Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups
Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metasta...
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| Format: | Article |
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Elsevier
2024-12-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037024000370 |
| _version_ | 1797281176278269952 |
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| author | Konrad Grützmann Theresa Kraft Matthias Meinhardt Friedegund Meier Dana Westphal Michael Seifert |
| author_facet | Konrad Grützmann Theresa Kraft Matthias Meinhardt Friedegund Meier Dana Westphal Michael Seifert |
| author_sort | Konrad Grützmann |
| collection | DOAJ |
| description | Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes. |
| first_indexed | 2024-03-07T16:53:45Z |
| format | Article |
| id | doaj.art-22878d96341a4e81866b8b51ae880f20 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-07T16:53:45Z |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-22878d96341a4e81866b8b51ae880f202024-03-03T04:29:36ZengElsevierComputational and Structural Biotechnology Journal2001-03702024-12-012310361050Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroupsKonrad Grützmann0Theresa Kraft1Matthias Meinhardt2Friedegund Meier3Dana Westphal4Michael Seifert5Institute for Medical Informatics and Biometry, Faculty of Medicine, TU Dresden, 01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Faculty of Medicine, TU Dresden, 01307 Dresden, GermanyDepartment of Pathology, University Hospital Carl Gustav Carus Dresden, TU Dresden, 01307 Dresden, GermanyDepartment of Dermatology, University Hospital Carl Gustav Carus Dresden, TU Dresden, 01307 Dresden, Germany; National Center for Tumor Diseases (NCT), D-01307 Dresden, GermanyDepartment of Dermatology, University Hospital Carl Gustav Carus Dresden, TU Dresden, 01307 Dresden, Germany; National Center for Tumor Diseases (NCT), D-01307 Dresden, GermanyInstitute for Medical Informatics and Biometry, Faculty of Medicine, TU Dresden, 01307 Dresden, Germany; National Center for Tumor Diseases (NCT), D-01307 Dresden, Germany; Corresponding author at: Institute for Medical Informatics and Biometry, Faculty of Medicine, TU Dresden, 01307 Dresden, Germany.Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.http://www.sciencedirect.com/science/article/pii/S2001037024000370Computational cancer biologyMelanoma metastasisGene regulatory network inferenceNetwork-based impact propagationPersonalized network-based gene expression and promoter methylation data analysis |
| spellingShingle | Konrad Grützmann Theresa Kraft Matthias Meinhardt Friedegund Meier Dana Westphal Michael Seifert Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups Computational and Structural Biotechnology Journal Computational cancer biology Melanoma metastasis Gene regulatory network inference Network-based impact propagation Personalized network-based gene expression and promoter methylation data analysis |
| title | Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| title_full | Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| title_fullStr | Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| title_full_unstemmed | Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| title_short | Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| title_sort | network based analysis of heterogeneous patient matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups |
| topic | Computational cancer biology Melanoma metastasis Gene regulatory network inference Network-based impact propagation Personalized network-based gene expression and promoter methylation data analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2001037024000370 |
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