PurposeTo create an interactive web-based tool for the Prediction of Risk of Metastasis in Uveal Melanoma (PRiMeUM) that can provide a personalized risk estimate of developing metastases within 48 months of primary uveal melanoma (UM) treatment. The model utilizes routinely collected clinical and tumor characteristics on 1227 UM, with the option of including chromosome information when available.MethodsUsing a cohort of 1227 UM cases, Cox proportional hazard modeling was used to assess significant predictors of metastasis including clinical and chromosomal characteristics. A multivariate model to predict risk of metastasis was evaluated using machine learning methods including logistic regression, decision trees, survival random forest, and survival-based regression models. Based on cross-validation results, a logistic regression classifier was developed to compute an individualized risk of metastasis based on clinical and chromosomal information.ResultsThe PRiMeUM model provides prognostic information for personalized risk of metastasis in UM. The accuracy of the risk prediction ranged between 80% (using chromosomal features only), 83% using clinical features only (age, sex, tumor location, and size), and 85% (clinical and chromosomal information). Kaplan-Meier analysis showed these risk scores to be highly predictive of metastasis (P < 0.0001).ConclusionsPRiMeUM provides a tool for predicting an individual's personal risk of metastasis based on their individual and tumor characteristics. It will aid physicians with decisions concerning frequency of systemic surveillance and can be used as a criterion for entering clinical trials for adjuvant therapies.

PURPOSE Tumor-only genomic profiling (TGP) is increasingly advocated for all patients with cancer given the possible therapeutic implications. It is critical to develop clinical algorithms to identify and address potentially actionable germline findings identified by TGP. METHODS A multidisciplinary team analyzed publicly available data for genes in which mutations are implicated in germline cancer susceptibility and established a pipeline to automate clinical referral for evaluation of TGP findings. RESULTS A total of 2,308 patients underwent TGP, with 81 patients (3.5%) identified by the automatic referral pipeline; 37 patients (1.6%) were referred outside the pipeline based on concerns by the molecular geneticist, pathologist, or oncologist regarding genotype-phenotype correlation. Thirty-one patients (38%) and 17 patients (46%) underwent germline testing from the automatic pipeline and other referrals, respectively, and of these patients, 23 (72%) and four (24%) had confirmed germline pathogenic variants (GPVs), respectively. The majority of confirmed GPVs were in automatic referral genes, with BRCA2 being most common (confirmed GPVs in 11 [85%] of 13 patients tested), followed by PALB2 (five [67%] of six patients), BRCA1 (two [40%] of five patients), MSH6 (two of three patients), and MLH1 (two of two patients). Forty-eight percent of confirmed GPVs were found in tumors known to be associated with germline mutations in the gene. Germline testing was not performed in 50 (62%) of 81 patients identified by automatic referral as a result of poor patient health or death (30%), lack of follow-up (30%), and patient refusal (30%). CONCLUSION Of patients undergoing TGP, 5% had somatic findings triggering referral, and implementation of an automatic referral pipeline based solely on gene versus other clinical or molecular features resulted in a 74% germline confirmation. However, only 41% of referred patients underwent germline testing. Systems-based approaches are needed to identify carriers of actionable germline cancer susceptibility mutations identified by TGP.

Background Somatic overgrowth conditions, including Proteus syndrome, Sturge–Weber syndrome, and PIK3CA ‐related overgrowth spectrum, are caused by post‐zygotic pathogenic variants, result in segmental mosaicism, and give rise to neural, cutaneous and/or lipomatous overgrowth. These variants occur in growth‐promoting pathways leading to cellular proliferation and expansion of tissues that arise from the affected cellular lineage. Methods We report on 80 serial patients evaluated for somatic overgrowth conditions in a diagnostic laboratory setting, including three prenatal patients. In total, 166 tissues from these 80 patients were subjected to targeted sequencing of an 8‐gene panel capturing 10.2 kb of sequence containing known pathogenic variants associated with somatic overgrowth conditions. Deep next‐generation sequencing was performed with the IonTorrent PGM platform at an average depth typically >5,000×. Results Likely pathogenic or pathogenic variants were identified in 36 individuals and variants of unknown significance in four. The overall molecular diagnostic yield was 45% but was highly influenced by both submitted tissue type and phenotype. In the prenatal setting, two patients had pathogenic variants identified in cultured amniocytes but in a third patient, the pathogenic variant was only present in post‐natal tissues. Finally, expanding the test to include full gene sequencing of PIK3CA in contrast to targeted sequencing identified likely pathogenic variants in 3 of 7 patients that tested negative on the original panel. Conclusion Next‐generation sequencing has enabled sensitive detection of somatic pathogenic variants associated with overgrowth conditions. However, as the pathogenic variant allele frequency varies by tissue type within an individual, submission of affected tissue(s) greatly increases the chances of a molecular diagnosis.

Juvenile polyposis syndrome (JPS) is a clinically diagnosed hamartomatous polyposis syndrome that increases the risk of gastrointestinal cancer. Approximately 40%–50% of JPS is caused by a germline disease-causing variant (DCV) in the SMAD4 or BMPR1A genes. The aim of this study was to characterize the phenotype of DCV-negative JPS and compare it with DCV-positive JPS. Herein, we analyzed a cohort of 145 individuals with JPS from nine institutions, including both pediatric and adult centers. Data analyzed included age at diagnosis, family history, cancer history, need for colectomy/gastrectomy, and polyp number and location. Compared with DCV-positive JPS, DCV-negative JPS was associated with younger age at diagnosis (P &lt; 0.001), lower likelihood of having a family history of JPS (P &lt; 0.001), and a lower risk of colectomy (P = 0.032). None of the DCV-negative individuals had gastric or duodenal polyps, and polyp burden decreased after the first decade compared with DCV-positive JPS. Subgroup analysis between SMAD4 and BMPR1A carriers showed that SMAD4 carriers were more likely to have a family history of JPS and required gastrectomy. Taken together, these data provide the largest phenotypic characterization of individuals with DCV-negative JPS to date, showing that this group has distinct differences compared with JPS due to a SMAD4 or BMPR1A variant. Better understanding of phenotype and cancer risk associated with JPS both with and without a DCV may ultimately allow for individualized management of polyposis and cancer risk. Prevention Relevance: Juvenile Polyposis Syndrome (JPS) is a gastrointestinal cancer predisposition syndrome requiring lifelong surveillance, however there is limited data comparing individuals with and without a germline disease-causing variant in SMAD4 or BMPR1A. Herein we show that individuals with JPS without an underlying disease-causing variant have distinct phenotypic differences including lack of upper gastrointestinal polyps and lower rates of a family history of JPS, suggesting that a different approach to management may be appropriate in this population.

Purpose: CTNNA1 is a potential diffuse gastric cancer risk gene, however CTNNA1 testing on multigene panel testing (MGPT) remains unstudied. Methods: De-identified data from 151,425 individuals who underwent CTNNA1 testing at a commercial laboratory between October 2015 and July 2019 were reviewed. Tissue α-E-catenin immunohistochemistry was performed on CTNNA1 c.1351C>T (p. Arg451*) carriers. Results: Fifty-two individuals (0.03% tested) had CTNNA1 loss-offunction (LOF) variants and 1057 individuals (0.7% tested) had a total of 302 distinct missense variants of uncertain significance. Detailed history was available on 33 CTNNA1 LOF carriers, with 21 unique CTNNA1 LOF variants. Four (12%) individuals had diffuse gastric cancer and 22 (67%) had breast cancer. Six (21%) and 24 (83%) of the 29 families reported a history of gastric or breast cancer, respectively. The CTNNA1 c.1351C>T nonsense variant was identified in three separate families with early-onset diffuse gastric cancer or breast cancer. Immunohistochemistry showed decreased α-E-catenin expression in gastric cancers. Conclusion: CTNNA1 LOF variants are detected on MGPT with a majority of these individuals having gastric or breast cancer. The overall risk of gastric cancer for CTNNA1 LOF carriers may be lower than expected. Given the uncertain phenotype and penetrance, management of individuals with CTNNA1 LOF variants remains challenging.