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

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

Expanding the living donor pool using domino liver transplantation: a systematic review

Introduction: To this day, a discrepancy exists between donor liver demand and supply. Domino liver transplantation (DLT) can contribute to increasing the number of donor livers available for transplantation. Methods: The design of this systematic review was based on the Preferred Reporting Items for Systematic Reviews (PRISMA). A qualitative analysis of included studies was performed. Primary outcomes were mortality and peri- and postoperative complications related to DLT. Results: Twelve studies met the inclusion criteria. All included studies showed that DLT outcomes were comparable to outcomes of deceased donor liver transplantation (DDLT) in terms of mortality and complications. One-year patient survival rate ranged from 66.7% to 100%. Re-transplantation rate varied from 0 to 12.5%. Most frequent complications were related to biliary (3.7%–37.5%), hepatic artery (1.6%–9.1%), portal vein (12.5–33.3%) and hepatic vein events (1.6%), recurrence of domino donor disease (3.3%–17.4%) and graft rejection (16.7%–37.7%). The quality of the evidence was rated as moderate according to the Newcastle–Ottawa scale (NOS). Conclusion: DLT outcomes were similar to DDLT in terms of mortality and complications. Even though DLT will not solve the entire problem of organ shortage, transplant programs should always consider using this tool to maximize the availability of liver grafts

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

textabstractPURPOSE. 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