Invention Grant
- Patent Title: Integrated machine-learning framework to estimate homologous recombination deficiency
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Application No.: US16789363Application Date: 2020-02-12
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Publication No.: US10975445B2Publication Date: 2021-04-13
- Inventor: Aarti Venkat , Jerod Parsons , Joshua S K Bell , Catherine Igartua , Yilin Zhang , Ameen Salahudeen , Verónica Sánchez Freire , Robert Tell
- Applicant: Tempus Labs, Inc.
- Applicant Address: US IL Chicago
- Assignee: Tempus Labs, Inc.
- Current Assignee: Tempus Labs, Inc.
- Current Assignee Address: US IL Chicago
- Agency: Morgan, Lewis & Bockius LLP
- Main IPC: C12Q1/6886
- IPC: C12Q1/6886 ; G16B40/00 ; G16B20/00 ; G06N3/02 ; G16B50/30 ; G06F17/18

Abstract:
Methods, systems, and software are provided for determining a homologous recombination pathway status of a cancer in a test subject, e.g., to improve cancer treatment predictions and outcomes. In some embodiments, classifiers using one or more of (i) a heterozygosity status for DNA damage repair genes in a cancerous tissue, (ii) a measure of the loss of heterozygosity across the genome of the cancerous tissue, (iii) a measure of variant alleles detected in a second plurality of DNA damage repair genes in the genome of the cancerous tissue, (iv) a measure of variant alleles detected in the second plurality of DNA damage repair genes in the genome of a non-cancerous tissue, and (v) tumor sample purity are provided.
Public/Granted literature
- US20200255909A1 INTEGRATED MACHINE-LEARNING FRAMEWORK TO ESTIMATE HOMOLOGOUS RECOMBINATION DEFICIENCY Public/Granted day:2020-08-13
Information query
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