SBIR Diagnostic Method to Identify approved drugs as treatment options in individuals with rare cancer
SBIR Diagnostic Method to Identify approved drugs as treatment options in individuals with rare cancer
批准号:
10931987
负责人:
GITTE PEDERSEN
金额:
$34.03万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-02-28 至 2024-02-27
关键词:
Antineoplastic AgentsAwardBiological AssayCancer PatientClinicalDNA Repair GeneDataDetectionDevice or Instrument DevelopmentDiagnosisDiagnosticDrug CombinationsDrug TargetingERBB2 geneExhibitsFDA approvedGene ExpressionGenesGenomicsMalignant Childhood NeoplasmMalignant NeoplasmsMalignant neoplasm of ovaryMessenger RNAMethodsOncologistPharmaceutical PreparationsPharmacotherapyPoly(ADP-ribose) Polymerase InhibitorReverse Transcriptase Polymerase Chain ReactionServicesSmall Business Innovation Research Grantclinically actionableimproved outcomeinnovationmRNA ExpressionmRNA sequencingovarian neoplasmoverexpressionprogrammed cell death ligand 1rare cancerresponse biomarkertargeted biomarkertumor
中文摘要
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英文摘要
The long term objective of this proposal is to improve outcomes for ovarian cancer patients in the frontline setting.
Few effective drug treatment options exist for ovarian cancer and other rare cancers whereas 300+ drugs have been
approved by the FDA to treat non-rare cancers. Analysis of tumor mRNA gene expression has the potential to identify
over expression of approved drug targets, such as HER2, AR, and PD-L1, and silencing of DNA repair genes that make
ovarian tumors more responsive to PARP inhibitors.
In this project, a proprietary tumor mRNA sequencing method called “OneRNA” will be analytically validated in 30
clinically annotated de-identified ovarian tumors by (1) comparing relative mRNA expression levels (tumor vs normal) to
reverse transcriptase PCR (RT-PCR) (2) evaluating concordance of aberrantly expressed genes detected with the
OneRNA assay with FDA approved immunohistochemical (IHC) assays. Based on preliminary data, we expect to
identify at least one clinically actionable aberrantly expressed gene in over 90% of tumors.
The resulting data will support the launch of an ovarian tumor expression analysis service by the Genomic Expression
CLIA lab to help oncologists identify which drugs and drug combinations are likely to benefit ovarian cancer patients.
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