Lindsay Stetson

Epidemiology of gliomas.

Gliomas are the most common type of primary intracranial tumors. Some glioma subtypes cause significant mortality and morbidity that are disproportionate to their relatively rare incidence. A very small proportion of glioma cases can be attributed to inherited genetic disorders. Many potential risk factors for glioma have been studied to date, but few provide explanation for the number of brain tumors identified. The most significant of these factors includes increased risk due to exposure to ionizing radiation, and decreased risk with history of allergy or atopic disease. The potential effect of exposure to cellular phones has been studied extensively, but the results remain inconclusive. Recent genomic analyses, using the genome-wide association study (GWAS) design, have identified several inherited risk variants that are associated with increased glioma risk. The following chapter provides an overview of the current state of research in the epidemiology of intracranial glioma.

A novel glycogen synthase kinase-3 inhibitor optimized for acute myeloid leukemia differentiation activity

Standard therapies used for the treatment of acute myeloid leukemia (AML) are cytotoxic agents that target rapidly proliferating cells. Unfortunately, this therapeutic approach has limited efficacy and significant toxicity and the majority of AML patients still die of their disease. In contrast to the poor prognosis of most AML patients, most individuals with a rare subtype of AML, acute promyelocytic leukemia, can be cured by differentiation therapy using regimens containing all-trans retinoic acid. GSK3 has been previously identified as a therapeutic target in AML where its inhibition can lead to the differentiation and growth arrest of leukemic cells. Unfortunately, existing GSK3 inhibitors lead to suboptimal differentiation activity making them less useful as clinical AML differentiation agents. Here, we describe the discovery of a novel GSK3 inhibitor, GS87. GS87 was discovered in efforts to optimize GSK3 inhibition for AML differentiation activity. Despite GS87s dramatic ability to induce AML differentiation, kinase profiling reveals its high specificity in targeting GSK3 as compared with other kinases. GS87 demonstrates high efficacy in a mouse AML model system and unlike current AML therapeutics, exhibits little effect on normal bone marrow cells. GS87 induces potent differentiation by more effectively activating GSK3-dependent signaling components including MAPK signaling as compared with other GSK3 inhibitors. GS87 is a novel GSK3 inhibitor with therapeutic potential as a differentiation agent for non-promyelocytic AML. Mol Cancer Ther; 15(7); 1485–94. ©2016 AACR.

Pharmacogenomic Approach to Identify Drug Sensitivity in Small-Cell Lung Cancer

There are currently no molecular targeted approaches to treat small-cell lung cancer (SCLC) similar to those used successfully against non-small-cell lung cancer. This failure is attributable to our inability to identify clinically-relevant subtypes of this disease. Thus, a more systematic approach to drug discovery for SCLC is needed. In this regard, two comprehensive studies recently published in Nature, the Cancer Cell Line Encyclopedia and the Cancer Genome Project, provide a wealth of data regarding the drug sensitivity and genomic profiles of many different types of cancer cells. In the present study we have mined these two studies for new therapeutic agents for SCLC and identified heat shock proteins, cyclin-dependent kinases and polo-like kinases (PLK) as attractive molecular targets with little current clinical trial activity in SCLC. Remarkably, our analyses demonstrated that most SCLC cell lines clustered into a single, predominant subgroup by either gene expression or CNV analyses, leading us to take a pharmacogenomic approach to identify subgroups of drug-sensitive SCLC cells. Using PLK inhibitors as an example, we identified and validated a gene signature for drug sensitivity in SCLC cell lines. This gene signature could distinguish subpopulations among human SCLC tumors, suggesting its potential clinical utility. Finally, circos plots were constructed to yield a comprehensive view of how transcriptional, copy number and mutational elements affect PLK sensitivity in SCLC cell lines. Taken together, this study outlines an approach to predict drug sensitivity in SCLC to novel targeted therapeutics.

Protein Markers Predict Survival in Glioma Patients

Glioblastoma multiforme (GBM) is a genomically complex and aggressive primary adult brain tumor, with a median survival time of 12–14 months. The heterogeneous nature of this disease has made the identification and validation of prognostic biomarkers difficult. Using reverse phase protein array data from 203 primary untreated GBM patients, we have identified a set of 13 proteins with prognostic significance. Our protein signature predictive of glioblastoma (PROTGLIO) patient survival model was constructed and validated on independent data sets and was shown to significantly predict survival in GBM patients (log-rank test: p = 0.0009). Using a multivariate Cox proportional hazards, we have shown that our PROTGLIO model is distinct from other known GBM prognostic factors (age at diagnosis, extent of surgical resection, postoperative Karnofsky performance score (KPS), treatment with temozolomide (TMZ) chemoradiation, and methylation of the MGMT gene). Tenfold cross-validation repetition of our model generation procedure confirmed validation of PROTGLIO. The model was further validated on an independent set of isocitrate dehydrogenase wild-type (IDHwt) lower grade gliomas (LGG)—a portion of these tumors progress rapidly to GBM. The PROTGLIO model contains proteins, such as Cox-2 and Annexin 1, involved in inflammatory response, pointing to potential therapeutic interventions. The PROTGLIO model is a simple and effective predictor of overall survival in glioblastoma patients, making it potentially useful in clinical practice of glioblastoma multiforme.

Epidemiology of Intracranial Gliomas

Gliomas are the most common primary intracranial neoplasms, which cause significant mortality and morbidity that is disproportionate to their relatively rare incidence. Many potential risk factors for glioma have been studied to date, but only few provide explanation for the number of brain tumor cases identified. The most significant findings include increased risk due to exposure to ionizing radiation and decreased risk with the history of allergy or atopic diseases. The potential effect of the cellular phone usage has been evaluated extensively, but the results remain inconclusive. A very small proportion of gliomas can be attributed to inherited genetic disorders. Additionally, recent analyses using the genome-wide association study design have identified several inherited genomic risk variants.

Abstract 297: Protein markers predict overall survival in glioblastoma multiforme

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Unrealized needs in the care of patients diagnosed with primary glioblastoma multiforme (GBM) are accurate and clinically relevant predictors of patient prognosis. Patients receiving standard therapy (surgery plus concurrent radiation and temozolomide) have variable clinical outcomes. Available prognostic indicators such as MGMT DNA methylation, IDH1 mutation, and the G-CIMP phenotype are only relevant for a small proportion of those diagnosed with primary GBM. Protein markers of GBM prognosis would not only provide a potential route for classifying and stratifying patients into treatment groups they could also provide an opportunity to identify potential novel drug targets. In this study, using reverse-phase protein array data from Cancer Genome Atlas (TCGA) GBMs, we have constructed and validated a PROTein signature predictive of GLIOblastoma survival (PROTGLIO). Using L1 penalized cox regression, we have identified six protein markers most associated with overall survival in a training set of 107 TCGA GBMs. Three proteins (annexin, cox-2, and FOX03) were associated with shorter overall survival, and three proteins (phosphorylated RPS6KA1, phosphorylated RB1, and TGM2) were associated with longer overall survival. PROTGLIO scores were defined as a linear combination of protein expression levels of the six proteins and the associated Cox regression coefficients, where a higher score indicates a worse prognosis. Based on PROTGLIO scores cases were classified into high and low risk groups. Kaplan-Meier survival analysis showed a significant difference (p = 0.01) in overall survival between the high and low risk groups in our training set. The performance of the PROTGLIO score was validated in a testing set, which consisted of 107 TCGA cases not included in the training set. In the validation set there was a significant difference in overall survival between the high and low risk groups (p = 0.02). We have verified that our signature is independent of known prognostic variables such as age, treatment pattern, and molecular subtype by applying multivariate analysis using a Cox proportional hazard model. The annexin family of proteins has been previously associated with glioma migration and growth and the cox-2 protein has been reported as a marker of poor prognosis among diffuse glioma patients. Our work points to these proteins, along with FOX03, as being negative prognosticators for GBMs and potential avenues for therapeutic intervention. Additionally, we report on the protective effects of phosphorylated RB1 expression, which is supported by previous studies recommending clinical stratification of patients based on RB1 alterations. Further work is needed to elucidate the protective mechanisms of RPS6KA1 and TGM2. Note: This abstract was not presented at the meeting. Citation Format: Lindsay C. Stetson, Jill S. Barnholtz-Sloan. Protein markers predict overall survival in glioblastoma multiforme. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 297. doi:10.1158/1538-7445.AM2014-297

Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence

Background Models of epigenetic aging (epigenetic clocks) have been implicated as potentially useful markers for cancer risk and prognosis. Using 2 previously published methods for modeling epigenetic age, Horvaths clock and epiTOC, we investigated epigenetic aging patterns related to World Health Organization grade and molecular subtype as well as associations of epigenetic aging with glioma survival and recurrence. Methods Epigenetic ages were calculated using Horvaths clock and epiTOC on 516 lower-grade glioma and 141 glioblastoma cases along with 136 nontumor (normal) brain samples. Associations of tumor epigenetic age with patient chronological age at diagnosis were assessed with correlation and linear regression, and associations were validated in an independent cohort of 203 gliomas. Contribution of epigenetic age to survival prediction was assessed using Cox proportional hazards modeling. Sixty-three samples from 18 patients with primary-recurrent glioma pairs were also analyzed and epigenetic age difference and rate of epigenetic aging of primary-recurrent tumors were correlated to time to recurrence. Results Epigenetic ages of gliomas were near-universally accelerated using both Horvaths clock and epiTOC compared with normal tissue. The 2 independent models of epigenetic aging were highly associated with each other and exhibited distinct aging patterns reflective of molecular subtype. EpiTOC was found to be a significant independent predictor of survival. Epigenetic aging of gliomas between primary and recurrent tumors was found to be highly variable and not significantly associated with time to recurrence. Conclusions We demonstrate that epigenetic aging reflects coherent modifications of the epigenome and can potentially provide additional prognostic power for gliomas.

Abstract 780: Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence

Varying possibilities of tumor relapse for lower grade glioma (LGG, WHO grade II and III) and glioblastoma (GBM, WHO grade IV) have led to heterogenous clinical outcomes for patients. Our current study aims to establish a molecular profile of recurrence of matched primary and recurrent LGG (n = 28) and recurrent GBM (n = 24) tumor samples. The Cancer Genome Atlas (TCGA) has comprehensively profiled these matched primary/recurrent tumor sets; whole genomes, coding exomes, methylomes, and transcriptomes have been sequenced, and the samples have undergone targeted profiling of the proteome. While unsupervised analysis techniques have not led to a clear recurrence signature, supervised analysis methods have revealed interesting patterns. Protein profiling has shown that recurrent gliomas retain the overall molecular signature of their primary counterpart, but the DNA damage response, apoptosis and RTK pathways are downregulated in the recurrent gliomas, in contrast to RAS/MAPK, PI3K/AKT, and EMT pathways, which are upregulated. Whole genome sequencing and rearrangement analysis have revealed increased genomic complexity among most recurrent gliomas as well as new fusions of interest in recurrent LGG samples (PTPRZ1-MET and involving ATRX). Using genome-wide Illumina HumanMethylation 450K data we observed that 78.6% of LGGs showed depletion of DNA methylation at recurrence and 50% of GBM tumors showed an enrichment of DNA methylation at recurrence. Patient centric enrichment analysis allowed us to discover a candidate biological subgroup characterized by a subset of LGG recurrences (50%) exhibiting an aberrant CpG methylation loss at inintergenic opensea regions when compared with canonical CpG islands and shores (fold > 1.3 and confidence intervals of 99%). Importantly, inspection of CpG sites significantly hypomethylated at openseas showed that this pronounced epigenetic signature maps to candidate TSS distal and hypomethylated enhancers. The gene-targets of these hypomethylated CpG sites show a corresponding up-regulation of expression. Pathway analysis has demonstrated that these upregulated genes are involved in cellular growth and proliferation, cellular function and maintenance, and cell cycle regulation. Our results provide evidence that DNA methylation may represent a stable signature of glioma recurrence and that the crosstalk between DNA hypomethylation at openseas and chromosomal instability may be involved in glioma recurrence. We plan to further integrate our findings between data types and correlate with treatment and patient clinical outcome. Citation Format: Lindsay C. Stetson, Camila Ferreira de Souza, Tathiane Maistro Malta, Thais Sarraf Sabedot, Quinn Ostrom, Peter Liao, Daniela Pretti da Cunha Tirapelli, Luciano Neder, Carlos Gilberto Carlotti, Rehan Akbani, Sofie Salama, Laila Poisson, Daniel Brat, The Cancer Genome Atlas Network, Houtan Noushmehr, Jill Barnholtz-Sloan. Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence. [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 780.

Abstract 4182: Bioinformatic analysis identifies polo-like kinase as a therapeutic target in small-cell lung cancer

Small cell lung cancer (SCLC) represents 15% of all lung carcinomas and is typically diagnosed when the disease has metastasized. Although most SCLC is initially sensitive to chemotherapy regimens, relapse is common and the survival benefit of second-line therapies, such as topotecan, is also limited. There are currently no molecular targeted approaches to treat SCLC similar to those used successfully against non-small-cell lung cancer (NSCLC). This failure is partly attributable to the empiric nature of these efforts. Thus, a more systematic approach to drug discovery for SCLC may lie in mining available databases on the drug sensitivities of SCLC cell lines. In this regard, two comprehensive studies recently published in Nature, the Cancer Cell Line Encyclopedia (CCLE) and the Cancer Genome Project (CGP), examined the drug sensitivities of cancer cell lines and attempted to link these to their genomic profiles. In the present study we have extracted data on SCLC cell lines from these two studies and mined it for new, promising therapeutic agents for SCLC. Our analyses demonstrate that the drug sensitivity of the SCLC cell lines reflects what is observed clinically for metastatic SCLC tumors. That is, most cells were extremely sensitive to topoisomerase (camptothecin) and microtubule (vinblastine and docetaxel) inhibitors, by contrast many tyrosine kinase inhibitors (erlotinib, sorafenib and imatinib) were ineffective. Importantly, we identified heat shock proteins (HSP), cyclin-dependent kinases (CDK) and polo-like kinases (PLK) as attractive molecular targets that have received little/no attention in clinical trials of SCLC. We further developed a gene signature for PLK inhibitor sensitivity and validated it in untested SCLC cell lines. This gene signature was incorporated into circos plots to yield a comprehensive view of how transcriptional, copy number and mutational elements affect PLK sensitivity in SCLC cell lines. Citation Format: Gary Wildey, Yanwen Chen, Ian Lent, Lindsay Stetson, John Pink, Jill Barnholtz-Sloan, Afshin Dowlati. Bioinformatic analysis identifies polo-like kinase as a therapeutic target in small-cell lung cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4182. doi:10.1158/1538-7445.AM2014-4182