Browsing by Author "Shajahan-Haq, Ayesha N."
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- ChIP-BIT: Bayesian inference of target genes using a novel joint probabilistic model of ChIP-seq profilesChen, Xi; Jung, Jin-Gyoung; Shajahan-Haq, Ayesha N.; Clarke, Robert; Shih, Ie-Ming; Wang, Yue; Magnani, Luca; Wang, Tian-Li; Xuan, Jianhua (Oxford, 2015-12-23)Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-seq) has greatly improved the reliability with which transcription factor binding sites (TFBSs) can be identified from genome-wide profiling studies. Many computational tools are developed to detect binding events or peaks, however the robust detection of weak binding events remains a challenge for current peak calling tools. We have developed a novel Bayesian approach (ChIP-BIT) to reliably detect TFBSs and their target genes by jointly modeling binding signal intensities and binding locations of TFBSs. Specifically, a Gaussian mixture model is used to capture both binding and background signals in sample data. As a unique feature of ChIP-BIT, background signals are modeled by a local Gaussian distribution that is accurately estimated from the input data. Extensive simulation studies showed a significantly improved performance of ChIP-BIT in target gene prediction, particularly for detecting weak binding signals at gene promoter regions. We applied ChIP-BIT to find target genes from NOTCH3 and PBX1 ChIP-seq data acquired from MCF-7 breast cancer cells. TF knockdown experiments have initially validated about 30% of co-regulated target genes identified by ChIP-BIT as being differentially expressed in MCF-7 cells. Functional analysis on these genes further revealed the existence of crosstalk between Notch and Wnt signaling pathways.
- Glutamine Metabolism Drives Growth in Advanced Hormone Receptor Positive Breast CancerDemas, Diane M.; Demo, Susan; Fallah, Yassi; Clarke, Robert; Nephew, Kenneth P.; Althouse, Sandra; Sandusky, George; He, Wei; Shajahan-Haq, Ayesha N. (Frontiers, 2019-08-02)Dependence on the glutamine pathway is increased in advanced breast cancer cell models and tumors regardless of hormone receptor status or function. While 70% of breast cancers are estrogen receptor positive (ER+) and depend on estrogen signaling for growth, advanced ER+ breast cancers grow independent of estrogen. Cellular changes in amino acids such as glutamine are sensed by the mammalian target of rapamycin (mTOR) complex, mTORC1, which is often deregulated in ER+ advanced breast cancer. Inhibitor of mTOR, such as everolimus, has shown modest clinical activity in ER+ breast cancers when given with an antiestrogen. Here we show that breast cancer cell models that are estrogen independent and antiestrogen resistant are more dependent on glutamine for growth compared with their sensitive parental cell lines. Co-treatment of CB-839, an inhibitor of GLS, an enzyme that converts glutamine to glutamate, and everolimus interrupts the growth of these endocrine resistant xenografts. Using human tumor microarrays, we show that GLS is significantly higher in human breast cancer tumors with increased tumor grade, stage, ER-negative and progesterone receptor (PR) negative status. Moreover, GLS levels were significantly higher in breast tumors from African-American women compared with Caucasian women regardless of ER or PR status. Among patients treated with endocrine therapy, high GLS expression was associated with decreased disease free survival (DFS) from a multivariable model with GLS expression treated as dichotomous. Collectively, these findings suggest a complex biology for glutamine metabolism in driving breast cancer growth. Moreover, targeting GLS and mTOR in advanced breast cancer may be a novel therapeutic approach in advanced ER+ breast cancer.
- Mathematical modelling of breast cancer cells in response to endocrine therapy and Cdk4/6 inhibitionHe, Wei; Demas, Diane M.; Conde, Isabel P.; Shajahan-Haq, Ayesha N.; Baumann, William T. (2020-08-26)Oestrogen receptor (ER)-positive breast cancer is responsive to a number of targeted therapies used clinically. Unfortunately, the continuous application of any targeted therapy often results in resistance to the therapy. Our ultimate goal is to use mathematical modelling to optimize alternating therapies that not only decrease proliferation but also stave off resistance. Toward this end, we measured levels of key proteins and proliferation over a 7-day time course in ER+ MCF-7 breast cancer cells. Treatments included endocrine therapy, either oestrogen deprivation, which mimics the effects of an aromatase inhibitor, or fulvestrant, an ER degrader. These data were used to calibrate a mathematical model based on key interactions between ER signalling and the cell cycle. We show that the calibrated model is capable of predicting the combination treatment of fulvestrant and oestrogen deprivation. Further, we show that we can add a new drug, palbociclib, to the model by measuring only two key proteins, cMyc and hyperphosphorylated RB1, and adjusting only parameters associated with the drug. The model is then able to predict the combination treatment of oestrogen deprivation and palbociclib. We illustrate the model's potential to explore protocols that limit proliferation and hold off resistance by not depending on any one therapy.
- Targeting WEE1 Inhibits Growth of Breast Cancer Cells That Are Resistant to Endocrine Therapy and CDK4/6 InhibitorsFallah, Yassi; Demas, Diane M.; Jin, Lu; He, Wei; Shajahan-Haq, Ayesha N. (2021-07-01)Despite the success of antiestrogens in extending overall survival of patients with estrogen receptor positive (ER+) breast tumors, resistance to these therapies is prevalent. ER+ tumors that progress on antiestrogens are treated with antiestrogens and CDK4/6 inhibitors. However, 20% of these tumors never respond to CDK4/6 inhibitors due to intrinsic resistance. Here, we used endocrine sensitive ER+ MCF7 and T47D breast cancer cells to generate long-term estrogen deprived (LTED) endocrine resistant cells that are intrinsically resistant to CDK4/6 inhibitors. Since treatment with antiestrogens arrests cells in the G1 phase of the cell cycle, we hypothesized that a defective G1 checkpoint allows resistant cells to escape this arrest but increases their dependency on G2 checkpoint for DNA repair and growth, and hence, targeting the G2 checkpoint will induce cell death. Indeed, inhibition of WEE1, a crucial G2 checkpoint regulator, with AZD1775 (Adavosertib), significantly decreased cell proliferation and increased G2/M arrest, apoptosis and gamma-H2AX levels (a marker for DNA double stranded breaks) in resistant cells compared with sensitive cells. Thus, targeting WEE1 is a promising anti-cancer therapeutic strategy in standard therapy resistant ER+ breast cancer.