Simona Dalin

Extensive changes in DNA methylation are associated with expression of mutant huntingtin

The earliest stages of Huntington disease are marked by changes in gene expression that are caused in an indirect and poorly understood manner by polyglutamine expansions in the huntingtin (HTT) protein. To explore the hypothesis that DNA methylation may be altered in cells expressing mutated HTT, we use reduced representation bisulfite sequencing (RRBS) to map sites of DNA methylation in cells carrying either wild-type or mutant HTT. We find that a large fraction of the genes that change in expression in the presence of mutant huntingtin demonstrate significant changes in DNA methylation. Regions with low CpG content, which have previously been shown to undergo methylation changes in response to neuronal activity, are disproportionately affected. On the basis of the sequence of regions that change in methylation, we identify AP-1 and SOX2 as transcriptional regulators associated with DNA methylation changes, and we confirm these hypotheses using genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq). Our findings suggest new mechanisms for the effects of polyglutamine-expanded HTT. These results also raise important questions about the potential effects of changes in DNA methylation on neurogenesis and cognitive decline in patients with Huntington disease.

Network Modeling Identifies Patient-specific Pathways in Glioblastoma.

Glioblastoma is the most aggressive type of malignant human brain tumor. Molecular profiling experiments have revealed that these tumors are extremely heterogeneous. This heterogeneity is one of the principal challenges for developing targeted therapies. We hypothesize that despite the diverse molecular profiles, it might still be possible to identify common signaling changes that could be targeted in some or all tumors. Using a network modeling approach, we reconstruct the altered signaling pathways from tumor-specific phosphoproteomic data and known protein-protein interactions. We then develop a network-based strategy for identifying tumor specific proteins and pathways that were predicted by the models but not directly observed in the experiments. Among these hidden targets, we show that the ERK activator kinase1 (MEK1) displays increased phosphorylation in all tumors. By contrast, protein numb homolog (NUMB) is present only in the subset of the tumors that are the most invasive. Additionally, increased S100A4 is associated with only one of the tumors. Overall, our results demonstrate that despite the heterogeneity of the proteomic data, network models can identify common or tumor specific pathway-level changes. These results represent an important proof of principle that can improve the target selection process for tumor specific treatments.

Hyper- and hypo- nutrition studies of the hepatic transcriptome and epigenome suggest that PPARα regulates anaerobic glycolysis

Diet plays a crucial role in shaping human health and disease. Diets promoting obesity and insulin resistance can lead to severe metabolic diseases, while calorie-restricted (CR) diets can improve health and extend lifespan. In this work, we fed mice either a chow diet (CD), a 16 week high-fat diet (HFD), or a CR diet to compare and contrast the effects of these diets on mouse liver biology. We collected transcriptomic and epigenomic datasets from these mice using RNA-Seq and DNase-Seq. We found that both CR and HFD induce extensive transcriptional changes, in some cases altering the same genes in the same direction. We used our epigenomic data to infer transcriptional regulatory proteins bound near these genes that likely influence their expression levels. In particular, we found evidence for critical roles played by PPARα and RXRα. We used ChIP-Seq to profile the binding locations for these factors in HFD and CR livers. We found extensive binding of PPARα near genes involved in glycolysis/gluconeogenesis and uncovered a role for this factor in regulating anaerobic glycolysis. Overall, we generated extensive transcriptional and epigenomic datasets from livers of mice fed these diets and uncovered new functions and gene targets for PPARα.

Differential selective pressure alters rate of drug resistance acquisition in heterogeneous tumor populations.

Recent drug discovery and development efforts have created a large arsenal of targeted and chemotherapeutic drugs for precision medicine. However, drug resistance remains a major challenge as minor pre-existing resistant subpopulations are often found to be enriched at relapse. Current drug design has been heavily focused on initial efficacy, and we do not fully understand the effects of drug selective pressure on long-term drug resistance potential. Using a minimal two-population model, taking into account subpopulation proportions and growth/kill rates, we modeled long-term drug treatment and performed parameter sweeps to analyze the effects of each parameter on therapeutic efficacy. We found that drugs with the same overall initial kill may exert differential selective pressures, affecting long-term therapeutic outcome. We validated our conclusions experimentally using a preclinical model of Burkitt’s lymphoma. Furthermore, we highlighted an intrinsic tradeoff between drug-imposed overall selective pressure and rate of adaptation. A principled approach in understanding the effects of distinct drug selective pressures on short-term and long-term tumor response enables better design of therapeutics that ultimately minimize relapse.

Abstract PR07: Collateral sensitivity in chemotherapy resistance

The current 5-year survival rate across all cancers is only 68%. The ability of tumors to develop resistance to chemotherapy is a major factor keeping survival rates down. Understanding the evolutionary paths tumors take towards resistance will aid in creating drug regimens designed to avoid resistant tumor states. Research in bacteria suggests that a specific type of drug pair, where resistance to each drug confers sensitivity to the other drug, can slow evolution toward drug resistance. This drug pair relationship, termed collateral sensitivity, has not been systematically investigated in cancer. Here, using a preclinical Eμ-myc; Arf-/- murine model of Burkitt lymphoma we investigate collateral sensitivities in this malignancy. We derived resistant cell lines in vitro by treating the parental cell line with dose escalating concentrations of doxorubicin or cisplatin. We screened a subset of these resistant cell lines against a panel of drugs and found several collateral sensitivities conferred by doxorubicin or cisplatin resistance. We are currently investigating the mechanism of one of these collateral sensitivities. We plan to derive cell lines resistant to a variety of other chemotherapies to learn about collateral sensitivities across many chemotherapeutics. Collateral sensitivity is a promising avenue towards rationally designing combination therapies that reduce the emergence of chemotherapy resistant disease. Citation Format: Simona Dalin, Boyang Zhao, Michael T. Hemann. Collateral sensitivity in chemotherapy resistance [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr PR07.

Abstract 35: Evolution of resistance to glucocorticoid receptor agonists

Chemotherapy resistance is a major obstacle to curing cancer patients. Over 90% of metastatic tumors are resistant to chemotherapy, leading to treatment failure. Although glucocorticoid receptor agonists (GRAs) are a very commonly used class of component drugs in front-line combination chemotherapies for hematopoietic cancer, our understanding of its mechanism(s) of action and resistance are very limited. Here using a preclinical murine model of Burkitt9s lymphoma, we investigated the mechanism of resistance to the glucocorticoid receptor agonist dexamethasone. Dose responses of dexamethasone on the parental E μ -myc; Arf-null cell line revealed a consistently small population of persistent survivors, suggesting a pre-existing subpopulation with innate dexamethasone resistance. To further address the evolution and selection of these survivors in the presence of GRAs, we derived resistant cell lines in vitro by treating the parental cell line with dose escalating concentrations of dexamethasone. These resistant cell lines were expectedly cross-resistant to other GRAs. However, loss of expression of the glucocorticoid receptor (GR) was not observed – ruling out one possible resistance mechanism. To explore alternative or downstream pathways that may be implicated, we subsequently acquired dose responses against a broad set of targeted kinase inhibitors, and observed modest sensitivity to the HSP90 inhibitor 17-AAG. This suggests that the resistance mechanism could be related to HSP909s role of holding ligand-free glucocorticoid receptor (GR) in the cytoplasm. We are now re-evolving the parental populations, and deriving clonal populations to confirm this phenotype. A better understanding of how hematopoietic cancer cells evolve resistance to GCAs will lead to improved design of drug combinations for prolonged survival. Citation Format: Simona Dalin, Boyang Zhao, Michael T. Hemann. Evolution of resistance to glucocorticoid receptor agonists. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 35.