Exploring complex modularization of intracellular signal transduction pathways is critical to understanding aberrant cellular responses during disease development and drug treatment. IMPALA (Inferred ...Modularization of PAthway LAndscapes) integrates information from high throughput gene expression experiments and genome-scale knowledge databases to identify aberrant pathway modules, thereby providing a powerful sampling strategy to reconstruct and explore pathway landscapes. Here IMPALA identifies pathway modules associated with breast cancer recurrence and Tamoxifen resistance. Focusing on estrogen-receptor (ER) signaling, IMPALA identifies alternative pathways from gene expression data of Tamoxifen treated ER positive breast cancer patient samples. These pathways were often interconnected through cytoplasmic genes such as IRS1/2, JAK1, YWHAZ, CSNK2A1, MAPK1 and HSP90AA1 and significantly enriched with ErbB, MAPK, and JAK-STAT signaling components. Characterization of the pathway landscape revealed key modules associated with ER signaling and with cell cycle and apoptosis signaling. We validated IMPALA-identified pathway modules using data from four different breast cancer cell lines including sensitive and resistant models to Tamoxifen. Results showed that a majority of genes in cell cycle/apoptosis modules that were up-regulated in breast cancer patients with short survivals (< 5 years) were also over-expressed in drug resistant cell lines, whereas the transcription factors JUN, FOS, and STAT3 were down-regulated in both patient and drug resistant cell lines. Hence, IMPALA identified pathways were associated with Tamoxifen resistance and an increased risk of breast cancer recurrence. The IMPALA package is available at https://dlrl.ece.vt.edu/software/ .
Optimising breast cancer treatment remains a challenge. Resistance to therapy is a major problem in both ER- and ER+ breast cancer. Tumour recurrence after chemotherapy and/or targeted therapy leads ...to more aggressive tumours with enhanced metastatic ability. Self-renewing cancer stem cells (CSCs) have been implicated in treatment resistance, recurrence and the development of metastatic disease.
In this study, we utilised in vitro, in vivo and ex vivo breast cancer models using ER+ MCF-7 and ER- MDA-MB-231 cells, as well as solid and metastatic breast cancer patient samples, to interrogate the effects of FKBPL and its peptide therapeutics on metastasis, endocrine therapy resistant CSCs and DLL4 and Notch4 expression. The effects of FKBPL overexpression or peptide treatment were assessed using a t-test or one-way ANOVA with Dunnett's multiple comparison test.
We demonstrated that FKBPL overexpression or treatment with FKBPL-based therapeutics (AD-01, pre-clinical peptide /ALM201, clinical peptide) inhibit i) CSCs in both ER+ and ER- breast cancer, ii) cancer metastasis in a triple negative breast cancer metastasis model and iii) endocrine therapy resistant CSCs in ER+ breast cancer, via modulation of the DLL4 and Notch4 protein and/or mRNA expression. AD-01 was effective at reducing triple negative MDA-MB-231 breast cancer cell migration (n ≥ 3, p < 0.05) and invasion (n ≥ 3, p < 0.001) and this was translated in vivo where AD-01 inhibited breast cancer metastasis in MDA-MB-231-lucD3H1 in vivo model (p < 0.05). In ER+ MCF-7 cells and primary breast tumour samples, we demonstrated that ALM201 inhibits endocrine therapy resistant mammospheres, representative of CSC content (n ≥ 3, p < 0.05). Whilst an in vivo limiting dilution assay, using SCID mice, demonstrated that ALM201 alone or in combination with tamoxifen was very effective at delaying tumour recurrence by 12 (p < 0.05) or 21 days (p < 0.001), respectively, by reducing the number of CSCs. The potential mechanism of action, in addition to CD44, involves downregulation of DLL4 and Notch4.
This study demonstrates, for the first time, the pre-clinical activity of novel systemic anti-cancer therapeutic peptides, ALM201 and AD-01, in the metastatic setting, and highlights their impact on endocrine therapy resistant CSCs; both areas of unmet clinical need.
Pathways involved in DCIS stem and progenitor signalling are poorly understood yet are critical to understand DCIS biology and to develop new therapies. Notch and ErbB1/2 receptor signalling cross ...talk has been demonstrated in invasive breast cancer, but their role in DCIS stem and progenitor cells has not been investigated. We have utilised 2 DCIS cell lines, MCF10DCIS.com (ErbB2-normal) and SUM225 (ErbB2-overexpressing) and 7 human primary DCIS samples were cultured in 3D matrigel and as mammospheres in the presence, absence or combination of the Notch inhibitor, DAPT, and ErbB1/2 inhibitors, lapatinib or gefitinib. Western blotting was applied to assess downstream signalling. In this study we demonstrate that DAPT reduced acini size and mammosphere formation in MCF10DCIS.com whereas there was no effect in SUM225. Lapatinb reduced acini size and mammosphere formation in SUM225, whereas mammosphere formation and Notch1 activity were increased in MCF10DCIS.com. Combined DAPT/lapatinib treatment was more effective at reducing acini size in both DCIS cell lines. Mammosphere formation in cell lines and human primary DCIS was reduced further by DAPT/lapatinib or DAPT/gefitinib regardless of ErbB2 receptor status. Our pre-clinical human models of DCIS demonstrate that Notch and ErbB1/2 both play a role in DCIS acini growth and stem cell activity. We report for the first time that cross talk between the two pathways in DCIS occurs regardless of ErbB2 receptor status and inhibition of Notch and ErbB1/2 was more efficacious than either alone. These data provide further understanding of DCIS biology and suggest treatment strategies combining Notch and ErbB1/2 inhibitors should be investigated regardless of ErbB2 receptor status.
Breast cancer is one of the most prevalent cancers in women, with more than 240,000 new cases reported in the United States in 2011. Classification of breast cancer based upon hormone and growth ...factor receptor profiling shows that approximately 70% of all breast cancers express estrogen receptor-α. Thus, drugs that either block estrogen biosynthesis (aromatase inhibitors like Letrozole), or compete with estrogen for estrogen receptor (ER) binding (selective ER modulators including tamoxifen; TAM) and/or cause ER degradation (selective estrogen receptor downregulators such as fulvestrant), are among the most prescribed targeted therapeutics for breast cancer. However, overall clinical benefit from the use of these drugs is often limited by resistance; ER
+
breast cancers either fail to respond to endocrine therapies initially (de novo resistance), or they respond and then lose sensitivity over time (acquired resistance). While several preclinical studies postulate how antiestrogen resistance occurs, for the most part, the molecular mechanism(s) of resistance is unknown.
Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational ...preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and “Triple-negative” (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward “credentialing” of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.
Abstract
De novo transcriptome assembly from billions of RNA-seq reads is very challenging due to alternative splicing and various levels of expression, which often leads to incorrect, mis-assembled ...transcripts. BayesDenovo addresses this problem by using both a read-guided strategy to accurately reconstruct splicing graphs from the RNA-seq data and a Bayesian strategy to estimate, from these graphs, the probability of transcript expression without penalizing poorly expressed transcripts. Simulation and cell line benchmark studies demonstrate that BayesDenovo is very effective in reducing false positives and achieves much higher accuracy than other assemblers, especially for alternatively spliced genes and for highly or poorly expressed transcripts. Moreover, BayesDenovo is more robust on multiple replicates by assembling a larger portion of common transcripts. When applied to breast cancer data, BayesDenovo identifies phenotype-specific transcripts associated with breast cancer recurrence.
Notch signaling regulates normal stem cells and is also thought to regulate cancer stem cells (CSCs). Recent data indicate that Notch signaling plays a role in the development and progression of ...osteosarcoma, however the regulation of Notch in chemo-resistant stem-like cells has not yet been fully elucidated. In this study we generated cisplatin-resistant osteosarcoma cells by treating them with sub-lethal dose of cisplatin, sufficient to induce DNA damage responses. Cisplatin-resistant osteosarcoma cells exhibited lower proliferation, enhanced spheroid formation and more mesenchymal characteristics than cisplatin-sensitive cells, were enriched for Stro-1+/CD117+ cells and showed increased expression of stem cell-related genes. A similar effect was observed in vivo, and in addition in vivo tumorigenicity was enhanced during serial transplantation. Using several publicly available datasets, we identified that Notch expression was closely associated with osteosarcoma stem cells and chemotherapy resistance. We confirmed that cisplatin-induced enrichment of osteosarcoma stem cells was mediated through Notch signaling in vitro, and immunohistochemistry showed that cleaved Notch1 (NICD1) positive cells were significantly increased in a relapsed xenograft which had received cisplatin treatment. Furthermore, pretreatment with a γ-secretase inhibitor (GSI) to prevent Notch signalling inhibited cisplatin-enriched osteosarcoma stem cell activity in vitro, including Stro-1+/CD117+ double positive cells and spheroid formation capacity. The Notch inhibitor DAPT also prevented tumor recurrence in resistant xenograft tumors. Overall, our results show that cisplatin induces the enrichment of osteosarcoma stem-like cells through Notch signaling, and targeted inactivation of Notch may be useful for the elimination of CSCs and overcoming drug resistance.
The majority of estrogen receptor (ER)-positive breast cancers are treated with endocrine therapy. While this is effective, acquired resistance to therapies targeted against ER is a major clinical ...challenge. Here, model systems of ER-positive breast cancers with differential susceptibility to endocrine therapy were employed to define common nodes for new therapeutic interventions. These analyses revealed that cell cycle progression is effectively uncoupled from the activity and functional state of ER in these models. In this context, cyclin D1 expression and retinoblastoma tumor suppressor protein (RB) phosphorylation are maintained even with efficient ablation of ER with pure antagonists. These therapy-resistant models recapitulate a key feature of deregulated RB/E2F transcriptional control. Correspondingly, a gene expression signature of RB-dysfunction is associated with luminal B breast cancer, which exhibits a relatively poor response to endocrine therapy. These collective findings suggest that suppression of cyclin D-supported kinase activity and restoration of RB-mediated transcriptional repression could represent a viable therapeutic option in tumors that fail to respond to hormone-based therapies. Consistent with this hypothesis, a highly selective CDK4/6 inhibitor, PD-0332991, was effective at suppressing the proliferation of all hormone refractory models analyzed. Importantly, PD-0332991 led to a stable cell cycle arrest that was fundamentally distinct from those elicited by ER antagonists, and was capable of inducing aspects of cellular senescence in hormone therapy refractory cell populations. These findings underscore the clinical utility of downstream cytostatic therapies in treating tumors that have experienced failure of endocrine therapy.
This review provides an overview of the progress made by computational and systems biologists in characterizing different cell death regulatory mechanisms that constitute the cell death network. We ...define the cell death network as a comprehensive decision-making mechanism that controls multiple death execution molecular circuits. This network involves multiple feedback and feed-forward loops and crosstalk among different cell death-regulating pathways. While substantial progress has been made in characterizing individual cell death execution pathways, the cell death decision network is poorly defined and understood. Certainly, understanding the dynamic behavior of such complex regulatory mechanisms can be only achieved by applying mathematical modeling and system-oriented approaches. Here, we provide an overview of mathematical models that have been developed to characterize different cell death mechanisms and intend to identify future research directions in this field.
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