Andrew D. Kelly

Metabolomic Profiling from Formalin-Fixed, Paraffin- Embedded Tumor Tissue Using Targeted LC/MS/MS: Application in Sarcoma

The relatively new field of onco-metabolomics attempts to identify relationships between various cancer phenotypes and global metabolite content. Previous metabolomics studies utilized either nuclear magnetic resonance spectroscopy or gas chromatography/mass spectrometry, and analyzed metabolites present in urine and serum. However, direct metabolomic assessment of tumor tissues is important for determining altered metabolism in cancers. In this respect, the ability to obtain reliable data from archival specimens is desirable and has not been reported to date. In this feasibility study, we demonstrate the analysis of polar metabolites extracted directly from ten formalin-fixed, paraffin-embedded (FFPE) specimens, including five soft tissue sarcomas and five paired normal samples. Using targeted liquid chromatography-tandem mass spectrometry (LC/MS/MS) via selected reaction monitoring (SRM), we detect an average of 106 metabolites across the samples with excellent reproducibility and correlation between different sections of the same specimen. Unsupervised hierarchical clustering and principal components analysis reliably recovers a priori known tumor and normal tissue phenotypes, and supervised analysis identifies candidate metabolic markers supported by the literature. In addition, we find that diverse biochemical processes are well-represented in the list of detected metabolites. Our study supports the notion that reliable and broadly informative metabolomic data may be acquired from FFPE soft tissue sarcoma specimens, a finding that is likely to be extended to other malignancies.

MicroRNA paraffin-based studies in osteosarcoma reveal reproducible independent prognostic profiles at 14q32

BackgroundAlthough microRNAs (miRNAs) are implicated in osteosarcoma biology and chemoresponse, miRNA prognostic models are still needed, particularly because prognosis is imperfectly correlated with chemoresponse. Formalin-fixed, paraffin-embedded tissue is a necessary resource for biomarker studies in this malignancy with limited frozen tissue availability.MethodsWe performed miRNA and mRNA microarray formalin-fixed, paraffin-embedded assays in 65 osteosarcoma biopsy and 26 paired post-chemotherapy resection specimens and used the only publicly available miRNA dataset, generated independently by another group, to externally validate our strongest findings (n = 29). We used supervised principal components analysis and logistic regression for survival and chemoresponse, and miRNA activity and target gene set analysis to study miRNA regulatory activity.ResultsSeveral miRNA-based models with as few as five miRNAs were prognostic independently of pathologically assessed chemoresponse (median recurrence-free survival: 59 months versus not-yet-reached; adjusted hazards ratio = 2.90; P = 0.036). The independent dataset supported the reproducibility of recurrence and survival findings. The prognostic value of the profile was independent of confounding by known prognostic variables, including chemoresponse, tumor location and metastasis at diagnosis. Model performance improved when chemoresponse was added as a covariate (median recurrence-free survival: 59 months versus not-yet-reached; hazard ratio = 3.91; P = 0.002). Most prognostic miRNAs were located at 14q32 - a locus already linked to osteosarcoma - and their gene targets display deregulation patterns associated with outcome. We also identified miRNA profiles predictive of chemoresponse (75% to 80% accuracy), which did not overlap with prognostic profiles.ConclusionsFormalin-fixed, paraffin-embedded tissue-derived miRNA patterns are a powerful prognostic tool for risk-stratified osteosarcoma management strategies. Combined miRNA and mRNA analysis supports a possible role of the 14q32 locus in osteosarcoma progression and outcome. Our study creates a paradigm for formalin-fixed, paraffin-embedded-based miRNA biomarker studies in cancer.

Next-generation sequencing and microarray-based interrogation of microRNAs from formalin-fixed, paraffin-embedded tissue: preliminary assessment of cross-platform concordance.

Next-generation sequencing is increasingly employed in biomedical investigations. Strong concordance between microarray and mRNA-seq levels has been reported in high quality specimens but information is lacking on formalin-fixed, paraffin-embedded (FFPE) tissues, and particularly for microRNA (miRNA) analysis. We conducted a preliminary examination of the concordance between miRNA-seq and cDNA-mediated annealing, selection, extension, and ligation (DASL) miRNA assays. Quantitative agreement between platforms is moderate (Spearman correlation 0.514-0.596) and there is discordance of detection calls on a subset of miRNAs. Quantitative PCR (q-RT-PCR) performed for several discordant miRNAs confirmed the presence of most sequences detected by miRNA-seq but not by DASL but also that miRNA-seq did not detect some sequences, which DASL confidently detected. Our results suggest that miRNA-seq is specific, with few false positive calls, but it may not detect certain abundant miRNAs in FFPE tissue. Further work is necessary to fully address these issues that are pertinent for translational research.

The promise of epigenetic therapy: reprogramming the cancer epigenome

Epigenetics refers to heritable molecular determinants of phenotype independent of DNA sequence. Epigenetic features include DNA methylation, histone modifications, non-coding RNAs, and chromatin structure. The epigenetic status of cells plays a crucial role in determining their differentiation state and proper function within multicellular organisms. Disruption of these processes is now understood to be a major contributor to cancer development and progression, and recent efforts have attempted to pharmacologically reverse such altered epigenetics. In this mini-review we introduce the concept of epigenetic drivers of cancer and discuss how aberrant DNA methylation, histone modifications, and chromatin states are being targeted using drugs either in preclinical, or clinical development, and how they fit in the context of existing therapies.

A CpG island methylator phenotype in acute myeloid leukemia independent of IDH mutations and associated with a favorable outcome

Genetic changes are infrequent in acute myeloid leukemia (AML) compared with other malignancies and often involve epigenetic regulators, suggesting that an altered epigenome may underlie AML biology and outcomes. In 96 AML cases including 65 pilot samples selected for cured/not-cured, we found higher CpG island (CGI) promoter methylation in cured patients. Expanded genome-wide digital restriction enzyme analysis of methylation data revealed a CGI methylator phenotype independent of IDH1/2 mutations we term AML-CGI methylator phenotype (CIMP) (A-CIMP+). A-CIMP was associated with longer overall survival (OS) in this data set (median OS, years: A-CIMP+=not reached, CIMP-=1.17; P=0.08). For validation we used 194 samples from The Cancer Genome Atlas interrogated with Illumina 450k methylation arrays where we confirmed longer OS in A-CIMP (median OS, years: A-CIMP+=2.34, A-CIMP-=1.00; P=0.01). Hypermethylation in A-CIMP+ favored CGIs (OR: CGI/non-CGI=5.21), and while A-CIMP+ was enriched in CEBPA (P=0.002) and WT1 mutations (P=0.02), 70% of cases lacked either mutation. Hypermethylated genes in A-CIMP+ function in pluripotency maintenance, and a gene expression signature of A-CIMP was associated with outcomes in multiple data sets. We conclude that CIMP in AML cannot be explained solely by gene mutations (for example, IDH1/2, TET2), and that curability in A-CIMP+ AML should be validated prospectively.

An imprinted non-coding genomic cluster at 14q32 defines clinically relevant molecular subtypes in osteosarcoma across multiple independent datasets

BackgroundA microRNA (miRNA) collection on the imprinted 14q32 MEG3 region has been associated with outcome in osteosarcoma. We assessed the clinical utility of this miRNA set and their association with methylation status.MethodsWe integrated coding and non-coding RNA data from three independent annotated clinical osteosarcoma cohorts (n = 65, n = 27, and n = 25) and miRNA and methylation data from one in vitro (19 cell lines) and one clinical (NCI Therapeutically Applicable Research to Generate Effective Treatments (TARGET) osteosarcoma dataset, n = 80) dataset. We used time-dependent receiver operating characteristic (tdROC) analysis to evaluate the clinical value of candidate miRNA profiles and machine learning approaches to compare the coding and non-coding transcriptional programs of high- and low-risk osteosarcoma tumors and high- versus low-aggressiveness cell lines. In the cell line and TARGET datasets, we also studied the methylation patterns of the MEG3 imprinting control region on 14q32 and their association with miRNA expression and tumor aggressiveness.ResultsIn the tdROC analysis, miRNA sets on 14q32 showed strong discriminatory power for recurrence and survival in the three clinical datasets. High- or low-risk tumor classification was robust to using different microRNA sets or classification methods. Machine learning approaches showed that genome-wide miRNA profiles and miRNA regulatory networks were quite different between the two outcome groups and mRNA profiles categorized the samples in a manner concordant with the miRNAs, suggesting potential molecular subtypes. Further, miRNA expression patterns were reproducible in comparing high-aggressiveness versus low-aggressiveness cell lines. Methylation patterns in the MEG3 differentially methylated region (DMR) also distinguished high-aggressiveness from low-aggressiveness cell lines and were associated with expression of several 14q32 miRNAs in both the cell lines and the large TARGET clinical dataset. Within the limits of available CpG array coverage, we observed a potential methylation-sensitive regulation of the non-coding RNA cluster by CTCF, a known enhancer-blocking factor.ConclusionsLoss of imprinting/methylation changes in the 14q32 non-coding region defines reproducible previously unrecognized osteosarcoma subtypes with distinct transcriptional programs and biologic and clinical behavior. Future studies will define the precise relationship between 14q32 imprinting, non-coding RNA expression, genomic enhancer binding, and tumor aggressiveness, with possible therapeutic implications for both early- and advanced-stage patients.

Abstract B22: Genome-wide methylation analysis reveals an independently validated CpG island methylator phenotype associated with favorable prognosis in acute myeloid leukemia.

Background: Acute myeloid leukemia (AML) accounts for the most leukemia-related deaths in the United States and its incidence has been rising as the population ages. Although certain molecular aberrations are prognostic and have come into mainstream clinical practice, the genetic and epigenetic determinants of curability in AML remain incompletely understood. Our study examines the role of DNA methylation patterns in AML prognosis and expands on our preliminary work showing DNA hypermethylation may associate with improved overall survival. Methods: To quantitatively interrogate genome-wide CpG methylation we used Digital Restriction Enzyme Analysis of Methylation (DREAM) on a cohort of 102 AML patient samples and 25 normal control samples. We validated our findings using DNA methylation data from 194 patient samples from The Cancer Genome Atlas (TCGA) on the Illumina Infinium HumanMethylation450 platform. Statistical analysis was done using R. Results: Preliminary analysis by our group of DNA methylation levels at promoter CpG islands (CGI) of OSCP1, NPM2, OLIG2, SCGB3A1, and SLC26A4 showed significant hypermethylation in a small group of long-surviving AML patients compared to a short-surviving cohort (median OS = 2,694 days vs. 207 days). We expanded on this observation using DREAM to measure genome-wide DNA methylation in clinical AML samples and found that hierarchical clustering based on 2,537 CpG sites with a standard deviation above 20% stratified patients into three groups with significant differences in overall survival. The hypermethylated cluster had the best prognosis and seemed to be defined by hypermethylation at promoter CGIs, suggesting that a CGI methylator phenotype (CIMP) in AML may be a favorable prognostic factor (median OS: CIMP = 5,110 days, Cluster 2 = 380 days, Cluster 3 = 555 days; log-rank p=0.0162). We then validated these findings using TCGA data from AML patient samples. Hierarchical clustering on the basis of CGI promoter sites revealed three distinct groups with the CIMP cluster having significantly improved overall survival compared to the other clusters (median OS: CIMP = 761 days, Cluster 2 = 306 days, Cluster 3 = 365 days; log-rank p=0.0013). There was also a trend in overall survival when non-CGI non-promoter sites were used to cluster samples (median OS: CIMP = 593 days, Cluster 2 = 245 days, Cluster 3 = 456 days; log-rank p=0.1530). Consistent with our DREAM data, combining CGI promoter sites with non-CGI, non-promoter sites revealed a hierarchical clustering pattern of three major clusters with significant differences in overall survival (median OS: CIMP = 822 days, Cluster 2 = 365 days, Cluster 3 = 365 days; log-rank p=0.0295). Despite technical differences between platforms, there was significant overlap in the genes most proximal to differentially methylated sites between the DREAM and TCGA analyses. These common genes were significantly enriched in transcription factors, pyrimidine metabolism genes, and development genes. Interestingly, the presence of IDH1 R140 mutations was significantly greater in the CIMP clusters in both the DREAM and TCGA analyses (p Conclusions: We propose that the CIMP methylation pattern is associated with favorable prognosis in AML. We have identified a subset of methylation sites that, when interrogated, predict overall survival independent of other clinical factors. Citation Format: Andrew D. Kelly, Heike Kroeger, Jumpei Yamazaki, Rodolphe Taby, Frank Neumann, Justin T. Lee, Rong He, Shoudan Liang, Yue Lu, Matteo Cesaroni, Sherry A. Pierce, Steven M. Kornblau, Carlos E. Bueso-Ramos, Farhad Ravandi, Hagop M. Kantarjian, Jean-Pierre J. Issa, Jaroslav Jelinek. Genome-wide methylation analysis reveals an independently validated CpG island methylator phenotype associated with favorable prognosis in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr B22.

A microRNA activity map of human mesenchymal tumors: connections to oncogenic pathways; an integrative transcriptomic study

BackgroundMicroRNAs (miRNAs) are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA activity patterns associated with cancer phenotypes and oncogenic pathways in mesenchymal tumors – a very heterogeneous class of malignancies.ResultsUsing a computational method, we identified differentially activated miRNAs between 77 normal tissue specimens and 135 sarcomas and we validated many of these findings with microarray interrogation of an independent, paraffin-based cohort of 18 tumors. We also showed that miRNA activity is imperfectly correlated with miRNA expression levels. Using next-generation miRNA sequencing we identified potential base sequence alterations which may explain differential activity. We then analyzed miRNA activity changes related to the RAS-pathway and found 21 miRNAs that switch from silenced to activated status in parallel with RAS activation. Importantly, nearly half of these 21 miRNAs were predicted to regulate integral parts of the miRNA processing machinery, and our gene expression analysis revealed significant reductions of these transcripts in RAS-active tumors. These results suggest an association between RAS signaling and miRNA processing in which miRNAs may attenuate their own biogenesis.ConclusionsOur study represents the first gene expression-based investigation of miRNA regulatory activity in human sarcomas, and our findings indicate that miRNA activity patterns derived from integrated transcriptomic data are reproducible and biologically informative in cancer. We identified an association between RAS signaling and miRNA processing, and demonstrated sequence alterations as plausible causes for differential miRNA activity. Finally, our study highlights the value of systems level integrative miRNA/mRNA assessment with high-throughput genomic data, and the applicability of paraffin-tissue-derived RNA for validation of novel findings.

Epigenetics and Precision Oncology

Epigenetic alterations such as DNA methylation defects and aberrant covalent histone modifications occur within all cancers and are selected for throughout the natural history of tumor formation, with changes being detectable in early onset, progression, and ultimately recurrence and metastasis. The ascertainment and use of these marks to identify at-risk patient populations, refine diagnostic criteria, and provide prognostic and predictive factors to guide treatment decisions are of growing clinical relevance. Furthermore, the targetable nature of epigenetic modifications provides a unique opportunity to alter treatment paradigms and provide new therapeutic options for patients whose malignancies possess these aberrant epigenetic modifications, paving the way for new and personalized medicine. DNA methylation has proven to be of significant clinical utility for its stability and relative ease of testing. The intent of this review is to elaborate upon well-supported examples of epigenetic precision medicine and how the field is moving forward, primarily in the context of aberrant DNA methylation.

Epigenetics and Cancer

Epigenetic characteristics are heritable features, propagated through cell division, that contribute to cellular identity independent of DNA sequence. Such characteristics include DNA methylation, covalent histone modifications, and non-coding RNA-dependent gene regulation. Over the past few decades, epigenetic changes in cancer have become recognized and widely accepted as important contributors to malignant transformation. Such alterations result in a transcriptional program that promotes molecular diversity and provides a selective advantage to cancer cells through tumor suppressor gene silencing and aberrant oncogene activation. Causes of epigenetic aberrations remain under active investigation and include at least stochastic changes associated with aging, mutations in epigenetic modifying enzymes, and altered cellular metabolism through changing the metabolite repertoire. A number of therapies targeting epigenetic modifiers have been approved by the FDA for cancer treatment, and many others are in clinical trials. Ongoing research is focused on better understanding mechanisms contributing to the altered epigenome, how the altered epigenome contributes to malignant transformation, and how epigenetic therapies can be best applied clinically to patients most likely to benefit from them.