APPLICATIONS OF TECHNOLOGY:
- Targeted cancer therapies
- Prediction of relapse-free breast cancer survival
- Determines most effective treatment options for patient quality of life
- Standardizes breast cancer prognoses
Berkeley Lab researchers Jian-Hua Mao and Antoine Snijders have identified a unique set of seven genes for Luminal A Type breast cancer and a unique set of 17 genes for the Basal Type that predict survival after radiotherapy for each subtype. These signatures could function as a prognostic test applied to resected tumor tissue and enable a more effective assignment of patients to radiation therapy or alternative post-surgical adjuvant therapy.
Breast cancer is the most common cancer diagnosis in females worldwide and the second leading cause of cancer death among women in the United States. Adjuvant radiotherapy is often used in an attempt to eradicate residual cancer after surgery with the goal of increasing relapse-free survival. Despite its widespread use, a statistically significant survival benefit is only observed in particular patients. Besides assigning patients to the most effective therapies, the gene signatures would also spare some patients the unnecessary toxicity of radiation therapy with no benefit, thus saving their physical resources for recovery from other, potentially more effective approaches such as chemotherapy or biological therapy.
DEVELOPMENT STAGE: Proven principle.
STATUS: Patent pending. Available for licensing or collaborative research.
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