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, RARβ, 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

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

Clustered somatic mutations are frequent in transcription factor binding motifs within proximal promoter regions in melanoma and other cutaneous malignancies

Most cancer DNA sequencing studies have prioritized recurrent non-synonymous coding mutations in order to identify novel cancer-related mutations. Although attention is increasingly being paid to mutations in non-coding regions, standard approaches to identifying significant mutations may not be appropriate and there has been limited analysis of mutational clusters in functionally annotated noncoding regions. We sought to identify clustered somatic mutations (hotspot regions across samples) in functionally annotated regions in melanoma and other cutaneous malignancies (cutaneous squamous cell carcinoma, basal cell carcinoma and Merkel cell carcinoma). Sliding window analyses revealed numerous recurrent clustered hotspot mutations in proximal promoters, with some specific clusters present in up to 25% of cases. Mutations in melanoma were clustered within ETS and Sp1 transcription factor binding motifs, had a UV signature and were identified in other cutaneous malignancies. Clinicopathologic correlation and mutation analysis support a causal role for chronic UV irradiation generating somatic mutations in transcription factor binding motifs of proximal promoters

Genome-scale methylation assessment did not identify prognostic biomarkers in oral tongue carcinomas

Background: DNA methylation profiling of heterogeneous head and neck squamous cell carcinoma (HNSCC) cohorts has been reported to predict patient outcome. We investigated if a prognostic DNA methylation profile could be found in tumour tissue from a single uniform subsite, the oral tongue. The methylation status of 109 comprehensively annotated oral tongue squamous cell carcinoma (OTSCC) formalin-fixed paraffin-embedded (FFPE) samples from a single institution were examined with the Illumina HumanMethylation450K (HM450K) array. Data pre-processing, quality control and analysis were performed using R packages. Probes mapping to SNPs, sex chromosomes and unreliable probes were accounted for prior to downstream analyses. The relationship between methylation and patient survival was examined using both agnostic approaches and feature selection. The cohort was enlarged by incorporation of 331 The Cancer Genome Atlas (TCGA) HNSCC samples, which included 91 TCGA OTSCC samples with HM450K and survival data available. Results: Given the use of FFPE-derived DNA, we defined different cohorts for separate analyses. Overall, similar results were found between cohorts. With an unsupervised approach, no distinct hypermethylated group of samples was identified and nor was a prognostic methylation profile identified. The use of multiple downstream feature selection approaches, including a linear models for microarray data (LIMMA), centroid feature selection (CFS), and recursive feature elimination (RFE) support vector machines, similarly failed to identify a significant methylation signature informative for patient prognosis or any clinicopathological data available. Furthermore, we were unable to confirm the prognostic methylation profiles or specific prognostic loci reported within the literature for HNSCC. Conclusions: With genome-scale assessment of DNA methylation using HM450K in one of the largest OTSCC cohorts to date, we were unable to identify a hypermethylated group of tumours or a prognostic methylation signature. This suggests that either DNA methylation in isolation is not likely to be of prognostic value or larger cohorts are required to identify such a biomarker for OTSCC

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

LRH-1 expression patterns in breast cancer tissues are associated with tumour aggressiveness

The significance and regulation of liver receptor homologue 1 (LRH-1, NR5A2), a tumour-promoting transcription factor in breast cancer cell lines, is unknown in clinical breast cancers. This study aims to determine LRH-1/NR5A2 expression in breast cancers and relationship with DNA methylation and tumour characteristics. In The Cancer Genome Atlas breast cancer cohort NR5A2 expression was positively associated with intragenic CpG island methylation (1.4-fold expression for fully methylated versus not fully methylated, p=0.01) and inversely associated with promoter CpG island methylation (0.6-fold expression for fully methylated versus not fully methylated, p=0.036). LRH-1 immunohistochemistry of 329 invasive carcinomas and ductal carcinoma in situ (DCIS) was performed. Densely punctate/ coarsely granular nuclear reactivity was significantly associated with high tumour grade (p < 0.005, p=0.033 in invasive carcinomas and DCIS respectively), negative estrogen receptor status (p=0.008, p=0.038 in overall cohort and invasive carcinomas, respectively), negative progesterone receptor status (p=0.003, p=0.013 in overall cohort and invasive carcinomas, respectively), HER2 amplification (overall cohort p=0.034) and non-luminal intrinsic subtype (p=0.018, p=0.038 in overall cohort and invasive carcinomas, respectively). These significant associations of LRH-1 protein expression with tumour phenotype suggest that LRH-1 is an important indicator of tumour biology in breast cancers and may be useful in risk stratification

Fc‐gamma receptor polymorphisms, cetuximab therapy, and overall survival in the CCTG CO.20 trial of metastatic colorectal cancer

Background: Two germ line Fc-γ receptor (FCGR) polymorphisms, rs1801274 [FCGR2A; His(H)131Arg(R)] and rs396991 [FCGR3A; Phe(F)158Val(V)], produce altered proteins through amino acid substitutions. We previously reported that the FCGR2A H/H genotype was associated with longer overall survival (OS) in cetuximab-treated chemotherapy-refractory patients with metastatic colorectal cancer. Here, we aimed to replicate and extend this finding in the Canadian Clinical Trials Group CO.20 trial. Methods: After germ line DNA genotyping, polymorphic relationships with survival were assessed using log-rank tests and hazard ratios (HR) from Cox proportional hazard models, adjusting for known prognostic factors. The dominant genetic inheritance model was used for the main analysis. Results: Of 592 wild-type KRAS patients treated with cetuximab, those with the FCGR2A H/H genotype (n = 165, 28%) had improved OS (HR: 0.66, P < 0.001; median absolute benefit, 1.3 months) compared to those with R/- genotype (n = 427, 72%). Patients with H/R had intermediate results under a codominant genetic inheritance model (HR: 0.72, P = 0.003). No significant associations were found between FCGR3A genotype and OS. In an exploratory analysis, patients with the combination of FCGR2A H/H + FCGR3A F/F genotype had significantly better OS (HR: 0.33, P = 0.003; median absolute benefit, 12.5 months) than patients with the combination of double-variant R/R + V/V genotype. Progression-free survival results were similar to OS. Toxicity rates were not associated with either polymorphism. Conclusions: The FCGR2A genotype was associated with efficacy but not with toxicity in wild-type KRAS, cetuximab-treated colorectal cancer patients. FCGR3A genotype may modulate the relationship between FCGR2A polymorphism and outcome. FCGR2A is a promising biomarker for clinical management for these patients

BCL-XL and MCL-1 are the key BCL-2 family proteins in melanoma cell survival

Malignant melanoma is one of the most difficult cancers to treat due to its resistance to chemotherapy. Despite recent successes with BRAF inhibitors and immune checkpoint inhibitors, many patients do not respond or become resistant to these drugs. Hence, alternative treatments are still required. Due to the importance of the BCL-2-regulated apoptosis pathway in cancer development and drug resistance, it is of interest to establish which proteins are most important for melanoma cell survival, though the outcomes of previous studies have been conflicting. To conclusively address this question, we tested a panel of established and early passage patient-derived cell lines against several BH3-mimetic drugs designed to target individual or subsets of pro-survival BCL-2 proteins, alone and in combination, in both 2D and 3D cell cultures. None of the drugs demonstrated significant activity as single agents, though combinations targeting MCL-1 plus BCL-XL, and to a lesser extent BCL-2, showed considerable synergistic killing activity that was elicited via both BAX and BAK. Genetic deletion of BFL-1 in cell lines that express it at relatively high levels only had minor impact on BH3-mimetic drug sensitivity, suggesting it is not a critical pro-survival protein in melanoma. Combinations of MCL-1 inhibitors with BRAF inhibitors also caused only minimal additional melanoma cell killing over each drug alone, whilst combinations with the proteasome inhibitor bortezomib was more effective in multiple cell lines. Our data show for the first time that therapies targeting specific combinations of BCL-2 pro-survival proteins, namely MCL-1 plus BCL-XL and MCL-1 plus BCL-2, could have significant benefit for the treatment of melanoma.</p

Condition-specific or generic preference-based measures in oncology? A comparison of the EORTC-8D and the EQ-5D-3L

Purpose: It has been argued that generic health-related quality of life measures are not sensitive to certain disease-specific improvements; condition-specific preference-based measures may offer a better alternative. This paper assesses the validity, responsiveness and sensitivity of a cancer-specific preference-based measure, the EORTC-8D, relative to the EQ-5D-3L. Methods: A longitudinal prospective population-based cancer genomic cohort, Cancer 2015, was utilised in the analysis. EQ-5D-3L and the EORTC QLQ-C30 (which gives EORTC-8D values) were asked at baseline (diagnosis) and at various follow-up points (3 months, 6 months, 12 months). Baseline values were assessed for convergent validity, ceiling effects, agreement and sensitivity. Quality-adjusted life-years (QALYs) were estimated and similarly assessed. Multivariate regression analyses were employed to understand the determinants of the difference in QALYs. Results: Complete case analysis of 1678 patients found that the EQ-5D-3L values at baseline were significantly lower than the EORTC-8D values (0.748 vs 0.829, p < 0.001). While the correlation between the instruments was high, agreement between the instruments was poor. The baseline health state values using both instruments were found to be sensitive to a number of patient and disease characteristics, and discrimination between disease states was found to be similar. Mean generic QALYs (estimated using the EQ-5D-3L) were significantly lower than condition-specific QALYs (estimated using the EORTC-8D) (0.860 vs 0.909, p < 0.001). The discriminatory power of both QALYs was similar. Conclusions: When comparing a generic and condition-specific preference-based instrument, divergences are apparent in both baseline health state values and in the estimated QALYs over time for cancer patients. The variability in sensitivity between the baseline values and the QALY estimations means researchers and decision makers are advised to be cautious if using the instruments interchangeably

Somatic GNAQ mutation in the forme fruste of Sturge-Weber syndrome

Objective: To determine whether the GNAQ R183Q mutation is present in the forme fruste cases of Sturge-Weber syndrome (SWS) to establish a definitive molecular diagnosis. Methods: We used sensitive droplet digital PCR (ddPCR) to detect and quantify the GNAQ mutation in tissues from epilepsy surgery in 4 patients with leptomeningeal angiomatosis; none had ocular or cutaneous manifestations. Results: Low levels of the GNAQ mutation were detected in the brain tissue of all 4 cases - ranging from 0.42% to 7.1% frequency - but not in blood-derived DNA. Molecular evaluation confirmed the diagnosis in 1 case in which the radiologic and pathologic data were equivocal. Conclusions: We detected the mutation at low levels, consistent with mosaicism in the brain or skin (1.0%-18.1%) of classic cases. Our data confirm that the forme fruste is part of the spectrum of SWS, with the same molecular mechanism as the classic disease and that ddPCR is helpful where conventional diagnosis is uncertain.</p