High-throughput dynamic BH3 profiling may quickly and accurately predict effective therapies in solid tumors

Bhola, Patrick; Ahmed, Eman Y.; Guerriero, Jennifer L.; Sicińska, Ewa; Su, Emily Chia Yu; Lavrova, Elizaveta; Ni, Jing; Chipashvili, Otari; Hagan, Timothy; Pioso, Marissa S.; McQueeney, Kelley E.; Ng, Kimmie; Aguirre, Andrew J.; Cleary, James M.; Cocozziello, David; Sotayo, Alaba; Ryan, Jeremy; Zhao, Jean J.; Letaï, Anthony

doi:10.1126/scisignal.aay1451

Cited by 48 publications

(52 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Early time point mitochondrial apoptotic signaling predicts treatment responses Dynamic BH3 profiling (DBP) [21,22] was performed on PDX-derived tumor cells corresponding to HCI-010 ( Fig. 5a) and HCI-025 ( Fig.…”

Section: Navitoclax Enhances the In Vivo Efficacy Of Abt-414 Or Abbv-321mentioning

confidence: 99%

Navitoclax enhances the effectiveness of EGFR-targeted antibody-drug conjugates in PDX models of EGFR-expressing triple-negative breast cancer

et al. 2020

Self Cite

View full text Add to dashboard Cite

Background Targeted therapies for triple-negative breast cancer (TNBC) are limited; however, the epidermal growth factor receptor (EGFR) represents a potential target, as the majority of TNBC express EGFR. The purpose of these studies was to evaluate the effectiveness of two EGFR-targeted antibody-drug conjugates (ADC: ABT-414; ABBV-321) in combination with navitoclax, an antagonist of the anti-apoptotic BCL-2 and BCL-XL proteins, in order to assess the translational relevance of these combinations for TNBC. Methods The pre-clinical efficacy of combined treatments was evaluated in multiple patient-derived xenograft (PDX) models of TNBC. Microscopy-based dynamic BH3 profiling (DBP) was used to assess mitochondrial apoptotic signaling induced by navitoclax and/or ADC treatments, and the expression of EGFR and BCL-2/XL was analyzed in 46 triple-negative patient tumors. Results Treatment with navitoclax plus ABT-414 caused a significant reduction in tumor growth in five of seven PDXs and significant tumor regression in the highest EGFR-expressing PDX. Navitoclax plus ABBV-321, an EGFR-targeted ADC that displays more effective wild-type EGFR-targeting, elicited more significant tumor growth inhibition and regressions in the two highest EGFR-expressing models evaluated. The level of mitochondrial apoptotic signaling induced by single or combined drug treatments, as measured by DBP, correlated with the treatment responses observed in vivo. Lastly, the majority of triple-negative patient tumors were found to express EGFR and co-express BCL-XL and/or BCL-2. Conclusions The dramatic tumor regressions achieved using combined agents in pre-clinical TNBC models underscore the abilities of BCL-2/XL antagonists to enhance the effectiveness of EGFR-targeted ADCs and highlight the clinical potential for usage of such targeted ADCs to alleviate toxicities associated with combinations of BCL-2/XL inhibitors and systemic chemotherapies.

show abstract

Section: Navitoclax Enhances the In Vivo Efficacy Of Abt-414 Or Abbv-321mentioning

confidence: 99%

Navitoclax enhances the effectiveness of EGFR-targeted antibody-drug conjugates in PDX models of EGFR-expressing triple-negative breast cancer

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…These cell line-specific results highlight an important lesson for the use of alpelisib and BH3 mimetics in the clinical setting of breast cancer: fully taking advantage of this drug combination will require determining the relevant anti-apoptotic BCL-2 family dependence in the tumor. This could be accomplished by directly quantifying these BCL-2 family members in the tumor and/or by using functional genomic approaches such as dynamic BH3 profiling (Montero et al 2015;Montero et al 2019;Bhola et al 2020). In line with this view, recent clinical trials on breast cancer tumors with high BCL-2 expression have shown promising results with the combination of approved breast cancer therapies with the BCL-2 inhibitor venetoclax (Whittle et al 2020;Lok et al 2019).…”

Section: Discussionmentioning

confidence: 99%

Cell line-specific network models of ER+ breast cancer identify PI3Kα inhibitor sensitivity factors and drug combinations

Zañudo

Mao

Alcon

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. A promising approach to tackle the cancer drug resistance problem is to build mechanistic mathematical models of the signaling network of cancer cells, and explicitly model the dynamics of information flow through this network under distinct genetic conditions and in response to perturbations. In this work, we use a network-based mathematical model to identify sensitivity factors and drug combinations for the PI3Kα inhibitor Alpelisib, which was recently approved for ER+ PIK3CA mutant breast cancer. We experimentally validate the model-predicted efficacious combination of Alpelisib and BH3 mimetics (e.g. MCL1 inhibitors), and the reduced sensitivity to Alpelisib caused by FOXO3 knockdown, which is a novel potential resistance mechanism. Our experimental results showed cell-line-specific sensitivity to the combination of Alpelisib and BH3 mimetics, which was driven by the choice of BH3 mimetics. We find that cell lines were sensitive to the addition of either MCL1 inhibitor S63845 alone or in combination with BCL-XL/BCL-2 inhibitor Navitoclax, and that the need for the combination of both BH3 mimetics was predicted by the expression of BCL-XL. Based on these results, we developed cell-line specific network models that are able to recapitulate the observed differential response to Alpelisib and BH3 mimetics, and also incorporate the most recent knowledge on resistance and response to PI3Kα inhibitors. In conclusion, we present an approach based on the development, experimental testing, and refining of mathematical models, which we apply to the context of PI3Kα inhibitor drug resistance in breast cancer. Our approach predicted and validated PI3Kα inhibitor sensitivity factors (FOXO3 knockdown) and drug combinations (BH3 mimetics), and illustrates that network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.

show abstract

“…Our present results demonstrated that tamoxifen, fulvestrant and anastrozole were effective against breast cancer cells regardless of ER-α and ER-β expression status, even if the mechanism of action is different for each endocrine therapy agent. BH3 pro ling and dynamic BH3 pro ling have been e ciently used to determine anti-apoptotic BCL-2 protein dependency and to predict therapy response in hematologic malignancies and solid tumors 15,16,24,25 . Even though baseline mitochondrial priming by means of BH3 pro ling failed to provide an e cacious prediction for endocrine therapy response, dynamic BH3 pro ling was more effective.…”

Section: Discussionmentioning

confidence: 99%

Mitochondrial estrogen receptors alter mitochondrial priming and response to endocrine therapy in breast cancer cells.

Kütük

Karakas

Aka

et al. 2021

Preprint

View full text Add to dashboard Cite

Breast cancer is the most common cancer with a high rate of mortality and morbidity among women worldwide. Estrogen receptor status is an important prognostic factor and endocrine therapy is the choice of first-line treatment in ER-positive breast cancer. However, most tumors develop resistance to endocrine therapy. Here we demonstrate that BH3 profiling technology, in particular dynamic BH3 profiling can predict the response to endocrine therapy agents as well as development of acquired resistance in breast cancer cells independent of estrogen receptor status. Immunofluorescence analysis and subcellular fractionation experiments revealed distinct ER-α and ER-β subcellular localization patterns in breast cancer cells, including mitochondrial localization of both receptor subtypes. shRNA-mediated depletion of ER-β in breast cancer cells led to resistance to endocrine therapy agents and selective reconstitution of ER-β in mitochondria restored sensitivity. Notably, mitochondria-targeted ER-α did not restore sensitivity, even conferred further resistance to endocrine therapy agents. In addition, expressing mitochondria-targeted ER-β in breast cancer cells resulted in decreased mitochondrial respiration alongside increased total ROS and mitochondrial superoxide production. Furthermore, our data demonstrated that mitochondrial ER-β can be successfully targeted by the selective. ER-β agonist Erteberel. Thus, our findings provide novel findings on mitochondrial estrogen signaling in breast cancer cells and suggest the implementation of dynamic BH3 technique as a tool to predict acquired endocrine therapy resistance.

show abstract

High-throughput dynamic BH3 profiling may quickly and accurately predict effective therapies in solid tumors

Cited by 48 publications

References 39 publications

Navitoclax enhances the effectiveness of EGFR-targeted antibody-drug conjugates in PDX models of EGFR-expressing triple-negative breast cancer

Navitoclax enhances the effectiveness of EGFR-targeted antibody-drug conjugates in PDX models of EGFR-expressing triple-negative breast cancer

Cell line-specific network models of ER+ breast cancer identify PI3Kα inhibitor sensitivity factors and drug combinations

Mitochondrial estrogen receptors alter mitochondrial priming and response to endocrine therapy in breast cancer cells.

Contact Info

Product

Resources

About