Determinants of sacituzumab govitecan therapeutic response in breast cancer models
Presenter: Carson Walker, BS Session: Drug Resistance 1: Antibodies and ADCs Time: 4/20/2026 2:00:00 PM → 4/20/2026 5:00:00 PM
Authors
Carson J. Walker 1 , Nina Dashti-Gibson 1 , Julia E. Altman 2 , Rachel K. Myrick 2 , Emily K. Zboril 1 , Oniya M. Smith 2 , David C. Boyd 2 , Bin Hu 1 , Mikhail G. Dozmorov 3 , Joshua C. Harrell 4 1 VCU Massey Comprehensive Cancer Center, Richmond, VA, 2 Virginia Commonwealth University, Richmond, VA, 3 Biostatistics, Virginia Commonwealth University, Richmond, VA, 4 Pathology, Virginia Commonwealth University, Richmond, VA
Abstract
This study identifies markers of Sacituzumab Govitecan (SG) response in triple-negative breast cancer (TNBC) models and introduces new SG acquired resistance patient derived xenografts (PDXs) that can serve as examples of patient-acquired mutations or gene regulation changes that confer resistance to this targeted therapy. SG is an antibody drug conjugate (ADC) that has been approved for treating TNBC and estrogen receptor positive breast cancers that have progressed on initial treatments. SG binds to TROP2 and delivers SN-38 as its payload; resistance to SG could be due to inefficient antibody internalization or lack of payload efficacy. We hypothesize that individual intrinsic and acquired SG resistance mechanisms will uncover features that can be targeted to extend the duration of response to SG. Using a linear mixed effects model, we mapped PDX responses to SG in vivo to their RNA expression in order to identify differences in gene expression that stratify SG response; developing an initial SG response predictor in this process. By administering suboptimal and continuous SG treatments to formerly SG-sensitive PDXs, we created acquired SG resistant (SGR) models. We then compared the RNA expression between these syngeneic pairs of PDXs to identify acquired resistance mechanisms and common pathways of resistance in patients. Performing antibody internalization assays on the paired sets allowed us to investigate if antibody or encapsulation mediated resistance was responsible for the continued tumor growth. Short-term SN38 testing was used to define the extent of payload resistance in paired models. Through these efforts, we identified 9 SG-sensitive and 3 intrinsically resistant TNBC PDXs whose differential expression led us to focus on 13 genes that predict SG response. Three of the most sensitive models were used to create acquired resistance models and analysis is underway to compare these to the intrinsic resistance models utilizing bulk and single-cell RNA-sequencing, proteomics, and cytotoxic compound screens. RNA sequencing of PDXs with innate SG resistance defined differences in gene expression related to extracellular matrix, angiogenesis, and metal ion trafficking. Conversely, acquired resistance models show diversity in resistance mechanisms including notably heightened extracellular matrix protein synthesis. Ongoing studies aim to define these mechanisms so that candidate therapeutics can be prioritized to overcome SG resistance. In conclusion, a preliminary SG resistance signature has been developed, which we will refine for clinical selection of patients to be treated with SG. Additionally, several biological processes are activated during acquired SG resistance and may be targetable.
Disclosure
C. J. Walker, None.. N. Dashti-Gibson, None.. J. E. Altman, None.. R. K. Myrick, None.. E. K. Zboril, None.. O. M. Smith, None.. D. C. Boyd, None.. B. Hu, None.. M. G. Dozmorov, None.. J. C. Harrell, None.
Cited in
Control: 7194 · Presentation Id: 5014 · Meeting 21436