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Translational Assays for Inflammatory Biomarkers for the Risk Stratification of Pancreatic Cystic Lesions

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43CA277913-01A1
Agency Tracking Number: R43CA277913
Amount: $399,885.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NCI
Solicitation Number: PA22-176
Timeline
Solicitation Year: 2022
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-05-01
Award End Date (Contract End Date): 2024-04-30
Small Business Information
1281 WIN HENTSCHEL BLVD
West Lafayette, IN 47906-4182
United States
DUNS: 080310994
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 DANIEL SHEIK
 (815) 979-4285
 dan.sheik@amplifiedsci.com
Business Contact
 DIANA CALDWELL
Phone: (317) 490-0511
Email: diana.caldwell@amplifiedsci.com
Research Institution
N/A
Abstract

PROJECT SUMMARY
Advances in clinical imaging technologies have increased the incidental detection rate of cystic pancreatic
lesions. However, patients remain at risk due to the lack of a definitive diagnosis that accurately assesses if
these cysts are pre-malignant. In the absence of robust diagnostic indicators, clinicians must balance patient
safety due to a cystic lesion's rapid and aggressive progression to a malignant pancreatic tumor with the severe
financial and physical morbidity and mortality associated with surgical interventions. Retrospective studies have
found almost a quarter of surgical interventions to address a pancreatic cyst are unwarranted. A confounder is
that retrospective studies have also revealed that when clinicians use a wait-and-see approach, up to a quarter
of patients receive surgical resection too late. The dual-edged nature of this process highlights the need for
better early-stage diagnostic tools. There remains an unmet clinical need for diagnostic information that can
accurately stratify the risk associated with pre-cancerous, fluid-filled pancreatic lesions that are commonly the
first sign of concern.
Currently, clinicians can obtain fluid from incidentally detected pancreatic cysts for chemical analysis of disease-
associated molecular markers. Pancreatic cyst fluid samples are most often highly viscous, making it difficult to
aliquot, and can be very limited in volume depending on the size of cyst. Furthermore, available biomarker assays
lack sensitivity, can have long turnaround times, and require high sample volumes. These traits limit the amount
and quality of information from single pancreatic cyst fluid samples. Clinicians must rely on their unique
experiences when choosing between appropriate analyses, which further confuses attempts at standardization
of clinical care. Amplified Sciences has developed a robust assay platform to analyze low-volume (down to 1 µL)
clinical pancreatic cyst fluid samples for protease activity to distinguish non-mucinous from mucinous pancreatic
cyst populations. In this proposal, Amplified Sciences is expanding the platform to provide higher content
diagnostic information about the malignant potential of the mucinous pancreatic cyst population.
Amplified Sciences assay and detection platforms are adaptable to new biomarker targets. This proposal aims
to create a multidimensional assay panel that accurately determines the risk of pancreatic cysts progression to
cancer. A combination of three (3) markers under investigation by collaborators at Alaunus Biosciences and
UCSF show promise to stratify the grade of dysplasia in a limited number of clinical mucinous pancreatic cyst
samples. This proposal will 1) validate the capacity of these markers to distinguish low- from high-grade dysplasia
in retrospective mucinous clinical samples and 2) translate low-volume assays for these markers into CLIA-ready
protocols to enable stacking of assays on individual samples. Upon completion, a novel assay panel will be
available that uses minimal cyst fluid volumes to quantitate the validated biomarkers, comprising a new method
for clinicians to maximize accurate diagnostic information from precious clinical samples with rapid turnaround.

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

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