BackgroundThe identification of blood-based biomarkers specific to the diagnosis of amyotrophic lateral sclerosis (ALS) is an active field of academic and clinical research. While inheritance studies have advanced the field, a majority of patients do not have a known genetic link to the disease, making direct sequence-based genetic testing for ALS difficult. The ability to detect biofluid-based epigenetic changes in ALS would expand the relevance of using genomic information for disease diagnosis.MethodsAssessing differences in chromosomal conformations (i.e. how they are positioned in 3-dimensions) represents one approach for assessing epigenetic changes. In this study, we used an industrial platform, EpiSwitch™, to compare the genomic architecture of healthy and diseased patient samples (blood and tissue) to discover a chromosomal conformation signature (CCS) with diagnostic potential in ALS. A three-step biomarker selection process yielded a distinct CCS for ALS, comprised of conformation changes in eight genomic loci and detectable in blood.FindingsWe applied the ALS CCS to determine a diagnosis for 74 unblinded patient samples and subsequently conducted a blinded diagnostic study of 16 samples. Sensitivity and specificity for ALS detection in the 74 unblinded patient samples were 83∙33% (CI 51∙59 to 97∙91%) and 76∙92% (46∙19 to 94∙96%), respectively. In the blinded cohort, sensitivity reached 87∙50% (CI 47∙35 to 99∙68%) and specificity was 75∙0% (34∙91 to 96∙81%).InterpretationsThe sensitivity and specificity values achieved using the ALS CCS identified and validated in this study provide an indication that the detection of chromosome conformation signatures is a promising approach to disease diagnosis and can potentially augment current strategies for diagnosing ALS.FundThis research was funded by Oxford BioDynamics and Innovate UK. Work in the Oxford MND Care and Research Centre is supported by grants from the Motor Neurone Disease Association and the Medical Research Council. Additional support was provided by the Northeast ALS Consortium (NEALS).

The major barrier to effective cancer therapy is the presence of genetic and phenotypic heterogeneity within cancer cell populations that provides a reservoir of therapeutically resistant cells. As the degree of heterogeneity present within tumours will be proportional to tumour burden, the development of rapid, robust, accurate and sensitive biomarkers for cancer progression that could detect clinically occult disease before substantial heterogeneity develops would provide a major therapeutic benefit. Here, we explore the application of chromatin conformation capture technology to generate a diagnostic epigenetic barcode for melanoma. The results indicate that binary states from chromatin conformations at 15 loci within five genes can be used to provide rapid, non-invasive multivariate test for the presence of melanoma using as little as 200 μl of patient blood.

The human genome is organized into topological domains with discrete structural and regulatory units that influence gene expression epigenetically (Crutchley et al., 2010). In glioma patients with IDH1 (R132H) mutations, researchers detected aberrant methylation of transcriptional CTCF-enhancer regions between the FIPL1L1 and PDGFRA genes. Conformational changes to the chromosomal arrangement of these regions have been shown to upregulate PDGFRA expression (Flavahan et al; 2016). Flavahan et al also demonstrated the down regulation of cell growth and proliferation in the glioma cells with the addition of tyrosine kinase inhibitors that target the interaction.We explored this epigenetic interaction and its utility in the stratification of patients for treatment with tyrosine kinase inhibitors. Using a high-resolution chromosome-conformation capture or 3C analysis platform known as EpiSwitchTMand quantitative PCR, we mapped, evaluated, and quantified the conformational juxtaposition between FIP1L1 and PDGFRA in glioma-cell lines with and without IDH mutations. Deregulation of PDGFRA by interstitial deletion at 4q12 and fusion to FIP1L1 associated with chronic esosinophic leukemias prompted our group to also investigate whether the same chromosome-conformation interactions are present in EOL-1 and other leukemic cell lines. EpiSwitchTM templates were produced using a modified process to purify the 3C DNA. Unlike previous protocols, only one set of primers is required. Chromosome conformation capture analysis with a probe, single step PCR and gel purification was used to identify and sequence 3C interactions in the AML cell lines EOL-1 and HL-60. qPCR templates, adjusted to 20 ng of 3C library DNA, were used with concentration-matched negative controls (ie, 3C libraries derived from adipose biopies and normal blood). A 3C interaction with MMP-1 was used as a internal control for the EpiSwitchTM library. A dual label hydrolysis probe was used to detect the sequenced interaction. Five novel interactions were identified between FIP1L1 and PDGFRA by single step PCR and confirmed by sequencing. We quantified one interaction with a dual-labeled hydrolysis probe based qPCR assay to determine copy number in eight cell lines: BT-412 (anaplastic oligoastrocytoma), DBTRG-05MG (glioblastoma multiforme), U-3T3 (glioblastoma astrocytoma), U-87 (glioblastoma astrocytoma), GDM-1 (acute myelomonocytic leukemia), EOL-1 (acute myeloid leukemia, AML), HL-60 (AML) and KG-1 (AML). Using EpiSwitchTMand ISO standard MIQE-compliant qPCR design, five specific epigenetic interactions were detected in three types of cancerous cell lines including EOL-1 and HL-60. qPCR was used to detect one specific difference between normal blood (n = 4) and leukemic cell lines (n = 4). By qPCR the interaction was detected in two AML cell lines known to be highly sensitive to the tyrosine kinase inhibitor Glivec (EOL-1 and GDM-1), as well as HL-60 cells, but not in KG-1. The FIP1L1 PDGFRA 3C interaction was also found in DBTRG-05MG and U-373 at a similar copy number compared to the AML cell lines. A glioma patient biopsy tissue also tested positive for the conformational-chromosome interaction by qPCR compared with an adipose biopsy control. An interaction in the MMP-1 gene was used as an internal positive control in all samples tested. Emerging epigenetic approaches, such as chromosome conformation signatures as detected by EpiSwitchTM, are providing sensitive and accurate methods for improving patient treatment stratification. Detection of interactions between PDGFRA and FIP1L1 based on chromosomal conformational changes have the potential to improve upon the available methods for identifying patients who may benefit from treatment with PDGFRA-targeted tyrosine kinase inhibitors. Further research is needed to validate the method described using blood and biopsy samples in patients with glioma, AML and other myeloproliferative neoplasms associated with the FIP1L1-PDGFRA fusion gene. Disclosures Grand: Oxford BioDynamics Limited: Employment, Equity Ownership. Bird:Oxford BioDynamics Limited: Employment. Corfield:Oxford BioDynamics Limited: Employment. Dezfouli:Oxford BioDynamics Limited: Employment. Warren:Oxford BioDynamics Limited: Employment. Foulkes:Oxford BioDynamics Limited: Employment. Khudari:Oxford BioDynamics Limited: Employment. Salter:Oxford BioDynamics Limited: Employment. Mahecha:Oxford BioDynamics Limited: Employment. Ssentongo:Oxford BioDynamics Limited: Employment. Green:Oxford BioDynamics Limited: Employment, Equity Ownership. Womersley:Oxford BioDynamics Limited: Employment, Patents & Royalties. Hunter:Oxford BioDynamics Limited: Employment. Ramadass:Oxford BioDynamics Limited: Employment. Akoulitchev:Oxford BioDynamics Limited: Employment, Equity Ownership.

6063 Background: NPC is highly curable in early stages but 70% of NPC patients are diagnosed with advanced disease due to lack of effective screening. Genetic and epigenetic alterations involved in the pathogenesis of NPC are known. The higher order chromosomal structures reflecting aberrant transcriptional states of these genes can be measured via techniques such as chromosome conformation capture. Detection of these changes in peripheral blood may provide an accurate test for the early cancer detection. Methods: Blood samples have been collected from 84 patients with histologically confirmed NPC and 100 matched controls. Samples from 45 NPC patients and 68 controls have been analyzed. Fourteen genes known to be dysregulated in NPC were investigated. Potential higher order juxtaposition sites in the candidate genes were predicted using pattern recognition software. PCR primer sets were designed around the chosen sites to screen potential markers. Twenty-two markers showing predictability between NPC and control samples were analysed for optimal reproducibility using alternative primer sets. The optimal sets of markers were then tested amongst the complete set of samples. The dataset was processed by re-sampling using the synthetic minority oversampling technique. The overall sample was split into two groups (66% training set and 34% test set) in the classification. Results: Sixteen markers from 7 candidate genes were found to be optimal in differentiating between NPC and control samples in the first 103 samples. Using the multilayer perceptron (MLP) classification, the following results were obtained: Sensitivity 88.9%, 95% CI (79.2% - 98.6%); Specificity 72.7%, 95% CI (58.9% - 86.5%); PPV 72.7%, 95% CI (58.9% - 86.5%); NPV 88.9%, 95% CI (79.2% - 98.6%). The accuracy of the test was similar in detection of stage I and II NPC versus that of stage III or IV NPC. Conclusions: Using a PCR-based method to detect alterations in the cancer epigenome, the feasibility of developing a blood test of potential utility in early diagnosis of NPC was demonstrated. Analysis of larger numbers of patient samples and optimization of markers are ongoing. The performance characteristics of the test in the total population of 184 samples will be presented.

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