driver mutations before receiving immunotherapy. Then we classified samples according to the follow-up results after two courses of immunotherapy and non-targeted metabolomics and proteomics analyses were performed to select different metabolites and proteins. Finally, potential biomarkers were picked out by applying machine learning methods including random forest and stepwise regression and prediction models were constructed by logistic regression.ResultsThe presence of metabolites and proteins in peripheral blood plasma was causally associated with both non-small cell lung cancer and PD-L1/PD-1 expression levels. A total of 2 differential metabolites including 5-sulfooxymethylfurfural and Anthranilic acid and 2 differential proteins including Immunoglobulin heavy variable 1-45 and Microfibril-associated glycoprotein 4 were selected as reliable biomarkers. The area under the curve (AUC) of the prediction model built on clinical risks was merely 0.659. The AUC of metabolomics prediction model was 0.977 and the AUC of proteomics was 0.875 while the AUC of the integrative-omics prediction model was 0.955.ConclusionsMetabolic and protein biomarkers in peripheral blood both have high efficacy and reliability in the prediction of immunotherapy sensitivity in unresectable stage III and IV non-small cell lung cancer, but validation in larger population-based cohorts is still needed.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1479550/fullnon-small cell lung cancerimmune checkpoint inhibitorsmetabolomicsproteomicsprediction models |
| spellingShingle | Rui Wu Kunchen Wei Xingshuai Huang Yinge Zhou Xiao Feng Xin Dong Hao Tang Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer Frontiers in Immunology non-small cell lung cancer immune checkpoint inhibitors metabolomics proteomics prediction models |
| title | Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer |
| title_full | Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer |
| title_fullStr | Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer |
| title_full_unstemmed | Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer |
| title_short | Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer |
| title_sort | multi omics analysis reveals the sensitivity of immunotherapy for unresectable non small cell lung cancer |
| topic | non-small cell lung cancer immune checkpoint inhibitors metabolomics proteomics prediction models |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1479550/full |
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