Browsing by Subject "Multi-OMICS"

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    Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors
    (MDPI, 2022-12-30) Pandya, Pankita H.; Jannu, Asha Jacob; Bijangi-Vishehsaraei, Khadijeh; Dobrota, Erika; Bailey, Barbara J.; Barghi, Farinaz; Shannon, Harlan E.; Riyahi, Niknam; Damayanti, Nur P.; Young, Courtney; Malko, Rada; Justice, Ryli; Albright, Eric; Sandusky, George E.; Wurtz, L. Daniel; Collier, Christopher D.; Marshall, Mark S.; Gallagher, Rosa I.; Wulfkuhle, Julia D.; Petricoin, Emanuel F.; Coy, Kathy; Trowbridge, Melissa; Sinn, Anthony L.; Renbarger, Jamie L.; Ferguson, Michael J.; Huang, Kun; Zhang, Jie; Saadatzadeh, M. Reza; Pollok, Karen E.; Pediatrics, School of Medicine
    Establishment of clinically annotated, molecularly characterized, patient-derived xenografts (PDXs) from treatment-naïve and pretreated patients provides a platform to test precision genomics-guided therapies. An integrated multi-OMICS pipeline was developed to identify cancer-associated pathways and evaluate stability of molecular signatures in a panel of pediatric and AYA PDXs following serial passaging in mice. Original solid tumor samples and their corresponding PDXs were evaluated by whole-genome sequencing, RNA-seq, immunoblotting, pathway enrichment analyses, and the drug−gene interaction database to identify as well as cross-validate actionable targets in patients with sarcomas or Wilms tumors. While some divergence between original tumor and the respective PDX was evident, majority of alterations were not functionally impactful, and oncogenic pathway activation was maintained following serial passaging. CDK4/6 and BETs were prioritized as biomarkers of therapeutic response in osteosarcoma PDXs with pertinent molecular signatures. Inhibition of CDK4/6 or BETs decreased osteosarcoma PDX growth (two-way ANOVA, p < 0.05) confirming mechanistic involvement in growth. Linking patient treatment history with molecular and efficacy data in PDX will provide a strong rationale for targeted therapy and improve our understanding of which therapy is most beneficial in patients at diagnosis and in those already exposed to therapy.