SBIR/STTR Research Award

An improved RT-qPCR method for quantitation of fragmented mRNAs

Award identifier bf2ee3f2c27ee19212d3f892ac0e3e19b068ddbe2e444edd650146ea94ae7138Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$287,788

Program and phase

SBIR · Phase I

Award year

2016

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Somagenics, Inc.
Proposal award date
2016-02-01
Contract end date
2017-10-31
UEI
NWMCAECH9RX7
Solicitation number
PA14-071
Topic code
200

Research abstract

DESCRIPTION provided by applicant Quantification of gene expression in formalin fixed paraffin embedded FFPE tissue samples is important for the discovery and validation of cancer biomarkers for tumor classification and to assess progress during cancer treatment Because RT qPCR assays are very sensitive and sequence specific they are currently preferred for mRNA expression profiling in FFPE tissues as well as for validation of data obtained by other expression profiling methods such as microarrays and sequencing RNA seq However use of these methods to analyze FFPE samples is constrained by the RNA fragmentation that occurs in these samples and limits the sensitivity and reproducibility of these assays To overcome this problem we proposed a novel method for assaying mRNA fragments in FFPE samples called mR FQ mRNA Fragment Quantification In Preliminary Studies we developed a mR FQ prototype which can work with very short mRNA fragments of nt and demonstrated its superior sensitivity over the TaqMan RT qPCR method in quantifying two model mRNAs from FFPE samples We analyzed HER a breast cancer biomarker and GAPDH internal reference mRNAs in total RNA isolated from breast cancer and prostate cancer FFPE samples In Phase I we plan to i validate the mR FQ method using a larger number of target mRNAs and more FFPE samples ii further optimize mR FQ iii demonstrate that mR FQ reliably quantifies mRNAs in FFPE samples containing highly fragmented mRNAs that are not detectable by currently leading RT qPCR methods run in parallel iv determine the maximum mRNA fragmentation level detectable by mR FQ In Phase II we will move towards commercialization by designing mR FQ assays for BC biomarker candidates and validating them on FFPE samples having a wide range of RNA fragmentation levels with focus on currently unusable samples those containing highly fragmented RNA that cannot be assayed by standard RT qPCR methods mR FQ and RNA seq analyses will be compared and we expect that mR FQ will be able to validate RNA seq results since both methods can work with highly fragmented RNA This will allow researchers to include a wider range of FFPE samples into retrospective studies for the development and validation of improved breast as well as other types of cancer diagnostics and treatment prognostics PUBLIC HEALTH RELEVANCE This project develops new technology for studying gene expression archived tissue specimens from cancer patients We plan to use it to develop better biomarkers for breast cancer the most common cancer among women About women were diagnosed and over died from the disease last year in the US alone The goal of this grant application is to develop a method for quantitation of fragmented mRNAs from standard histology specimens FFPE blocks that will provide superior sensitivity and accuracy at a reasonable cost to facilitate research in and diagnosis of breast cancer as well as treatment prognosis

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

39 SBIR/STTR records share this UEI (1994–2020). Reported award amounts total $23,258,381. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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