SBIR/STTR Research Award
Microfluidic system for complete and automated dissociation of tumor tissue into single cells
Award amount
$311,322Program and phase
SBIR · Phase IAward year
2022Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- Kino Discovery, Inc.
- Proposal award date
- 2022-09-01
- Contract end date
- 2023-08-31
- UEI
- E3HTXJ13CYN5
- Solicitation number
- PA21-259
- Topic code
- 100
Research abstract
ABSTRACT
Solid tumors contain diverse cellular ecosystems, and this heterogeneity has been implicated as a key factor
driving disease progression, metastasis, and drug resistance. Hence, identifying the presence and function of
each cell subtype is needed to fully understand tumor drivers and guide therapeutic decisions. Increasingly,
single cell analysis methods are being used to define cellular subsets within tumors to address biological and
therapeutic questions. A method that is rapidly emerging is single cell RNA sequencing (scRNA-seq), which
enables identification of cell type and function based on the transcriptome. However, tumor tissue must first be
converted into single cells, and this step is a critical barrier to more widespread use of single cell analysis
methods, particularly in clinical settings. Standard tissue dissociation protocols involve several manual steps
that are slow, inefficient, and highly variable. Commercial systems only accomplish part of the workflow and
are not well-characterized. In previous work, we developed novel microfluidic digestion, dissociation, and
filtration devices that utilized hydrodynamic forces to break down tissue into single cells. We recently combined
the devices into a platform and attained excellent results for various murine tissues, including breast tumors.
Specifically, the device platform significantly enhanced single cell recovery and decreased cell subtype biasing.
To date, these devices have not been applied to human tumor specimen. In this proposal, we will develop a
powerful tumor dissociation platform that can perform the entire workflow in a fast, efficient, and gentle manner.
We will focus on creating a prototype benchtop fluidic system that contains all of the necessary components
(i.e. pumps, valves, monitoring capabilities, control software) to operate the microfluidic cartridges in an optimal
and automated manner. We will first create the system and perform basic feasibility and quality control tests.
We will then optimize performance of the fluidic system and microfluidic cartridges using a murine breast tumor
model, with single cells analyzed by flow cytometry and scRNA-seq. As part of this work, we will also increase
tissue sample size so that entire tumor resections can be processed. Finally, we will perform a small validation
study using human breast tumor specimens. The Specific Aims for this 6 month project include (1) create the
prototype fluidic system, (2) optimize fluidic system using murine tumor tissue, and (3) validate performance
using human breast tumor specimen. The single cell analysis market is expected to grow robustly, driven by
growing biotechnology and pharmaceutical industries, rise in single cell genomics, and applicability to cancer
for basic research and personalized medicine. Our microfluidic dissociation technologies are poised to make a
significant impact on the single cell analysis of tumor tissues by making it easier and more reliable to prepare
samples. There is minimal competition at this time, and we are positioned to offer the only solution that can
perform all tasks in the tissue processing workflow and, most importantly, achieve performance metrics that
cannot be matched. A portfolio containing 7 patents that have issued or are pending is currently being licensed
by Kino Discovery. The research plan was directly informed by extensive marketing discussions with leading
pharmaceutical, biotechnology, and life science companies through a microfluidic-based center at UC Irvine
and the MedTech Innovator BioTools program.
Technology keywords
Not reported
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