title: ITCC-P4: Molecular characterization and multi-omics analysis of pediatric patient tumor and Patient-Derived Xenograft (PDX) models for preclinical model selection
creator: Gopisetty, Apurva
subject: ddc-004
subject: 004 Data processing Computer science
subject: ddc-500
subject: 500 Natural sciences and mathematics
subject: ddc-570
subject: 570 Life sciences
description: 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/).
date: 2024
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/34239/1/ApurvaGopisetty_PhD_Dissertation.pdf
identifier: DOI:10.11588/heidok.00034239
identifier: urn:nbn:de:bsz:16-heidok-342390
identifier:   Gopisetty, Apurva  (2024) ITCC-P4: Molecular characterization and multi-omics analysis of pediatric patient tumor and Patient-Derived Xenograft (PDX) models for preclinical model selection.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/34239/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng