OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer
Abstract Background Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies. Methods We constructed a prognostic and risk assessmen...
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| Format: | Article |
| Language: | English |
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BMC
2025-01-01
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| Series: | Biology Direct |
| Online Access: | https://doi.org/10.1186/s13062-025-00596-0 |
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| author | Qihui Sun Xiaoqi Zhu Qi Zou Yang Chen Tingting Wen Tingting Jiang Xiaojia Li Fang Wei Keping Xie Jia Liu |
| author_facet | Qihui Sun Xiaoqi Zhu Qi Zou Yang Chen Tingting Wen Tingting Jiang Xiaojia Li Fang Wei Keping Xie Jia Liu |
| author_sort | Qihui Sun |
| collection | DOAJ |
| description | Abstract Background Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies. Methods We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis. We integrated multi-dataset analyses, single-cell transcriptomic data, and functional experiments to explore the role of OSBPL3 in pancreatic cancer. Results Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. Notably, the “rf” algorithm model showed an AUC of 1 in the training set and AUCs of 0.887 and 0.977 in two validation datasets. Ridge regression analysis identified OSBPL3 as a core prognostic feature gene. High OSBPL3 expression in pancreatic cancer samples was associated with immunosuppressive characteristics, including reduced CD8 + T cell infiltration and increased immunosuppressive cell populations such as Treg cells and M2 macrophages. Transcriptomic sequencing following OSBPL3 knockdown revealed enrichment of immune-related pathways, suggesting OSBPL3’s influence on the immune microenvironment. Single-cell analyses further confirmed OSBPL3’s role in shaping the immunosuppressive landscape by modulating Treg cells and M2 macrophages. Additionally, OSBPL3 expression was linked to resistance to immunotherapy, with high OSBPL3 expression associated with lower Immunophenoscore (IPS) scores, indicating poor responsiveness to immunotherapy. Conclusions Our study reveals OSBPL3 as a critical regulator of the immunosuppressive microenvironment in pancreatic cancer and a potential therapeutic target. Targeting OSBPL3 may enhance the efficacy of immunotherapy and improve patient outcomes. Further research is warranted to explore OSBPL3 as a biomarker for predicting immunotherapy response and as a potential therapeutic target in combination with anti-PD1 therapy. |
| format | Article |
| id | doaj-art-5193434e1aec4be4a1d35651d515837b |
| institution | Kabale University |
| issn | 1745-6150 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Biology Direct |
| spelling | doaj-art-5193434e1aec4be4a1d35651d515837b2025-01-12T12:11:27ZengBMCBiology Direct1745-61502025-01-0120111810.1186/s13062-025-00596-0OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancerQihui Sun0Xiaoqi Zhu1Qi Zou2Yang Chen3Tingting Wen4Tingting Jiang5Xiaojia Li6Fang Wei7Keping Xie8Jia Liu9Center for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineCenter for Pancreatic Cancer Research, Department of Immunology, The South China University of Technology School of MedicineSchool of Medicine, South China University of TechnologyAbstract Background Pancreatic cancer is characterized by a complex tumor microenvironment that hinders effective immunotherapy. Identifying key factors that regulate the immunosuppressive landscape is crucial for improving treatment strategies. Methods We constructed a prognostic and risk assessment model for pancreatic cancer using 101 machine learning algorithms, identifying OSBPL3 as a key gene associated with disease progression and prognosis. We integrated multi-dataset analyses, single-cell transcriptomic data, and functional experiments to explore the role of OSBPL3 in pancreatic cancer. Results Our risk prediction model, developed using machine learning algorithms, demonstrated high predictive accuracy across multiple datasets. Notably, the “rf” algorithm model showed an AUC of 1 in the training set and AUCs of 0.887 and 0.977 in two validation datasets. Ridge regression analysis identified OSBPL3 as a core prognostic feature gene. High OSBPL3 expression in pancreatic cancer samples was associated with immunosuppressive characteristics, including reduced CD8 + T cell infiltration and increased immunosuppressive cell populations such as Treg cells and M2 macrophages. Transcriptomic sequencing following OSBPL3 knockdown revealed enrichment of immune-related pathways, suggesting OSBPL3’s influence on the immune microenvironment. Single-cell analyses further confirmed OSBPL3’s role in shaping the immunosuppressive landscape by modulating Treg cells and M2 macrophages. Additionally, OSBPL3 expression was linked to resistance to immunotherapy, with high OSBPL3 expression associated with lower Immunophenoscore (IPS) scores, indicating poor responsiveness to immunotherapy. Conclusions Our study reveals OSBPL3 as a critical regulator of the immunosuppressive microenvironment in pancreatic cancer and a potential therapeutic target. Targeting OSBPL3 may enhance the efficacy of immunotherapy and improve patient outcomes. Further research is warranted to explore OSBPL3 as a biomarker for predicting immunotherapy response and as a potential therapeutic target in combination with anti-PD1 therapy.https://doi.org/10.1186/s13062-025-00596-0 |
| spellingShingle | Qihui Sun Xiaoqi Zhu Qi Zou Yang Chen Tingting Wen Tingting Jiang Xiaojia Li Fang Wei Keping Xie Jia Liu OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer Biology Direct |
| title | OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| title_full | OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| title_fullStr | OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| title_full_unstemmed | OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| title_short | OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| title_sort | osbpl3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer |
| url | https://doi.org/10.1186/s13062-025-00596-0 |
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