Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): a cloud-based platform for curating and classifying germline variants.

Variant interpretation in the era of massively parallel sequencing is challenging. Although many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here, we present the Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE), a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in variant call format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4000 pediatric cancer patients and serves as a repository for the expert-reviewed results. PeCanPIE was originally developed for pediatric cancer but can be easily extended for use for nonpediatric cancers and noncancer genetic diseases. Although PeCanPIE's web-based interface was designed to be accessible to non-bioinformaticians, its back-end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

Germline Mutations in Predisposition Genes in Pediatric Cancer.

BACKGROUND: The prevalence and spectrum of predisposing mutations among children and adolescents with cancer are largely unknown. Knowledge of such mutations may improve the understanding of tumorigenesis, direct patient care, and enable genetic counseling of patients and families. METHODS: In 1120 patients younger than 20 years of age, we sequenced the whole genomes (in 595 patients), whole exomes (in 456), or both (in 69). We analyzed the DNA sequences of 565 genes, including 60 that have been associated with autosomal dominant cancer-predisposition syndromes, for the presence of germline mutations. The pathogenicity of the mutations was determined by a panel of medical experts with the use of cancer-specific and locus-specific genetic databases, the medical literature, computational predictions, and second hits identified in the tumor genome. The same approach was used to analyze data from 966 persons who did not have known cancer in the 1000 Genomes Project, and a similar approach was used to analyze data from an autism study (from 515 persons with autism and 208 persons without autism). RESULTS: Mutations that were deemed to be pathogenic or probably pathogenic were identified in 95 patients with cancer (8.5%), as compared with 1.1% of the persons in the 1000 Genomes Project and 0.6% of the participants in the autism study. The most commonly mutated genes in the affected patients were TP53 (in 50 patients), APC (in 6), BRCA2 (in 6), NF1 (in 4), PMS2 (in 4), RB1 (in 3), and RUNX1 (in 3). A total of 18 additional patients had protein-truncating mutations in tumor-suppressor genes. Of the 58 patients with a predisposing mutation and available information on family history, 23 (40%) had a family history of cancer. CONCLUSIONS: Germline mutations in cancer-predisposing genes were identified in 8.5% of the children and adolescents with cancer. Family history did not predict the presence of an underlying predisposition syndrome in most patients. (Funded by the American Lebanese Syrian Associated Charities and the National Cancer Institute.).

A hybrid method of correcting CBCT for proton range estimation with deep learning and deformable image registration.

Objective. This study aimed to develop a novel method for generating synthetic CT (sCT) from cone-beam CT (CBCT) of the abdomen/pelvis with bowel gas pockets to facilitate estimation of proton ranges.Approach. CBCT, the same-day repeat CT, and the planning CT (pCT) of 81 pediatric patients were used for training (n= 60), validation (n= 6), and testing (n= 15) of the method. The proposed method hybridizes unsupervised deep learning (CycleGAN) and deformable image registration (DIR) of the pCT to CBCT. The CycleGAN and DIR are respectively applied to generate the geometry-weighted (high spatial-frequency) and intensity-weighted (low spatial-frequency) components of the sCT, thereby each process deals with only the component weighted toward its strength. The resultant sCT is further improved in bowel gas regions and other tissues by iteratively feeding back the sCT to adjust incorrect DIR and by increasing the contribution of the deformed pCT in regions of accurate DIR.Main results. The hybrid sCT was more accurate than deformed pCT and CycleGAN-only sCT as indicated by the smaller mean absolute error in CT numbers (28.7 ± 7.1 HU versus 38.8 ± 19.9 HU/53.2 ± 5.5 HU;P≤ 0.012) and higher Dice similarity of the internal gas regions (0.722 ± 0.088 versus 0.180 ± 0.098/0.659 ± 0.129;P≤ 0.002). Accordingly, the hybrid method resulted in more accurate proton range for the beams intersecting gas pockets (11 fields in 6 patients) than the individual methods (the 90th percentile error in 80% distal fall-off, 1.8 ± 0.6 mm versus 6.5 ± 7.8 mm/3.7 ± 1.5 mm;P≤ 0.013). The gamma passing rates also showed a significant dosimetric advantage by the hybrid method (99.7 ± 0.8% versus 98.4 ± 3.1%/98.3 ± 1.8%;P≤ 0.007).Significance. The hybrid method significantly improved the accuracy of sCT and showed promises in CBCT-based proton range verification and adaptive replanning of abdominal/pelvic proton therapy even when gas pockets are present in the beam path.

Pre- and Posttherapy Risk Factors for Vasculopathy in Pediatric Patients With Craniopharyngioma Treated With Surgery and Proton Radiation Therapy.

PURPOSE: Vasculopathy (VAS) is a significant complication associated with radiation therapy in patients treated for brain tumors. We studied the type, location, severity, timing, and resolution of VAS in children with craniopharyngioma treated with proton radiation therapy (PRT) and evaluated predictors of stenosis (STN) using a novel patient and imaging-based modeling approach. METHODS AND MATERIALS: Children with craniopharyngioma (n = 94) were treated with 54 Gy relative biological effectiveness PRT in a clinical trial, NCT01419067. We evaluated VAS type, location, severity, and resolution. VAS events were segmented and related to their location, operative corridor, PRT dose, and vascular territory to facilitate mixed effect logistic regression modeling of spatial predictors of STN events. RESULTS: Forty-five (47.9%) patients had 111 instances of confirmed VAS (pre-PRT n = 37, 33.3%). The median time to post-PRT VAS was 3.41 years (95% confidence interval, 1.86-6.11). STN events were observed post-PRT in 23.4% (n = 22) of patients. Post-PRT VAS was detected by cerebral angiogram in 9.6% (n = 9), severe in 4.3% (n = 4), and compensated on perfusion in 2.1% (n = 2). Revascularization was required for 5 (5.3%) patients. Postsurgical, pre-PRT VAS, and PRT dose to unperturbed vessels were predictive of STN. The effect of PRT on STN was negligible within the surgical corridor. CONCLUSIONS: VAS often precedes PRT and was the strongest predictor of post-PRT STN. The adverse effect of PRT on STN was only apparent in unperturbed vasculature beyond the operative corridor.

Revised clinical and molecular risk strata define the incidence and pattern of failure in medulloblastoma following risk-adapted radiotherapy and dose-intensive chemotherapy: results from a phase III multi-institutional study.

BACKGROUND: We characterize the patterns of progression across medulloblastoma (MB) clinical risk and molecular subgroups from SJMB03, a Phase III clinical trial. METHODS: One hundred and fifty-five pediatric patients with newly diagnosed MB were treated on a prospective, multi-center phase III trial of adjuvant radiotherapy (RT) and dose-intense chemotherapy with autologous stem cell transplant. Craniospinal radiotherapy to 23.4 Gy (average risk, AR) or 36-39.6 Gy (high risk, HR) was followed by conformal RT with a 1 cm clinical target volume to a cumulative dose of 55.8 Gy. Subgroup was determined using 450K DNA methylation. Progression was classified anatomically (primary site failure (PSF) +/- distant failure (DF), or isolated DF), and dosimetrically. RESULTS: Thirty-two patients have progressed (median follow-up 11.0 years (range, 0.3-16.5 y) for patients without progression). Anatomic failure pattern differed by clinical risk (P = .0054) and methylation subgroup (P = .0034). The 5-year cumulative incidence (CI) of PSF was 5.1% and 5.6% in AR and HR patients, respectively (P = .92), and did not differ across subgroups (P = .15). 5-year CI of DF was 7.1% vs. 28.1% for AR vs. HR (P = .0003); and 0% for WNT, 15.3% for SHH, 32.9% for G3, and 9.7% for G4 (P = .0024). Of 9 patients with PSF, 8 were within the primary site RT field and 4 represented SHH tumors. CONCLUSIONS: The low incidence of PSF following conformal primary site RT is comparable to prior studies using larger primary site or posterior fossa boost volumes. Distinct anatomic failure patterns across MB subgroups suggest subgroup-specific treatment strategies should be considered.