Biology subjects

Campone, M.

Publications and source records attributed to Campone, M..

6 recordsLinked to original sources

bioRxiv2025

MCL-1 as a molecular switch between myofibroblastic and pro-angiogenic features of breast cancer-associated fibroblasts

Breast cancer-associated fibroblasts (bCAFs) comprise inflammatory CAFs (iCAFs), characterized by the secretion of pro-inflammatory cytokines, and myofibroblastic CAFs (myCAFs), distinguished by their high production of extracellular matrix and their immunosuppressive properties. We previously showed that targeting the anti-apoptotic protein MCL-1 in primary culture of bCAF derived directly from human samples reduces their myofibroblastic characteristics. We herein show by single-cell RNA-sequencing analysis of bCAFs that MCL-1 knock down induces a phenotypic shift from wound-myCAF to IL-iCAF, characterized by the upregulation of genes associated with inflammation as well as angiogenesis-related genes. In vitro, genetic and pharmacologic MCL-1 inhibition increases VEGF secretion by bCAFs, enhancing endothelial cell tubulogenesis. In a chicken chorioallantoic membrane (CAM) model in ovo, co-engraftment of breast cancer cells and bCAFs with reduced MCL-1 expression leads to heightened peritumoral vascular density, driven by VEGF. Mechanistically, the pro-angiogenic phenotype revealed by MCL-1 inhibition is dependent on BAX-BAK activity. It results in NF-{kappa}B activation, inhibition of which by a IKK{beta} inhibitor suppresses the transcription of VEGF and pro-inflammatory factors triggered by MCL-1 inhibition in bCAFs. Chemotherapy induces a downregulation of MCL-1 in bCAFs and it promotes a pro-angiogenic phenotype, counteracted by overexpressed MCL-1. Overall, these findings uncover a novel regulatory function of MCL-1 in determining bCAF subpopulation differentiation and highlight its role in modulating their pro-angiogenic properties, in response to treatment in particular.

cancer biology↗

bioRxiv2024

Primary cilia promote EMT-induced triple-negative breast tumor heterogeneity and resistance to therapy

Tumor heterogeneity and plasticity, driven by Epithelial-Mesenchymal Transition (EMT), enable cancer therapeutic resistance. We previously showed that EMT promotes primary cilia formation, which enables stemness and tumorigenesis in triple-negative breast cancer (TNBC). Here, we establish a role for primary cilia in human TNBC chemotherapeutic resistance. We developed patient-derived organoids, and showed that these recapitulated the cellular heterogeneity of TNBC biopsies. Notably, one of the identified cell states bore a quasi-mesenchymal phenotype, primary cilia, and stemness signatures. We treated our TNBC organoids with chemotherapeutics and observed partial killing. The surviving cells with organoid-reconstituting capacity showed selective enrichment for the quasi-mesenchymal ciliated cell subpopulation. Genomic analyses argue that this enrichment reflects a combination of pre-existing cells and ones that arose through drug-induced cellular plasticity. We developed a family of small-molecule inhibitors of ciliogenesis and show that these, or genetic ablation of primary cilia, suppress chemoresistance. We conclude that primary cilia help TNBC to evade chemotherapy. SignificanceCancer cells that activate EMT to acquire a quasi-mesenchymal state form primary cilia to evade chemotherapy in human triple-negative breast cancer. Pharmacological inhibition of primary ciliogenesis counteracts EMT-induced chemoresistance.

cancer biology↗

bioRxiv2023

NOXA/MCL-1 axis determines cell-death decision between apoptosis and pyroptosis and the inflammatory secretome of breast cancer cells treated with anti-mitotics.

Understanding how the malignant cells respond to chemotherapy is essential to prevent the development of resistance and to improve the efficiency of anti-cancer drugs. Recently, we established that, by intrinsic and paracrine mechanisms, taxol treatment in breast tumor cells increases NOXA a pro-apoptotic protein functioning as an endogenous inhibitor of survival protein MCL-1, thereby enhancing cytotoxic load on the compensatory survival protein BCL-xL. We herein sought to define the contribution of NOXA/MCL-1 to the modality of cell death secretome composition upon anti-mitotic treatment associated with a BCL-xL antagonist. We observed that genetic inactivation of NOXA (enforcing MCL-1 pro-survival activity) in cancer cells not only delays their death when exposed to taxol in combination with the BCL-xL antagonist A1331852, but also alters its morphological characteristics with the apparition of features evoking pyroptosis. We identified the Caspase3-GSDME axis as regulating pyroptotic-like features suggesting that NOXA may act as a negative regulator of this cell death process (and MCL-1 as a positive regulator for it). Furthermore, comparative analysis of secretomes from the NOXA proficient or deficient cancer cells treated by taxol reveals variations in inflammatory cytokine production including those of IL-1{beta} and IL-18. Thus, our results show that anti-mitotic treatments are able to induce death by apoptosis and/or pyroptosis depending on BCL-2 family balance in breast cancer cells. Furthermore, NOXA/MCL-1 ratio appears to control the communication between these two types of cell death and their associated extracellular inflammatory signals in coordination with the pore-forming gasdermin GSDME.

cancer biology↗

bioRxiv2023

Cancer associated fibroblasts mitigate the efficacy of the combination treatment of chemotherapy and BCL-xL targeting in triple negative breast cancer cells

Triple negative breast cancers (TNBC) present a poor prognosis primarily due to their resistance to chemotherapy. This resistance is understood to associate with elevated expression of certain antiapoptotic members within the proteins of the BCL-2 family (namely BCL-xL, MCL-1 and BCL-2). These regulate cell death by inhibiting pro-apoptotic protein activation through binding and sequestration and they can be selectively antagonized by BH3 mimetics. Yet the individual influences of BCL-xL, MCL-1, and BCL-2 on the sensitivity of TNBC cells to chemotherapy, and their regulation by cancer-associated fibroblasts (CAFs), major components of the tumor stroma and key contributors to therapy resistance remain to be delineated. By utilizing engineered TNBC cell line MDA-MB-231 deficient in BCL-2 family proteins and BH3 mimetics, we show that BCL-xL and MCL-1 promote cancer cell survival by compensatory mechanisms. This cell line shows limited sensitivity to chemotherapy, in line with the clinical resistance observed in TNBC patients. We elucidate that BCL-xL plays a pivotal role in therapy response, as its depletion or pharmacological inhibition heightened chemotherapy effectiveness. Moreover, BCL-xL expression is associated to chemotherapy resistance in patient-derived tumoroids where its pharmacological inhibition enhances ex vivo response to chemotherapy. In a co-culture model of cancer cells and CAFs, we observe that even in a context where BCL-xL inhibition renders cancer cells more susceptible to chemotherapy, those in contact with CAFs display reduced sensitivity to chemotherapy. Thus CAFs exert a profound pro-survival effect in breast cancer cells, even in a setting highly favoring cell death through combined chemotherapy and inhibition of the main actor of chemoresistance, BCL-xL.

cancer biology↗

bioRxiv2021

Targeting of MCL-1 in breast cancer associated fibroblasts reverses their myofibroblastic phenotype and pro-invasive properties

Cancer associated fibroblasts (CAF) are a major cellular component of epithelial tumors. In breast cancers in particular these stromal cells have numerous tumorigenic effects in part due to their acquisition of a myofibroblastic phenotype. Breast CAFs (bCAFS) typically express MCL-1. We show here that targeting this regulator of mitochondrial integrity using a specific BH-3 mimetic promotes fragmentation of these organelles without inducing cell death. MCL-1 antagonism in primary bCAFs directly derived from human samples mitigates myofibroblastic features and decreases expression of genes involved in actomyosin organization and contractility, associated with a cytoplasmic retention of the transcriptional regulator, Yes-Associated Protein (YAP). Such treatment decreases bCAFs ability to promote cancer cells invasion in 3D co-culture assays. These effects are counteracted by an inhibitor of the mitochondrial fission protein DRP-1, which interacts with MCL-1 upon BH3 mimetic treatment. Our findings underscore the usefulness of targeting MCL-1 in breast cancer ecosystems, not only to favor death of cancer cells but also to counteract the tumorigenic activation of fibroblasts with which they co-evolve. The authors declare no conflict of interest.

cancer biology↗

bioRxiv2020

Development of an absolute assignment predictor for triple-negative breast cancer subtyping using machine learning approaches

Triple-negative breast cancer (TNBC) heterogeneity represents one of the main impediment to precision medicine for this disease. Recent concordant transcriptomics studies have shown that TNBC could be splitted into at least three subtypes with potential therapeutic implications. Although, a few studies have been done to predict TNBC subtype by means of transcriptomics data, subtyping was partially sensitive and limited by batch effect and dependence to a given dataset, which may penalize the switch to routine diagnostic testing. Therefore, we sought to build an absolute predictor (i.e. intra-patient diagnosis) based on machine learning algorithm with a limited number of probes. To this end, we started by introducing probe binary comparison for each patient (indicators). We based predictive analysis on this transformed data. Probe selection was first performed by combining both filter and wrapper methods for variable selection using cross validation. We thus tested three prediction models (random forest, gradient boosting [GB] and extreme gradient boosting) using this optimal subset of indicators as inputs. Nested cross-validation allowed us to consistently choose the best model. Results showed that the 50 selected indicators highlighted biological characteristics associated with each TNBC subtype. The GB based on this subset of indicators has better performances as compared to the other models.

bioinformatics↗