CNVisor is introduced, a statistical framework for reliable and robust CNV detection from long-read sequencing, even under ultra-low coverage, and established real-time CNV profiling using ultra-low coverage nanopore sequencing as a feasible strategy for intraoperative, genomics-informed assessment of CNS tumors.
Abstract
Copy number variations (CNVs) can serve as important clinical biomarkers for tumor classification and stratification. However, the utility of these CNV biomarkers for intraoperative tumor assessment within the timeframe of neurosurgical procedures has remained elusive due to the protracted duration of conventional CNV characterization methods. Here, we introduce CNVisor, a statistical framework for reliable and robust CNV detection from long-read sequencing, even under ultra-low coverage. Applied to neurosurgical tumor specimens, the proposed method enabled genome-wide CNV profiling and identified clinically relevant CNVs using roughly 60,000 reads within 20 minutes of sequencing. Integrating CNVisor with methylation-based classifiers can further reduce turnaround time and increase the accuracy of glioma subtype stratification. Together, these findings establish real-time CNV profiling using ultra-low coverage nanopore sequencing as a feasible strategy for intraoperative, genomics-informed assessment of CNS tumors.
A strategy is presented that calculates the median and median absolute deviation of gene-level fold changes across all samples within each sequencing batch and incorporates these measures into the result interpretation, providing batch-level reference metrics and supporting more reliable interpretation in comprehensive genomic profiling.
Chung Lee, Sejoon Lee, Hyun-Hee Koh et al.· Journal of Molecular Diagnos...· 0 citations
Abstract Copy number variations (CNVs) are genomic structural variants that are strongly linked to cancer progression and genetic disorders. CNVs can be highly heterogeneous at population and tissue scale; thus, single-cell resolution detection holds great promise for studying clonal evolution and CNV-driven changes. Despite advanced sc-RNA-seq CNV detection methods, accurate methods for epigenomic single-cell modalities lag behind. We developed RIDDLER; a robust, unsupervised method that uses outlier-aware statistical modeling to detect CNVs across multiple single-cell modalities and assays. RIDDLER utilizes a robust regression framework to model the expected distribution of reads genome-wide by accounting for assay-specific biases, identifying CNVs as outliers from that distribution. This versatile framing allows deployment of RIDDLER in multiple modalities with appropriate bias features. We demonstrate the accuracy of RIDDLER in calling single-cell CNVs and dissecting clonal heterogeneity in sc-ATAC-seq and sc-methylation. RIDDLER is more accurate and more robust to data sparsity than competing methods. We illustrate useful applications of RIDDLER for dissection of clonal structure, identification of subclonal accessibility peaks, and multimodal integration from CNV structure. RIDDLER stands out as a scalable, generalizable multi-modal method for accurate CNV detection, empowering studies aiming to link CNV dynamics to epigenetic alterations within the same cell.
Travis W Moore, H. Mohammed, Andrew C. Adey et al.· Nucleic Acids Research· 0 citations
Screening tumor types for which a first-line, integrated DNA-RNA NGS strategy provides a valuable advantage for rapid therapeutic decisions demonstrates that integrated DNA-RNA high-throughput NGS enables timely, precise molecular profiling for personalized therapy in solid tumors.
A. Destro, Federica Panebianco, Cecília Durães et al.· Virchows Archiv· 0 citations
DNA methylation–based classification has transformed the diagnosis of central nervous system (CNS) tumours. However, methylation profiling alone is insufficient for definitive diagnosis and must be integrated with genomic alterations such as single nucleotide variants, structural variants, and gene fusions. Molecular diagnostics are therefore moving towards unified sequencing approaches capable of simultaneously capturing epigenomic and genomic information within a single assay. Rapid nanopore sequencing has demonstrated the feasibility of combined methylation and genomic profiling within an intraoperative timeframe. Illumina 5-base whole-genome sequencing is a recently released short-read technology that distinguishes methylated from unmethylated cytosines, enabling integrated epigenomic and genomic analysis. Here, we compare the diagnostic performance of these long- and short-read methylation-aware sequencing platforms in CNS tumours.
We analysed a matched cohort of 30 CNS tumour samples previously characterised using a rapid nanopore diagnostic workflow. Illumina 5-base whole-genome sequencing was generated for each case, alongside conventional methylation array profiling. Tumour classification was performed using Random Forest, NanoDx, Sturgeon, and mnp-Flex, referencing Heidelberg classifier versions 11 and 12.8. Concordance between nanopore, Illumina 5-base, and standard-of-care methylation array classifications was assessed. Detection of diagnostically relevant genomic alterations, including single nucleotide variants, structural variants, and gene fusions, was compared across platforms.
Illumina 5-base sequencing demonstrated strong concordance with rapid nanopore classifications and established methylation array diagnoses. Agreement was consistent across classifiers and reference versions. Both approaches identified key diagnostic genomic alterations, supporting comprehensive molecular characterisation from a single assay.
Integrated methylation-aware sequencing platforms enabling simultaneous epigenomic and genomic profiling show robust cross-platform concordance and clinical feasibility for CNS tumour diagnostics.
S. Deacon, Inswasti Cahyani, Nadine Holmes et al.· Neuro-Oncology· 0 citations
Soft tissue sarcomas (STSs) are a heterogeneous group of rare mesenchymal malignancies with overlapping morphological and immunohistochemical features, often making definitive diagnosis challenging. Recent advances in next-generation sequencing (NGS) have enabled the identification of recurrent molecular alterations that contribute to tumor classification, prognostic stratification, and precision oncology approaches. This retrospective study aimed to evaluate the diagnostic and clinical impact of molecular profiling in pediatric soft tissue sarcomas using the Oncomine Childhood Cancer Research Assay (OCCRA) panel. Fifty-five frozen tumor samples representing 24 distinct soft tissue sarcoma subtypes were obtained from the Pediatric Oncology Institute -IOP/GRAACC/UNIFESP Biobank (B-053). Molecular analysis was performed using NGS to identify gene fusions, single nucleotide variants (SNVs), copy number variations (CNVs), and insertions/deletions (InDels). Clinically relevant molecular alterations were identified in 70% (37/55) of cases, including 18 fusion transcripts, 13 SNVs, 8 CNVs, and 6 InDels. Recurrent and diagnostically relevant alterations included BCOR::CCNB3, ASPSCR1::TFE3, NFR1::BRAF, FUS::DDIT3, EML4::NTRK3, ETV6::NTRK3, CIC::DUX4, NAB2::STAT6 and SS18::SSX1/2 fusions, as well as amplifications involving PDGFRA, FGFR1, GLI1, CDK4, ERBB3, and KIT. Pathogenic variants affecting genes involved in tumor suppression and chromatin remodeling, including TP53, NF1, DICER1, SMARCA4, PTEN, and PIK3CA, were also detected. Importantly, molecular profiling had significant diagnostic impact in several histologically ambiguous tumors, enabling molecular reclassification and refinement of previously inconclusive or inaccurate pathological diagnoses. In multiple cases, NGS transformed descriptive histopathological interpretations into genetically defined sarcoma entities, including NTRK-rearranged spindle cell neoplasms, CIC-rearranged sarcomas, synovial sarcoma, low-grade fibromyxoid sarcoma, and clear cell sarcoma. Furthermore, the identification of actionable alterations highlighted potential opportunities for targeted therapies and precision medicine approaches. Our findings demonstrate that comprehensive molecular profiling significantly enhances diagnostic accuracy in pediatric soft tissue sarcomas, particularly in morphologically challenging cases. The integration of NGS into routine sarcoma diagnostics enables biologically informed tumor classification and supports personalized therapeutic strategies.
F. Tesser-Gamba, T. B. Mendes, Fernanda Teresa de Lima et al.· International Journal of Mol...· 0 citations
Next-generation sequencing (NGS) has become a cornerstone of precision oncology in colorectal cancer (CRC), although its role in routine patient stratification remains incompletely defined. This retrospective single-centre study characterised the molecular landscape of clinically selected CRC patients undergoing routine NGS and explored associations between genomic alterations and clinicopathological features. 97 eligible patients who underwent targeted NGS using two validated sequencing platforms were selected. Demographic, clinicopathological, and molecular data were integrated, and associations were evaluated using descriptive statistics, exploratory association testing, principal component analysis, and multiple correspondence analysis. At least one reportable genetic alteration was identified in 91 patients (93.8%), comprising 198 alteration events across multiple cancer-related genes. The most frequently altered genes with pathogenic or likely pathogenic variants were TP53 (55.7%), KRAS (40.2%), PIK3CA (18.6%), and BRAF (11.5%), while microsatellite instability was detected in 19.1% of evaluable tumours. Exploratory analyses identified associations between selected molecular alterations and clinicopathological characteristics. However, these were generally modest, frequently limited by small subgroup sizes, and none survived Benjamini–Hochberg correction. Principal component analysis demonstrated substantial molecular heterogeneity without defining distinct clinicopathological subgroups. Routine targeted NGS provides detailed molecular characterisation of CRC and generates information relevant to biomarker-informed clinical decision-making in real-world practice. However, targeted panels alone were insufficient to establish robust molecular subgroups in this retrospective cohort. These findings highlight the biological complexity of CRC and support larger prospective studies incorporating broader molecular profiling to improve precision patient stratification and optimise personalised therapeutic strategies.
Afonso Cunha, C. Robalo, C. Lemos et al.· International Journal of Mol...· 0 citations