Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

A Synthetic Lethality-Focused Algorithm to Identify Therapeutic Options in Advanced Metastatic Breast Cancer (SYNTHESIS-Breast)

National Cancer Institute (NCI) · 2026
ClinicalTrials.gov · Datasets · License: Public Domain · 2026
Open Source ↗
breast-cancerbreast-carcinomana
Background: Breast cancer is the most common cancer in US women. There are different types of breast cancers; some are aggressive and difficult to treat. Researchers want to know if an algorithm (ENLIGHT) can help choose approved drugs that will treat these cancers more effectively. Objective: To test whether ENLIGHT can find better treatments for aggressive breast cancers. Eligibility: People aged 18 years and older with triple-negative or endocrine therapy resistant breast cancer; the cancer must have either failed to respond to treatment or come back after treatment. Design: Participants will be screened. A sample of tissue taken from the tumor will be tested using ENLIGHT as well as another method (TruSight Oncology 500). Participants will be assigned to 1 of 3 groups based on the algorithm search results: Group 1: No drug option was recommended. Participants will continue with their standard treatment with their local doctors. Group 2: A drug already approved for the participant's disease was recommended, but the participant has not yet received it. These results will be sent to the participant's local doctors. Participants may return to the NIH if their disease gets worse after using the suggested drugs. Group 3: A drug approved for other uses was recommended. Participants will be treated with the recommended drugs at the NIH; their care will be managed by an NIH doctor. They will continue to receive treatment as long as the drugs are helping them. They will have follow-up visits for 2 years after treatment ends. Participants who are not treated at the NIH will be contacted for a check on their health every 3 months for 2 years.
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 849721
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive