Anna Petrovskis, Betty Bekemeier, Jenna van Draanen, Elizabeth Heitkemper
Grouping Public Health Skills to Facilitate Workforce Development: A Factor Analysis of PH WINS
Journal of public health management and practice : JPHMP
glioblastoma multiforme gbm remains particularly difficult cancer treat survival outcomes remain poor addition lack dedicated drug discovery programs gbm extensive intratumor heterogeneity epigenetic plasticity related cellstate transitions major roadblocks successful drug therapy gbm study phenomenon publicly available snrnaseq bulk rnaseq data patient samples used categorize cells patients four cell states ie phenotypes namely neural progenitorlike npclike ii oligodendrocyte progenitorlike opclike iii astrocytelike aclike iv mesenchymallike meslike patients subsequently grouped subpopulations based cellstate dominant respective tumor incorporating phosphoproteomic measurements patients proteinprotein interaction network ppin constructed cell state fourcell state ppins pooled form single boolean network used silico protein knockout simulations investigate mechanisms either promote prevent cell state transitions simulation results input boosted tree machine learning model predicted cell states phenotypes gbm patients independent public data source glioma longitudinal analysis glass consortium combining simulation results machine learning predictions generated hypotheses clinically relevant causal mechanisms cell state transitions example transcription factor tfap2a seen promote transition npclike meslike state protein nodes associated signaling pathways provide potential drug targets tested vitro support cell statedirected csd therapy