The development and translational potential of therapeutic strategies for cancer is limited, in part, by a lack of biological
models that capture important aspects of tumor growth and treatment response. It is also becoming increasingly evident
that no single treatment will be curative for this complex disease. Rationally-designed combination regimens that impact
multiple targets provide the best hope of significantly improving clinical outcomes for cancer patients. Rapidly
identifying treatments that cooperatively enhance treatment efficacy from the vast library of candidate interventions is
not feasible, however, with current systems. There is a vital, unmet need to create cell-based research platforms that
more accurately mimic the complex biology of human tumors than monolayer cultures, while providing the ability to
screen therapeutic combinations more rapidly than animal models. We have developed a highly reproducible in vitro
three-dimensional (3D) tumor model for micrometastatic ovarian cancer (OvCa), which in conjunction with quantitative
image analysis routines to batch-process large datasets, serves as a high throughput reporter to screen rationally-designed
combination regimens. We use this system to assess mechanism-based combination regimens with photodynamic
therapy (PDT), which sensitizes OvCa to chemo and biologic agents, and has shown promise in clinic trials. We show
that PDT synergistically enhances carboplatin efficacy in a sequence dependent manner. In printed heterocellular
cultures we demonstrate that proximity of fibroblasts enhances 3D tumor growth and investigate co-cultures with
endothelial cells. The principles described here could inform the design and evaluation of mechanism-based therapeutic
options for a broad spectrum of metastatic solid tumors.
Cell-based biosensors (CBBs) have important applications in biosecurity and rapid diagnostics. Current CBB
technologies have challenges including cell immobilization on the sensors, high throughput fabrication and portability,
and rapid detection of responses to environmental changes. We address these challenges by developing an integrated
CBB platform that merges cell printing technology, a lensless charge-coupled device (CCD) imaging system, and
custom-developed cell image processing software. Cell printing was used to immobilize cells within hydrogel droplets
and pattern these droplets on a microfluidic chip. The CCD was used to detect the morphological response of the
immobilized cells to external stimuli (e.g., environmental temperature change) using lensless shadow images. The
morphological information can be also detected by sensing a small disturbance in cell alignment, i.e., minor alignment
changes of smooth muscles cells on the biosensors. The automatic cell alignment quantification software was used to
process the cell images (microscopic image was used as an example) and calculate the cell orientation in seconds. The
same images were also manually processed as a control to validate and characterize the integrated platform functionality.
The results showed software can measure the cell morphology (i.e., orientation) in an automated way without the need
for labeling (e.g., florescent staining). Such an integrated CBB system will allow fabrication of CBBs at high throughput
as well as rapidly monitor and measure morphological cellular responses.
The World Health Organization (WHO) is rapidly expanding antiretroviral treatment (ART) in sub-Saharan countries.
However, virological failure of ART is rarely monitored due to the lack of affordable and sustainable viral load assays
suitable for resource-limited settings. Here, we report a prototype of a rapid virus detection method based on
microfluidic technologies. In this method, HIV-1 particles from 10 μL whole blood were captured by anti-gp120
antibody coated on the microchannel surface and detected by dual fluorescence signals under microscopy. Next,
captured HIV-1 particles were counted using the free software, ImageJ (http://rsbweb.nih.gov/ij/). This rapid HIV-1
detection method has potential to be further developed for viral load monitoring at resource-limited settings.
Sepsis causes 9.3% of overall deaths in United States. To diagnose sepsis, cell/bacteria capture and culturing methods
have been widely investigated in the medical field. Escherichia Coli (E. Coli) is used as a model organism for sepsis in
blood stream since wide variety of antibodies are established and the genetic modification process is well documented
for fluorescent tagging. In point-of-care testing applications, the sepsis diagnostics require fast monitoring, inexpensive
testing, and reliable results at resource limited settings, i.e. battle field, home care for dialysis. However, the cell/E.coli
are hard to directly capture and see at the POCT because of the small size, 2 μm long and 0.5 μm in diameter, and the
bacteria are rare in the blood stream in sepsis. Here, we propose a novel POCT platform to image and enumerate
cell/E.coli on a microfluidic surface to diagnose sepsis at resource limited conditions. We demonstrate that target cells
are captured from 5 μl of whole blood using specific antibodies and E.coli are imaged using a lens-free imaging
platform, 2.2 μm pixel CMOS based imaging sensor. This POCT cell/bacteria capture and enumeration approach can
further be used for medical diagnostics of sepsis. We also show approaches to rapidly quantify white blood cell counts
from blood which can be used to monitor immune response.
We demonstrate a cell based detection system that could be used for monitoring an underwater target volume and environment using a microfluidic chip and charge-coupled-device (CCD). This technique allows us to capture specific cells and enumerate these cells on a large area on a microchip. The microfluidic chip and a lens-less imaging platform were then merged to monitor cell populations and morphologies as a system that may find use in distributed sensor networks. The chip, featuring surface chemistry and automatic cell imaging, was fabricated from a cover glass slide, double sided adhesive film and a transparent Polymethlymetacrylate (PMMA) slab. The optically clear chip allows detecting cells with a CCD sensor. These chips were fabricated with a laser cutter without the use of photolithography. We utilized CD4<sup>+</sup> cells that are captured on the floor of a microfluidic chip due to the ability to address specific target cells using antibody-antigen binding. Captured CD4<sup>+</sup> cells were imaged with a fluorescence microscope to verify the chip specificity and efficiency. We achieved 70.2 ± 6.5% capturing efficiency and 88.8 ± 5.4% specificity for CD4<sup>+</sup> T lymphocytes (n = 9 devices). Bright field images of the captured cells in the 24 mm × 4 mm × 50 μm microfluidic chip were obtained with the CCD sensor in one second. We achieved an inexpensive system that rapidly captures cells and images them using a lens-less CCD system. This microfluidic device can be modified for use in single cell detection utilizing a cheap light-emitting diode (LED) chip instead of a wide range CCD system.