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Title:Micro-nano scale diagnostics and therapeutic platforms for personalized medicine
Author(s):Ganguli, Anurup
Director of Research:Bashir, Rashid
Doctoral Committee Chair(s):Bashir, Rashid
Doctoral Committee Member(s):Cunningham, Brian; Smith, Andrew; Clare, Susan
Department / Program:Bioengineering
Discipline:Bioengineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Personalized medicine
Cancer drug screening
hanging drop culture
3D organoid culture
molecular analysis
spatial gene expression analysis
tissue analysis
point-of-care diagnostics
lab on a chip
blood based diagnostics
infectious disease diagnostics
zika virus
Dengue virus
smartphone
Abstract:Personalized medicine can be defined as the use of the combined knowledge (molecular analysis and symptoms) about an individual to predict disease susceptibility, disease prognosis, or treatment response and thereby improve that person's health. The goal is to perform specific analyses of the patient’s sample and other conventionally used indicators for creating an individualized treatment response for the patient that would yield better outcomes. In cancer, the approach of personalized medicine is to analyze the patient’s tumor biopsy for genetic mutations and gene expression alterations and use this data to provide targeted drugs specifically for that patient’s alterations. However, there are a significant number of cases where genomic analysis currently fails to identify effective drugs or applicable clinical trials. Towards this, intratumor heterogeneity represents a major obstacle to effective cancer treatment and personalized medicine as currently, cancer diagnosis is performed on biopsies of a small region of a tumor, which may not necessarily provide representative biological information for the tumor as a whole. Therefore, there is a need for platforms that can provide insights into this intratumor heterogeneity in a clinical setting and elucidate the spatial sub-clonal architecture within a tumor at a molecular level. In this thesis, we present a platform that performs spatial gene expression analysis on a tumor tissue section using a microchip and provides the spatial map of target mRNA biomarker in less than 2 hours. The microchip allows for on-chip picoliter real-time reverse transcriptase loop mediated isothermal amplification (RT-LAMP) reactions on a histological tissue section without any analyte purification while preserving the native spatial location of the nucleic acid molecules. A major challenge towards this goal was to perform automated microdissection of the tissue on the microchip while preserving the spatial orientation. This was solved by engineering the chip design to have knife-like individual well edges and developing a novel tissue pixelation protocol. In the other subset of cases, where the molecular analysis of tumor biopsy does identify targetable genomic alterations, patients do not always respond to therapy. For such cases, strategies to confirm therapeutic efficacy of drug candidates or identify additional drug options would be beneficial to both clinicians and patients. In these cases, the approach of personalized medicine is to use the patient’s tumor biopsy sample to form and culture tumor organoids using a compatible three-dimensional culture platform and downstream perform empirical drug testing on these organoids to yield the best possible drug candidate for the patient. In this thesis, we also present a high throughput hanging drop 3D culture platform, performed on a microchip, with potential applications in cancer drug screening. We also explore the utility of other micro-nano scale biosensing and diagnostic platforms in enabling personalized medicine. Towards this, we demonstrate a label free ion-sensitive field effect transistor (ISFET) based microRNA sensing platform where we show robust detection of Let 7b microRNA, which is a biomarker for human lung, breast and prostate cancer, using a million transistors on a single chip. We have also explored the application of biosensing platforms for personalized medicine in infectious diseases. In this thesis, we demonstrate a point-of-care biosensing platform that can detect zika virus directly from a whole blood sample using real-time reverse-transcription loop-mediated isothermal amplification (RT-LAMP) and a smartphone-based imaging setup.
Issue Date:2019-07-11
Type:Text
URI:http://hdl.handle.net/2142/105918
Rights Information:Copyright 2019 Anurup Ganguli
Date Available in IDEALS:2019-11-26
Date Deposited:2019-08


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