4.6 Article

Stepwise molecular mechanisms responsible for chemoresistance in bladder cancer cells

Journal

CELL DEATH DISCOVERY
Volume 8, Issue 1, Pages -

Publisher

SPRINGERNATURE
DOI: 10.1038/s41420-022-01242-8

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Funding

  1. National Research Foundation of Korea (NRF) - Korea government [2020R1A2C1007356, 2022R1A2C1012173]
  2. National Research Foundation of Korea [2020R1A2C1007356, 2022R1A2C1012173] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study establishes a gemcitabine-resistant bladder cancer cell line to investigate the molecular mechanisms of chemoresistance. The analysis of gene expression profiles reveals a multigene signature and a chemoresistance score that can predict the responsiveness to gemcitabine treatment. These findings are important for predicting chemoresistance and improving the prognosis of bladder cancer patients.
Chemotherapy resistance is an obstacle to cancer therapy and is considered a major cause of recurrence. Thus, understanding the mechanisms of chemoresistance is critical to improving the prognosis of patients. Here, we have established a stepwise gemcitabine-resistant T24 bladder cancer cell line to understand the molecular mechanisms of chemoresistance within cancer cells. The characteristics of the stepwise chemoresistance cell line were divided into 4 phases (parental, early, intermediate, and late phases). These four phase cells showed increasingly aggressive phenotypes in vitro and in vivo experiments with increasing phases and revealed the molecular properties of the biological process from parent cells to phased gemcitabine-resistant cell line (GRC). Taken together, through the analysis of gene expression profile data, we have characterized gene set of each phase indicating the response to anticancer drug treatment. Specifically, we identified a multigene signature (23 genes including GATA3, APOBEC3G, NT5E, MYC, STC1, FOXD1, SMAD9) and developed a chemoresistance score consisting of that could predict eventual responsiveness to gemcitabine treatment. Our data will contribute to predicting chemoresistance and improving the prognosis of bladder cancer patients.

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