Single-cell transcriptomics identifies potential cells of origin of MYC rhabdoid tumors

Rhabdoid tumors (RT) are rare and highly aggressive pediatric neoplasms. Their epigenetically-driven intertumoral heterogeneity is well described; however, the cellular origin of RT remains an enigma. Here, we establish and characterize different genetically engineered mouse models driven under the control of distinct promoters and being active in early progenitor cell types with diverse embryonic onsets. From all models only Sox2-positive progenitor cells give rise to murine RT. Using single-cell analyses, we identify distinct cells of origin for the SHH and MYC subgroups of RT, rooting in early stages of embryogenesis. Intra- and extracranial MYC tumors harbor common genetic programs and potentially originate from fetal primordial germ cells (PGCs). Using PGC specific Smarcb1 knockout mouse models we validate that MYC RT originate from these progenitor cells. We uncover an epigenetic imbalance in MYC tumors compared to PGCs being sustained by epigenetically-driven subpopulations. Importantly, treatments with the DNA demethylating agent decitabine successfully impair tumor growth in vitro and in vivo. In summary, our work sheds light on the origin of RT and supports the clinical relevance of DNA methyltransferase inhibitors against this disease

Liver transplantation as a potentially lifesaving measure in neuroblastoma stage 4S

Neuroblastoma (NBL) stage 4s is an incompletely understood phenomenon with variable clinical course. While the majority of patients may undergo spontaneous regression and achieve complete resolution without intensive therapy, a small proportion is at increased risk of developing secondary complications. One such situation is liver insufficiency due to diffuse metastases. We report a patient suffering from NBL 4S who required double lifesaving liver transplantation. Abdominal and respiratory complications due to hepatomegaly are crucial determinants for treatment intensity and duration in 4S NBL [1,2]. We provide an algorithm in order to facilitate the clinical decision when dealing with similar potentially life-threatening events