APPLICATION OF STRUCTURAL, MOLECULAR, AND PROTOEMIC STUDIES TO INVESTIGATE ON-TARGET AND OFF-TARGET MECHANISMS OF LORLATINIB RESISTANCE IN ALK DRIVEN NEUROBLASTOMA
Degree type
Graduate group
Discipline
Biology
Bioinformatics
Subject
Kinase Inhibitors
Neuroblastoma
Pediatric Oncology
Proteomics
Structural Biology
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Contributor
Abstract
Pediatric cancers are the second leading cause of deaths in children after accidents. The last few decades have seen tremendous improvement in cancer patient survival because of development of targeted therapies. In neuroblastoma, a common childhood cancer, approval of anti-GD2 immune therapy has improved patient survival and discovery of anaplastic lymphoma kinase (ALK) receptor activating mutations and amplification has provided hope to further increase of patient survival. Despite this success and that of precision medicine at large, patients treated with ALK inhibitor lorlatinib have developed resistance, a common problem with targeted therapy. The future of cancer treatments and improvement of therapies relies on current studies of mechanisms of resistance to targeted therapy. Understanding tumor heterogeneity and metastasis related to neoplastic nature of cancer and changes caused by treatment will help us develop more rational therapies. In this thesis, I discuss models and techniques used to study on-target and off-target mechanisms of lorlatinib resistance in neuroblastoma. In the first and second chapter of this thesis, I describe how we applied structural biology along with cell based assays and patient derived xenograft models (PDX) to uncover mechanism of on-target resistance caused by acquired secondary mutations in ALK kinase domain. In the third chapter, I describe how we applied transcriptomic and proteomics methods to elucidate potential mechanism of ALK independent, or off-target resistance to lorlatinib in resistant neuroblastoma PDX. These studies highlight the importance of application and integration of biologically relevant cancer models like PDXs and large scale studies ranging from structural biology to -omics platforms to understand cancer resistance and develop better therapies to patients.
Advisor
Radhakrishnan, Ravi