Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer
Abstract Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumo...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-024-84874-3 |
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| author | Jesenia M. Perez Jolene M. Duda Joohyun Ryu Mihir Shetty Subina Mehta Pratik D. Jagtap Andrew C. Nelson Boris Winterhoff Timothy J. Griffin Timothy K. Starr Stefani N. Thomas |
| author_facet | Jesenia M. Perez Jolene M. Duda Joohyun Ryu Mihir Shetty Subina Mehta Pratik D. Jagtap Andrew C. Nelson Boris Winterhoff Timothy J. Griffin Timothy K. Starr Stefani N. Thomas |
| author_sort | Jesenia M. Perez |
| collection | DOAJ |
| description | Abstract Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer. |
| format | Article |
| id | doaj-art-6ae2deb4ffbb434ea4e654f33c766270 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-6ae2deb4ffbb434ea4e654f33c7662702025-01-05T12:16:16ZengNature PortfolioScientific Reports2045-23222025-01-0115111810.1038/s41598-024-84874-3Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancerJesenia M. Perez0Jolene M. Duda1Joohyun Ryu2Mihir Shetty3Subina Mehta4Pratik D. Jagtap5Andrew C. Nelson6Boris Winterhoff7Timothy J. Griffin8Timothy K. Starr9Stefani N. Thomas10Microbiology, Immunology, and Cancer Biology Graduate Program, University of Minnesota School of MedicineBiochemistry, Molecular Biology and Biophysics, University of Minnesota School of MedicineDepartment of Laboratory Medicine and Pathology, University of Minnesota School of MedicineMasonic Cancer Center and Department of Obstetrics, Gynecology and Women’s Health, University of MinnesotaBiochemistry, Molecular Biology and Biophysics, University of Minnesota School of MedicineBiochemistry, Molecular Biology and Biophysics, University of Minnesota School of MedicineDepartment of Laboratory Medicine and Pathology, University of Minnesota School of MedicineMasonic Cancer Center and Department of Obstetrics, Gynecology and Women’s Health, University of MinnesotaBiochemistry, Molecular Biology and Biophysics, University of Minnesota School of MedicineMasonic Cancer Center and Department of Obstetrics, Gynecology and Women’s Health, University of MinnesotaDepartment of Laboratory Medicine and Pathology, University of Minnesota School of MedicineAbstract Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer. We demonstrate that the utilization of patient-specific databases guided by transcriptional profiles increases the depth of human protein identification in PDX models. Our data show that human proteomes of serially passaged PDXs differ significantly from their patient-derived tumor of origin. Analysis of differentially abundant proteins revealed enrichment of distinct biological pathways with major downregulated processes including extracellular matrix organization and the immune system. Finally, we investigated the relative abundances of ovarian cancer-related proteins identified from the Cancer Gene Census across serially passaged PDXs, and found their protein levels to be unstable across PDX models. Our findings highlight features of distinct and dynamic proteomes of serially-passaged PDX models of ovarian cancer.https://doi.org/10.1038/s41598-024-84874-3Patient-derived xenograft models (PDX)Ovarian cancerProteogenomicsMass spectrometryProteomics |
| spellingShingle | Jesenia M. Perez Jolene M. Duda Joohyun Ryu Mihir Shetty Subina Mehta Pratik D. Jagtap Andrew C. Nelson Boris Winterhoff Timothy J. Griffin Timothy K. Starr Stefani N. Thomas Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer Scientific Reports Patient-derived xenograft models (PDX) Ovarian cancer Proteogenomics Mass spectrometry Proteomics |
| title | Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer |
| title_full | Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer |
| title_fullStr | Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer |
| title_full_unstemmed | Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer |
| title_short | Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer |
| title_sort | investigating proteogenomic divergence in patient derived xenograft models of ovarian cancer |
| topic | Patient-derived xenograft models (PDX) Ovarian cancer Proteogenomics Mass spectrometry Proteomics |
| url | https://doi.org/10.1038/s41598-024-84874-3 |
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