Biology subjects

O'Regan, R.

Publications and source records attributed to O'Regan, R..

3 recordsLinked to original sources

bioRxiv2023

The efficacy of CB-103, a first-in-class transcriptional Notch inhibitor, in preclinical models of breast cancer

BackgroundNotch signaling has been shown to mediate treatment resistance and support cancer stem cells (CSCs) in endocrine-resistant estrogen receptor positive (ER+) and triple negative breast cancers (TNBCs). The clinical development of GSIs, first generation Notch inhibitors, has been hindered by lack of Notch specificity and dose-limiting toxicity. Here we describe the safety and efficacy of a first-in-class, clinical stage, orally available small molecule pan-Notch inhibitor, CB-103. Due to its unique mode of action, CB-103 doesnt induce GI toxicities noted with GSIs. There is a critical need for effective, safe, targeted therapies for patients with endocrine-refractory metastatic breast cancer. Recently approved targeted therapies for TNBC are only effective for a subset of patients. Moreover, GSI-resistant, constitutively activating Notch1 or Notch2 mutations are observed in [~]10% of TNBC. Our study elucidating the synergy of CB-103 with fulvestrant and paclitaxel in preclinical models of both hormone-refractory ER+ BC and TNBC respectively provides a novel and unique opportunity to address major unmet therapeutic needs. MethodsCB-103 was screened in combination with a panel of anti-neoplastic drugs. We evaluated the anti-tumor activity of CB-103 with fulvestrant in ESR1-mutant (Y537S), endocrine-resistant BC xenografts. In the same model, we examined anti-CSC activity in mammosphere formation assays for CB-103 alone or in combination with fulvestrant or palbociclib. We also evaluated the effect of CB-103 plus paclitaxel on primary tumors and CSC in GSI-resistant TNBC model HCC1187. Comparisons between groups were performed with two-sided unpaired Students t-test. One-way or two-way ANOVA followed by Tukeys post analysis was performed to analyze in vivo efficacy study results. ResultsCB-103 showed synergism with fulvestrant in ER+ cells and with paclitaxel in TNBC cells. CB-103 combined with fulvestrant or paclitaxel potently inhibited mammosphere formation in both models. Combination of CB-103 and fulvestrant significantly reduced tumor volume in an ESR1-mutant, endocrine-resistant BC model. In a GSI-resistant TNBC model, CB-103 plus paclitaxel significantly delayed tumor growth compared to paclitaxel alone. ConclusionsOur data indicate that CB-103 is an attractive candidate for clinical investigation in endocrine resistant, recurrent breast cancers with biomarker-confirmed Notch activity in combination with SERDs and/or CDKis and in TNBCs with biomarker-confirmed Notch activity in combination with taxane-containing chemotherapy regimens.

cancer biology↗

bioRxiv2021

Convergent evolution of resistance pathways during early stage breast cancer treatment with combination cell cycle (CDK) and endocrine inhibitors

Combining cyclin-dependent kinase (CDK) inhibitors with endocrine therapy improves outcomes for metastatic estrogen receptor positive (ER+), HER2 negative, breast cancer patients. However, the value of this combination in potentially curable earlier stage patients is not clear. Using single cell transcriptomic profiling, we examined the evolutionary trajectories of early stage breast cancer tumors using serial tumor biopsies from a clinical trial of preoperative endocrine therapy (letrozole) alone or in combination with the cell cycle inhibitor ribociclib. Applying hierarchical regression and Gaussian process mathematical modelling, we classified each tumor by whether it shrinks or persists with therapy and determined cancer phenotypes related to evolution of resistance and cell cycle transcriptional rewiring. We found that all patients tumors undergo subclonal evolution during therapy, irrespective of the clinical response. However, tumors subjected to endocrine therapy alone showed reduced diversity over time, while those facing combination therapy exhibited increased diversity. Despite different subclonal diversity, single nuclei RNA sequencing uncovered common phenotypic changes in tumor cells that persist following treatment. In these tumors, cancer cells with accelerated loss of estrogen signaling have convergent up-regulation of the JNK pathway, while cells that maintain estrogen signaling during therapy show potentiation of CDK4/6 activation consistent with ERBB4 and ERK signaling up-regulation. These convergent phenotypes were associated with growing tumors resistant to combination therapy. Cell cycle reconstruction identified that these tumors can rebound during combination therapy treatment, indicating stronger selection and promotion of a proliferative state. These results indicate that combination therapy in early stage ER+ breast cancers with ER and CDK inhibition drives rapid evolution of resistance via a shift from estrogen signaling to alternative growth factor receptor mediated proliferation and JNK signaling activation, concordant with a bypass in the G1 checkpoint.

cancer biology↗

bioRxiv2021

Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities.

BackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution. MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms. ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population. ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

systems biology↗