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CancerScreen Panels

Highly optimized NGS panel for somatic cancer

Overview
Features & Benefits
Specification
Related Products
Resources
References
Overview
Features & Benefits
Specification
Related Products
Resources
References

Overview

CancerScreen Panel Core/50/100/400/Comprehensive

CancerScreen panel is an NGS assay designed to detect all types of variants for up to 765 genes associated with somatic cancer. Targeting the selected genes with high sensitivity and specificity enables saving cost and effort.

Celemics provides full exclusive bioinformatics support.
The generated report consists of the primary, secondary, and tertiary results for the in-depth understanding and interpretation of sequencing data.

Also, if the gene of interest does not exist in the panel, it can be added separately through our gene add-on service

CancerScreen Panels
Features & Benefits

Optimized Comprehensive Panel for Solid Cancer Analysis

The panel is designed to assess the whole CDS region (RefSeq) of up to 765 genes 

and rearrangement regions associated with solid cancer. Using the CancerScreen panel, 

you can detect all mutation types, including SNV, Indel, Large Inde, CNV, rearrangements, MSI, and TMB as well as other immuno-oncology markers in a single assay.

Performance Comparison with Competitor Product

  • Higher on-target ratio, uniformity, coverage at 100X compared to competitor product over the target regions including exons and introns
Performance Comparison with Competitor Product

Superior Sensitivity and Specificity

CancerScreen panel is suitable for detecting low-frequency and rare variants with high sequencing depths. With Celemics’ proprietary probe design technology, it provides superior capture performance even in GC-rich and homologous regions or any type of clinical samples, such as poor-quality FFPE or ctDNA with the highest sensitivity and specificity.

Maximized Sequencing Efficiency

Celemics’ assay and reagent optimization technology will significantly increase the sequencing efficiency while maintaining the market leading on-target ratio and uniformity. Also, the precisely optimized and balanced chemistry will allow panels and kits to be compatible with various sequencing platform of your choice at much reduced sequencing cost compared to other competitor products. 

Performance Comparison over GC-rich Regions

  • More uniform read depths over GC-rich regions compared to competitor products.
Performance Comparison over GC-rich Regions
Performance Comparison over GC-rich Regions

Specification

Gene count*13/54/99/407/706 genes
Target size61/197/299/1,123/2,521 kb + Rearrangement
Mutation typeSNV, Indel, CNV, Rearrangement, MSI, TMB
Sample type(amount)FFPE, frozen tissue, cfDNA, RNA
PlatformAll sequencers from Illumina, Thermo Fisher, MGI, PacBio, and Oxford Nanopore
Bioinformatics Support① Primary Analysis: FASTQ to annotated VCF
② Secondary Analysis: CNV, Large InDel
③ Tertiary Analysis: Clinical interpretation

Specification - Gene List

  • 13 genes | Gene count
  • 61 kb | Target Size
  • Whole CDS, Rearrangement | Target Region
ALKAPCBRAFEGFRERBB2KRASMETNRASPIK3CARETROS1SMAD4TP53
  • 54 genes | Gene count
  • 197 kb | Target Size
  • Whole CDS, Rearrangement | Target Region
ABL1AKT1ALKAPCATMBRAFBRCA1BRCA2CDH1CDK4CDK6CDKN2A
CSF1RCTNNB1DDR2EGFRERBB2ERBB4ESR1FGFR1FGFR2FGFR3GNA11GNAQ
GNASHRASIDH1IDH2JAK2KDRKITKRASMAP2K1METMLH1MTOR
MYCMYCNNOTCH1NRASNTRK1PDGFRAPIK3CAPTCH1PTENPTPN11RB1RET
ROS1SMAD4SMOSRCSTK11TP53
  • 99 genes | Gene count
  • 299 kb | Target Size
  • CDS | Target Region
ABL1AKT1AKT2AKT3ALKAPCARID1AARID1BARID2ATMATRXAURKA
AURKBBARD1BCL2BLMBMPR1ABRAFBRCA1BRCA2BRIP1CDH1CDK4CDK6
CDKN2ACHEK2CSF1RCTNNB1DDR2EGFREPCAMEPHB4ERBB2ERBB3ERBB4EZH2
FBXW7FGFR1FGFR2FGFR3FLT3GNA11GNAQGNASHNF1AHRASIDH1IDH2
IGF1RITKJAK1JAK2JAK3KDRKITKRASMDM2METMLH1MPL
MRE11MSH2MSH6MTORMUTYHNBNNF1NOTCH1NPM1NRASNTRK1PALB2
PDGFRAPDGFRBPIK3CAPIK3R1PMS2PRSS1PTCH1PTCH2PTENPTPN11RAD50RAD51C
RAD51DRB1RETROS1SLX4SMAD4SMARCB1SMOSRCSTK11SYKTERT
TOP1TP53VHL
  • 407 genes | Gene count
  • 1,123 kb | Target Size
  • CDS | Target Region
ABL1ABL2ADGRA2AKT1AKT2AKT3ALKAMER1APCAPCDD1APEX1APOB
APOBEC1ARARAFARFRP1ARID1AARID1BARID2ASXL1ATMATP11BATRATRX
AURKAAURKBAXIN1AXLB2MB3GAT1BACH1BAP1BARD1BCL2BCL6BCL9
BCORBCRBIRC2BIRC3BLMBRAFBRCA1BRCA2BRD2BRD3BRD4BRIP1
BTG1BTKBTLACARD11CASP5CASP8CBFBCBLCD274CDK12CDK4CDK6
CDK8CDKN1ACDKN1BCDKN2ACDKN2BCDKN2CCDX2CEBPACHD1CHD2CHD4CHEK1
CHEK2CHUKCICCRBNCREBBPCRKLCRLF2CSF1RCSF2CSF2RACSF2RBCSNK2A1
CTCFCTLA4CTNNA1CTNNB1CUL3CUL4ACUL4BCXCL10CXCL11CXCL9CXCR3CYLD
CYP17A1DAXXDCUN1D1DDR2DICER1DIS3DNMT1DNMT3ADOCK2DOT1LEGFRELMO1
EML4EMSYEP300EPHA3EPHA5EPHA6EPHA7EPHB1EPHB4EPHB6ERBB2ERBB3
ERBB4ERCC1ERCC2ERGERRFI1ESR1ETV1ETV4ETV5ETV6EWSR1EYA2
EZH2FANCAFANCCFANCD2FANCEFANCFFANCGFANCIFANCLFANCMFASFAT1
FAT3FBXW7FGF1FGF10FGF12FGF14FGF19FGF2FGF23FGF3FGF4FGF6
FGF7FGFR1FGFR2FGFR3FGFR4FHFLCNFLT1FLT3FLT4FOXA1FOXL2
FOXO3FOXP3FRS2FUBP1GABRA6GAS6GATA1GATA2GATA3GATA4GATA6GID4
GLI1GNA11GNA13GNAQGNASGRIN2AGRM3GSK3BGUCY1A2GZMAGZMBGZMH
H3F3AHGFHIST1H3BHNF1AHOXA3HRASHSD3B1HSP90AA1IDH1IDH2IDO1IDO2
IFITM1IFITM3IFNA1IFNB1IFNGIGF1IGF1RIGF2IGF2RIKBKEIKZF1IL12A
IL12BIL2IL23AIL6IL7RINHBAINPP4BINSRIRF2IRF4IRS2ITGAE
ITKJAK1JAK2JAK3JUNKAT6AKDM5AKDM5CKDM6AKDRKEAP1KEL
KITKLF4KLHL6KMT2AKMT2BKMT2CKNSTRNKRASLAG3LMO1LRP1BLRP6
LTKLYNLZTR1MAGI2MAGOHMAML1MAP2K1MAP2K2MAP2K4MAP3K1MAP3K13MAPK1
MAXMCL1MDM2MDM4MED12MEF2BMEN1METMITFMLH1MPLMRE11
MSH2MSH6MTORMUTYHMYBMYCMYCLMYCNMYD88MYO18ANCOA3NCOR1
NF1NF2NFE2L2NFKBIANOTCH1NOTCH2NOTCH3NOTCH4NPM1NRASNSD1NSD3
NTRK1NTRK2NTRK3NUP93NUTM1PAK3PAK5PALB2PARP1PARP2PARP3PARP4
PAX5PBRM1PDCD1PDCD1LG2PDGFRAPDGFRBPDK1PGRPHF6PHLPP2PIK3C2BPIK3C3
PIK3CAPIK3CBPIK3CGPIK3R2PKHD1PLCG1PLCG2PMS2PNPPNRC1POLD1POLE
PPARGPPP2R1APRDM1PREX2PRF1PRKAR1APRKCIPRKDCPRPF40BPRSS8PTCH1PTCH2
PTENPTK2PTPN11PTPRCPTPRDQKIRAB35RAC1RAC2RAD17RAD50RAD51
RAD52RAD54LRAF1RANBP2RARARB1RBM10RELRETRHEBRHOARHOB
RICTORROBO1ROBO2ROS1RPA1RPS6KB1RPTORRUNX1RUNX1T1RUNX3SDHASDHB
SDHCSDHDSEMA3ASEMA3ESETSETBP1SETD2SF3A1SF3B1SH2B3SKP2SLIT2
SMAD2SMAD3SMAD4SRSF2SRSF7STAG2STAT3STAT4TERTTET2TP53 
  • 706 genes (697 genes for DNA, 68 genes for RNA) | Gene count
  • 2.32 Mb (DNA), 201 Kb (RNA) | Target Size
  • CDS, Hotspot variant, UTR, Intronic, Intergenic regions, and MSI markers | Target Region

[DNA – Gene List]

ABL1ABL2ABRAXAS1ACVR1ACVR1BACVR2AADAM29ADGRA2ADTRPAKT1AKT2AKT3
ALKALOX12BALOX15BAMER1ANKRD11ANKRD26APCAPCDD1APEX1APOBAPOBEC1APOBEC3A
APOBEC3BARARAFARFRP1ARID1AARID1BARID2ARID5BASTE1ASXL1ASXL2ATM
ATP11BATRATRXAURKAAURKBAXIN1AXIN2AXLB2MB3GAT1BACH1BAP1
BARD1BAXBBC3BCL10BCL2BCL2A1BCL2L1BCL2L11BCL2L2BCL6BCL9BCOR
BCORL1BCRBEX5BIRC2BIRC3BLMBMPR1ABRAFBRCA1BRCA2BRD2BRD3
BRD4BRIP1BTG1BTKBTLACADM1CALRCARD11CASP5CASP8CBFBCBL
CCDC150CCDC168CCDC43CCL2CCL4CCN6CCND1CCND2CCND3CCNE1CD27CD274
CD276CD28CD3DCD3ECD3GCD4CD40CD44CD74CD79ACD79BCD8A
CDC42CDC73CDH1CDH2CDH20CDH5CDK12CDK4CDK6CDK8CDKN1ACDKN1B
CDKN2ACDKN2BCDKN2CCDX2CEBPACENPACHD1CHD2CHD4CHEK1CHEK2CHUK
CICCOLEC12COP1CRBNCREBBPCRKCRKLCRLF2CSF1RCSF2CSF2RACSF2RB
CSF3RCSNK1A1CSNK2A1CTCFCTLA4CTNNA1CTNNB1CUL3CUL4ACUL4BCUX1CXCL10
CXCL11CXCL9CXCR3CXCR4CYLDCYP17A1CYP4Z2PDAXXDCUN1D1DDHD1DDR2DDX41
DEFB105ADHX15DICER1DIS3DNAJB1DNMT1DNMT3ADNMT3BDOCK2DOCK3DOT1LE2F3
EEDEGFL7EGFREIF1AXEIF4A2EIF4EELMO1ELOCEML4EMP1EMSYEP300
EPCAMEPHA3EPHA5EPHA6EPHA7EPHB1EPHB4EPHB6ERBB2ERBB3ERBB4ERCC1
ERCC2ERCC3ERCC4ERCC5ERGERRFI1ESR1ETS1ETV1ETV4ETV5ETV6
EWSR1EYA2EZH2FANCAFANCCFANCD2FANCEFANCFFANCGFANCIFANCLFANCM
FASFAT1FAT3FBXW7FGF1FGF10FGF12FGF14FGF19FGF2FGF23FGF3
FGF4FGF5FGF6FGF7FGF8FGF9FGFR1FGFR2FGFR3FGFR4FHFLCN
FLI1FLT1FLT3FLT4FOXA1FOXL2FOXO1FOXO3FOXP1FOXP3FRS2FUBP1
FYNGABRA6GAS6GATA1GATA2GATA3GATA4GATA6GEN1GID4GLI1GNA11
GNA13GNAQGNASGPS2GREM1GRIN2AGRM3GSK3BGUCY1A2GZMAGZMBGZMH
H1-2H2AC13H2BC5H3-3AH3-3BH3-4H3-5H3C1H3C11H3C12H3C13H3C14
H3C15H3C2H3C3H3C4H3C6H3C7H3C8HGFHLA-AHLA-BHLA-CHLA-DRA
HLA-EHLA-FHLA-GHNF1AHNRNPKHOXA3HOXB13HRASHSD3B1HSP90AA1ICOSLGID3
IDH1IDH2IDO1IDO2IFITM1IFITM3IFNA1IFNB1IFNGIFNGR1IGF1IGF1R
IGF2IGF2RIKBKEIKZF1IL10IL12AIL12BIL2IL23AIL6IL7RINHA
INHBAINPP4AINPP4BINSRIRF2IRF4IRS1IRS2ITGAEITKJAK1JAK2
JAK3JUNKAT6AKDM5AKDM5CKDM6AKDRKEAP1KELKIF5BKITKLF4
KLHL6KMT2AKMT2BKMT2CKMT2DKNSTRNKRASLAG3LAMP1LATS1LATS2LMO1
LRP1BLRP6LTKLTN1LYNLZTR1MAGI2MAGOHMALT1MAML1MAP2K1MAP2K2
MAP2K4MAP3K1MAP3K13MAP3K14MAP3K4MAPK1MAPK3MAXMCL1MDC1MDM2MDM4
MED12MEF2BMEF2CMEN1METMGAMITFMLH1MLLT3MPLMRE11MSH2
MSH3MSH6MST1MST1RMTMR11MTORMTRMUTYHMYBMYCMYCLMYCN
MYD88MYL1MYLKMYO18AMYOD1NAB2NBNNCOA3NCOR1NDUFC2NEGR1NF1
NF2NFE2L2NFKBIANKX2-1NKX2-8NKX3-1NOMO1NOTCH1NOTCH2NOTCH3NOTCH4NPM1
NRASNRG1NSD1NSD3NTRK1NTRK2NTRK3NUP93NUTM1PAK1PAK3PAK5
PALB2PARP1PARP2PARP3PARP4PAX3PAX5PAX7PAX8PBRM1PCDH17PDCD1
PDCD1LG2PDE4DPDGFRAPDGFRBPDK1PDPK1PGRPHF6PHLPP2PHOX2BPIK3C2BPIK3C2G
PIK3C3PIK3CAPIK3CBPIK3CDPIK3CGPIK3R1PIK3R2PIK3R3PIM1PKHD1PLCG1PLCG2
PLK2PMAIP1PMS1PMS2PNPPNRC1POLD1POLEPPARGPPM1DPPP2R1APPP2R2A
PPP6CPRDM1PREX2PRF1PRKAR1APRKCIPRKDCPRKNPRPF40BPRSS8PTCH1PTCH2
PTENPTK2PTPN11PTPRCPTPRDPTPRSPTPRTPUS3QKIRAB35RAC1RAC2
RAD17RAD21RAD50RAD51RAD51BRAD51CRAD51DRAD52RAD54LRAF1RANBP2RARA
RASA1RB1RBM10RBMXL1RECQL4RELRETRFX1RHEBRHOARHOBRICTOR
RIT1RNF19BRNF43ROBO1ROBO2ROS1RPA1RPS6KA4RPS6KB1RPS6KB2RPTORRUNX1
RUNX1T1RUNX3RYBPSDHASDHAF2SDHBSDHCSDHDSEC31ASEMA3ASEMA3ESET
SETBP1SETD2SF3A1SF3B1SH2B3SH2D1ASHQ1SKP2SLC22A9SLIT2SLITRK3SLX4
SMAD2SMAD3SMAD4SMAP1SMARCA1SMARCA4SMARCB1SMARCD1SMC1ASMC3SMOSNCAIP
SOCS1SOX10SOX17SOX2SOX9SPENSPOPSPTA1SRCSRSF1SRSF2SRSF7
STAG1STAG2STAT3STAT4STAT5ASTAT5BSTC1STK11STK40SUFUSUZ12SYK
TACC3TAF1TBX22TBX3TCF3TCF7L2TENT5CTERCTERTTET1TET2TFE3
TFRCTGFBR1TGFBR2TIAF1TIGITTIPARPTMEM127TMPRSS2TNFTNFAIP3TNFRSF14TNFRSF18
TNFRSF4TNFSF13BTNKSTNKS2TOP1TOP2ATP53TP63TRAF2TRAF7TRRAPTSC1
TSC2TSHRU2AF1U2AF2USP9XVEGFAVHLVSIRVTCN1WNT1WT1WWP1
XBP1XIAPXPO1XRCC2XRCC3YAP1YES1ZBTB2ZBTB7AZFHX3ZNF217ZNF703
ZRSR2           

 

[RNA – Gene List]

ABL1AKT3ALKARAXLBAIAP2L1BCL2BRAFBRCA1BRCA2CCDC6CD74
CDK4CSF1REGFREML4ERBB2ERGESR1ETS1ETV1ETV4ETV5ETV6
EWSR1FGFR1FGFR2FGFR3FGFR4FLI1FLT1FLT3JAK2KDRKIF5BKIT
KMT2ALMNAMETMLLT3MSH2MYCNCOA4NOTCH1NOTCH2NOTCH3NRG1NTRK1
NTRK2NTRK3PAX3PAX7PAX8PDGFRAPDGFRBPIK3CAPPARGRAF1RETROS1
RPS6KB1SEPTIN14SLC34A2SLC45A3TACC3TFGTMPRSS2TPM3    

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Resources

Technical Resources

[Product Sheet] Celemics CancerScreen Focus

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[Product Sheet] Celemics CancerScreen Core/50/100/400

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[Product Sheet] Celemics CancerScreen Comprehensive

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[Product Sheet] Celemics CancerScreen CUP(Cancer of Unknown Primary)

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Celemics Target Enrichment Panel Overview

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Celemics Products & Servics

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Safety Data Sheets

If you require the latest MSDS file, please contact us via ‘Contact Us‘.

MSDS_CancerScreen Panels_Illumina

MSDS_CancerScreen Panels_Thermo Fisher

MSDS_CancerScreen Panels_MGI

References

Distant origin of glioblastoma recurrence: neural stem cells in the subventricular zone serve as a source of tumor reconstruction after primary resection

Molecular Cancer

Distant origin of glioblastoma recurrence: neural stem cells in the subventricular zone serve as a source of tumor reconstruction after primary resection

Li, X., Kim, H. J., Yoo, J., Lee, Y., Nam, C. H., Park, J., … & Lee, J. H. (2025). Distant origin of glioblastoma recurrence: neural stem cells in the subventricular zone serve as a source of tumor reconstruction after primary resection. Molecular Cancer, 24(1), 64.

 

10.1186/s12943-025-02273-2


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The clinical relevance of surgical specimens for RNA sequencing in lung cancer: a cohort study

Frontiers in Oncology

The clinical relevance of surgical specimens for RNA sequencing in lung cancer: a cohort study

Eom, J. S., Kim, S. H., Kim, K., Kim, A., Ahn, H. Y., Mok, J., … & Kim, M. H. (2024). The clinical relevance of surgical specimens for RNA sequencing in lung cancer: A cohort study. Frontiers in Oncology, 14, 1462519.

 

10.3389/fonc.2024.1462519


View Detail >

Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: A Multicenter Phase Ib/II Study (K-MASTER-13)

Cancer Research and Treatment

Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: A Multicenter Phase Ib/II Study (K-MASTER-13)

Koo DH, Jung M, Kim YH, Jeung HC, Zang DY, Bae WK, Kim H, Kim HS, Lee CK, Kwon WS, Chung HC. Varlitinib and Paclitaxel for EGFR/HER2 Co-Expressing Advanced Gastric Cancer: a Multicenter Phase Ib/II Study (K-MASTER-13). Cancer Research and Treatment. 2024 Apr 29.

 

10.4143/crt.2023.1324


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Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel

Cancers

Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel

Hwang J, Bang S, Choi MH, Hong SH, Kim SW, Lee HE, Yang JH, Park US, Choi YJ. Discovery and Validation of Survival-Specific Genes in Papillary Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel. Cancers. 2024 Jan;16(11):2006.

 

10.3390/cancers16112006


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