What changed from existing technology?
This study analyzed DNA from the blood of over 12,000 patients with advanced breast cancer to understand how their cancer's genetic makeup changes and affects treatment response.
This is the first large-scale study to use a machine learning model to classify metastatic breast cancer subtypes from circulating DNA, revealing new insights into genetic changes during cancer progression.
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This is not a success probability or investment opinion. It prioritizes follow-up using evidence available when the paper was published.
Verified evidence · 2
landscape and dynamics in circulating DNA from 12,827 patients with metastatic breast cancer. Abstract Plasma cell-free DNA (cfDNA) is a sensitive, noninvasi
Title ↗OpenAlex author affiliations: Guardant (United States)
Abstract ↗- 시제품·장치 구현 근거 미확인
- 제조·규모 확장 근거 미확인
Later patent, company, clinical, and production events are added separately only after verification.
Patent check: Not checked yetCurrent technology stage: Near commercialization
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What still needs to be solved?
Repeated real-world validation, manufacturability, cost, and long-term stability still require follow-up evidence.
What could change if this succeeds?
This research could help develop better non-invasive tests to monitor cancer progression and guide treatment decisions based on genetic changes in circulating DNA.
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