A new open-source software platform could bring high-resolution chromosome analysis closer to routine cancer care, allowing clinicians to inspect tumor DNA for missing, duplicated and amplified genomic regions through an interactive interface rather than relying on static laboratory reports. Called CnQuant, the system converts data from DNA methylation microarrays into copy-number profiles, then displays the results as annotated, case-specific plots and cohort-wide maps of recurrent abnormalities. The developers say the tool is designed for hospitals, where limited computing resources, incompatible data formats and the need to interpret results quickly can make sophisticated genomic analysis difficult to deploy. In an internal validation involving 30 tumors, CnQuant agreed with accredited diagnostic findings at 153 of 155 examined genomic loci, corresponding to a visually assessed concordance of 98.71 percent. The software and its reference datasets are available free of charge, potentially lowering the technical barrier to using chromosomal information in precision oncology.
Cancer cells frequently alter the number of copies they carry of particular DNA segments. A deletion can remove a gene that restrains cell growth, while a gain or amplification can increase the dosage of an oncogene, intensifying signals that promote proliferation or survival. These changes, collectively called copy-number variations, may span an entire chromosome or be confined to a small genomic region containing a clinically important gene. Their patterns can help identify tumor types, distinguish biologically different disease subgroups and reveal potential treatment targets. DNA methylation arrays were originally developed primarily to measure chemical tags attached to DNA, especially methyl groups that influence gene regulation. Yet the same arrays also provide indirect information about copy number because the intensity of signals from thousands of genomic probes changes when DNA is gained or lost. CnQuant is designed to extract and organize that secondary signal, turning a widely used epigenetic assay into a broader genomic profiling tool.
The platform builds on the team’s earlier EpiDiP system and incorporates the Mepylome toolkit for processing methylation and copy-number data. Its architecture separates analysis services from the visual interfaces used by clinicians. A coordinating component, CQmanager, directs files through a local application programming interface and can be incorporated into existing diagnostic workflows, including hospital systems that must keep patient data on site. CQcalc calculates copy-number alterations using array-specific, gender-balanced reference data, which are essential because normal signal levels vary between platforms and can be affected by sex-chromosome composition. The software stores reference information in compressed, checksum-verified form to reduce storage and computational demands. Once profiles have been generated, CQall_plotter can overlay data from multiple samples and array types, while the CQall and CQcase interfaces present cohort-level and individual-patient views through a web-based graphical environment.
That distinction between population patterns and single-patient inspection is central to CnQuant’s clinical design. CQall functions as an atlas of recurrent abnormalities, allowing users to examine how often a chromosomal gain or deletion appears within a reference cohort. Such frequency information can provide a plausibility check when a new diagnostic result seems unusual, and it may also help researchers investigate the genomic architecture of rare tumors. CQcase focuses on one specimen at a time, displaying selected genomic regions at high resolution and attaching gene-level annotations to the plot. A clinician can therefore move from a broad chromosome-wide pattern to a specific locus, such as ERBB2, MDM2 or PDGFRA, or to tumor-suppressor regions including CDKN2A. The interface is intended to be usable without specialist bioinformatics training. Annotated plots can be downloaded into electronic health records or shared through links during multidisciplinary tumor-board discussions, although the researchers emphasize that the links preserve visualization and annotation rather than exposing identifying patient information.
The system’s reference strategy also addresses a subtle problem in comparing data produced by different generations of methylation arrays. A reference cohort may combine samples analyzed on the older HumanMethylation450K platform with samples processed on EPIC arrays, whose probe content is not identical. If a comparison uses probes present on only one platform, apparent differences may reflect technology rather than tumor biology. CnQuant therefore restricts cross-platform cohort analyses to genomic probes shared by all included array types. That choice can reduce the number of measurements available, but it makes comparisons more conservative and helps avoid misleading conclusions, particularly in rare tumor entities where cohorts are small and heterogeneous. The researchers report that the software supports conventional methylation-array versions and supplies the corresponding copy-number-neutral reference data, enabling a unified approach rather than requiring each laboratory to assemble its own normalization framework.
Examples shown by the investigators illustrate how chromosomal signatures can mirror recognized tumor biology. In posterior fossa pilocytic astrocytomas, the platform identified recurrent gain of chromosome 7 associated with an internal tandem duplication. In diffuse midline gliomas carrying H3K27 alterations, it highlighted frequent gain involving PDGFRA. A recurrent loss of chromosome 7 together with gain of chromosome 10 appeared in RTK II glioblastomas that lacked IDH mutations, while sporadic amplification of the ERBB2 locus was visible in breast carcinomas. These patterns are not, by themselves, substitutes for a complete diagnosis. Instead, they provide genomic context that can be interpreted alongside histology, methylation-based tumor classification, sequencing and immunohistochemistry. At the individual-gene level, a copy-number plot may help explain a high or low variant allelic frequency in parallel sequencing, or clarify whether an apparent sequencing signal is consistent with a deletion, duplication or amplification in the surrounding DNA.
To test whether the visual output corresponded to established clinical results, the team examined four groups of tumors: breast-cancer metastases, H3K27-altered diffuse midline gliomas, IDH-wild-type RTK II glioblastomas and posterior fossa pilocytic astrocytomas. The 30 cases contained oncologically relevant copy-number changes and had already been assessed using accredited diagnostic methods. Depending on the tumor, the comparison data came from second-generation DNA or RNA sequencing panels, including the Oncomine Comprehensive Assay V2 and Archer FUSIONPlex Core Solid Tumor panel, or from HER2 fluorescence in situ hybridization and immunohistochemistry. Across 155 genomic loci assessed by visual comparison, 153 matched the routine results. The 98.71 percent figure is encouraging, but it comes from a small internal study and reflects visual concordance rather than a large prospective clinical trial with prespecified performance measures. Broader testing across institutions, tumor types and sample qualities will be needed before the software’s clinical reliability can be fully established.
CnQuant could also extend copy-number interpretation beyond microarrays, according to its developers. The cohort atlas may serve as a reference when clinicians interpret targeted sequencing or newer nanopore sequencing results, both of which can produce ambiguous evidence for gains and losses depending on coverage, assay design and tumor purity. Because the platform is locally installable through Docker or Windows Subsystem for Linux, it does not require a cloud-based analysis service or extensive computing infrastructure. Its open-source code and public reference resources may make it easier for laboratories to inspect, adapt and integrate the system into their own workflows. The authors argue that existing tools, including Conumee 2.0 and SeSAMe, do not combine interactive graphical exploration, on-the-fly gene annotation, high processing speed and low resource requirements in the same way. If independent validation confirms the initial results, a tool that makes chromosome-scale abnormalities immediately visible could help transform copy-number data from an underused by-product of methylation testing into a practical component of personalized cancer diagnosis and treatment planning.
Subject of Research: Open-source, high-resolution chromosomal copy-number profiling from DNA methylation array data for clinical precision oncology.
Subject of Research: Medicine
Article Title: CnQuant: high-resolution chromosomal copy number profiling for precision oncology in the clinics
Article References: Freyter, B. M., Hultschig, C., Brugger, J., Bratic Hench, I., Frank, S., & Hench, J. (2026). CnQuant: high-resolution chromosomal copy number profiling for precision oncology in the clinics. Acta Neuropathologica, 151(1), Article 53. https://doi.org/10.1007/s00401-026-03025-2
Image Credits: AI Generated
DOI: 10.1007/s00401-026-03025-2
Keywords: CnQuant, copy-number variation, DNA methylation arrays, precision oncology, tumor diagnostics, chromosomal profiling, cancer genomics, glioma, interactive bioinformatics, clinical genomics
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Rowan B. (August 29, 2026). CnQuant Enables High-Resolution Chromosomal Copy Number Profiling for Precision Oncology Clinics. Scienmag. https://scienmag.com/cnquant-enables-high-resolution-chromosomal-copy-number-profiling-for-precision-oncology-clinics/
Rowan B. “CnQuant Enables High-Resolution Chromosomal Copy Number Profiling for Precision Oncology Clinics.” Scienmag, 29 August 2026, https://scienmag.com/cnquant-enables-high-resolution-chromosomal-copy-number-profiling-for-precision-oncology-clinics/. Accessed 29 August 2026.
Rowan B. “CnQuant Enables High-Resolution Chromosomal Copy Number Profiling for Precision Oncology Clinics.” Scienmag. August 29, 2026. https://scienmag.com/cnquant-enables-high-resolution-chromosomal-copy-number-profiling-for-precision-oncology-clinics/
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