Manjusha Thakar

Decitabine induces delayed reactive oxygen species (ROS) accumulation in leukemia cells and induces the expression of ROS generating enzymes

Purpose: Azanucleoside DNA methyltransferase (DNMT) inhibitors are currently approved by the U.S. Food and Drug Administration for treatment of myelodysplastic syndrome. The relative contributions of DNMT inhibition and other off-target effects to their clinical efficacy remain unclear. Data correlating DNA methylation reversal and clinical response have been conflicting. Consequently, it is necessary to investigate so-called off-target effects and their impact on cell survival and differentiation. Experimental Design: Flow cytometry was used for cell cycle, apoptosis, and reactive oxygen species (ROS) accumulation analysis. Gene expression analysis was performed using real-time PCR. DNA methylation was detected by methylation-specific PCR. Mitochondrial membrane potential was analyzed using JC-1 dye staining. Western blotting was used for quantitative protein expression analysis. Results: 5-Aza-2′-deoxycytidine (DAC) induced cell-cycle arrest and apoptosis in leukemia cells. p53 expression was dispensable for DAC-induced apoptosis. DAC induced delayed ROS accumulation in leukemia cells but not in solid tumor cells and p53 expression was dispensable for ROS increase. ROS increase was deoxycytidine kinase dependent, indicating that incorporation of DAC into nuclear DNA is required for ROS generation. ROS accumulation by DAC was caspase-independent and mediated the dissipation of the mitochondrial membrane potential. Concordantly, ROS scavengers diminished DAC-induced apoptosis. DAC induced the expression of different NADPH oxidase isoforms and upregulated Nox4 protein expression in an ATM-dependent manner, indicating the involvement of DNA damage signaling in Nox4 upregulation. Conclusion: These data highlight the importance of mechanisms other than DNA cytosine demethylation in modulating gene expression and suggest investigating the relevance of ROS accumulation to the clinical activity of DAC. Clin Cancer Res; 20(5); 1249–58. ©2014 AACR.

Decreased SMAD4 expression is associated with induction of epithelial-to-mesenchymal transition and cetuximab resistance in head and neck squamous cell carcinoma

Epidermal growth factor receptor (EGFR) is frequently overexpressed in head and neck squamous cell carcinoma (HNSCC) and cetuximab, a monoclonal antibody targeting this receptor, is widely used to treat these patients. In the following investigation, we examined the role of SMAD4 down-regulation in mediating epithelial-to-mesenchymal transition (EMT) and cetuximab resistance in HNSCC. We determined that SMAD4 downregulation was significantly associated with increased cell motility, increased expression of vimentin, and cetuximab resistance in HNSCC cell lines. In the HNSCC genomic dataset obtained from The Cancer Genome Atlas, SMAD4 was altered in 20/279 (7%) of HNSCC via homozygous deletion, and nonsense, missense, and silent mutations. When SMAD4 expression was compared with respect to human papillomavirus (HPV) status, HPV-positive tumors had higher expression compared to HPV-negative tumors. Furthermore, higher SMAD4 expression also correlated with higher CDKN2A (p16) expression. Our data suggest that SMAD4 down-regulation plays an important role in the induction of EMT and cetuximab resistance. Patients with higher SMAD4 expression may benefit from cetuximab use in the clinic.

CoGAPS matrix factorization algorithm identifies transcriptional changes in AP-2alpha target genes in feedback from therapeutic inhibition of the EGFR network

Patients with oncogene driven tumors are treated with targeted therapeutics including EGFR inhibitors. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates molecular alterations to EGFR, MAPK, and PI3K pathways in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to delineate interactions resulting from EGFR inhibitor use in cancer cells with these genetic alterations. We modify the HaCaT keratinocyte cell line model to simulate cancer cells with constitutive activation of EGFR, HRAS, and PI3K in a controlled genetic background. We then measure gene expression after treating modified HaCaT cells with gefitinib, afatinib, and cetuximab. The CoGAPS algorithm distinguishes a gene expression signature associated with the anticipated silencing of the EGFR network. It also infers a feedback signature with EGFR gene expression itself increasing in cells that are responsive to EGFR inhibitors. This feedback signature has increased expression of several growth factor receptors regulated by the AP-2 family of transcription factors. The gene expression signatures for AP-2alpha are further correlated with sensitivity to cetuximab treatment in HNSCC cell lines and changes in EGFR expression in HNSCC tumors with low CDKN2A gene expression. In addition, the AP-2alpha gene expression signatures are also associated with inhibition of MEK, PI3K, and mTOR pathways in the Library of Integrated Network-Based Cellular Signatures (LINCS) data. These results suggest that AP-2 transcription factors are activated as feedback from EGFR network inhibition and may mediate EGFR inhibitor resistance.

Treatment with epigenetic agents profoundly inhibits tumor growth in leiomyosarcoma

Leiomyosarcomas are rare mesenchymal neoplasms characterized by a smooth muscle differentiation pattern. Due to the extremely poor prognosis in patients, the development of novel chemotherapeutic regimens remains critically important. In this study, multiple leiomyosarcoma cell lines, SK-UT1, SK-LMS1, and MES-SA were treated with varying doses of the DNA Methyltransferase Inhibitors (DNMTi) 5-azacitidine (Aza), 5-aza-2-deoxycytidine (DAC), and guadecitabine (SGI-110). The effect of these epigenetic modulators was measured using both in-vitro and in-vivo models. Of the three epigenetic modulators, Guadecitabine was the most effective at decreasing cell survival in LMS cell lines. SK-UT1 was found to be the more sensitive to all three epigenetic modulators, while SK-LMS1 and MES-SA were more resistant. The contrast in sensitivity seen was also represented by the increase in apoptosis in Aza and guadecitabine. In parallel with Aza, guadecitabine was observed to also arrest the cell cycle. Treatment with guadecitabine led to a decrease in growth across the spectrum of sensitivity in LMS cell lines, both in a delayed in vitro and in vivo model; in parallel experiments, apoptotic pathways were activated in sensitive and less sensitive lines. Additional studies are required to explore potential therapeutic applications and mechanisms for leiomyosarcoma treatment.

Untangling The Gene-Epigenome Networks: Timing Of Epigenetic Regulation Of Gene Expression In Acquired Cetuximab Resistance

Widespread characterization of the genomic landscape of tumors has enabled precision treatment strategies. Despite significant advances in development of targeted therapies, patients with tumors sensitive to inhibitors often acquire resistance and succumb to their tumors. The timing and function of gene regulation responsible for resistance remain unknown. Clinical gains from the use of the anti-EGFR antibody, cetuximab, in head and neck squamous cell carcinoma (HNSCC) lead to FDA approval. However, cetuximab is not curative for HNSCC patients and a significant proportion acquire resistance to the treatment. A comprehensive characterization of the mechanisms resulting in acquired cetuximab resistance is critical to delineate new strategies to overcome resistance. To this end, we developed a novel time course analysis to study the in vitro progression of the molecular mechanisms resulting in acquired cetuximab resistance in HNSCC. Specifically, we collected multiple experimentally equivalent cultures over several generations in order to measure changes in gene expression, DNA methylation, and proliferation as resistance developed. This new long-term treatment protocol models the progression of acquired therapeutic resistance, including controls for clonal selection unrelated to treatment. The epigenetic regulation of FGFR1 expression emerged as the dominant mechanism of acquired therapeutic resistance in this system and was confirmed in primary tumors from The Cancer Genome Atlas (TCGA). The association of FGFR1 overexpression with cetuximab resistance is consistent with previous studies. Even in a subset of cetuximab stable resistant clones presenting substantial epigenetic heterogeneity, FGFR1 up-regulation in response to loss of promoter methylation emerged as a key regulator of resistance corroborating our pooled time course epigenetics data. Therefore, we hypothesize that alternative molecular mechanisms giving rise to EGFR inhibitor resistance could be overcome with the introduction of combined FGFR1 inhibition. Taken together, our time course profiling of DNA methylation and gene expression data provide a significant contribution to the characterization of mechanisms involved in acquired cetuximab resistance in HNSCC and provides new insights to alternative options for targeted therapy in this tumor type.BACKGROUND Targeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients’ treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors. To determine the dynamics of these molecular changes, we obtained high throughput omics data weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. RESULTS An unsupervised algorithm, CoGAPS, was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically. CONCLUSIONS Genes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize resistance. These genes include FGFR1, which was associated with EGFR inhibitor resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. Our findings provide a relevant towards better understanding of the time course progression of changes resulting in acquired resistance to targeted therapies. This is an important contribution to the development of alternative treatment strategies that would introduce new drugs before the resistant phenotype develops.

A novel epigenetic modulating agent sensitizes pancreatic cells to a chemotherapy agent

Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second leading cause of cancer mortality by 2030. PDAC remains resistant to the majority of systemic chemotherapies. In this paper, we explore if epigenetic sensitization can improve chemotherapy response in PDAC. Multiple PDAC cell lines were tested with serial concentrations of the epigenetic modulators 5-azacitidine (Aza) and guadecitabine (SGI-110). Guadecitabine was effective at inhibiting the expression of DNA Methyltransferase 1 (DNMT1) and in decreasing cell viability at nanomolar concentrations. We also report that guadecitabine has increased efficacy following a delay period or as we reference, a ‘rest period’. Sensitization with guadecitabine improved response to the chemotherapeutic agent–Irinotecan- as measured by decreased cell viability and accompanied by an increase in caspase activity. Additional studies are needed to understand the mechanism of action.

Abstract A35: Treatment with demethylating drugs inhibits tumor growth in leiomyosarcoma cell lines and xenograft models

Introduction: Leiomyosarcomas are rare mesenchymal neoplasms characterized by a smooth-muscle differentiation pattern. Patients show poor disease-specific survival due to high recurrence rates and low response to chemotherapy and radiation. Development of novel chemotherapeutic regimens is the need of the hour. Epigenetic mechanisms such as hypermethylation of gene promotor regions lead to abnormal gene silencing and have been found to influence the initiation and progression of cancer. Epigenetic drugs have been approved for treatment of various malignancies such as myelodysplastic syndrome, acute myeloid leukemias, and subsets of lymphomas. This study aims to understand the potential efficacy of epigenetic drugs called DNA methyltransferease inhibitors (DNMTi) in the treatment of leiomyosarcomas. Methods: DNMTi used in this study include azacytidine (Aza), decitabine (Dac), and guadecitabine. Aza and Dac are antimetabolites, which get incorporated onto RNA and DNA, respectively, leading to inhibition of DNMT. Guadecitabine is a novel prodrug for Dac with a longer half-life. Various leiomyosarcoma cell lines (SK-UT1, SK-LMS, and MES) were treated with varying doses of guadecitabine (0.01-5 ug/ml), decitabine (Dac: 0.1 uM-5uM), or azacitidine (Aza: 0.1 uM-5 uM) and incubated for a maximum of five days. Cell viability was measured daily via MTT assay. To further characterize the mechanism(s) of drug induced cell death, Caspase Glo® Assay (G8090) was utilized as a measure of apoptosis by proxy of Caspase 3 and 7 activity. CellToxTM Green Cytotoxicity Assay was then employed to measure membrane integrity, thus quantifying nonspecific cell death. This would further measure the toxic effect of the demethylating drugs on leiomyosarcoma cell lines. We also studied the effect of guadecitabine (3 mg/kg, 2x/week) treatment in vivo, using subcutaneous xenografts in NOD/SCID mice. Statistical analysis was conducted using GraphPad Prism 6. Results: Decreased cell viability was observed in all three leiomyosarcoma cell lines upon exposure to demethylating agents. SK-UT1 showed the highest sensitivity to all three epigenetic drugs (IC50 values: guadecitabine-0.3 uM, Aza-2.1 uM, and Dac-2.3 uM), MES was sensitive to Aza and guadecitabine (IC50 values: Aza-3.2 uM, guadecitabine-6.14 uM, and Dac-11.77 uM), and SK-LMS was sensitive only to Aza (IC50 values: Aza-2.6 uM, guadecitabine-9.6 uM, and Dac-10.3 uM). To better understand the effect of guadecitabine and AZA on these cell lines, we measured the Caspase 3/7 activity of SK-UT1 and SK-LMS using a Promega kit as a readout for apoptosis. The Caspase activity measured in SKUT1 was remarkably higher in both drugs when compared to that of SK-LMS in presence of same drugs. The amount of necrosis measured in both cell lines in presence of guadecitabine and Aza was negligible. Considerable tumor growth inhibition was also observed after in vivo treatment with guadecitabine in both SK-UT1 and SK-LMS mice xenografts. Conclusion: The use of demethylating agents leads to substantial inhibition of tumor growth in leiomyosarcoma cell lines and xenograft models. Further studies are required to explore the potential therapeutic applications and precise mechanism of action of demethylating agents in leiomyosarcoma treatment. Funding supported by ASTEX Pharmaceuticals. Note: uM= Micromole Citation Format: Cynthia De Carvalho Fischer, Yue Hu, Jasvinder Singh, Maya Thakar, Manjusha Thakar, Nita Ahuja. Treatment with demethylating drugs inhibits tumor growth in leiomyosarcoma cell lines and xenograft models [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr A35.

Abstract 777: The CoGAPS matrix factorization algorithm infers feedback mechanisms from therapeutic inhibition of EGFR that increases expression of growth factor receptors

Next generation sequencing technologies enable precise personalized medicine. Thus, patients with oncogene driven tumors are currently treated with targeted therapeutics such as EGFR inhibitors. However, drug interactions with other activated signaling pathways in treated tumors often alter predicted therapeutic response. Therefore, bioinformatics algorithms are needed to infer unanticipated molecular interactions from anticipated molecular response to targeted therapeutics in diverse genetic backgrounds. To model heterogeneous genetic backgrounds in HNSCC, we use HaCaT cells with forced overexpression of EGFR, HRAS, and PIK3CA. Previously, the CoGAPS matrix factorization algorithm was shown to infer the specific signaling pathways that were activated in these HaCaT knock-in constructs from gene expression data. In this study, we evaluated whether CoGAPS could also delineate unanticipated signaling changes from anticipated cellular signaling response caused by targeted therapeutic in diverse genetic backgrounds. To delineate these signaling responses, we measured gene expression after treating the modified HaCaT cells with three EGFR targeted agents (gefitinib, cetuximab and afatinib) for 24 hours. The CoGAPS matrix factorization algorithm distinguished a gene expression signature associated with the anticipated silencing of the EGFR network and a signature associated with unanticipated transcriptional feedback in HaCaT constructs that were sensitive to EGFR inhibitors. Notably, the feedback signature showed that EGFR gene expression itself increased in cells that were responsive to EGFR inhibitors. The CoGAPS algorithm further associated such feedback with increased expression of several growth factor receptors by the AP-2 family of transcription factors. Once transcribed, these growth factor receptors may ultimately compensate for EGFR inhibition in these sensitive cells. Our data suggest, that CoGAPS gene expression signatures delineate on target and feedback effects of drugs related to therapeutic sensitivity in diverse genetic backgrounds. Citation Format: Elana J. Fertig, Hiroyuki Ozawa, Manjusha Thakar, Jason Howard, Gabriel Krigsfeld, Alexander V. Favorov, Daria A. Gaykalova, Michael F. Ochs, Christine H. Chung. The CoGAPS matrix factorization algorithm infers feedback mechanisms from therapeutic inhibition of EGFR that increases expression of growth factor receptors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 777.