Overview
The detection sensitivity for low-frequency variants froma limited amount of sample is of great importanceto a ctDNA analysis kit.
Celemics has developed ctDNA-based kits for colon, breast, and lung cancer assays through collaborative research with Seoul National University Hospital since 2017. We have integrated our market-leading proprietary technologies including probe design algorithms, noise removal techniques, and reagent optimization. The panel is thoroughly validated and ready to use for clinical diagnostics.
Features &
Benefits
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- Detects ctDNA for colorectal cancer, breast cancer, and lung cancer
- Assess 16 key genes for colorectal cancer, 14 for breast cancer,15 for lung cancer
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- Highly optimized panel for clinical testing with exceptional accuracy
- Complete validated panel performance conducted with patient samples
through collaborative research with Seoul National University Hospital
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- Provides Unique Molecular Identifiers (UMI) and Bioinformatics Software
- Receive high-quality data supported by Celemics proprietary UMI algorithms
and analysis software, enabling efficient duplication removal
and minimizing sequencing noise
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- Algorithms to reduce sequencing background noise to
accurate analysis of low-frequency variants - Celemics applies algorithms for reducing the sequencing noise
to provide accurate and reliable sequencing results to our customers
- Algorithms to reduce sequencing background noise to
Panel
Performance
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Colorectal Cancer Sensitivity Freq. 0.5% 100% Freq. 1.0% 100% Specificity 97.9% 
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Breast Cancer Sensitivity Freq. 0.5% 94.4% Freq. 1.0% 100% Specificity 96.3% 
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Lung Cancer Sensitivity Freq. 0.5% 100% Freq. 1.0% 100% Specificity 100% 
Each of the three ctDNA panels showed greater than 94% sensitivity and 96% specificity when used in the ctDNA research and clinical fields
Workflow
Workflow of Celemics’ Circulating Tumor DNA Panel
- Able to assess ctDNA with ultra-low variant allele frequency (VAF)
- Modular algorithm to be applied in the existing pipeline.
- Retrieves more unique reads than that from conventional duplication removal algorithms, reducing sequencing costs
- Noise removal and accurate calls due to proprietary consensus sequence
generation algorithm
Bioinformatics SW for noise reduction and duplicate read recovery
- Minimizes the noise for accurate analysis of variants with ultra-low VAF from ctDNA
- Generates consensus read to support noise suppression
- Continuous improvement of the noise removal technology by data accumulation
Applications
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Early diagnosis of cancers
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Observation of the prognosis