Gene expression signatures, clinicopathological features, and individualized therapy in breast cancer
Acharya CR et al. - Incorporation of gene expression signatures into clinical risk stratification can refine prognosis Methods- Retrospective study of early stage breast carcinoma candidates for adjuvant chemotherapy
- Review of microarray data for 964 clinically annotated breast tumor samples (573 in initial set; 391 in validation cohort)
- Relapse risk scores based on respective clinicopathologic features
- Main outcome measures: gene expression signatures and clinicopathological variables in early stage breast cancer to determine a refined estimation of relapse-free survival and sensitivity to chemotherapy
Results- In initial 573 pts, prognostically significant clusters as patterns of oncogenic pathway activation and tumor biology/microenvironment states were identified within the low-, intermediate-, and high-risk model cohorts
- Multivariate analyses confirmed independent prognostic value of genomic clusters
- Related, not identical, clusters in the independent validation cohort established reproducibility and validity of pathway deregulation patterns in predicting relapse risk
- The prognostic clinicogenomic clusters showed unique sensitivity patterns to commonly used cytotoxic therapies
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