Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Gene expression profiling of drug-tolerant persister BT474 breast cancer cells derived from lapatinib treatment


ABSTRACT: Acquired drug resistance prevents targeted cancer therapy from achieving stable and complete responses. Emerging evidence implicates a key role for nonmutational mechanisms including changes in cell state during early stages of acquired drug resistance. Targeting nonmutational resistance may therefore present a therapeutic opportunity to eliminate residual surviving tumor cells and impede relapse. A variety of cancer cell lines harbor quiescent, reversibly drug-tolerant “persister” cells which survive cytotoxic drugs including targeted therapies and chemotherapies. These persister cells survive drug through nonmutational mechanisms which are poorly understood. Specifically targeting persister cells is a promising strategy to prevent tumor relapse. We sought to identify therapeutically exploitable vulnerabilities in persister cells using the HER2-amplified breast cancer line BT474 as an experimental model. Similar to other persister cell models, upon treatment with the HER2 inhibitor lapatinib (2uM concentration) for nine or more days, the majority of BT474 cells die, revealing a small population of quiescent surviving persister cells. Removal of lapatinib allows the persister cells to regrow and to re-acquire sensitivity to lapatinib. Subsequent lapatinib treatment re-derives persister cells. The reversibility of persister cell drug resistance indicates a nonmutational resistance mechanism. Here we provide RNAseq gene expression profiling data generated from parental BT474 cells compared to BT474 persister cells generated from nine days of treatment with 2 uM lapatinib. These data can be used to identify genes and pathways which are upregulated in persister cells, revealing potential therapeutic targets. 3 biological replicates of BT474 persister cells, two biological replicates of BT474 parental cells

ORGANISM(S): Homo sapiens

SUBMITTER: Matthew Hangauer 

PROVIDER: E-GEOD-84896 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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