Multiplexed drug testing of micro-dissected tumors using a microfluidic platform with integrated electrochemical aptasensors

摘要：将电化学生物传感器与微电子技术相结合，为生物传感器的研究提供了一条独特的途径

ABSTRACT: The integration of electrochemical biosensors with microelectronics offers a unique avenue for miniaturized, low-cost systems that merge biomolecular sensing with digital computing, programming, and communication. Here we propose to integrate electrochemical aptamer-based sensors (“aptasensors”) into a microfluidic multi-well platform to enable multi-time-point, highly parallel readouts of cell death and cytokine secretion from intact tumor biopsies during and after drug treatment. Our platform will allow for gathering the large amounts of molecular data that are needed for machine learning approaches to drug testing. Cancer drug testing – a central process in cancer drug development and personalized oncology – is often inaccurate and inefficient because it typically relies on studies in cell cultures or animals that lack the human tumor microenvironment (TME). Only <4% of cancer drugs out of the ~1,000 drugs in clinical trials each year pass the safety and efficacy tests; more than half of the failures are due to lack of efficacy. Hence, on average, bringing a drug to market takes >10 years and costs >$1 billion, often resulting in high prices for the drugs. In the last decade, technologies such as patient-derived organoids and organs-on-chips have brought some hope. However, these approaches have much lower throughput than traditional cell cultures and are generally unable to fully recreate the TME of an intact tissue. These limitations are a fundamental hurdle for the personalization of therapies which often need to be customized to the unique TME of the patient, and also for the development of combination immunotherapies, which target the TME and are exponentially increasing in number. Thus, a different paradigm for drug testing that preserves the human TME is critically needed to help transition oncology into a stage of more affordable and rapidly evolving treatments. The Folch and Gujral labs have developed an intact-tissue microfluidic drug testing platform based on regularly- sized, cuboidal-shaped microdissected tissues (referred to as “cuboids”) that are mechanically cut with a tissue chopper. In under an hour, more than 10,000 cuboids (~400 µm-wide) can be produced from ~1 cm3 of solid tumor. The cuboids are never dissociated and retain much of the native TME (e.g. immune cells and microvasculature). The platform is a user-friendly multi-well device that can microfluidically trap and selectively treat a large array of cuboids. Here we propose to integrate electrochemical aptasensors into our cuboids platform to enable the automated, multi-time-point monitoring of secreted compounds (cytokines or cell death indicators) within the wells and the straightforward implementation of electrical readouts from large cuboid arrays. As a proof of concept, we will use cuboids from mouse tumors and patient samples in a 96-well format. We will use a mouse model and patient samples of colorectal cancer (CRC) liver metastases. Using machine learning techniques, we will implement a proof-of-concept drug screen on mouse cuboids and a proof-of-concept combination immunotherapy drug evaluation on patient cuboids.