Amy E Schade, Naiara Perurena, Yoona Yang, Carrie L Rodriguez, Anjana Krishnan, Alycia Gardner, Patrick Loi, Yilin Xu, Van T M Nguyen, G M Mastellone, Natalie F Pilla, Marina Watanabe, Keiichi Ota, Rachel A Davis, Kaia Mattioli, Dongxi Xiang, Jason J Zoeller, Jia-Ren Lin, Stefania Morganti, Ana C Garrido-Castro, Sara M Tolaney, Zhe Li, David A Barbie, Peter K Sorger, Kristian Helin, Sandro Santagata, Simon R V Knott, Karen Cichowski
{"title":"AKT and EZH2 inhibitors kill TNBCs by hijacking mechanisms of involution.","authors":"Amy E Schade, Naiara Perurena, Yoona Yang, Carrie L Rodriguez, Anjana Krishnan, Alycia Gardner, Patrick Loi, Yilin Xu, Van T M Nguyen, G M Mastellone, Natalie F Pilla, Marina Watanabe, Keiichi Ota, Rachel A Davis, Kaia Mattioli, Dongxi Xiang, Jason J Zoeller, Jia-Ren Lin, Stefania Morganti, Ana C Garrido-Castro, Sara M Tolaney, Zhe Li, David A Barbie, Peter K Sorger, Kristian Helin, Sandro Santagata, Simon R V Knott, Karen Cichowski","doi":"10.1038/s41586-024-08031-6","DOIUrl":null,"url":null,"abstract":"<p><p>Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and has the highest rate of recurrence<sup>1</sup>. The predominant standard of care for advanced TNBC is systemic chemotherapy with or without immunotherapy; however, responses are typically short lived<sup>1,2</sup>. Thus, there is an urgent need to develop more effective treatments. Components of the PI3K pathway represent plausible therapeutic targets; more than 70% of TNBCs have alterations in PIK3CA, AKT1 or PTEN<sup>3-6</sup>. However, in contrast to hormone-receptor-positive tumours, it is still unclear whether or how triple-negative disease will respond to PI3K pathway inhibitors<sup>7</sup>. Here we describe a promising AKT-inhibitor-based therapeutic combination for TNBC. Specifically, we show that AKT inhibitors synergize with agents that suppress the histone methyltransferase EZH2 and promote robust tumour regression in multiple TNBC models in vivo. AKT and EZH2 inhibitors exert these effects by first cooperatively driving basal-like TNBC cells into a more differentiated, luminal-like state, which cannot be effectively induced by either agent alone. Once TNBCs are differentiated, these agents kill them by hijacking signals that normally drive mammary gland involution. Using a machine learning approach, we developed a classifier that can be used to predict sensitivity. Together, these findings identify a promising therapeutic strategy for this highly aggressive tumour type and illustrate how deregulated epigenetic enzymes can insulate tumours from oncogenic vulnerabilities. These studies also reveal how developmental tissue-specific cell death pathways may be co-opted for therapeutic benefit.</p>","PeriodicalId":50,"journal":{"name":"Langmuir","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Langmuir","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41586-024-08031-6","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype and has the highest rate of recurrence1. The predominant standard of care for advanced TNBC is systemic chemotherapy with or without immunotherapy; however, responses are typically short lived1,2. Thus, there is an urgent need to develop more effective treatments. Components of the PI3K pathway represent plausible therapeutic targets; more than 70% of TNBCs have alterations in PIK3CA, AKT1 or PTEN3-6. However, in contrast to hormone-receptor-positive tumours, it is still unclear whether or how triple-negative disease will respond to PI3K pathway inhibitors7. Here we describe a promising AKT-inhibitor-based therapeutic combination for TNBC. Specifically, we show that AKT inhibitors synergize with agents that suppress the histone methyltransferase EZH2 and promote robust tumour regression in multiple TNBC models in vivo. AKT and EZH2 inhibitors exert these effects by first cooperatively driving basal-like TNBC cells into a more differentiated, luminal-like state, which cannot be effectively induced by either agent alone. Once TNBCs are differentiated, these agents kill them by hijacking signals that normally drive mammary gland involution. Using a machine learning approach, we developed a classifier that can be used to predict sensitivity. Together, these findings identify a promising therapeutic strategy for this highly aggressive tumour type and illustrate how deregulated epigenetic enzymes can insulate tumours from oncogenic vulnerabilities. These studies also reveal how developmental tissue-specific cell death pathways may be co-opted for therapeutic benefit.
期刊介绍:
Langmuir is an interdisciplinary journal publishing articles in the following subject categories:
Colloids: surfactants and self-assembly, dispersions, emulsions, foams
Interfaces: adsorption, reactions, films, forces
Biological Interfaces: biocolloids, biomolecular and biomimetic materials
Materials: nano- and mesostructured materials, polymers, gels, liquid crystals
Electrochemistry: interfacial charge transfer, charge transport, electrocatalysis, electrokinetic phenomena, bioelectrochemistry
Devices and Applications: sensors, fluidics, patterning, catalysis, photonic crystals
However, when high-impact, original work is submitted that does not fit within the above categories, decisions to accept or decline such papers will be based on one criteria: What Would Irving Do?
Langmuir ranks #2 in citations out of 136 journals in the category of Physical Chemistry with 113,157 total citations. The journal received an Impact Factor of 4.384*.
This journal is also indexed in the categories of Materials Science (ranked #1) and Multidisciplinary Chemistry (ranked #5).