Epigenetic Classifiers for Precision Diagnosis Description:

The identification and characterization of disease-specific epigenetic alterations, particularly DNA methylation, continues to grow at a rapid pace, highlighting the important and numerous roles these modifications play in disease etiology and progression. DNA methylation profiling of tumors has revealed actionable targets that can serve as both biomarkers for tumor classification and therapeutic targets. These powerful analyses can aid in clinical decision making by providing robust diagnostic, prognostic, and predictive information specific to the tumor type.

Researcher working at a computer in the epigenetics lab
  • The combination of high quality DNA methylation profiling with machine learning approaches has allowed us to develop and validate cancer-specific epigenetic classifiers.
  • Our lab has developed novel brain metastasis DNA methylation classifiers (BrainMETH) which can accurately identify the type of brain tumor and the tissue of origin for the three most frequent types of metastatic brain tumors: lung, breast and melanoma. This classifier can further refine tumor type by identifying the therapeutic subtype in breast cancer. Future directions include expanding our classifiers to identify brain metastases originating from additional tumor types.
  • Significant efforts have been made to stratify triple negative breast cancer (TNBC) into distinct  subtypes. TNBC is an extremely aggressive form of breast cancer, making up 15-20% of all breast cancer cases. Our lab aims to sub-classify TNBC based on robust epigenetic profiling to guide clinical decisions.