Morphological screening of mesenchymal mammary tumor organoids to identify drugs that reverse epithelial-mesenchymal transition.
Na ZhaoReid T PowellXueying YuanGoeun BaeKevin P RoartyFabio StossiMartina StrempflMichael J ToneffHannah L JohnsonSendurai A ManiPhilip JonesClifford C StephanJeffrey M RosenPublished in: Nature communications (2021)
The epithelial-mesenchymal transition (EMT) has been implicated in conferring stem cell properties and therapeutic resistance to cancer cells. Therefore, identification of drugs that can reprogram EMT may provide new therapeutic strategies. Here, we report that cells derived from claudin-low mammary tumors, a mesenchymal subtype of triple-negative breast cancer, exhibit a distinctive organoid structure with extended "spikes" in 3D matrices. Upon a miR-200 induced mesenchymal-epithelial transition (MET), the organoids switch to a smoother round morphology. Based on these observations, we developed a morphological screening method with accompanying analytical pipelines that leverage deep neural networks and nearest neighborhood classification to screen for EMT-reversing drugs. Through screening of a targeted epigenetic drug library, we identified multiple class I HDAC inhibitors and Bromodomain inhibitors that reverse EMT. These data support the use of morphological screening of mesenchymal mammary tumor organoids as a platform to identify drugs that reverse EMT.
Keyphrases
- epithelial mesenchymal transition
- stem cells
- transforming growth factor
- bone marrow
- signaling pathway
- drug induced
- neural network
- induced apoptosis
- high throughput
- machine learning
- gene expression
- cell proliferation
- long non coding rna
- deep learning
- emergency department
- oxidative stress
- cell death
- mesenchymal stem cells
- big data
- mass spectrometry
- electronic health record
- liquid chromatography
- cell therapy