Personalized medicine: the road ahead.

Area of Science:

• Oncology
• Genomics
• Personalized Medicine

Background:

• Breast cancer is a heterogeneous disease necessitating individualized treatment approaches.
• Traditional prognostic markers (tumor size, lymph node status, grade, hormone receptors, HER2) are now augmented by gene expression profiling.
• Existing molecular tools like PAM50 and MammaPrint show limitations due to overreliance on proliferation genes.

Purpose of the Study:

• To review the evolution and limitations of breast cancer prognostic and predictive markers.
• To discuss the potential and challenges of pathway-based signatures and newer molecular markers.
• To highlight the need for an integrated prognostic tool for personalized breast cancer management.

Main Methods:

• Literature review of classic and contemporary breast cancer prognostic and predictive markers.
• Analysis of gene expression-based tools, pathway signatures, and emerging molecular markers (cancer stem cells, SNPs, miRNAs).
• Discussion of the Oncotype DX assay's utility in ER-positive tumors.

Main Results:

• Classic markers provide foundational prognostic information.
• Gene expression and pathway-based signatures offer advancements but have limitations.
• The Oncotype DX assay demonstrates value for specific breast cancer subtypes.
• Emerging markers require further validation.

Conclusions:

• No single tool reliably predicts breast cancer outcomes due to disease complexity.
• An ideal prognostic tool should integrate clinical variables with high-throughput molecular data and pharmacogenomics.
• Such a tool is crucial for defining prognostic subgroups and predicting treatment response.