Gene Expression Profiles for Post-Treatment Breast Cancer Prognosis
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Solution Overview
Problem
Current treatments for hormone-dependent breast cancer, such as tamoxifen therapy, fail to predict which patients will benefit from subsequent letrozole treatment, leading to overtreatment of breast cancer-free subjects.
Innovation Solution
Utilizing gene expression profiles, particularly the HoxB13:IL17BR ratio and the Breast Cancer Index (BCI) comprising HoxB13 and additional genes, to predict cancer recurrence and responsiveness to endocrine therapies, allowing for personalized treatment switches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If letrozole treatment is applied to all breast cancer-free subjects after five years of tamoxifen, then breast cancer-free survival may be improved for some patients, but overtreatment occurs in patients who would not benefit
Solution Approach 1:
The patent applies preliminary action by using gene expression profiling (HoxB13:IL17BR ratio) on tumor samples obtained before letrozole treatment to predict which patients will benefit from therapy switch. This advance assessment allows clinicians to pre-identify suitable candidates for letrozole treatment, avoiding overtreatment of patients unlikely to respond while ensuring appropriate patients receive the beneficial therapy.
2Adaptability or versatility
If gene expression profiling is implemented to predict treatment response, then personalized treatment selection improves, but treatment cost and diagnostic complexity increase
Solution Approach 1:
The patent applies the extraction principle by focusing on specific, clinically relevant genes (HoxB13 and IL17BR) rather than analyzing the entire genome. By extracting and measuring only the expression levels of these two specific genes using targeted assays like qRT-PCR, the diagnostic complexity is significantly reduced while still providing actionable predictive information for treatment decision-making.
Data Source
AI summary
The disclosure includes the identification and use of gene expression profiles, or patterns, with clinical relevance to extended treatment and cancer-free survival in a patient. In particular, the disclosure includes the identities of genes that are expressed in correlation with benefit in a switch in endocrine therapy used to treat a patient. The levels of gene expression are disclosed as a molecular index for predicting clinical outcome, and so prognosis, for the patient. The disclosure further includes methods for predicting cancer recurrence, and/or predicting occurrence of metastatic cancer, after initial treatment with an anti-estrogen agent. The disclosure further includes methods for determining or selecting the treatment of a subject based upon the likelihood of life expectancy, cancer recurrence, and/or cancer metastasis.