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Dynamic BH3 Profiling Predicts Drug Response

The dynamic BH3 profiling (DBP) platform measures drug-induced cell death signaling, which predicts in vivo response to a wide spectrum of anti-cancer agents.   

  • Diagnostics

Project Overview

  • Dynamic BH3 profiling (DBP) has been shown to be useful to predict and monitor the effectiveness of chemotherapeutics and create new clinical applications for existing therapies.  
  • Dana-Farber scientists have developed the DBP platform to measure how close a cancer cell is to death following exposure to drugs or other compounds of interest. 
  • Dana-Farber is seeking an interested party for sponsored research or to license the technology for development to the clinic.  

Technology

Most chemotherapeutics kill tumor cells by pushing them over the threshold of cancer cell death, or apoptosis. Anthony Letai, MD, PhD at Dana-Farber constructed a novel predictive assay, Dynamic BH3 Profiling (DBP) to measure how much a cancer drug pushes a cancer cell toward the threshold of apoptosis, a measure which has been shown to predict in vivo efficacy of a treatment in individual patients. Since nearly all classes of chemotherapeutics utilize the mitochondrial pathway of apoptosis, DBP has been found to predict response to a wide range of agents, including kinase inhibitors, epigenetic agents, BH3 mimetics, Imids, and SMAC mimetics.  

The DBP assay involves exposing cancer cell mitochondria to a panel of BH3 peptides (derived from the BH3 domains of pro-death BCL-2 family proteins that regulate apoptosis) after treatment of patient cancer cells with a compound of interest to rapidly detect whether the drug has provoked pro-apoptotic signaling. In general, the more sensitive a mitochondrion is to a BH3 peptide, the more primed it is, and the closer to apoptosis.  

By measuring the mitochondria’s responses at short time points, researchers can observe which compounds force the cancer cell toward the threshold of apoptosis. Since the assay measures the initiation of apoptosis, it can return actionable information after relatively brief exposures of patient samples to drugs of interest. Thus, there is no requirement for the establishment of complex models or for prolonged ex vivo culture, which can skew results. An important consequence is that this assay can be performed on nearly any type of patient tumor with nearly any type of drug, and results are available within just a few days.  

The dynamic BH3 profiling functional assay measures the interaction of proteins involved in apoptosis.   

Team Members: Anthony Letai, MD, PhD, Patrick Bhola, PhD, Emma Mihihane, PhD, Jeremy Ryan

Applications

In retrospective studies, DBP profiling has been clinically validated to predict a response to chemotherapies in several cancer types including acute myeloid leukemia, acute lymphocytic leukemia (AML), chronic myelogenous leukemia (CML), chronic lymphocytic leukemia (CLL), mesothelioma, and ovarian cancer.  In human organoid cancer models, the platform provides up to 100% sensitivity and specificity in predicting therapeutic response. Because it is a functional assay, it can directly test the efficacy of combinations as well as single agents.  

The technology may be useful in several other potential indications. 

  • As a companion diagnostic, for an active drug that requires a predictive biomarker to identify a large enough population for regulatory approval 
  • As personalized therapy tool for an individual patient, assisting in choosing the right drugs for the right patient.  
  • As a discovery tool, testing patient samples directly, with far greater speed and scalability than patient-derived xenografts (PDX) and other patient-derived models. 

Interested in learning more?

Dynamic BH3 profiling identifies active BH3 mimetic combinations in non-small cell lung

Nature Cell Death and Disease paper

Dynamic BH3 Profiling: Personalized Cancer Therapy

INPART technology summary

Opportunities

Dana-Farber welcomes discussions with interested parties to license this technology.  

Get in touch

Team Members