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3 results on '"Drabarek W"'

1. Multi-Modality Analysis Improves Survival Prediction in Enucleated Uveal Melanoma Patients.

Author

Drabarek W, Yavuzyigitoglu S, Obulkasim A, van Riet J, Smit KN, van Poppelen NM, Vaarwater J, Brands T, Eussen B, Verdijk RM, Naus NC, Mensink HW, Paridaens D, Boersma E, van de Werken HJG, Kilic E, and de Klein A

Subjects
Aged, DNA Copy Number Variations, DNA, Neoplasm genetics, Disease-Free Survival, Female, Humans, Male, Melanoma diagnosis, Middle Aged, Proportional Hazards Models, Uveal Neoplasms diagnosis, Eukaryotic Initiation Factor-1 genetics, Eye Enucleation, Melanoma genetics, Melanoma surgery, Phosphoproteins genetics, Polymorphism, Single Nucleotide, RNA Splicing Factors genetics, Tumor Suppressor Proteins genetics, Ubiquitin Thiolesterase genetics, Uveal Neoplasms genetics, Uveal Neoplasms surgery
Abstract

Purpose: Uveal melanoma (UM) is characterized by multiple chromosomal rearrangements and recurrent mutated genes. The aim of this study was to investigate if copy number variations (CNV) alone and in combination with other genetic and clinico-histopathological variables can be used to stratify for disease-free survival (DFS) in enucleated patients with UM., Methods: We analyzed single nucleotide polymorphisms (SNP) array data of primary tumors and other clinical variables of 214 UM patients from the Rotterdam Ocular Melanoma Study (ROMS) cohort. Nonweighted hierarchical clustering of SNP array data was used to identify molecular subclasses with distinct CNV patterns. The subclasses associate with mutational status of BAP1, SF3B1, or EIF1AX. Cox proportional hazard models were then used to study the predictive performance of SNP array cluster-, mutation-, and clinico-histopathological data, and their combination for study endpoint risk., Results: Five clusters with distinct CNV patterns and concomitant mutations in BAP1, SF3B1, or EIF1AX were identified. The sample's cluster allocation contributed significantly to mutational status of samples in predicting the incidence of metastasis during a median of 45.6 (interquartile range [IQR]: 24.7-81.8) months of follow-up (P < 0.05) and vice versa. Furthermore, incorporating all data sources in one model yielded a 0.797 C-score during 100 months of follow-up., Conclusions: UM has distinct CNV patterns that correspond to different mutated driver genes. Incorporating clinico-histopathological, cluster and mutation data in the analysis results in good performance for UM-related DFS prediction.

Published
2019
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2. Correlation of Gene Mutation Status with Copy Number Profile in Uveal Melanoma.

Author

Yavuzyigitoglu S, Drabarek W, Smit KN, van Poppelen N, Koopmans AE, Vaarwater J, Brands T, Eussen B, Dubbink HJ, van Riet J, van de Werken HJ, Beverloo B, Verdijk RM, Naus N, Paridaens D, Kilic E, and de Klein A

Subjects
DNA Mutational Analysis, DNA, Neoplasm genetics, Female, Gene Expression Profiling, Humans, Karyotyping, Male, Polymorphism, Single Nucleotide, Chromosome Aberrations, DNA Copy Number Variations, Eukaryotic Initiation Factor-1 genetics, Melanoma genetics, Mutation, Phosphoproteins genetics, RNA Splicing Factors genetics, Tumor Suppressor Proteins genetics, Ubiquitin Thiolesterase genetics, Uveal Neoplasms genetics
Published
2017
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3. Multi-Modality Analysis Improves Survival Prediction in Enucleated Uveal Melanoma Patients

Author

Drabarek, W., Yavuzyigitoglu, S., Obulkasim, A., Riet, J., Smit, K.N., Poppelen, N.M., Vaarwater, J., Brands, T., Eussen, B., Verdijk, R.M., Naus, N.C., Mensink, H.W., Paridaens, D., Boersma, E., Werken, H.J.G. van de, Kilic, E., Klein, A. de, Keizer, R.O.B. de, Beek, J. van, Rij, C.M. van, Brosens, E., Ipenburg, J.A. van, Bruyn, D.P. de, Rotterdam Ocular Melanoma Study, Ophthalmology, Pediatrics, Urology, Clinical Genetics, Pathology, Cardiology, Virology, and Radiotherapy

Subjects
0301 basic medicine, Oncology, Male, Uveal Neoplasms, medicine.medical_specialty, DNA Copy Number Variations, Eukaryotic Initiation Factor-1, Single-nucleotide polymorphism, Biology, Gene mutation, survival, Polymorphism, Single Nucleotide, Disease-Free Survival, Eye Enucleation, unsupervised clustering, 03 medical and health sciences, 0302 clinical medicine, Interquartile range, Internal medicine, medicine, SNP, Humans, Copy-number variation, gene mutation, Melanoma, Aged, Proportional Hazards Models, BAP1, Proportional hazards model, Tumor Suppressor Proteins, copy number variation, DNA, Neoplasm, Middle Aged, Phosphoproteins, 030104 developmental biology, 030221 ophthalmology & optometry, Female, RNA Splicing Factors, uveal melanoma, Ubiquitin Thiolesterase, SNP array
Abstract

PURPOSE. Uveal melanoma (UM) is characterized by multiple chromosomal rearrangements and recurrent mutated genes. The aim of this study was to investigate if copy number variations (CNV) alone and in combination with other genetic and clinico-histopathological variables can be used to stratify for disease-free survival (DFS) in enucleated patients with UM.METHODS. We analyzed single nucleotide polymorphisms (SNP) array data of primary tumors and other clinical variables of 214 UM patients from the Rotterdam Ocular Melanoma Study (ROMS) cohort. Nonweighted hierarchical clustering of SNP array data was used to identify molecular subclasses with distinct CNV patterns. The subclasses associate with mutational status of BAP1, SF3B1, or EIF1AX. Cox proportional hazard models were then used to study the predictive performance of SNP array cluster-, mutation-, and clinico-histopathological data, and their combination for study endpoint risk.RESULTS. Five clusters with distinct CNV patterns and concomitant mutations in BAP1, SF3B1, or EIF1AX were identified. The sample's cluster allocation contributed significantly to mutational status of samples in predicting the incidence of metastasis during a median of 45.6 (interquartile range [IQR]: 24.7-81.8) months of follow-up (P < 0.05) and vice versa. Furthermore, incorporating all data sources in one model yielded a 0.797 C-score during 100 months of follow-up.CONCLUSIONS. UM has distinct CNV patterns that correspond to different mutated driver genes. Incorporating clinico-histopathological, cluster and mutation data in the analysis results in good performance for UM-related DFS prediction.

Published
2019

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