Deep Learning and Multidisciplinary Imaging in Pediatric Surgical Oncology: A Scoping Review.

Background: Medical images play an important role in diagnosis and treatment of pediatric solid tumors. The field of radiology, pathology, and other image-based diagnostics are getting increasingly important and advanced. This indicates a need for advanced image processing technology such as Deep Learning (DL).

Prognostic Value of Molecular Aberrations in Low- or Intermediate-Risk Neuroblastomas: A Systematic Review.

Background: The 5-year prognosis of non-high-risk neuroblastomas is generally good (>90%). However, a proportion of patients show progression and succumb to their disease. We aimed to identify molecular aberrations (not incorporated in the current risk stratification) associated with overall survival (OS) and/or event-free survival (EFS) in patients diagnosed with non-high-risk neuroblastoma.

M&M: an RNA-seq based pan-cancer classifier for paediatric tumours.

Background: With many rare tumour types, acquiring the correct diagnosis is a challenging but crucial process in paediatric oncology. Historically, this is done based on histology and morphology of the disease. However, advances in genome wide profiling techniques such as RNA sequencing now allow the development of molecular classification tools.

A germline PDGFRB splice site variant associated with infantile myofibromatosis and resistance to imatinib.

Purpose: Infantile myofibromatosis is characterized by the development of myofibroblastic tumors in young children. In most cases, the disease is caused by somatic gain-of-function variants in platelet-derived growth factor (PDGF) receptor beta (PDGFRB). Here, we reported a novel germline intronic PDGFRB variant, c.

Divergent WNT signaling and drug sensitivity profiles within hepatoblastoma tumors and organoids.

Hepatoblastoma, the most prevalent pediatric liver cancer, almost always carries a WNT-activating CTNNB1 mutation, yet exhibits notable molecular heterogeneity. To characterize this heterogeneity and identify novel targeted therapies, we perform comprehensive analysis of hepatoblastomas and tumor-derived organoids using single-cell RNA-seq/ATAC-seq, spatial transcriptomics, and high-throughput drug profiling. We identify two distinct tumor epithelial signatures: hepatic 'fetal' and WNT-high 'embryonal', displaying divergent WNT signaling patterns.