Does the Addition of Mutations of CTNNB1 S45F to Clinical Factors Allow Prediction of Local Recurrence in Patients With a Desmoid Tumor? A Local Recurrence Risk Model.

BACKGROUND: The initial approach to the treatment of desmoid tumors has changed from surgical resection to watchful waiting. However, surgery is still sometimes considered for some patients, and it is likely that a few patients would benefit from tumor removal if the likelihood of local recurrence could be predicted. However, to our knowledge, there is no tool that can provide guidance on this for clinicians at the point of care. QUESTION/PURPOSE: We sought to explore whether a combined molecular and clinical prognostic model for relapse in patients with desmoid tumors treated with surgery would allow us to identify patients who might do well with surgical excision. METHODS: This was a retrospective, single-center study of 107 patients with desmoid tumors who were surgically treated between January 1980 and December 2015, with a median follow-up of 106 months (range 7 to 337 months). We correlated clinical variables (age, tumor size, and localization) and CTNNB1 gene mutations with recurrence-free survival. Recurrence-free survival was estimated using a Kaplan-Meier curve. Univariate and multivariable analyses of time to local recurrence were performed using Cox regression models. A final nomogram model was constructed according to the final fitted Cox model. The predictive performance of the model was evaluated using measures of calibration and discrimination: calibration plot and the Harrell C-statistic, also known as the concordance index, in which values near 0.5 represent a random prediction and values near 1 represent the best model predictions. RESULTS: The multivariable analysis showed that S45F mutations (hazard ratio 5.25 [95% confidence interval 2.27 to 12.15]; p < 0.001) and tumor in the extremities (HR 3.15 [95% CI 1.35 to 7.33]; p = 0.008) were associated with a higher risk of local recurrence. Based on these risk factors, we created a model; we observed that patients considered to be at high risk of local recurrence as defined by having one or two factors associated with recurrence (extremity tumors and S45F mutation) had an HR of 8.4 compared with patients who had no such factors (95% CI 2.84 to 24.6; p < 0.001). From these data and based on the multivariable Cox models, we also developed a nomogram to estimate the individual risk of relapse after surgical resection. The model had a concordance index of 0.75, or moderate discrimination. CONCLUSION: CTNNB1 S45F mutations combined with other clinical variables are a potential prognostic biomarker associated with the risk of relapse in patients with desmoid tumors. The developed nomogram is simple to use and, if validated, could be incorporated into clinical practice to identify patients at high risk of relapse among patients opting for surgical excision and thus help clinicians and patients in decision-making. A large multicenter study is necessary to validate our model and explore its applicability. LEVEL OF EVIDENCE: Level III, therapeutic study.

Recurrent somatic mutation in DROSHA induces microRNA profile changes in Wilms tumour.

Wilms tumour (WT) is an embryonal kidney neoplasia for which very few driver genes have been identified. Here we identify DROSHA mutations in 12% of WT samples (26/222) using whole-exome sequencing and targeted sequencing of 10 microRNA (miRNA)-processing genes. A recurrent mutation (E1147K) affecting a metal-binding residue of the RNase IIIb domain is detected in 81% of the DROSHA-mutated tumours. In addition, we identify non-recurrent mutations in other genes of this pathway (DGCR8, DICER1, XPO5 and TARBP2). By assessing the miRNA expression pattern of the DROSHA-E1147K-mutated tumours and cell lines expressing this mutation, we determine that this variant leads to a predominant downregulation of a subset of miRNAs. We confirm that the downregulation occurs exclusively in mature miRNAs and not in primary miRNA transcripts, suggesting that the DROSHA E1147K mutation affects processing of primary miRNAs. Our data underscore the pivotal role of the miRNA biogenesis pathway in WT tumorigenesis, particularly the major miRNA-processing gene DROSHA.