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Nebdal, D.

Publications and source records attributed to Nebdal, D..

2 recordsLinked to original sources

CANCAN: high-resolution copy number and mutation heterogeneity analysis of DNA sequence data for clinical applications

High-throughput DNA sequencing is central to precision oncology, yet robust and interpretable methods for integrated analysis of copy number alterations and somatic variants across sequencing platforms remain limited. We present CANCAN (Copy number integrative ANalysis in CANcer), a platform-agnostic computational framework for high-resolution analysis of allele-specific copy number and variant data. CANCAN integrates novel normalization and segmentation strategies and enables inference of tumor purity, ploidy, subclonality and mutation multiplicity, while providing statistical confidence estimates and transparent evaluation of alternative solutions. Benchmarking across whole-genome, whole-exome and targeted sequencing datasets from TCGA and the IMPRESS-Norway study demonstrates high concordance with established methods, with particularly strong performance on targeted sequencing data. CANCAN accurately estimates global genomic features, including purity and ploidy, even at reduced sequencing coverage, and shows comparable or improved agreement relative to existing tools. In addition, it provides detailed visualization of the genomic context of clinically relevant biomarkers, supporting diagnostic interpretation. CANCAN constitutes a reproducible and interpretable approach for integrated genomic analysis, addressing key methodological and practical challenges in clinical cancer genomics.

bioinformatics↗

Intra-tumor heterogeneity defines treatment-resistant HER2+ breast tumors

Targeted therapy for patients with HER2 positive (HER2+) breast cancer has improved the overall survival, but many patients still suffer relapse and death of the disease. Intra-tumor heterogeneity of both estrogen receptor (ER) and HER2 expression has been proposed to play a key role in treatment failure, but little work has been done to comprehensively study this heterogeneity at the single-cell level.\n\nIn this study, we explored the clinical impact of intra-tumor heterogeneity of ER protein expression, HER2 protein expression, and HER2 gene copy number alterations. Using combined immunofluorescence and in situ hybridization on tissue sections followed by a validated computational approach, we analyzed more than 13,000 single tumor cells across 37 HER2+ breast tumors. The samples were taken both before and after neoadjuvant chemotherapy plus HER2-targeted treatment, enabling us to study tumor evolution as well.\n\nWe found that intra-tumor heterogeneity for HER2 copy number varied substantially between patient samples. Highly heterogeneous tumors were associated with significantly shorter disease-free survival and fewer long-term survivors. Patients for which HER2 characteristics did not change during treatment had a significantly worse outcome.\n\nThis work shows the impact of intra-tumor heterogeneity in molecular diagnostics for treatment selection in HER2+ breast cancer patients and the power of computational scoring methods to evaluate in situ molecular markers in tissue biopsies.

cancer biology↗