Activation of the tyrosine kinase c-Src promotes breast cancer progression and poor outcome, yet the underlying mechanisms are incompletely understood. Here, we have shown that deleting c-Src in a genetically engineered model mimicking the Luminal B molecular subtype of breast cancer abrogates the activity of Forkhead Box M1 (FOXM1), a master transcriptional regulator of the cell cycle. We determined that c-Src phosphorylates FOXM1 on two tyrosine residues to stimulate its nuclear localization and target gene expression. These included key regulators of G2-M cell cycle progression as well as c-Src itself, forming a positive feedback loop that drove proliferation in genetically engineered and patient-derived models of Luminal B-like breast cancer. Using genetic approaches and small molecules that destabilize the FOXM1 protein, we found that targeting this mechanism induced G2-M cell cycle arrest and apoptosis, blocked tumor progression and impaired metastasis. We identified a positive correlation between FOXM1 and c-Src expression in human breast cancer and showed that the expression of FOXM1 target genes predicts poor outcome and associates with the Luminal B subtype, which responds poorly to approved therapies. These findings have revealed a regulatory network centered on c-Src and FOXM1 that is a targetable vulnerability in aggressive luminal breast cancers.
Breast cancer (BC) exhibits a wide range of morphologic phenotypes and gene expression profiles. Most of the studies that led to the identification of intrinsic molecular subtypes in BC were limited to invasive ductal carcinomas of the breast and did not take rare histopathologic subtypes into account. Rare histopathologic BC subtypes (collectively less than 2% of all breast cancer) have particular prognostic and clinical characteristics. There is no current established treatment that takes into account the specificity of rare BC subtypes. This is mainly due to the absence of clinical trials to determine the optimal management of these rare pathologies. The establishment of relevant preclinical models and molecular characterization of rare BC subtypes is essential for identifying directed and suitable therapeutic regimens for BC patients diagnosed with these rare histopathologic variants. Patient-derived xenograft (PDX) has been recognized as a valuable method to evaluate the clinical diversity of breast cancer. These models were shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, and personalized medicine strategies. We developed a cohort of eight BC rare histopathologic subtypes, including four metaplastic, one adenoid cystic, one IDC pleomorphic, one neuroendocrine, and one mucinous BC subtype. These PDXs and their primary tumors were submitted to whole-genome sequencing (WGS) and RNA sequencing. We also evaluated a total of 255 proteins by reverse phase protein array (RPPA) in these PDX samples. We are currently performing conditional reprogramming experiments to generate cell lines from these rare BC PDXs. Our preliminary results indicate that pathways related to PI3K/AKT, ERK/MAPK, mTOR, HGF, ERBB, AMPK and IL3 signaling are disrupted in rare BC subtypes. Several genes belonging to these pathways are dysregulated in rare BC tumors, and therefore represent potential therapeutic targets for personalized treatment. Citation Format: Hellen Kuasne, Paul Savage, Constanza Martinez Ramirez, Leah Liu, Valentina Muñoz-Ramos, Virginie Pilon, Anie Monast, Radia Johnson, Nicholas Bertos, Jamil Asselah, Nathaniel Bouganim, Kevin Petrecca, Sarkis Meterissian, Atilla Omeroglu, Mark Basik, Morag Park. Establishment and characterization of rare breast patient-derived xenograft models as a potential resource for personalized medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1044.
Invasive breast carcinoma is a combination of heterogeneous diseases with distinct molecular and clinical features. Some subsets of breast cancer present major clinical challenges, including triple-negative, metastatic/recurrent disease and rare breast histologies. Previously, we developed a unique resource of 37 hard-to-treat breast cancer patient-derived xenografts (PDX). This set included mainly triple negative breast cancer (TNBC) patients that presented poor response to neoadjuvant chemotherapies (Savage et al. 2020 - PMID: 32546838). PDXs accurately reproduce the molecular heterogeneity of the primary tumors and show that multi-drug chemoresistance was retained upon xenotransplantation. Here, we present the characterization of PDX 3-dimensional cultures organoids (8) and PDX derived epithelial cell lines (11). Using single-cell RNAseq we showed that an organoid cultured for several passages (P8) maintained the heterogeneity of the matched PDX. Although in different proportions, all cancer cell populations found in the PDX were retained in matched organoids supporting that organoids are suitable models that recapitulates the tumor heterogeneity and are therefore a suitable model for drug screening. Among our new PDXs models (30), we have developed four PDXs from rare metaplastic breast cancers (MpBC), an aggressive subtype of breast cancer that present the poorest response to standard of care chemotherapy. We also developed one male breast cancer PDX with matched organoid. Omic analysis on our pre-clinical models and patient primary tumor and metastasis will inform development of therapeutic opportunities. This molecular information will guide selection of compounds that will be validated using our high throughput organoid drug screening pipeline. This will allow rapid screens of thousands of approved drugs, enhancing drug repurposing with potential for rapid clinical translation. The combined use of 3D tumor organoids and PDXs, is an important opportunity poised to transform identification of new therapeutic options for hard-to-treat lethal breast cancers. Citation Format: Hellen Kuasne, Anne-Marie fortier, Sandrine Busque, Simon Mathien, Paul Savage, Constanza Martinez Ramirez, Anie Monast, Margarita Soleinova, Atilla Omeroglu, Jamil Asselah, Nathaniel Bouganim, Sarkis Meterissian, Mark Basik, Morag Park. Development and molecular characterization of hard-to-treat breast cancer pre-clinical models to enhance precision medicine [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-08-09.
Despite major advances in the treatment of breast cancer (BC), it remains the most diagnosed and second most deadly cancer among American women. BC is a heterogeneous disease consisting of distinct subtypes, including hormone receptor-positive, HER2 receptor-positive and cancers that lack these receptors categorized as triple-negative breast cancers (TNBC). The TNBC subtype presents the worst outcome and the highest rates of recurrence and metastasis. The absence of targets prevents the use of established precision therapies in TNBC, and the standard of care remains neoadjuvant chemotherapy. While this is effective in some patients, about 50% develop resistance, leading to the development of metastasis. It is known that selective pressures exerted by chemotherapy treatment can promote the outgrowth of resistant tumor subclones. However, the diverse intra-tumoral population and the mechanisms that lead to chemotherapy resistance in TNBC are still poorly understood. We hypothesized that therapeutic regimens influence tumor plasticity by exerting selective pressures leading to the outgrowth of resistant subpopulations with the greatest survival advantage. To evaluate this hypothesis, we aimed to generate in vivo models of chemotherapy resistance and to investigate the plasticity of tumor cell subpopulations challenged with standard-of-care chemotherapies. To this end, we selected a multi-drug resistant (Doxorubicin, Cyclophosphamide, Cisplatin, and Paclitaxel) BC patient and developed a patient-derived xenograft (PDX) from the primary tumor and the lung metastasis. The metastasis PDX model was initially responsive to Gemcitabine (as observed in the BC patient) but eventually developed resistance. We challenged this metastasis PDX with several cycles of Gemcitabine and obtained residual, rebound, and resistant tumor samples. We performed single-cell RNA sequencing (scRNAseq) of these models using a droplet-based technology from 10X Genomics. This scRNAseq data was used to compare the changes in the proportions of cellular subpopulations in each model. Interestingly, our data shows that the rebound model presents greater similarity to the untreated metastasis, while the resistant model has significant differences in cell population expression profiles. We identified a hypoxic population in the primary tumor and its matched metastasis. This population was validated in these models by Nanostring GeoMx Digital Spatial Profiler. Our recent analyses have identified that this hypoxic population persists in the residual, rebound and resistant models. In addition, we have identified other populations that vary in these models. We are currently investigating their cellular mechanisms and gene expression patterns. Using scRNA-sequencing to understand the clonal expansion of resistant subpopulations following chemotherapy reveals distinctive resistant cell features enabling the identification of the vulnerabilities of these tumors. Citation Format: Sandrine Busque, Constanza Martinez Ramirez, Hellen Kuasne, Paul Savage, Anne-Marie Fortier, Anie Monast, Atilla Omeroglu, Jamil Asselah, Nathaniel Bouganim, Sarkis Meterissian, Claudia Kleinman, Mark Basik, Morag Park. Identification of gemcitabine-resistant populations using scRNA-sequencing in triple negative breast cancer patient-derived xenograft [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr A033.
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