Development of drug resistance and clonal selection of ESR1 mutants in a breast cancer model

Joint Event on 2^nd International Conference on Cancer Biology, Therapeutics and Drug Discovery and Delivery & 10^th Annual Congress on Biomarkers, Clinical Research & Therapeutics

October 03-04, 2018 | Los Angeles, USA

Sunil Kumar and Gaorav P Gupta

University of North Carolina School of Medicine, USA

Scientific Tracks Abstracts: J Cancer Sci Ther

Abstract :

Estrogen receptor-α (ER, encoded by ESR1) is expressed in two-thirds of the breast cancer patients. Ligand-binding domain mutations in ESR1 have emerged as a clinically significant mechanism of endocrine therapy resistance in ER+ MBC. Over one-third of the identified ESR1 mutations cluster as �??hotspot�?� missense mutations at the 537 and 538 amino acid residues. We have generated variants of T47D and MCF7 cell-lines by introducing the mutation at 537 or 538 amino acid positions using CRISPR-Cas9 targeting. We monitored the growth advantage of ESR1 mutant versus wild-type clones using digital droplet PCR in a competition assay. D538G and Y537S mutants were selected when the cell population was treated with the estrogen receptor degrader, Fulvestrant. These mutants were also enriched during growth in estrogen-depleted media, which mimics aromatase inhibitor treatment. Combination drug treatment with fulvestrant and inhibitors of cdk4/6 (palbociclib), mTOR (everolimus) and PI3K (alpelisib) reduced the selective advantage of the ESR1 mutant clones. The use of palbociclib with fulvestrant worked best to control the clonal expansion of T47D-D538G mutants, while fulvestrant with either palbociclib, everolimus or alpelisib was effective in controlling the growth of T47D-Y537S mutants. Our results are consistent with clinical findings that combination drug therapy is more effective than endocrine therapy alone in patients with ESR1 mutations. The cellular competition-based assay described here may also be applicable to the study of how mutations in other cancer genes impact drug sensitivity in a preclinical model system.

Biography :

Sunil Kumar has expertise in biomarker discovery with the particular focus on Translational Research and Targeted Therapy. His research is focused on finding novel biomarkers for breast cancer and head and neck cancer. His breast cancer research aims to find biomarkers and early drivers of metastatic breast cancer. He has used CRISPR targeting to study drug sensitivity. He has been serving as an editorial board member for three journals and reviewed more than 50 manuscripts.

E-mail: sunil02@med.unc.edu