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Patient derived xenograft models of small-cell lung cancer provide molecular insights into mechanisms of chemotherapy cross-resistance

Small Cell Lung Cancer (SCLC) is a highly aggressive neuroendocrine tumor with a 5% survival rate over 5 years. Though SCLC comprises 13% of all cases of lung cancer the median survival time of 14.5 months has seen little improvement over the last four decades. Standard treatment relies on DNA damaging agents such as Cisplatin/Etoposide (EP) which induce a high response rate of 60-70%. Despite this initial response, nearly all patients will relapse rendering first-line therapies ineffective. Furthermore, SCLC has been shown to develop chemotherapy cross-resistance in which resistance to first-line chemotherapies will confer resistance to additional DNA damaging agents thereby reducing treatment efficacy and duration of response. Cross-Resistance constitutes a major clinical issue whose underlying mechanisms remain a mystery.
The modest improvements in SCLC patient outcomes over the decades may be partially explained by the existing systems of study. Current methodologies of SCLC study rely on cell lines, patient samples, and Genetically Engineered Mouse Models which have little functional correlation to clinical outcomes. While few sources have proposed Patient Derived Xenograft (PDX) systems as an improved alternative, significant data remains sparse. Without a robust model system which accurately recapitulates patient outcomes, molecular pathways driving resistance cannot be uncovered. Here we present the generation of 34 SCLC PDX models which maintain both genomic and functional fidelity. Furthermore, treatment of a 30-model subset with first-line chemotherapy EP and a novel chemotherapy Olaparib/Temozolomide (OT) allowed for functional and molecular comparison between groups. Our findings demonstrate incomplete independent resistance mechanisms between EP and OT treatment with a small overlap of 31 genes involved in glycolysis and xenobiotic metabolism.

Identiferoai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/31262
Date24 July 2018
CreatorsMyers, David Thomas
ContributorsMacNeil, Maryann
Source SetsBoston University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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