@article{204151,
  keywords = {Animals, Humans, signal transduction, Membrane Proteins, Cell Proliferation, Disease Models, Animal, Mice, Female, Cell Line, Tumor, Breast Neoplasms, Gene Expression Regulation, Neoplastic, Mice, Knockout, Breast, Calcium-Binding Proteins, Cell Survival, Drug Resistance, Neoplasm, Receptors, Notch, Neoplastic Stem Cells, Antineoplastic Combined Chemotherapy Protocols, Benzamides, Datasets as Topic, Doxorubicin, NF-kappa B p50 Subunit, RNA-Seq},
  author = {Sushil Kumar and Ajeya Nandi and Snahlata Singh and Rohan Regulapati and Ning Li and John Tobias and Christian Siebel and Mario Andres Blanco and Andres Klein-Szanto and Christopher Lengner and Alana Welm and Yibin Kang and Rumela Chakrabarti},
  title = {Dll1 quiescent tumor stem cells drive chemoresistance in breast cancer through NF-κB survival pathway},
  abstract = {<p>Development of chemoresistance in breast cancer patients greatly increases mortality. Thus, understanding mechanisms underlying breast cancer resistance to chemotherapy is of paramount importance to overcome this clinical challenge. Although activated Notch receptors have been associated with chemoresistance in cancer, the specific Notch ligands and their molecular mechanisms leading to chemoresistance in breast cancer remain elusive. Using conditional knockout and reporter mouse models, we demonstrate that tumor cells expressing the Notch ligand Dll1 is important for tumor growth and metastasis and bear similarities to tumor-initiating cancer cells (TICs) in breast cancer. RNA-seq and ATAC-seq using reporter models and patient data demonstrated that NF-κB activation is downstream of Dll1 and is associated with a chemoresistant phenotype. Finally, pharmacological blocking of Dll1 or NF-κB pathway completely sensitizes Dll1 tumors to chemotherapy, highlighting therapeutic avenues for chemotherapy resistant breast cancer patients in the near future.</p>
},
  year = {2021},
  journal = {Nat Commun},
  volume = {12},
  pages = {432},
  month = {01/2021},
  issn = {2041-1723},
  doi = {10.1038/s41467-020-20664-5},
  language = {eng},
}