Akıllı malzemeler entegre edilen mikroakışkan çiplerde biyomoleküllerin ve nadir kanser hücrelerinin yakalanması ve salınması

Prevalent clinical conditions are impacting notably on our daily lives and the global economy. Healthcare system is hence garnering more interest in developing innovative material-based technologies along with accurate surface chemistry and signal generation reactions to measure biomarkers for disease diagnosis. In particular, biomedical studies focus to diagnose complex cases such as cancer. For instance, there are some critical stages in cancer development and metastasis. Moreover, impractical, invasive methods, and the restricted repertoire of targeted therapies are driving factors for researchers to find out new monitoring techniques that anticipate the future journey of cancer cells. On the other hand, the analysis of bodily fluids containing circulating tumor cells (CTCs) and biomarkers allows more insight into detecting/monitoring cancer as early as possible, and it would provide more information than that of any single-site biopsies. Yet, implementing the current technologies focusing on CTC detection and isolation in the clinics have notable challenges, i.e., expensive reagents/assays, complex operation, lengthy processes, bio-compatibility, and the need for specialized personnel. In this thesis, we have designed a microfluidic chip to hurdle these existing challenges, and for this regard, we tuned the surface area of the chip by integrating bio-mimetic smart materials (different shapes of silica particles-coated with poly(N -isopropylacrylamide). Initially, we tested our strategy with model proteins for both capture and release aspects. The smart materials were then modified with anti-EpCAM antibodies to capture human breast cancer cells (MCF-7) as a cancer model. Once the cells were captured in the chip, they were released by simply altering the 3-dimensional structure of smart materials above to lower critical solution temperature. Herein, we have anticipated that the developed platform would resolve cost, bio-compatibility, applicability, complexity, and assay duration-related challenges of current technologies in this realm.