SBIR/STTR Research Award

Development of lavage EV protein biomarkers for minimally-invasive detection of endometrial cancer

Award identifier f000dee6aeb56bf8e446e9bb578fc9b7fd4218acfe4742e900298b7033927bc6Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$290,000

Program and phase

SBIR · Phase I

Award year

2022

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
TYMORA ANALYTICAL OPERATIONS LLC
Proposal award date
2022-09-01
Contract end date
2023-08-31
UEI
ZFFZKDYTF5Q9
Solicitation number
PA21-259
Topic code
102

Research abstract

PROJECT SUMMARY Early detection of endometrial cancer can increase the 5-year survival rate from lt20% to rt95%. However, currently there are no non-invasive methods for its detection. We propose the use of cell-secreted extracellular vesicles (EVs) as the source of new diagnostic biomarkers from uterine lavage – a sample that is much more targeted to endometrial cancer. Within the scope of biomarker detection, EVs offer numerous benefits for clinical analysis, including non-invasive collection, a suitable sample source for longitudinal disease monitoring, higher stability and sample volumes, faster processing times and lower cost. However, the analysis of exosomes and other EV has not really been possible for early endometrial cancer detection. The common procedures for biofluid EV biomarker analysis are very long and cumbersome due to extremely low target levels and high background of free proteins. In order to enable better biomarker discovery and endometrial cancer diagnosis, a more reliable and efficient approach is needed, capable of enriching potential cancer-associated proteins with higher purity. In this NIH SBIR Phase I study, we will implement our novel method for fast and reproducible enrichment of EVs with rt95% recovery yield and rt99.9% purity for analysis of endometrial cancer from lavage samples. We have already carried out initial lavage EV validation and biomarker discovery experiments, and selected over a dozen of high-quality protein targets that enable effective differentiation of endometrial cancer from non-cancer controls. The following aims will be completed in the Phase I of the proposal: Aim #1: Determine the feasibility of the discovered endometrial cancer biomarkers from lavage EVs to differentiate the disease and refine the panel. Aim #2: Evaluate and implement the novel uterine lavage collection device for fast and effective EV isolation and measurement. By the completion of this project, the non-invasive endometrial cancer biomarker discovery platform from lavage EVs will be developed, and a minimally invasive early endometrial cancer detection assay will be validated that can overcome the limitations of current approaches, and thus could have an enormous public health impact and market potential.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

17 SBIR/STTR records share this UEI (2011–2024). Reported award amounts total $7,866,983. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.