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The CancerMaster panel is designed to detect all variant types and the I-O markers, microsatellite instability (MSI) and tumor mutational burden (TMB), which are crucial biomarkers for cancer immunotherapy. For CNV analysis, a different cut-off is applied according to the ratio of cancer cells. The panel is also designed to detect Epstein-Barr virus (EBV) and […]
The CancerMaster panel is designed to detect all variant types and the I-O markers, microsatellite instability (MSI) and tumor mutational burden (TMB), which are crucial biomarkers for cancer immunotherapy. For CNV analysis, a different cut-off is applied according to the ratio of cancer cells. The panel is also designed to detect Epstein-Barr virus (EBV) and Human Papillomaviruses (HPV) allowing for comprehensive analysis of cancer-associated genes.
A broad range of targeting elements including somatic variants, IO-signatures (TMB, MSI), EBV and HPV, for clinical diagnoses of different cancer types and precision medicine.
Robust panel performance is supported by extensive validation tests with reference samples and clinical specimens.
|Gene count*||524 genes|
|Covered regions||Whole CDS, custom regions of oncogenes, immune response genes, EBV and HPV viruses|
|Mutation type||SNV, indel, CNV, rearrangement, TMB, MSI, EBV, HPV|
|Sample type||FFPE, fresh-frozen tissue (> 50ng of fragmented DNA)|
|Platform||All sequencers from Illumina, Thermo Fisher, MGI, Pac Bio and Oxford Nanopore|
|Bioinformatics pipeline||Primary, secondary and tertiary analysis result (FASTQ to VCF, VCF to clinical report)|
|Publication||Molecular Characterization of Biliary Tract Cancer Predicts Chemotherapy
and PD-1/PD-L1 Blockade Responses, Hepatology, 2021
*Gene add-on service: Genes can be added or removed according to customer needs
The probes are designed to include the intron regions as well as clinically significant biomarkers. By conducting extensive validation studies with clinical samples, the panel was examined to show its performance with high sensitivity and specificity in detecting the variants in cancer-associated genes.
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