Study of the 3D ROT biochip on drug effect for lung cancer cell

  • 吳 哲華

Student thesis: Master's Thesis


Molecular-targeted therapeutics for cancer bring hope to patients providing higher efficacy and lower toxicity than conventional treatment However the benefit of the target drug in the treatment of lung cancer will be limited unless the patients would be screen properly For instance the lung cancer patients with Epidermal Growth Factor Receptor (EGFR)-activating gene mutations have a better prognostic and longer medium survival time than the patients without mutations under EGFR tyrosine kinase inhibitor (TKI) treatments Thus EGFR mutation test is now the standard protocol for EGFR TKI treatment in lung cancer patient The traditional EGFR mutation tests such as DNA sequencing PCR and IHC are relatively expensive and time-consuming Here we try to improve drug susceptibility test by using the on-chip electrokinetics assay combining with image analyzing system to create a novel detecting platform In this thesis two subjects will be discussed (1) Optimization of the 3D ROT biochip There are many problems in the traditional ROT technology For example the cell could not be rotated in the center of electrodes when the frequency of ROT signal increased and the axis of rotation was not fixed These reasons caused the unreliable ROT spectrum Therefore we developed a novel ROT technique to solve these problems After optimizing the parameters the cell could be rotated stably in the whole frequency range (2) Dielectrophoresis-based drug susceptibility test In the second part the application of ROT on rapid diagnosis of EGFR TKI susceptibility in lung cancer was tested In the susceptible lung cancer cell lines significant changes in ROT behavior can be observed In contrast the resistant cell lines there was no significant changes in ROT behavior In summary the techniques of electrokinetics microfluidics and the image analyzing system were integrated into this novel platform for rapidly detecting cancer cell drug sensitivity
Date of Award2014 Aug 20
Original languageEnglish
SupervisorHsien-Chang Chang (Supervisor)

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