Osteosarcoma: Novel prognostic biomarkers using circulating and cell-free tumour DNA

AIM: Osteosarcoma (OS) is the most common primary bone tumour in children and adolescents. Circulating free (cfDNA) and circulating tumour DNA (ctDNA) are promising biomarkers for disease surveillance and prognostication in several cancer types; however, few such studies are reported for OS. The purpose of this study was to discover and validate methylation-based biomarkers to detect plasma ctDNA in patients with OS and explore their utility as prognostic markers. METHODS: Candidate CpG markers were selected through analysis of methylation array data for OS, non-OS tumours and germline samples. Candidates were validated in two independent OS datasets (n = 162, n = 107) and the four top-performing markers were selected. Methylation-specific digital droplet PCR (ddPCR) assays were designed and experimentally validated in OS tumour samples (n = 20) and control plasma samples. Finally, ddPCR assays were applied to pre-operative plasma and where available post-operative plasma from 72 patients with OS, and findings correlated with outcome. RESULTS: Custom ddPCR assays detected ctDNA in 69% and 40% of pre-operative plasma samples (n = 72), based on thresholds of one or two positive markers respectively. ctDNA was detected in 5/17 (29%) post-operative plasma samples from patients, which in four cases were associated with or preceded disease relapse. Both pre-operative cfDNA levels and ctDNA detection independently correlated with overall survival (p = 0.0015 and p = 0.0096, respectively). CONCLUSION: Our findings illustrate the potential of mutation-independent methylation-based ctDNA assays for OS. This study lays the foundation for multi-institutional collaborative studies to explore the utility of plasma-derived biomarkers in the management of OS

Individualized dynamic methylation-based analysis of cell-free DNA in postoperative monitoring of lung cancer

Background The feasibility of DNA methylation-based assays in detecting minimal residual disease (MRD) and postoperative monitoring remains unestablished. We aim to investigate the dynamic characteristics of cancer-related methylation signals and the feasibility of methylation-based MRD detection in surgical lung cancer patients.// Methods: Matched tumor, tumor-adjacent tissues, and longitudinal blood samples from a cohort (MEDAL) were analyzed by ultra-deep targeted sequencing and bisulfite sequencing. A tumor-informed methylation-based MRD (timMRD) was employed to evaluate the methylation status of each blood sample. Survival analysis was performed in the MEDAL cohort (n = 195) and validated in an independent cohort (DYNAMIC, n = 36).// Results: Tumor-informed methylation status enabled an accurate recurrence risk assessment better than the tumor-naïve methylation approach. Baseline timMRD-scores were positively correlated with tumor burden, invasiveness, and the existence and abundance of somatic mutations. Patients with higher timMRD-scores at postoperative time-points demonstrated significantly shorter disease-free survival in the MEDAL cohort (HR: 3.08, 95% CI: 1.48–6.42; P = 0.002) and the independent DYNAMIC cohort (HR: 2.80, 95% CI: 0.96–8.20; P = 0.041). Multivariable regression analysis identified postoperative timMRD-score as an independent prognostic factor for lung cancer. Compared to tumor-informed somatic mutation status, timMRD-scores yielded better performance in identifying the relapsed patients during postoperative follow-up, including subgroups with lower tumor burden like stage I, and was more accurate among relapsed patients with baseline ctDNA-negative status. Comparing to the average lead time of ctDNA mutation, timMRD-score yielded a negative predictive value of 97.2% at 120 days prior to relapse.// Conclusions: The dynamic methylation-based analysis of peripheral blood provides a promising strategy for postoperative cancer surveillance

Circulating tumour DNA is a promising biomarker for risk stratification of central chondrosarcoma with IDH1/2 and GNAS mutations

Chondrosarcoma (CS) is a rare tumour type and the most common primary malignant bone cancer in adults. The prognosis, currently based on tumour grade, imaging and anatomical location, is not reliable, and more objective biomarkers are required. We aimed to determine whether the level of circulating tumour DNA (ctDNA) in the blood of CS patients could be used to predict outcome. In this multi-institutional study, we recruited 145 patients with cartilaginous tumours, of which 41 were excluded. ctDNA levels were assessed in 83 of the remaining 104 patients, whose tumours harboured a hotspot mutation in IDH1/2 or GNAS. ctDNA was detected pre-operatively in 31/83 (37%) and in 12/31 (39%) patients postoperatively. We found that detection of ctDNA was more accurate than pathology for identification of high-grade tumours and was associated with a poor prognosis; ctDNA was never associated with CS grade 1/atypical cartilaginous tumours (ACT) in the long bones, in neoplasms sited in the small bones of the hands and feet or in tumours measuring less than 80 mm. Although the results are promising, they are based on a small number of patients, and therefore, introduction of this blood test into clinical practice as a complementary assay to current standard-of-care protocols would allow the assay to be assessed more stringently and developed for a more personalised approach for the treatment of patients with CS

<i>mi</i>R-625-3<i>p</i> regulates oxaliplatin resistance by targeting MAP2K6-p38 signalling in human colorectal adenocarcinoma cells

Oxaliplatin resistance in colorectal cancers (CRC) is a major medical problem, and predictive markers are urgently needed. Recently, miR-625-3p was reported as a promising predictive marker. Herein, we show that miR-625-3p functionally induces oxaliplatin resistance in CRC cells, and identify the signalling networks affected by miR-625-3p. We show that the p38 MAPK activator MAP2K6 is a direct target of miR-625-3p, and, accordingly, is downregulated in non-responder patients of oxaliplatin therapy. miR-625-3p-mediated resistance is reversed by anti-miR-625-3p treatment and ectopic expression of a miR-625-3p insensitive MAP2K6 variant. In addition, reduction of p38 signalling by using siRNAs, chemical inhibitors or expression of a dominant-negative MAP2K6 protein induces resistance to oxaliplatin. Transcriptome, proteome and phosphoproteome profiles confirm inactivation of MAP2K6-p38 signalling as one likely mechanism of oxaliplatin resistance. Our study shows that miR-625-3p induces oxaliplatin resistance by abrogating MAP2K6-p38-regulated apoptosis and cell cycle control networks, and corroborates the predictive power of miR-625-3p

A genetic model for central chondrosarcoma evolution correlates with patient outcome

Background Central conventional chondrosarcoma (CS) is the most common subtype of primary malignant bone tumour in adults. Treatment options are usually limited to surgery, and prognosis is challenging. These tumours are characterised by the presence and absence of IDH1 and IDH2 mutations, and recently, TERT promoter alterations have been reported in around 20% of cases. The effect of these mutations on clinical outcome remains unclear. The purpose of this study was to determine if prognostic accuracy can be improved by the addition of genomic data, and specifically by examination of IDH1, IDH2, and TERT mutations. Methods In this study, we combined both archival samples and data sourced from the Genomics England 100,000 Genomes Project (n = 356). Mutations in IDH1, IDH2, and TERT were profiled using digital droplet PCR (n = 346), whole genome sequencing (n=68), or both (n = 64). Complex events and other genetic features were also examined, along with methylation array data (n = 84). We correlated clinical features and patient outcomes with our genetic findings. Results IDH2-mutant tumours occur in older patients and commonly present with high-grade or dedifferentiated disease. Notably, TERT mutations occur most frequently in IDH2-mutant tumours, although have no effect on survival in this group. In contrast, TERT mutations are rarer in IDH1-mutant tumours, yet they are associated with a less favourable outcome in this group. We also found that methylation profiles distinguish IDH1- from IDH2-mutant tumours. IDH wild-type tumours rarely exhibit TERT mutations and tend to be diagnosed in a younger population than those with tumours harbouring IDH1 and IDH2 mutations. A major genetic feature of this group is haploidisation and subsequent genome doubling. These tumours evolve less frequently to dedifferentiated disease and therefore constitute a lower risk group. Conclusions Tumours with IDH1 or IDH2 mutations or those that are IDHwt have significantly different genetic pathways and outcomes in relation to TERT mutation. Diagnostic testing for IDH1, IDH2, and TERT mutations could therefore help to guide clinical monitoring and prognostication

Sarcoma classification by DNA methylation profiling

Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications

DREAMS: deep read-level error model for sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Abstract Circulating tumor DNA detection using next-generation sequencing (NGS) data of plasma DNA is promising for cancer identification and characterization. However, the tumor signal in the blood is often low and difficult to distinguish from errors. We present DREAMS (Deep Read-level Modelling of Sequencing-errors) for estimating error rates of individual read positions. Using DREAMS, we develop statistical methods for variant calling (DREAMS-vc) and cancer detection (DREAMS-cc). For evaluation, we generate deep targeted NGS data of matching tumor and plasma DNA from 85 colorectal cancer patients. The DREAMS approach performs better than state-of-the-art methods for variant calling and cancer detection

H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours

Diagnosing MPNST can be challenging, but genetic alterations recently identified in polycomb repressive complex 2 (PRC2) core component genes, EED and SUZ12, resulting in global loss of the histone 3 lysine 27 trimethylation (H3K27me3) epigenetic mark, represent drivers of malignancy and a valuable diagnostic tool. However, the reported loss of H3K27me3 expression ranges from 35–84%. We show that advances in molecular pathology now allows many MPNST mimics to be classified confidently. We confirm that MPNSTs harbouring mutations in PRC2 core components are associated with loss of H3K27me3 expression; whole genome doubling was detected in 68%, and SSTR2 was amplified in 32% of MPNSTs. We demonstrate that loss of H3K27me3 expression occurs overall in 38% of MPNSTs, but is lost in 76% of histologically classical cases, whereas loss was detected in only 23% cases with heterologous elements and 14% where the diagnosis could not be provided on morphology alone. H3K27me3 loss is rarely seen in other high‐grade sarcomas and was not found to be associated with an inferior outcome in MPNST. We show that DNA methylation profiling distinguish MPNST from its histological mimics, was unrelated to anatomical site and formed two main clusters, MeGroup 4 and 5. MeGroup 4 represents classical MPNSTs lacking H3K27me3 expression in the majority of cases, whereas MeGroup 5 comprise MPNSTs exhibiting non‐classical histology and expressing H3K27me3 and cluster with undifferentiated sarcomas. The two MeGroups are distinguished by differentially methylated PRC2‐associated genes, the majority of which are hypermethylated in the promoter regions in MeGroup 4, indicating that the PRC2 target genes are not expressed in these tumours. The methylation profiles of MPNSTs with retention of H3K27me3 in MeGroup 4 and 5 are independent of mutations in PRC2 core components and the driver(s) in these groups remain to be identified. Our results open new avenues of investigation