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@PHDTHESIS{Gopisetty:294896,
      author       = {A. Gopisetty$^*$},
      title        = {{ITCC}-{P}4: {M}olecular characterization and multi-omics
                      analysis of pediatric patient tumor and {P}atient-{D}erived
                      {X}enograft ({PDX}) models for preclinical model selection},
      school       = {Universität Heidelberg},
      type         = {Dissertation},
      publisher    = {Heidelberg University Library},
      reportid     = {DKFZ-2024-02606},
      year         = {2024},
      note         = {Dissertation, Universität Heidelberg, 2023},
      abstract     = {Cancer persists as one of the prevailing causes of death in
                      children and adolescents aged 0 to 19 years. There remains
                      to be an unmet need for identification of therapeutic
                      biomarkers and better treatment interventions for these
                      patients. Advancements in state-of-the-art molecular
                      profiling techniques have resulted in better understanding
                      of pediatric cancers and their driver events. It has become
                      apparent that pediatric malignancies are significantly more
                      heterogeneous than previously thought as evidenced by the
                      number of novel entities and subtypes that have been
                      identified with distinct molecular and clinical
                      characteristics. For most of these newly recognized entities
                      there are currently extremely limited treatment options
                      available. Unfortunately, there is also a lack of compiled
                      and consistently analysed molecular data available, along
                      with limited data of characterization and documentation of
                      patient-derived models and/or genetic mouse models from
                      high-risk pediatric tumors. Both my studies fall under the
                      “Innovative Therapies for Children with Cancer Pediatric
                      Preclinical Proof-of-concept Platform” (ITCC-P4)
                      consortium which is an international collaboration between
                      different European academic institutes, several partnering
                      pharmaceutical companies and three contract research
                      organizations. The two studies aim to shed light on
                      identification of potential promising treatment options that
                      specifically match the patient’s specific molecular tumour
                      characteristics and the patient’s genetic data. Genetic
                      information at the molecular level from pediatric tumors in
                      relapsed patients has contributed to advancing our
                      understanding of disease progression and treatment
                      resistance. The first study overall aims to establish a
                      sustainable platform of >400 molecularly well- characterized
                      PDX models of high-risk pediatric cancers, including the
                      analysis of their original tumors and matching controls.
                      This will enable the selection of PDX models for in vivo
                      testing of novel mechanism-of-action based treatments.
                      Hence, facilitating the prioritization of pediatric drug
                      development and clinical stratification of patients across
                      entities. In a first batch, 251 models were fully
                      characterized, including 180 brain and 71 non- brain PDX
                      models, representing 112 primary models, 93 relapse, 42
                      metastasis and 4 progressions under treatment models. Using
                      low-coverage whole-genome and deep whole exome sequencing,
                      complemented with total RNA sequencing and methylation
                      analysis, the aim was to define genetic features in the
                      ITCC-P4 PDX cohort and assess the molecular fidelity of PDX
                      models compared to the original tumor. Based on DNA
                      methylation profiling 43 different tumor subgroups within 18
                      cancer entities were included. Mutational landscape analysis
                      identified key somatic and germline oncogenic drivers where
                      Ependymoma PDX models displayed the C11orf95-RELA fusion
                      event, YAP1, C11orf95 and RELA structural variants.
                      Medulloblastoma models were driven by MYCN, TP53, GLI2, SUFU
                      and PTEN. High-grade glioma samples showed TP53, ATRX, MYCN
                      and PIK3CA somatic SNVs, along with focal deletions in
                      CDKN2A in chromosome 9. Neuroblastoma models were enriched
                      for ALK SNVs and/or MYCN focal amplification, ATRX SNVs and
                      CDKN2A/B deletions. Sarcoma models displayed characteristic
                      alterations with PAX3-FOXO1 fusions detected in embryonal
                      rhabdomyosarcoma, along with TP53, CDKN2A, NRAS SNVs, NCOA1
                      gains, NF1 and CDK4 SVs. Ewing sarcoma PDX models displayed
                      the defining EWSR1-FLI1 gene fusion in most cases, along
                      with two rarer cases of EWSR1-ERG and EWSR1-FEV observed in
                      the cohort. Osteosarcomas were defined by highly unstable
                      genomes with large chromosomal alterations, TP53 and RB1
                      tumor suppressor genes were frequently altered and ATRX loss
                      and MYC gains were observed. Additional sarcomas such as
                      clear cell sarcoma of the kidney showed CDKN2A loss, MYC
                      gain, NF1 loss, TP53 mutations, while Synovial sarcoma
                      models were driven by SSX gene fusions and alterations.
                      Large chromosomal aberrations (deletions, duplications)
                      detected in the PDX models were concurrent with molecular
                      alterations frequently observed in each tumor type
                      –isochromosome 17 was detected in five medulloblastoma
                      models, while deletion of chromosome arm 1p or gain of parts
                      of 17q in neuroblastomas which correlate with tumor
                      progression. Tumor mutational burden across entities and
                      copy number analysis was performed to identify
                      allele-specific copy number events in tumor-normal pairs.
                      Clonal evolution of somatic variants was not only found in
                      certain PDX-tumor pairs but also between disease states.
                      Across the 16 serial model cases, discordance in targetable
                      SNV, SV and CNV, alterations were observed in later disease
                      progressed states compared to the primary models. The
                      multi-omics approach in this study provides insight into the
                      mutational landscape and patterns of the PDX models thus
                      providing an overview of molecular mechanisms facilitating
                      the identification and prioritization of oncogenic drivers
                      and potential biomarkers for optimal treatment. The second
                      study was a Target Actionability Review on replication
                      stress. Detrimental long-term side effects due to
                      chemotherapy drastically affect the lives of patients under
                      treatment, hence there is an urgent need to identify novel
                      target driven therapies. Decades of published data provide
                      evidence for targeting replication stress therapeutically.
                      Hence, in this study, we evaluated specific targets within
                      the replication stress response (RSR) pathway. A
                      comprehensive, well-structured, and critically evaluated
                      overview of literature related to replication stress across
                      16 pediatric solid malignancies was generated. The
                      methodology focuses on the systemic extraction and
                      structured evaluation of replication stress as a target.
                      This aims to align targeted anti- cancer therapeutic
                      interventions with specific cancer subtypes based on
                      clinical studies. ATR, ATM, PARP, WEEI were observed to
                      represent the most promising targets either using single
                      agents or in combination with chemotherapy or radiotherapy.
                      Evidence on CHK1 and DNA-PK although limited, showed
                      potential to further investigate these promising targets
                      over broader tumor types. The collective data and results
                      from both studies, the “ITCC-P4: Molecular
                      characterization and multi-omics analysis of Patient-Derived
                      Xenograft (PDX) models from high-risk pediatric cancer”
                      and the “Target actionability review on replication
                      stress”, can be explored further on the interactively
                      designed R2 platform, once users create an account to gain
                      access to the cohort data. (https://r2-itcc-p4.amc.nl/).},
      keywords     = {004 Data processing Computer science (Other) / 500 Natural
                      sciences and mathematics (Other) / 570 Life sciences
                      (Other)},
      cin          = {B062},
      cid          = {I:(DE-He78)B062-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.11588/HEIDOK.00034239},
      url          = {https://inrepo02.dkfz.de/record/294896},
}