Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer
BackgroundImmune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure.MethodsWe evaluated the circulating levels of 14 immune checkpoint-re...
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.887916/full |
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| author | Qinchuan Wang Qinchuan Wang Qinchuan Wang Yue He Yue He Wanlu Li Wanlu Li Xiaohang Xu Xiaohang Xu Qingfeng Hu Qingfeng Hu Zilong Bian Zilong Bian Andi Xu Andi Xu Huakang Tu Huakang Tu Ming Wu Xifeng Wu Xifeng Wu |
| author_facet | Qinchuan Wang Qinchuan Wang Qinchuan Wang Yue He Yue He Wanlu Li Wanlu Li Xiaohang Xu Xiaohang Xu Qingfeng Hu Qingfeng Hu Zilong Bian Zilong Bian Andi Xu Andi Xu Huakang Tu Huakang Tu Ming Wu Xifeng Wu Xifeng Wu |
| author_sort | Qinchuan Wang |
| collection | DOAJ |
| description | BackgroundImmune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure.MethodsWe evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation.ResultsWe found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset.ConclusionOur study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients. |
| first_indexed | 2024-04-13T11:47:37Z |
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| language | English |
| last_indexed | 2024-04-13T11:47:37Z |
| publishDate | 2022-07-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-d147cdbd63ee42a08e9fc149780ed9662022-12-22T02:48:08ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-07-011310.3389/fimmu.2022.887916887916Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung CancerQinchuan Wang0Qinchuan Wang1Qinchuan Wang2Yue He3Yue He4Wanlu Li5Wanlu Li6Xiaohang Xu7Xiaohang Xu8Qingfeng Hu9Qingfeng Hu10Zilong Bian11Zilong Bian12Andi Xu13Andi Xu14Huakang Tu15Huakang Tu16Ming Wu17Xifeng Wu18Xifeng Wu19Center for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaDepartment of Surgical Oncology, Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaDepartment of Thoracic Surgery, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCenter for Biostatistics, Bioinformatics and Big Data, The Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, ChinaThe Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, ChinaBackgroundImmune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure.MethodsWe evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation.ResultsWe found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset.ConclusionOur study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients.https://www.frontiersin.org/articles/10.3389/fimmu.2022.887916/fullsoluble immune checkpoint-related proteinnon-small cell lung canceradenocarcinoma in situinvasive adenocarcinomaprediction model |
| spellingShingle | Qinchuan Wang Qinchuan Wang Qinchuan Wang Yue He Yue He Wanlu Li Wanlu Li Xiaohang Xu Xiaohang Xu Qingfeng Hu Qingfeng Hu Zilong Bian Zilong Bian Andi Xu Andi Xu Huakang Tu Huakang Tu Ming Wu Xifeng Wu Xifeng Wu Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer Frontiers in Immunology soluble immune checkpoint-related protein non-small cell lung cancer adenocarcinoma in situ invasive adenocarcinoma prediction model |
| title | Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer |
| title_full | Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer |
| title_fullStr | Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer |
| title_full_unstemmed | Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer |
| title_short | Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer |
| title_sort | soluble immune checkpoint related proteins in blood are associated with invasion and progression in non small cell lung cancer |
| topic | soluble immune checkpoint-related protein non-small cell lung cancer adenocarcinoma in situ invasive adenocarcinoma prediction model |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.887916/full |
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