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Ultra-high content analyses of circulating and solid tumor cells: A diagnostic reference system for disease burden

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 4R44CA250861-02
Agency Tracking Number: R44CA250861
Amount: $1,689,915.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 102
Solicitation Number: PA20-260
Timeline
Solicitation Year: 2020
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-09-14
Award End Date (Contract End Date): 2024-08-31
Small Business Information
2657 MONROEVILLE BOULEVARD
Monroeville, PA 15146-2301
United States
DUNS: 078362963
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 MICHEL NEDERLOF
 (412) 389-2083
 nederlofontheroad@mac.com
Business Contact
 MICHEL NEDERLOF
Phone: (412) 389-2083
Email: nederlofontheroad@mac.com
Research Institution
N/A
Abstract

ABSTRACT
We propose to create a modular suite of products to facilitate highly multiplexed imaging and quantita-
tive analyses of individual cells in intact tissue, and cells circulating in blood to be used to establish
disease status. Our imaging software analyses platform supporting interactive data visualization will
connect protein-based cellular features between tissue resident cells and disseminated cells to lever-
age mechanisms of cancer cell dissemination to detect disease earlier, to identify risk for metastases,
and to track response to treatment. Our goal is to develop an imaging software analyses platform,
biomarker panels for highly multiplexed imaging using cyclic immunostaining and a newly discovered
tumor cell population for translation to clinical assay development. Our suite of products will fill an unmet
clinical need as no visual platforms exist that can link analyses of individual highly metastatic cells
poised to escape the primary tumor with their disseminated counterparts in blood to inform disease
status. Our technology has translational impact in developing a non-invasive biomarker for prognosti-
cation and for monitoring treatment response in cancer patients. To ensure successful development of
a visualization platform with translational potential, we will extend our close partnership with Oregon
Health and Science University (OHSU) and strong collaborations at the Knight Cancer Institute for
biologic analyses with translation to patient care. We will leverage a novel disseminated tumor popula-
tion (i.e., circulating hybrid cells [CHCs]), discovered at OHSU, and a novel cyclic immunofluorescence
(cyCIF) technology based on oligonucleotide conjugated antibodies. Currently, little functionality exists
to optimally extract the wealth of phenotypic information from highly multiplexed cyCIF images of cells
produced on ours or similar staining platforms. Herein, we introduce a novel tool to manage, process,
and dynamically visualize such images, with superior single cell analytics even in complex tissue. The
proposed labeling platform is the foundation for a new field of advanced multi-parametric analytics that
can correlate architectural and functional aspects of intact tissue then apply these finding to corre-
sponding cells from blood; a critical aspect of lethal tumor progression. In Phase I, a prototype imaging
platform will be built and tested with an integral set of biomarkers for identification of CHC in blood and
their corresponding hybrid cell in the primary tumor. Upon confirming feasibility, Phase II will focus on
expansion of this technology to address three critical clinical questions: (1) Can cancer be reliably de-
tected with a blood test? (2) Can occult metastatic disease be detected in early stage cancers? (3) Can
a blood test aid in treatment monitoring to personalize cancer therapy? Successful completion of this
work will result in biomarker panels and a software solution to answer these questions as demonstrated
in pancreatic and colorectal cancers herein, that can be readily expanded to other cancer types.

* Information listed above is at the time of submission. *

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