Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction
Abstract Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20–30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E)-stained pathological slides are used for routine diagnosis of cancer type, they may also con...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-025-00808-w |
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| _version_ | 1832586095947153408 |
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| author | Oz Kilim Alex Olar András Biricz Lilla Madaras Péter Pollner Zoltán Szállási Zsofia Sztupinszki István Csabai |
| author_facet | Oz Kilim Alex Olar András Biricz Lilla Madaras Péter Pollner Zoltán Szállási Zsofia Sztupinszki István Csabai |
| author_sort | Oz Kilim |
| collection | DOAJ |
| description | Abstract Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20–30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E)-stained pathological slides are used for routine diagnosis of cancer type, they may also contain diagnostically useful information about treatment response. Our study demonstrates that combining H&E-stained whole slide images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts. This method outperforms the Homologous Recombination Deficiency (HRD) score in predicting platinum response and overall patient survival. Our study suggests that histology and proteomics contain complementary information about biological processes determining response to first line platinum treatment in HGSOC. This integrative approach has the potential to improve personalized treatment and provide insights into the therapeutic vulnerabilities of HGSOC. |
| format | Article |
| id | doaj-art-e6d96de231d642999b3d5308bc2d0ca3 |
| institution | Kabale University |
| issn | 2397-768X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Precision Oncology |
| spelling | doaj-art-e6d96de231d642999b3d5308bc2d0ca32025-01-26T12:12:54ZengNature Portfolionpj Precision Oncology2397-768X2025-01-019111510.1038/s41698-025-00808-wHistopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response predictionOz Kilim0Alex Olar1András Biricz2Lilla Madaras3Péter Pollner4Zoltán Szállási5Zsofia Sztupinszki6István Csabai7Eötvös Loránd University, Department of Physics of Complex SystemsEötvös Loránd University, Department of Physics of Complex SystemsEötvös Loránd University, Department of Physics of Complex SystemsSemmelweis University, 2nd Department of PathologySemmelweis University, Data-Driven Health Division of National Laboratory for Health Security, Health Services Management Training CentreDanish Cancer InstituteDanish Cancer InstituteEötvös Loránd University, Department of Physics of Complex SystemsAbstract Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20–30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E)-stained pathological slides are used for routine diagnosis of cancer type, they may also contain diagnostically useful information about treatment response. Our study demonstrates that combining H&E-stained whole slide images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts. This method outperforms the Homologous Recombination Deficiency (HRD) score in predicting platinum response and overall patient survival. Our study suggests that histology and proteomics contain complementary information about biological processes determining response to first line platinum treatment in HGSOC. This integrative approach has the potential to improve personalized treatment and provide insights into the therapeutic vulnerabilities of HGSOC.https://doi.org/10.1038/s41698-025-00808-w |
| spellingShingle | Oz Kilim Alex Olar András Biricz Lilla Madaras Péter Pollner Zoltán Szállási Zsofia Sztupinszki István Csabai Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction npj Precision Oncology |
| title | Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction |
| title_full | Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction |
| title_fullStr | Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction |
| title_full_unstemmed | Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction |
| title_short | Histopathology and proteomics are synergistic for high-grade serous ovarian cancer platinum response prediction |
| title_sort | histopathology and proteomics are synergistic for high grade serous ovarian cancer platinum response prediction |
| url | https://doi.org/10.1038/s41698-025-00808-w |
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