Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence
Abstract Background Ovarian cancer is the most lethal gynecological malignancy, often diagnosed at advanced stages with poor prognosis. The tumor microenvironment (TME) plays a critical role in disease progression and treatment response. This study aimed to construct a prognostic model for ovarian c...
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| Format: | Article |
| Language: | English |
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BMC
2025-06-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-025-06745-3 |
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| author | Sai Li Boyang Jiang Hongying Zhou Sifu Yang Liu Yang Yupeng Hong |
| author_facet | Sai Li Boyang Jiang Hongying Zhou Sifu Yang Liu Yang Yupeng Hong |
| author_sort | Sai Li |
| collection | DOAJ |
| description | Abstract Background Ovarian cancer is the most lethal gynecological malignancy, often diagnosed at advanced stages with poor prognosis. The tumor microenvironment (TME) plays a critical role in disease progression and treatment response. This study aimed to construct a prognostic model for ovarian cancer patients by evaluating the tumor immune landscape using multiplex immunofluorescence (mIF) staining, which focused on the spatial distribution and interactions of immune cells within the TME. Methods Formalin-fixed paraffin-embedded (FFPE) tissues from 129 ovarian cancer patients were analyzed using mIF to assess the expression of PD-L1(Programmed death-ligand 1, PD-L1), CD8(Cluster of Differentiation 8, CD8), TOX (Thymocyte Selection-Associated HMG Box, TOX), CD68(Cluster of Differentiation 68, CD68), and CK (Cytokeratin, CK). The Vectra Polaris quantitative pathology imaging system and Inform software were employed for image and spatial analysis. The LASSO Cox regression model was used for feature selection, and Kaplan-Meier survival analysis was performed to evaluate the prognostic significance of immune cell markers. A nomogram was developed to predict overall survival (OS) based on clinical parameters and the Immune Cell Related Prognostic Index (ICRPI). Results High percentages of CD8 + T cells, CD68 + macrophages, and CD68 + PD-L1 + macrophages were significantly associated with poor OS. Moreover, a high percentage of CD8 + T cells, CD68 + macrophages was significantly associated with poor disease-free survival (DFS). Spatial analysis revealed that a higher average count of CD68 + PD-L1 + macrophages within 30 μm of CD8 + T cells correlated with worse prognosis. The ICRPI model, incorporating CD68+, CD68 + PD-L1+, and spatial variables, effectively stratified patients into high- and low-risk groups, with high-risk patients showing significantly poorer OS. Conclusion This study highlights the prognostic value of immune cell spatial distribution in ovarian cancer. The ICRPI model, integrating immune cell markers and spatial analysis, provides a novel framework for predicting patient outcomes. Further validation in prospective studies is warranted to confirm the clinical utility of this model. |
| format | Article |
| id | doaj-art-173136c3bbae421996f643cca3ab9232 |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-173136c3bbae421996f643cca3ab92322025-08-24T11:48:05ZengBMCJournal of Translational Medicine1479-58762025-06-0123111510.1186/s12967-025-06745-3Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescenceSai Li0Boyang Jiang1Hongying Zhou2Sifu Yang3Liu Yang4Yupeng Hong5Ambulatory Surgery Center, Women’s Hospital, Zhejiang University School of MedicineCancer Center, Department of Medical Oncology, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical CollegeCancer Center, Department of Medical Oncology, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical CollegeCancer Center, Department of Medical Oncology, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical CollegeCancer Center, Department of Medical Oncology, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical CollegeCancer Center, Department of Medical Oncology, Zhejiang Provincial People’s Hospital(Affiliated People’s Hospital), Hangzhou Medical CollegeAbstract Background Ovarian cancer is the most lethal gynecological malignancy, often diagnosed at advanced stages with poor prognosis. The tumor microenvironment (TME) plays a critical role in disease progression and treatment response. This study aimed to construct a prognostic model for ovarian cancer patients by evaluating the tumor immune landscape using multiplex immunofluorescence (mIF) staining, which focused on the spatial distribution and interactions of immune cells within the TME. Methods Formalin-fixed paraffin-embedded (FFPE) tissues from 129 ovarian cancer patients were analyzed using mIF to assess the expression of PD-L1(Programmed death-ligand 1, PD-L1), CD8(Cluster of Differentiation 8, CD8), TOX (Thymocyte Selection-Associated HMG Box, TOX), CD68(Cluster of Differentiation 68, CD68), and CK (Cytokeratin, CK). The Vectra Polaris quantitative pathology imaging system and Inform software were employed for image and spatial analysis. The LASSO Cox regression model was used for feature selection, and Kaplan-Meier survival analysis was performed to evaluate the prognostic significance of immune cell markers. A nomogram was developed to predict overall survival (OS) based on clinical parameters and the Immune Cell Related Prognostic Index (ICRPI). Results High percentages of CD8 + T cells, CD68 + macrophages, and CD68 + PD-L1 + macrophages were significantly associated with poor OS. Moreover, a high percentage of CD8 + T cells, CD68 + macrophages was significantly associated with poor disease-free survival (DFS). Spatial analysis revealed that a higher average count of CD68 + PD-L1 + macrophages within 30 μm of CD8 + T cells correlated with worse prognosis. The ICRPI model, incorporating CD68+, CD68 + PD-L1+, and spatial variables, effectively stratified patients into high- and low-risk groups, with high-risk patients showing significantly poorer OS. Conclusion This study highlights the prognostic value of immune cell spatial distribution in ovarian cancer. The ICRPI model, integrating immune cell markers and spatial analysis, provides a novel framework for predicting patient outcomes. Further validation in prospective studies is warranted to confirm the clinical utility of this model.https://doi.org/10.1186/s12967-025-06745-3Ovarian cancerMultiplex immunofluorescence (mIF)Spatial analysisImmune Cell Related Prognostic Index (ICRPI) modelNomogram |
| spellingShingle | Sai Li Boyang Jiang Hongying Zhou Sifu Yang Liu Yang Yupeng Hong Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence Journal of Translational Medicine Ovarian cancer Multiplex immunofluorescence (mIF) Spatial analysis Immune Cell Related Prognostic Index (ICRPI) model Nomogram |
| title | Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence |
| title_full | Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence |
| title_fullStr | Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence |
| title_full_unstemmed | Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence |
| title_short | Development of a prognostic immune cell-based model for ovarian cancer using multiplex immunofluorescence |
| title_sort | development of a prognostic immune cell based model for ovarian cancer using multiplex immunofluorescence |
| topic | Ovarian cancer Multiplex immunofluorescence (mIF) Spatial analysis Immune Cell Related Prognostic Index (ICRPI) model Nomogram |
| url | https://doi.org/10.1186/s12967-025-06745-3 |
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