Low Levels of Hepatocyte-Specific Methylation in Cell-Free DNA Are a Strong Negative Predictor for Acute T Cell-Mediated Rejection Requiring Treatment Following Liver Transplantation.

Graft-derived cell-free DNA (gdcfDNA) quantification is a promising, minimally invasive tool for detecting acute T cell-mediated rejection (ATCMR) following liver transplantation (LT). We investigated the utility of measuring hepatocyte-specific methylation in cfDNA (HS-cfDNA) to quantify gdcfDNA, examining its accuracy in detecting ATCMR in a prospective, cross-sectional study. Blood was collected from LT recipients immediately prior to graft biopsy for suspected rejection. HS-cfDNA was quantified using droplet-digital polymerase chain reaction. Prebiopsy liver function tests (LFTs) and HS-cfDNA levels were correlated with biopsy results and the primary outcome of treated biopsy-proven acute rejection (tBPAR). A total of 51 patients were recruited; 37 had evidence of rejection on biopsy and 20 required treatment. As much as 11 patients needed inpatient treatment for rejection. HS-cfDNA significantly outperformed LFTs in identifying patients with tBPAR, particularly those needing inpatient treatment (area under the curve, 73.0%; 95% confidence interval, 55.4%-90.6%; P = 0.01). At a threshold of <33.5% of the total cfDNA fraction, HS-cfDNA had a specificity of 97%, correctly excluding tBPAR in 30/31 patients. Quantifying graft-specific methylation in cfDNA has a major advantage over previous gdcfDNA techniques: it does not require genotyping/sequencing, lending it greater feasibility for translation into transplantation care. Low levels of HS-cfDNA were a strong negative predictor for tBPAR (negative predictive value, 86%) and may have a future role in triaging patients prior to invasive graft biopsies.

A Synthetic DNA Construct to Evaluate the Recovery Efficiency of Cell-Free DNA Extraction and Bisulfite Modification.

BACKGROUND: Despite improvements in the genetic and epigenetic analysis of cell-free DNA (cfDNA), there has been limited focus on assessing the preanalytical variables of recovery efficiency following cfDNA extraction and bisulfite modification. Quantification of recovery efficiency after these steps can facilitate quality assurance and improve reliability when comparing serial samples. METHODS: We developed an exogenous DNA Construct to Evaluate the Recovery Efficiency of cfDNA extraction and BISulfite modification (CEREBIS) after cfDNA extraction and/or subsequent bisulfite modification from plasma. The strategic placement of cytosine bases in the 180 bp CEREBIS enabled PCR amplification of the construct by a single primer set both after plasma DNA extraction and following subsequent bisulfite modification. RESULTS: Plasma samples derived from 8 organ transplant donors and 6 serial plasma samples derived from a liver transplant recipient were spiked with a known number of copies of CEREBIS. Recovery of CEREBIS after cfDNA extraction and bisulfite modification was quantified with high analytical accuracy by droplet digital PCR. The use of CEREBIS and quantification of its recovery was useful in identifying problematic extractions. Furthermore, its use was shown to be invaluable towards improving the reliability of the analysis of serial samples. CONCLUSIONS: CEREBIS can be used as a spike-in control to address the preanalytical variable of recovery efficiency both after cfDNA extraction from plasma and following bisulfite modification. Our approach can be readily implemented and its application may have significant benefits, especially in settings where longitudinal quantification of cfDNA for disease monitoring is necessary.

Elevated levels of circulating mitochondrial DNA predict early allograft dysfunction in patients following liver transplantation.

BACKGROUND AND AIM: The role of circulating mitochondrial DNA (cmtDNA) in transplantation remains to be elucidated. cmtDNA may be released into the circulation as a consequence of liver injury; yet recent work also suggests a causative role for cmtDNA leading to hepatocellular injury. We hypothesized that elevated cmtDNA would be associated with adverse events after liver transplantation (LT) and conducted an observational cohort study. METHODS: Twenty-one patients were enrolled prospectively prior to LT. RESULTS: Postoperative complications were observed in 47.6% (n = 10). Seven patients (33.3%) had early allograft dysfunction (EAD), and six patients (28.5%) experienced acute cellular rejection within 6 months of LT. cmtDNA levels were significantly elevated in all recipients after LT compared with healthy controls and preoperative samples (1 361 937 copies/mL [IQR 586 781-3 399 687] after LT; 545 531 copies/mL [IQR 238 562-1 381 015] before LT; and 194 562 copies/mL [IQR 182 359-231 515] in healthy controls) and returned to normal levels by 5 days after transplantation. cmtDNA levels were particularly elevated in those who developed EAD in the early postoperative period (P < 0.001). In all patients, there was initially a strong overall positive correlation between cmtDNA and plasma hepatocellular enzyme levels (P < 0.05). However, the patients with EAD demonstrated a second peak in cmtDNA at postoperative day 7, which did not correlate with liver function tests. CONCLUSIONS: The early release of plasma cmtDNA is strongly associated with hepatocellular damage; however, the late surge in cmtDNA in patients with EAD appeared to be independent of hepatocellular injury as measured by conventional tests.

A new normalization for Nanostring nCounter gene expression data.

The Nanostring nCounter gene expression assay uses molecular barcodes and single molecule imaging to detect and count hundreds of unique transcripts in a single reaction. These counts need to be normalized to adjust for the amount of sample, variations in assay efficiency and other factors. Most users adopt the normalization approach described in the nSolver analysis software, which involves background correction based on the observed values of negative control probes, a within-sample normalization using the observed values of positive control probes and normalization across samples using reference (housekeeping) genes. Here we present a new normalization method, Removing Unwanted Variation-III (RUV-III), which makes vital use of technical replicates and suitable control genes. We also propose an approach using pseudo-replicates when technical replicates are not available. The effectiveness of RUV-III is illustrated on four different datasets. We also offer suggestions on the design and analysis of studies involving this technology.

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly.

The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler. By combining assembly, split read, and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line, and patient tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.

DNA Methylation Profiling of Breast Cancer Cell Lines along the Epithelial Mesenchymal Spectrum-Implications for the Choice of Circulating Tumour DNA Methylation Markers.

(1) Background: Epithelial⁻mesenchymal plasticity (EMP) is a dynamic process whereby epithelial carcinoma cells reversibly acquire morphological and invasive characteristics typical of mesenchymal cells. Identifying the methylation differences between epithelial and mesenchymal states may assist in the identification of optimal DNA methylation biomarkers for the blood-based monitoring of cancer. (2) Methods: Methylation-sensitive high-resolution melting (MS-HRM) was used to examine the promoter methylation status of a panel of established and novel markers in a range of breast cancer cell lines spanning the epithelial⁻mesenchymal spectrum. Pyrosequencing was used to validate the MS-HRM results. (3) Results: VIM, DKK3, and CRABP1 were methylated in the majority of epithelial breast cancer cell lines, while methylation of GRHL2, MIR200C, and CDH1 was restricted to mesenchymal cell lines. Some markers that have been used to assess minimal residual disease such as AKR1B1 and APC methylation proved to be specific for epithelial breast cell lines. However, RASSF1A, RARß, TWIST1, and SFRP2 methylation was seen in both epithelial and mesenchymal cell lines, supporting their suitability for a multimarker panel. (4) Conclusions: Profiling DNA methylation shows a distinction between epithelial and mesenchymal phenotypes. Understanding how DNA methylation varies between epithelial and mesenchymal phenotypes may lead to more rational selection of methylation-based biomarkers for circulating tumour DNA analysis.

Breast ductal carcinoma in situ carry mutational driver events representative of invasive breast cancer.

The spectrum of genomic alterations in ductal carcinoma in situ (DCIS) is relatively unexplored, but is likely to provide useful insights into its biology, its progression to invasive carcinoma and the risk of recurrence. DCIS (n=20) with a range of phenotypes was assessed by massively parallel sequencing for mutations and copy number alterations and variants validated by Sanger sequencing. PIK3CA mutations were identified in 11/20 (55%), TP53 mutations in 6/20 (30%), and GATA3 mutations in 9/20 (45%). Screening an additional 91 cases for GATA3 mutations identified a final frequency of 27% (30/111), with a high proportion of missense variants (8/30). TP53 mutations were exclusive to high grade DCIS and more frequent in PR-negative tumors compared with PR-positive tumors (P=0.037). TP53 mutant tumors also had a significantly higher fraction of the genome altered by copy number than wild-type tumors (P=0.005), including a significant positive association with amplification or gain of ERBB2 (P<0.05). The association between TP53 mutation and ERBB2 amplification was confirmed in a wider DCIS cohort using p53 immunohistochemistry as a surrogate marker for TP53 mutations (P=0.03). RUNX1 mutations and MAP2K4 copy number loss were novel findings in DCIS. Frequent copy number alterations included gains on 1q, 8q, 17q, and 20q and losses on 8p, 11q, 16q, and 17p. Patterns of genomic alterations observed in DCIS were similar to those previously reported for invasive breast cancers, with all DCIS having at least one bona fide breast cancer driver event. However, an increase in GATA3 mutations and fewer copy number changes were noted in DCIS compared with invasive carcinomas. The role of such alterations as prognostic and predictive biomarkers in DCIS is an avenue for further investigation.

Probe-Free Digital PCR Quantitative Methodology to Measure Donor-Specific Cell-Free DNA after Solid-Organ Transplantation.

BACKGROUND: Donor-specific cell-free DNA (dscfDNA) is increasingly being considered as a noninvasive biomarker to monitor graft health and diagnose graft rejection after solid-organ transplantation. However, current approaches used to measure dscfDNA can be costly and/or laborious. A probe-free droplet digital PCR (ddPCR) methodology using small deletion/insertion polymorphisms (DIPs) was developed to circumvent these limitations without compromising the quantification of dscfDNA. This method was called PHABRE-PCR (Primer to Hybridize across an Allelic BREakpoint-PCR). The strategic placement of one primer to hybridize across an allelic breakpoint ensured highly specific PCR amplification, which then enabled the absolute quantification of donor-specific alleles by probe-free ddPCR. METHODS: dscfDNA was serially measured in 3 liver transplant recipients. Donor and recipient genomic DNA was first genotyped against a panel of DIPs to identify donor-specific alleles. Alleles that differentiated donor-specific from recipient-specific DNA were then selected to quantify dscfDNA in the recipient plasma. RESULTS: Lack of amplification of nontargeted alleles confirmed that PHABRE-PCR was highly specific. In recipients who underwent transplantation, dscfDNA was increased at day 3, but decreased and plateaued at a low concentration by 2 weeks in the 2 recipients who did not develop any complications. In the third transplant recipient, a marked increase of dscfDNA coincided with an episode of graft rejection. CONCLUSIONS: PHABRE-PCR was able to quantify dscfDNA with high analytical specificity and sensitivity. The implementation of a DIP-based approach permits surveillance of dscfDNA as a potential measure of graft health after solid-organ transplantation.

Reducing Artifactual EGFR T790M Mutations in DNA from Formalin-Fixed Paraffin-Embedded Tissue by Use of Thymine-DNA Glycosylase.

BACKGROUND: False-positive EGFR T790M mutations have been reported in formalin-fixed lung tumors, but the cause of the false positives has not been identified. The T790M mutation results from a C>T change at the cytosine of a CpG dinucleotide. The presence or absence of methylation at this cytosine has different consequences following deamination, resulting in a thymine or uracil, respectively, both of which however result in an artifactual change. Uracil-DNA glycosylase (UDG) can be used to eliminate DNA templates with uracil residues but is not active against artifactual thymines. We therefore investigated the use of thymine-DNA glycosylase (TDG) to reduce artifactual T790M mutations. METHODS: Formalin-fixed normal lung tissues and lung squamous cell carcinomas were tested to measure the frequency of false-positive EGFR mutations by use of droplet digital PCR before and after treatment with either UDG or TDG. Methylation at the cytosine at EGFR T790 was assessed by pyrosequencing and by analysis of public databases. RESULTS: Artifactual EGFR T790M mutations were detected in all of the archival formalin-fixed normal lung and lung squamous cell carcinomas at mutant allele frequencies of 1% or lower. The cytosine at EGFR T790 showed high levels of methylation in all lung cancer samples and normal tissues. Pretreatment of the formalin-fixed DNA with either UDG or TDG reduced the false EGFR T790M mutations, but a greater reduction was seen with the TDG treatment. CONCLUSIONS: Both U:G and T:G lesions in formalin-fixed tissue are sources of false-positive EGFR T790M mutations. This is the first report of the use of TDG to reduce sequence artifacts in formalin-fixed DNA and is applicable to the accurate detection of mutations arising at methylated cytosines.

BRCA2 carriers with male breast cancer show elevated tumour methylation.

BACKGROUND: Male breast cancer (MBC) represents a poorly characterised group of tumours, the management of which is largely based on practices established for female breast cancer. However, recent studies demonstrate biological and molecular differences likely to impact on tumour behaviour and therefore patient outcome. The aim of this study was to investigate methylation of a panel of commonly methylated breast cancer genes in familial MBCs. METHODS: 60 tumours from 3 BRCA1 and 25 BRCA2 male mutation carriers and 32 males from BRCAX families were assessed for promoter methylation by methylation-sensitive high resolution melting in a panel of 10 genes (RASSF1A, TWIST1, APC, WIF1, MAL, RARß, CDH1, RUNX3, FOXC1 and GSTP1). An average methylation index (AMI) was calculated for each case comprising the average of the methylation of the 10 genes tested as an indicator of overall tumour promoter region methylation. Promoter hypermethylation and AMI were correlated with BRCA carrier mutation status and clinicopathological parameters including tumour stage, grade, histological subtype and disease specific survival. RESULTS: Tumours arising in BRCA2 mutation carriers showed significantly higher methylation of candidate genes, than those arising in non-BRCA2 familial MBCs (average AMI 23.6 vs 16.6, p = 0.01, 45% of genes hypermethylated vs 34%, p < 0.01). RARß methylation and AMI-high status were significantly associated with tumour size (p = 0.01 and p = 0.02 respectively), RUNX3 methylation with invasive carcinoma of no special type (94% vs 69%, p = 0.046) and RASSF1A methylation with coexistence of high grade ductal carcinoma in situ (33% vs 6%, p = 0.02). Cluster analysis showed MBCs arising in BRCA2 mutation carriers were characterised by RASSF1A, WIF1, RARß and GTSP1 methylation (p = 0.02) whereas methylation in BRCAX tumours showed no clear clustering to particular genes. TWIST1 methylation (p = 0.001) and AMI (p = 0.01) were prognostic for disease specific survival. CONCLUSIONS: Increased methylation defines a subset of familial MBC and with AMI may be a useful prognostic marker. Methylation might be predictive of response to novel therapeutics that are currently under investigation in other cancer types.

MethPat: a tool for the analysis and visualisation of complex methylation patterns obtained by massively parallel sequencing.

BACKGROUND: DNA methylation at a gene promoter region has the potential to regulate gene transcription. Patterns of methylation over multiple CpG sites in a region are often complex and cell type specific, with the region showing multiple allelic patterns in a sample. This complexity is commonly obscured when DNA methylation data is summarised as an average percentage value for each CpG site (or aggregated across CpG sites). True representation of methylation patterns can only be fully characterised by clonal analysis. Deep sequencing provides the ability to investigate clonal DNA methylation patterns in unprecedented detail and scale, enabling the proper characterisation of the heterogeneity of methylation patterns. However, the sheer amount and complexity of sequencing data requires new synoptic approaches to visualise the distribution of allelic patterns. RESULTS: We have developed a new analysis and visualisation software tool "Methpat", that extracts and displays clonal DNA methylation patterns from massively parallel sequencing data aligned using Bismark. Methpat was used to analyse multiplex bisulfite amplicon sequencing on a range of CpG island targets across a panel of human cell lines and primary tissues. Methpat was able to represent the clonal diversity of epialleles analysed at specific gene promoter regions. We also used Methpat to describe epiallelic DNA methylation within the mitochondrial genome. CONCLUSIONS: Methpat can summarise and visualise epiallelic DNA methylation results from targeted amplicon, massively parallel sequencing of bisulfite converted DNA in a compact and interpretable format. Unlike currently available tools, Methpat can visualise the diversity of epiallelic DNA methylation patterns in a sample.

Comparison of 3 Methodologies for Genotyping of Small Deletion and Insertion Polymorphisms.

BACKGROUND: The quantification of genomic chimerism is increasingly recognized for its clinical significance after transplantation. Before the measurement of chimerism, accurate genotyping of genetic polymorphisms for informative alleles that can distinguish donor DNA from recipient DNA is essential. The ease of allelic discrimination of small deletion and insertion polymorphisms (DIPs) makes DIPs attractive markers to track chimerism. Current methodologies for the genotyping of DIPs are largely based on "open-tube" approaches. "Closed-tube" approaches involving no or minimal post-PCR handling are preferred. We compared 3 distinct methodologies to determine an optimal platform for DIP genotyping. METHODS: Genomic DNA from 19 normal individuals was genotyped for 6 small biallelic DIPs using high-resolution melting analysis (HRMA), probe-free droplet digital PCR (ddPCR), and microfluidic electrophoresis of PCR products. For HRMA, 3 different platforms were compared. RESULTS: Our newly developed probe-free ddPCR approach allowed the genotype of each DIP to be determined by fluorescence intensity based on amplicon size. Microfluidic electrophoresis also allowed genotypes to be determined by amplicon size. HRMA assays allowed the genotype of each DIP to be determined by melting profile. Genotyping results were concordant between the 3 methodologies. HRMA was the most readily performed methodology and was robust across 3 separate HRMA-capable platforms. CONCLUSIONS: We demonstrated the effectiveness of probe-free ddPCR to accurately genotype small biallelic DIPs. Nevertheless, HRMA proved to be the optimal approach for genotyping small DIPs because closed-tube approaches are preferred owing to rapid and less laborious workflows and least risk of PCR contamination.

Digital PCR of Genomic Rearrangements for Monitoring Circulating Tumour DNA.

Identifying circulating tumour DNA (ctDNA) for monitoring of cancer therapy is dependent on the development of readily designed, sensitive cancer-specific DNA markers. Genomic rearrangements that are present in the vast majority of cancers provide such markers.Tumour DNA isolated from two fresh-frozen lung tumours underwent whole genome sequencing. Genomic rearrangements were detected using a new computational algorithm, GRIDSS. Four genomic rearrangements from each tumour were chosen for further study using rearrangement-specific primers. Six of the eight rearrangements tested were identified as tumour-specific, the remaining two were present in the germline. ctDNA was quantified using digital PCR for the tumour genomic rearrangements in patient blood. Interestingly, one of the patients had no detectable ctDNA either prior to or post surgery although the rearrangements were readily detectable in the tumour DNA.This study demonstrates the feasibility of using digital PCR based on genomic rearrangements for the monitoring of minimal residual disease. In addition, whole genome sequencing provided further information enabling therapeutic choices including the identification of a cryptic EGFR exon 19 deletion in one patient and the identification of a high somatic mutation load in the other patient. This approach can be used as a model for all cancers with rearranged genomes.

Appraisal of the technologies and review of the genomic landscape of ductal carcinoma in situ of the breast.

Ductal carcinoma in situ is a biologically diverse entity. Whereas some lesions are cured by local surgical excision, others recur as in situ disease or progress to invasive carcinoma with subsequent potential for metastatic spread. Reliable prognostic biomarkers are therefore desirable for appropriate clinical management but remain elusive. In common with invasive breast cancer, ductal carcinoma in situ exhibits many genomic changes, predominantly copy number alterations. Although studies have revealed the genomic heterogeneity within individual ductal carcinoma in situ lesions and the association of certain copy number alterations with nuclear grade, none of the genomic changes defined so far is consistently associated with invasive transformation or recurrence risk in pure ductal carcinoma in situ. This article will review the current landscape of genomic alterations in ductal carcinoma in situ and their potential as prognostic biomarkers together with the technologies used to define these.

Heterozygosity for the common perforin mutation, p.A91V, impairs the cytotoxicity of primary natural killer cells from healthy individuals.

The production and delivery of functional perforin (PRF; PRF1 gene) by cytotoxic lymphocytes maintains immune homeostasis and tumour immune surveillance. In humans, inheritance of the common PRF1 polymorphism, p.A91V, (c.272C>T) found in 8-9% of the Caucasian population, with another mutated allele resulting in reduced PRF function or trafficking, has been shown to result in hyperinflammatory diseases and/or haematological cancers. In this study, we sought to investigate the function of p.A91V on a wild-type (WT) perforin background. We first developed an assay that distinguishes the relative levels of transcription of individual PRF1 alleles, including p.A91V. The p.A91V allele was seen to be expressed at similar levels as the WT allele in primary human natural killer (NK) cells, ruling out that allelic expression imbalance influenced their function. We then demonstrated that the p.A91V mutation results in protein misfolding and an appreciable reduction in NK-cell cytotoxicity in healthy carriers of p.A91V. We propose that this level of cytotoxic dysfunction may readily account for the predisposition to immune-mediated disease in individuals homozygous for p.A91V. Also, the fact that monoallelic mutations of PRF1 decrease NK-cell cytotoxicity should be considered in individuals presenting with the manifestations of immune deficiency states that impinge on NK-cell cytotoxicity.

Copy number analysis of ductal carcinoma in situ with and without recurrence.

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer and a frequent mammographic finding requiring treatment. Up to 25% of DCIS can recur and half of recurrences are invasive, but there are no reliable biomarkers for recurrence. We hypothesised that copy number aberrations could predict likelihood of recurrence. We analysed a cohort of pure DCIS cases treated only with wide local excision for genome-wide copy number and loss of heterozygosity using Affymetrix OncoScan MIP arrays. Cases included those without recurrence within 7 years (n = 25) and with recurrence between 1 and 5 years after diagnosis (n = 15). Pure DCIS were broadly similar in copy number changes compared with invasive breast cancer, with the consistent exception of a greater frequency of ERBB2 amplification in DCIS. There were no significant differences in age or ER status between the cases with a recurrence vs those without. Overall, the DCIS cases with recurrence had more copy number events than the DCIS without recurrence. The increased copy number appeared non-random with several genomic regions showing an increase in frequency in recurrent cases, including 20 q gain, ERBB2 amplification and 15q loss. Copy number changes may provide prognostic information for DCIS recurrence, but validation in additional cohorts is required.

Sequence artifacts in DNA from formalin-fixed tissues: causes and strategies for minimization.

BACKGROUND: Precision medicine is dependent on identifying actionable mutations in tumors. Accurate detection of mutations is often problematic in formalin-fixed paraffin-embedded (FFPE) tissues. DNA extracted from formalin-fixed tissues is fragmented and also contains DNA lesions that are the sources of sequence artifacts. Sequence artifacts can be difficult to distinguish from true mutations, especially in the context of tumor heterogeneity, and are an increasing interpretive problem in this era of massively parallel sequencing. Understanding of the sources of sequence artifacts in FFPE tissues and implementation of preventative strategies are critical to improve the accurate detection of actionable mutations. CONTENT: This mini-review focuses on DNA template lesions in FFPE tissues as the source of sequence artifacts in molecular analysis. In particular, fragmentation, base modification (including uracil and thymine deriving from cytosine deamination), and abasic sites are discussed as indirect or direct sources of sequence artifacts. We discuss strategies that can be implemented to minimize sequence artifacts and to distinguish true mutations from sequence artifacts. These strategies are applicable for the detection of actionable mutations in both single amplicon and massively parallel amplicon sequencing approaches. SUMMARY: Because FFPE tissues are usually the only available material for DNA analysis, it is important to maximize the accurate informational content from FFPE DNA. Careful consideration of each step in the work flow is needed to minimize sequence artifacts. In addition, validation of actionable mutations either by appropriate experimental design or by orthogonal methods should be considered.